physics updates on arXiv.org

<p>We propose a theoretical model of quark-gluon plasma (QGP) produced at the Brookhaven National Laboratory (BNL) Relativistic Heavy Ion Collider (RHIC). In this model, we hypothesize that the gas of quarks and gluons are confined within the film of gravitons as a Bose-Einstein condensate (BEC) during the production of QGP. The structure of this theoretical model of QGP explains why QGP behaves in a liquid-like manner, resembling a perfect fluid rather than a gas. Based on this theoretical model, we calculated the shear viscosity of QGP. This is essentially the shear viscosity of the BEC film of gravitons. The computational results obtained in this study appear to be consistent with experimental findings. </p>

<p>Weather radar is the primary tool used by forecasters to detect and warn for tornadoes in near-real time. In order to assist forecasters in warning the public, several algorithms have been developed to automatically detect tornadic signatures in weather radar observations. Recently, Machine Learning (ML) algorithms, which learn directly from large amounts of labeled data, have been shown to be highly effective for this purpose. Since tornadoes are extremely rare events within the corpus of all available radar observations, the selection and design of training datasets for ML applications is critical for the performance, robustness, and ultimate acceptance of ML algorithms. This study introduces a new benchmark dataset, TorNet to support development of ML algorithms in tornado detection and prediction. TorNet contains full-resolution, polarimetric, Level-II WSR-88D data sampled from 10 years of reported storm events. A number of ML baselines for tornado detection are developed and compared, including a novel deep learning (DL) architecture capable of processing raw radar imagery without the need for manual feature extraction required for existing ML algorithms. Despite not benefiting from manual feature engineering or other preprocessing, the DL model shows increased detection performance compared to non-DL and operational baselines. The TorNet dataset, as well as source code and model weights of the DL baseline trained in this work, are made freely available. </p>

<p>There has been some good news, and some bad news in the controlled fusion community recently. The good news is that the Lawrence Livermore National Laboratory (LLNL) has recently produced a burning plasma. It succeeded on several of its shots where ~1.5-2 megajoules from its laser (National Ignition Facility, or NIF) has generated ~ 1.3-3 megajoules of fusion products. The highest ratio of fusion energy to laser energy it achieved, defined as its Q, was 1.5 at the time of this writing. While LLNL is sponsored by nuclear stockpile stewardship, this author sees a likely path from their result to fusion for energy for the world, a path using a very different laser and a very different target configuration. The bad news is that the International Tokamak Experimental Reactor (ITER) has continued to stumble on more and more delays and cost overruns, as its capital cost has mushroomed from ~$5 billion to ~ $25B. This paper argues that the American fusion effort, for energy for the civilian economy, should switch its emphasis not only from magnetic fusion to inertial fusion but should also take much more seriously fusion breeding. Over the next few decades, the world might well be setting up more and more thermal nuclear reactors, and these might need fuel which only fusion breeders can supply. In other words, fusion should begin to color outside the lines. </p>

<p>Wavefront errors are a common artifact in laser light generation and imaging. They can be described as an aberration from the spherical wavefront of an ideal Gaussian beam by combinations of higher-order Hermite- or Laguerre-Gaussian terms. Here, we present an algorithm called Beamfit to estimate the mode composition from a series of CCD images taken over the Rayleigh range of a laser beam. The algorithm uses a user-defined set of Hermite- or Laguerre-Gaussian modes as the basis of its theoretical model. A novel method reduces the number of calculations needed to compute the model's intensity profiles. For a given model containing $N$ modes, the number of Hermite-Gaussian complex amplitudes needed to calculate are reduced from orders of $\mathcal{O}(N^2)$ to $\mathcal{O}(N)$ and replaced by simple multiplications. Additionally, non-beam parameters are pre-calculated to further reduce the search space dimension and its resulting calculation time. It is planned to release the Beamfit software to the public under an open-source license. </p>

<p>Extracting consistent statistics between relevant free-energy minima of a molecular system is essential for physics, chemistry and biology. Molecular dynamics (MD) simulations can aid in this task but are computationally expensive, especially for systems that require quantum accuracy. To overcome this challenge, we develop an approach combining enhanced sampling with deep generative models and active learning of a machine learning potential (MLP). We introduce an adaptive Markov chain Monte Carlo framework that enables the training of one Normalizing Flow (NF) and one MLP per state. We simulate several Markov chains in parallel until they reach convergence, sampling the Boltzmann distribution with an efficient use of energy evaluations. At each iteration, we compute the energy of a subset of the NF-generated configurations using Density Functional Theory (DFT), we predict the remaining configuration's energy with the MLP and actively train the MLP using the DFT-computed energies. Leveraging the trained NF and MLP models, we can compute thermodynamic observables such as free-energy differences or optical spectra. We apply this method to study the isomerization of an ultrasmall silver nanocluster, belonging to a set of systems with diverse applications in the fields of medicine and catalysis. </p>

<p>This work demonstrates the viability of scandium oxide deposition on silicon by means of high pressure sputtering. Deposition pressure and radio frequency power are varied for optimization of the properties of the thin films and the ScOx-Si interface. The physical characterization was performed by ellipsometry, Fourier transform infrared spectroscopy, x-ray diffraction and transmission electron microscopy. Aluminum gate electrodes were evaporated for metal-insulator-semiconductor (MIS) fabrication. From the electrical characterization of the MIS devices, the density of interfacial defects is found to decrease with deposition pressure, showing a reduced plasma damage of the substrate surface for higher pressures. This is also supported by lower flatband voltage shifts in the capacitance versus voltage hysteresis curves. Sputtering at high pressures (above 100 Pa) reduces the interfacial SiOx formation, according to the infrared spectra. The growth rates decrease with deposition pressure, so a very accurate control of the layer thicknesses could be provided. </p>

<p>High k gadolinium oxide thin layers were deposited on silicon by high-pressure sputtering (HPS). In order to optimize the properties for microelectronic applications, different deposition conditions were used. Ti (scavenger) and Pt (nonreactive) were e-beam evaporated to fabricate metal-insulator-semiconductor (MIS) devices. According to x-ray diffraction, x-ray photoelectron spectroscopy, and Fourier-transform infrared spectroscopy, policrystaline stoichiometric Gd2O3 films were obtained by HPS. MIS with the dielctric deposited at higher pressures also present lower flatband voltage shifts in the C-V hysteris curves. </p>

<p>Pneumatic systems are common in manufacturing, healthcare, transportation, robotics, and many other fields. Failures in these systems can have very serious consequences, particularly if they go undetected. In this work, we present an air-powered error detector device that can detect and respond to failures in pneumatically actuated systems. The device contains 21 monolithic membrane valves that act like transistors in a pneumatic logic "circuit" that uses vacuum to represent TRUE and atmospheric pressure as FALSE. Three pneumatic exclusive-OR (XOR) gates are used to calculate the parity bit corresponding to the values of several control bits. If the calculated value of the parity bit differs from the expected value, then an error (like a leak or a blocked air line) has been detected and the device outputs a pneumatic error signal which can in turn be used to alert a user, shut down the system, or take some other action. As a proof-of-concept, we used our pneumatic error detector to monitor the operation of a medical device, an intermittent pneumatic compression (IPC) device commonly used to prevent the formation of life-threatening blood clots in the wearer's legs. Experiments confirm that when the IPC device was damaged, the pneumatic error detector immediately recognized the error (a leak) and alerted the wearer using sound. By providing a simple and low-cost way to add fault detection to pneumatic actuation systems without using sensors, our pneumatic error detector can promote safety and reliability across the wide range of pneumatic systems. </p>

<p>AmorphousGd2O3 and Sc2O3 thin films were deposited on Si by high-pressure sputtering (HPS). In order to reduce the uncontrolled interfacial SiOx growth, firstly a metallic film of Gd or Sc was sputtered in pure Ar plasma. Subsequently, they were in situ plasma oxidized in an Ar/O2 atmosphere. For post-processing interfacial SiOx thickness reduction, three different top metal electrodes were studied: platinum, aluminum and titanium. For both dielectrics, it was found that Pt did not react with the films, while Al reacted with them forming an aluminate-like interface and, finally, Ti was effective in scavenging the SiO2 interface thickness without severely compromising gate dielectric leakage. </p>

<p>We achieve high detectivity terahertz sensing using a silicon nitride nanomechanical resonator functionalized with a metasurface absorber. High performances are achieved by striking a fine balance between the frequency stability of the resonator, and its responsivity to absorbed radiation. Using this approach, we demonstrate a detectivity $D^*=3.4\times10^9~\mathrm{cm\cdot\sqrt{Hz}/W}$ and a noise equivalent power $\mathrm{NEP}=36~\mathrm{pW/\sqrt{Hz}}$ that outperform the best room-temperature on-chip THz detectors (i.e., pyroelectrics). Our optical absorber consists of a 1-mm diameter metasurface, which currently enables a 0.5-3 THz detection range but can easily be scaled to other frequencies in the THz and infrared ranges. In addition to demonstrating high-performance terahertz sensing, our work unveils an important fundamental trade-off between high frequency stability and high responsivity in thermal-based nanomechanical radiation sensors. </p>

<p>I argue that research in physics operates under an implicit community philosophy, and I offer a definition I think physicists would accept, by and large. I compare this definition to what philosophers, sociologists, and historians of science, with physicists, say we are doing. </p>

<p>Predicting extreme events in chaotic systems, characterized by rare but intensely fluctuating properties, is of great importance due to their impact on the performance and reliability of a wide range of systems. Some examples include weather forecasting, traffic management, power grid operations, and financial market analysis, to name a few. Methods of increasing sophistication have been developed to forecast events in these systems. However, the boundaries that define the maximum accuracy of forecasting tools are still largely unexplored from a theoretical standpoint. Here, we address the question: What is the minimum possible error in the prediction of extreme events in complex, chaotic systems? We derive lower bounds for the minimum probability of error in extreme event forecasting using the information-theoretic Fano's inequality. The limits obtained are universal, in that they hold regardless of the modeling approach: from traditional linear regressions to sophisticated neural network models. The approach also allows us to assess whether reduced-order models are operating near their theoretical maximum performance or if further improvements are theoretically possible. </p>

<p>We present a conceptually novel approach to achieve selective area epitaxy of GaN nanowires. The approach is based on the fact that these nanostructures do not form in plasma-assisted molecular beam epitaxy on structurally and chemically uniform cation-polar substrates. By in situ depositing and nitridating Si on a Ga-polar GaN film, we locally reverse the polarity to induce the selective area epitaxy of N-polar GaN nanowires. We show that the nanowire number density can be controlled over several orders of magnitude by varying the amount of pre-deposited Si. Using this growth approach, we demonstrate the synthesis of single-crystalline and uncoalesced nanowires with diameters as small as 20 nm. The achievement of nanowire number densities low enough to prevent the shadowing of the nanowire sidewalls from the impinging fluxes paves the way for the realization of homogeneous core-shell heterostructures without the need of using ex situ pre-patterned substrates. </p>

<p>Artificial intelligence (AI) has seen remarkable advancements across various domains, including natural language processing, computer vision, autonomous vehicles, and biology. However, the rapid expansion of AI technologies has escalated the demand for more powerful computing resources. As digital computing approaches fundamental limits, neuromorphic photonics emerges as a promising platform to complement existing digital systems. In neuromorphic photonic computing, photonic devices are controlled using analog signals. This necessitates the use of digital-to-analog converters (DAC) and analog-to-digital converters (ADC) for interfacing with these devices during inference and training. However, data movement between memory and these converters in conventional von Neumann computing architectures consumes energy. To address this, analog memory co-located with photonic computing devices is proposed. This approach aims to reduce the reliance on DACs and ADCs and minimize data movement to enhance compute efficiency. This paper demonstrates a monolithically integrated neuromorphic photonic circuit with co-located capacitive analog memory and compares various analog memory technologies for neuromorphic photonic computing using the MNIST dataset as a benchmark. </p>

<p>This work investigates the electronic stopping power for protons of a tungsten plasma at various electron densities and temperatures. The study employs a dielectric formalism to model the stopping power due to free and bound electrons, considering relativistic and non-relativistic effects. The bound electron stopping power is modeled using the shellwise local plasma approximation (SLPA) introduced by Montanari and Miraglia. The ionization state of the plasma is also examined, revealing its impact on the bound electron contribution. We compare our results with the T-Matrix approach and the Li-Petrasso model for free electrons in combination with SLPA calculations for the bound electron ones. Results demonstrate the significance of bound electron stopping power, particularly for plasma with high-Z ions. This investigation contributes valuable insights into plasma physics and fusion energy research, providing essential data for future experiments and simulations. </p>

<p>We present quasi-real-time dual-comb spectroscopy (DCS) using two Yb:fiber combs with ~750 MHz repetition rates. A computational coherent averaging technique is employed to correct timing and phase fluctuations of the measured dual-comb interferogram (IGM). Quasi-real-time phase correction of 1-ms long acquisitions occurs every 1.5 seconds and is assisted by coarse radio frequency (RF) phase-locking of an isolated RF comb mode. After resampling and global offset phase correction, the RF comb linewidth is reduced from 200 kHz to ~1 kHz, while the line-to-floor ratio increases 13 dB in power in 1 ms. Using simultaneous offset frequency correction in opposite phases, we correct the aliased RF spectrum spanning three Nyquist zones, which yields an optical coverage of ~180 GHz around 1.035 $\mu$m probed on a sub-microsecond timescale. The absorption profile of gaseous acetylene is observed to validate the presented technique. </p>

<p>We experimentally investigate the statistics of zero-height isolines in gravity wave turbulence as physical candidates for conformal invariant curves. We present direct evidence that they can be described by the family of conformal invariant curves called stochastic Schramm-L\"owner evolution (or SLE$_{\kappa}$), with diffusivity $\kappa = 2.88(8)$. A higher nonlinearity in the height fields is shown to destroy this symmetry, though scale invariance is retained. </p>

<p>The ability to distinguish between stochastic systems based on their trajectories is crucial in thermodynamics, chemistry, and biophysics. The Kullback-Leibler (KL) divergence, $D_{\text{KL}}^{AB}(0,\tau)$, quantifies the distinguishability between the two ensembles of length-$\tau$ trajectories from Markov processes A and B. However, evaluating $D_{\text{KL}}^{AB}(0,\tau)$ from histograms of trajectories faces sufficient sampling difficulties, and no theory explicitly reveals what dynamical features contribute to the distinguishability. This letter provides a general formula that decomposes $D_{\text{KL}}^{AB}(0,\tau)$ in space and time for any Markov processes, arbitrarily far from equilibrium or steady state. It circumvents the sampling difficulty of evaluating $D_{\text{KL}}^{AB}(0,\tau)$. Furthermore, it explicitly connects trajectory KL divergence with individual transition events and their waiting time statistics. The results provide insights into understanding distinguishability between Markov processes, leading to new theoretical frameworks for designing biological sensors and optimizing signal transduction. </p>

<p>Electronic charge delocalization on the molecular backbones of ionic liquid-forming ions substantially impacts their molecular polarizabilities. Density functional theory calculations of polarizabilities and volumes of many cations and anions are reported and applied to yield refractive indices of 1216 ionic liquids. A novel expression for the precise estimation of the molecular volumes of the ionic liquids from simulation data is also introduced, adding quadratic corrections to the usual sum of atomic volumes. Our significant findings include i) that the usual assumption of uniform, additive atomic polarizabilities is challenged when highly mobile electrons in conjugated systems are present, and ii) that cations with conjugated large carbon chains can be used together with anions for the design of ionic liquids with very high refractive indices. A novel relation for the polarizability volume is reported together with a refractive index map made up of the studied ionic liquids </p>

<p>This article presents a concise survey of basic discrete and semi-discrete nonlinear models which produce two- and three-dimensional (2D and 3D) solitons, and a summary of main theoretical and experimental results obtained for such solitons. The models are based on the discrete nonlinear Schroeodinger (DNLS) equations and their generalizations, such as a system of discrete Gross- Pitaevskii (GP) equations with the Lee-Huang-Yang corrections, the 2D Salerno model (SM), DNLS equations with long-range dipole-dipole and quadrupole-quadrupole interactions, a system of coupled discrete equations for the second-harmonic generation with the quadratic (chi^(2)) nonlinearity, a 2D DNLS equation with a superlattice modulation opening mini-gaps, a discretized NLS equation with rotation, a DNLS coupler and its PT-symmetric version, a system of DNLS equations for the spin-orbit-coupled (SOC) binary Bose-Einstein condensates, and others. The article presents a review of basic species of multidimensional discrete modes, including fundamental (zero-vorticity) and vortex solitons, their bound states, gap solitons populating mini-gaps, symmetric and asymmetric solitons in the conservative and PT-symmetric couplers, cuspons in the 2D SM, discrete SOC solitons of the semi-vortex and mixed-mode types, 3D discrete skyrmions, and some others. </p>

<p>We characterized and analyzed the effect of intracavity spectral filtering in the Er:fiber laser mode-locked with a semiconductor saturable absorber mirror (SESAM). We studied the dispersive properties of bandpass filters and their influence on the characteristics of generated soliton pulses. Our analysis showed that various sideband structures were induced by the filter dispersion profiles and shaped through the interaction of the soliton with the dispersive wave. In addition, intracavity filtering improved the intensity and phase noise of the laser significantly, and we showed optimal filtering conditions for both types of noise. By adding a 10 nm bandpass filter to the laser resonator, the intensity and phase noise were improved 2- and 2.6 times, respectively. </p>

<p>We demonstrate a novel method to determine the longitudinal phase-space distribution of a cryogenic buffer gas beam of barium-fluoride molecules based on a two-step laser excitation scheme. The spatial resolution is achieved by a transversely aligned laser beam that drives molecules from the ground state $X^2\Sigma^+$ to the $A^2\Pi_{1/2}$ state around 860 nm, while the velocity resolution is obtained by a laser beam that is aligned counter-propagating with respect to the molecular beam and that drives the Doppler shifted $A^2\Pi_{1/2}$ to $D^2\Sigma^+$ transition around 797 nm. Molecules in the $D$-state are detected virtually background-free by recording the fluorescence from the $D-X$ transition at 413 nm. As molecules in the ground state do not absorb light at 797 nm, problems due to due to optical pumping are avoided. Furthermore, as the first step uses a narrow transition, this method can also be applied to molecules with hyperfine structure. The measured phase-space distributions, reconstructed at the source exit, show that the average velocity and velocity spread vary significantly over the duration of the molecular beam pulse. Our method gives valuable insight into the dynamics in the source and helps to reduce the velocity and increase the intensity of cryogenic buffer gas beams. In addition, transition frequencies are reported for the $X-A$ and $X-D$ transitions in barium fluoride with an absolute accuracy below 0.3 MHz. </p>

<p>Recently, we have demonstrated a method to record the longitudinal phase-space distribution of a pulsed cryogenic buffer gas cooled beam of barium fluoride molecules. In this paper, we use this method to determine the influence of various source parameters. Besides the expected dependence on temperature and pressure, the forward velocity of the molecules is strongly correlated with the time they exit the cell, revealing the dynamics of the gas inside the cell. Three observations are particularly noteworthy: (1) The velocity of the barium fluoride molecules increases rapidly as a function of time, reaches a maximum 50-200 $\mu$s after the ablation pulse and then decreases exponentially. We attribute this to the buffer gas being heated up by the plume of hot atoms released from the target by the ablation pulse and subsequently being cooled down via conduction to the cell walls. (2) The time constant associated with the exponentially decreasing temperature increases when the source is used for a longer period of time, which we attribute to the formation of a layer of isolating dust on the walls of the cell. By thoroughly cleaning the cell, the time constant is reset to its initial value. (3) The velocity of the molecules at the trailing end of the molecular pulse depends on the length of the cell. For short cells, the velocity is significantly higher than expected from the sudden freeze model. We attribute this to the target remaining warm over the duration of the molecular pulse giving rise to a temperature gradient within the cell. Our observations will help to optimize the source parameters for producing the most intense molecular beam at the target velocity. </p>

<p>In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF non-invasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. This study aims to introduce a compact speckle visibility spectroscopy (SVS) device designed for non-invasive CBF measurements, offering cost-effectiveness and scalability while tracking CBF with remarkable sensitivity and temporal resolution. The wearable hardware has a modular design approach consisting solely of a laser diode as the source and a meticulously selected board camera as the detector. They both can be easily placed on the head of a subject to measure CBF with no additional optical elements. The SVS device can achieve a sampling rate of 80 Hz with minimal susceptibility to external disturbances. The device also achieves better SNR compared with traditional fiber-based SVS devices, capturing about 70 times more signal and showing superior stability and reproducibility. It is designed to be paired and distributed in multiple configurations around the head, and measure signals that exceed the quality of prior optical CBF measurement techniques. Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing non-invasive cerebral monitoring technologies. </p>

<p>For more than 25 years, the Instituto Argentino de Radioastronom\'ia has been directing efforts from basic research and radio astronomy development to technology transfer projects around Argentina's National Space Plan and to Small and Medium Enterprises. With the surge of COVID-19, our organization's transformation accelerated, bringing new opportunities and challenges which can be applied to impact health, education, processes and businesses. In this article, we explore our efforts to bridge the gap between basic science and the needs of our society. </p>

<p>A thorough analysis of the refractive index of eleven 1-alkyl-3-methylimidazolium-based ionic liquids with three different anions, tetrafluoroborate bis(trifluoromethylsulfonyl)imide, and trifluoromethanesulfonate, is reported. Refractive indices were estimated, in the temperature interval from 298.15 to 323.15 K, using an Abbe refractometer to determine the value at the sodium D line and white light spectral interferometry to obtain dispersion in the range of wavelengths from 400 to 1000 nm. The first part of the manuscript is focused on the dependence of refractive index with wavelength, temperature, cation alkyl chain length, and anion nature. Once the main features are detailed, and in order to explain the experimental trends, a model for the refractive index is considered where its square is expressed by a single resonance Sellmeier dispersion formula. This formula has two coefficients: the first one identifies the position of the resonance in the spectral axis, and the second one specifies its strength. It was found that, for a given compound, the resonances position is independent of temperature, while the strength varies linearly with it. This model reproduces successfully the experimental data within the refractive index uncertainty. Furthermore, the model allows calculating the thermo-optic coefficient and its wavelength dependence. </p>

<p>Tens of thousands of galaxy-galaxy strong lensing systems are expected to be discovered by the end of the decade. These will form a vast new dataset that can be used to probe subgalactic dark matter structures through its gravitational effects, which will in turn allow us to study the nature of dark matter at small length scales. This work shows how we can leverage machine learning to search through the data and identify which systems are most likely to contain dark matter substructure and thus can be studied in greater depth. We use a UNet, an image segmentation architecture, on a simulated strongly-lensed dataset with realistic sources (COSMOS galaxies), lenses (power-law elliptical profiles with multipoles and external shear), and noise. Our machine learning algorithm is able to quickly detect most substructure at high image resolution and subhalo concentration. At a false positive rate of $10\%$, we are able to identify systems with substructure at a true positive rate of $71\%$ for a subhalo mass range of $10^{9}\text{-}10^{9.5}\,M_\odot$. While recent detections are consistent with higher concentrations, we find that our algorithm fails at detecting subhalos with lower concentrations (expected from $\Lambda$CDM simulations). </p>

<p>Recently developed locally scaled self-interaction correction (LSIC) is a one-electron SIC method that, when used with a ratio of kinetic energy densities (z$_\sigma$) as iso-orbital indicator, performs remarkably well for both thermochemical properties as well as for barrier heights overcoming the paradoxical behavior of the well-known Perdew-Zunger self-interaction correction (PZSIC) method. In this work, we examine how well the LSIC method performs for the delocalization error. Our results show that both LSIC and PZSIC methods correctly describe the dissociation of H$_2^+$ and He$_2^+$ but LSIC is overall more accurate than the PZSIC method. Likewise, in the case of the vertical ionization energy of an ensemble of isolated He atoms, the LSIC and PZSIC methods do not exhibit delocalization errors. For the fractional charges, both LSIC and PZSIC significantly reduce the deviation from linearity in the energy versus number of electrons curve, with PZSIC performing superior for C, Ne, and Ar atoms while for Kr they perform similarly. The LSIC performs well at the endpoints (integer occupations) while substantially reducing the deviation. The dissociation of LiF shows both LSIC and PZSIC dissociate into neutral Li and F but only LSIC exhibits charge transfer from Li$^+$ to F$^-$ at the expected distance from the experimental data and accurate ab initio data. Overall both the PZSIC and LSIC methods reduce the delocalization errors substantially. </p>

<p>The total number of fatalities of an epidemic outbreak is a dramatic but extremely informative quantity. Knowledge of the statistics of this quantity allows the calculation of the mean total number of fatalities conditioned to the fact that the outbreak has surpassed a given number of fatalities, which is very relevant for risk assessment. However, the fact that the total number of fatalities seems to be characterized by a power-law tailed distribution with exponent (of the survival function) smaller than one poses an important theoretical difficulty, due to the non-existence of a mean value for such distributions. Cirillo and Taleb [Nature Phys. 16, 606 (2020)] propose a transformation from a so-called dual variable, which displays a power-law tail, to the total number of fatalities, which becomes bounded by the total world population. Here, we (i) show that such a transformation is ad hoc and unphysical; (ii) propose alternative transformations and distributions (also ad hoc); (iii) argue that the right framework for this problem is statistical physics, through finite-size scaling; and (iv) demonstrate that the real problem is not the non-existence of the mean value for power-law tailed distributions but the fact that the tail of the different theoretical distributions (which is what distinguishes one model from the other) is far from being well sampled with the available number of empirical data. Our results are also valid for many other hazards displaying (apparent) power-law tails in their size. </p>

<p>The rapid advancement of artificial intelligence technologies, particularly in recent years, has led to the emergence of several large parameter artificial intelligence weather forecast models. These models represent a significant breakthrough, overcoming the limitations of traditional numerical weather prediction models and indicating a potential second revolution for weather forecast. This study explores the evolution of these advanced artificial intelligence forecast models, and based on the identified commonalities, proposes the "Three Large Rules" for their development. We discuss the potential of artificial intelligence in revolutionizing numerical weather prediction, briefly outlining the underlying reasons for this potential. Additionally, we explore key areas for future development prospects for large artificial intelligence weather forecast models, integrating the entire numerical prediction process. Through an example that combines a large artificial intelligence model with ocean wave forecasting, we illustrate how forecasters can adapt and leverage the advanced artificial intelligence model. While acknowledging the high accuracy, computational efficiency, and ease of deployment of large artificial intelligence forecast models, we emphasize the irreplaceable values of traditional numerical forecasts. We believe that the optimal future of weather forecasting lies in achieving a seamless integration of artificial intelligence and traditional numerical models. Such a synthesis is anticipated to offer a more comprehensive and reliable approach for future weather forecasting. </p>

<p>A novel, data-driven model of deflagration-to-detonationtransition (DDT) is constructed for application to explosions of thermonuclear supernovae (SN Ia). The DDT mechanism has been suggested as the necessary physics process to obtain qualitative agreement between SN Ia observations and computational explosion models. This work builds upon a series of studies of turbulent combustion that develops during the final stages of the SN explosion. These studies suggest that DDT can occur in the turbulerized flame of the white dwarf via the Zel'dovich reactivity gradient mechanism when hotspots are formed. We construct a large database of direct numerical simulations that explore the parameter space of the Zel'dovich initiated detonation. We use this database to construct a neural network classifier for hotspots. The classifier is integrated into our supernova simulation code, FLASH/Proteus, and is used as the basis for a subgrid-scale model for DDT. The classifier is evaluated both in the training environment and in reactive turbulence simulations to verify its accuracy in realistic conditions. </p>

<p>The upgrade of the ATLAS Liquid Argon Calorimeter readout system calls for the development of radiation tolerant, high speed and low power serializer ASIC. We have designed a phase locked loop using a commercial 0.25 um Silicon-on-Sapphire (SoS) CMOS technology. Post-layout simulation indicates that tuning range is 3.79-5.01 GHz and power consumption is 104 mW. The PLL has been submitted for fabrication. The design and simulation results are presented. </p>

<p>Social physics explores responses to information exchange in a social network, and can be mapped down to bacterial collective signaling. Here, we explore how social inter-bacterial communication includes coordination of response to communication loss, as opposed to solitary searching for food, with collective response emergence at the population level. We present a 2-dimensional enclosed microfluidic environment that utilizes concentric rings of funnel ratchets, which direct motile E.coli bacteria towards a sole exit hole, an information ``black hole'', passage into the black hole irreversibly sweeps the bacteria away via hydrodynamic flow. We show that the spatiotemporal evolution of entropy production reveals how bacteria avoid crossing the hydrodynamic black hole information horizon. </p>

<p>A Newton's cradle is a device that demonstrates conservation of momentum using a series of identical colliding pendula. Despite being a famous example that demonstrates the concept of momentum conservation, extensive analysis of the system is rarely reported in literature. Here, we model the system as a collection of identical nonlinear spring pendulums performing viscoelastic collisions, which shows excellent agreement with experiments performed at various conditions. Dependence of its synchronization rate on four key system parameters are studied in detail. Interestingly, the resonance between radial and angular motion was found to modulate the synchronization rate. The proposed theory with full consideration of two dimensional motion and string hysteresis provides an excellent long-term prediction of the synchronized cradle motion. </p>

<p>We have realized a suspended, high-reflectivity focusing metamirror ($f\approx 10$ cm, $\mathcal{R} \approx 99\%$) by non-periodic photonic crystal patterning of a Si$_3$N$_4$ membrane. The design enables construction of a stable, short ($L$ = 30 $\mu$m), high-finesse ($\mathcal{F}&gt;600$) membrane cavity optomechanical system using a single plano dielectric end-mirror. We present the metamirror design, fabrication process, and characterization of its reflectivity using both free space and cavity-based transmission measurements. The mirror's effective radius of curvature is inferred from the transverse mode spectrum of the cavity. In combination with phononic engineering and metallization, focusing membrane mirrors offer a route towards high-cooperativity, vertically-integrated cavity optomechanical systems with applications ranging from precision force sensing to hybrid quantum transduction. </p>

<p>Transit-time damping (TTD) is a process in which the magnetic mirror force -- induced by the parallel gradient of magnetic field strength -- interacts with resonant plasma particles, leading to the collisionless damping of electromagnetic waves and the resulting energization of those particles through the perpendicular component of the electric field, $E_\perp$. In this study, we utilize the recently developed field-particle correlation technique to analyze gyrokinetic simulation data. This method enables the identification of the velocity-space structure of the TTD energy transfer rate between waves and particles during the damping of plasma turbulence. Our analysis reveals a unique bipolar pattern of energy transfer in velocity space characteristic of TTD. By identifying this pattern, we provide clear evidence of TTD's significant role in the damping of strong plasma turbulence. Additionally, we compare the TTD signature with that of Landau damping (LD). Although they both produce a bipolar pattern of phase-space energy density loss and gain about the parallel resonant velocity of the \Alfvenic waves, they are mediated by different forces and exhibit different behaviors as $v_\perp \to 0$. We also explore how the dominant damping mechanism varies with ion plasma beta $\beta_i$, showing that TTD dominates over LD for $\beta_i &gt; 1$. This work deepens our understanding of the role of TTD in the damping of weakly collisional plasma turbulence and paves the way to seek the signature of TTD using in situ spacecraft observations of turbulence in space plasmas. </p>

<p>Magnetic position sensors find extensive applications in various industrial sectors and consumer products. However, measuring angles in the full range of 0{\deg} to 360{\deg} in a wide field range using a single magnetic sensor remains a challenge. Here, we propose a magnetic position sensor based on a single Wheatstone bridge structure made from a single ferromagnetic layer. By measuring the anisotropic magnetoresistance (AMR) signal from the bridge and two sets of anomalous Nernst effect (ANE) signals from the transverse ports on two perpendicular Wheatstone bridge arms concurrently, we show that it is possible to achieve 0{\deg} to 360{\deg} angle detection using a single bridge sensor. The combined use of AMR and ANE signals allows to achieve a mean angle error in the range of 0.51{\deg} to 1.05{\deg} within a field range of 100 Oe to 10,000 Oe. </p>

<p>Surfaces (interfaces) dictate many physical and chemical properties of solid materials and adsorbates considerably affect these properties. Nitrogen molecules, which are the most abundant constituent in ambient air, are considered to be inert. Our study combining atomic force microscopy (AFM), X-ray photoemission spectroscopy (XPS), and thermal desorption spectroscopy (TDS) revealed that nitrogen and water molecules can self-assemble into two-dimensional domains, forming ordered stripe structures on graphitic surfaces in both water and ambient air. The stripe structures of this study were composed of approximately 90% and 10% water and nitrogen molecules, respectively, and survived in ultra-high vacuum (UHV) conditions at temperatures up to approximately 350 K. Because pure water molecules completely desorb from graphitic surfaces in a UHV at temperatures lower than 200 K, our results indicate that the incorporation of nitrogen molecules substantially enhanced the stability of the crystalline water hydrogen bonding network. Additional studies on interfacial gas hydrates can provide deeper insight into the mechanisms underlying formation of gas hydrates. </p>

<p>The interaction of electronic spin and molecular vibrations mediated by spin-orbit coupling governs spin relaxation in molecular qubits. I derive an extended molecular spin Hamiltonian that includes both adiabatic and non-adiabatic spin-dependent interactions, and I implement the computation of its matrix elements using state-of-the-art density functional theory. The new molecular spin Hamiltonian contains a novel spin-vibrational orbit interaction with non-adiabatic origin together with the traditional molecular Zeeman and zero-field splitting interactions with adiabatic origin. The spin-vibrational orbit interaction represents a non-Abelian Berry curvature on the ground-state electronic manifold and corresponds to an effective magnetic field in the electronic spin dynamics. I further develop a spin relaxation rate model that estimates the spin relaxation time via the two-phonon Raman process. An application of the extended molecular spin Hamiltonian together with the spin relaxation rate model to Cu(II) porphyrin, a prototypical $S=1/2$ molecular qubit, demonstrates that the spin relaxation time at elevated temperatures is dominated by the non-adiabatic spin-vibrational orbit interaction. The computed spin relaxation rate and its magnetic field orientation dependence are in excellent agreement with experimental measurements. </p>

<p>Laser sources power extreme data transmission as well as computing acceleration, access to ultrahigh-speed signaling, and sensing for chemicals, distance, and pattern recognition. The ever-growing scale of these applications drives innovation in multi-wavelength lasers for massively parallel processing. We report a nanophotonic Kerr-resonator circuit that consumes the power of an input laser and generates a soliton frequency comb at approaching unit efficiency. By coupling forward and backward propagation, we realize a bidirectional Kerr resonator that supports universal phase matching but also opens excess loss by double-sided emission. Therefore, we induce reflection of the resonator's forward, external-coupling port to favor backward propagation, resulting in efficient, one-sided soliton formation. Coherent backscattering with nanophotonics provides the control to put arbitrary phase-matching and efficient laser-power consumption on equal footing in Kerr resonators. In the overcoupled-resonator regime, we measure 65% conversion efficiency of a 40 mW input pump laser, and the nonlinear circuit consumes 97% of the pump, generating the maximum possible comb power. Our work opens up high-efficiency soliton formation in integrated photonics, exploring how energy flows in nonlinear circuits and enabling laser sources for advanced transmission, computing, quantum sensing, and artificial-intelligence applications. </p>

<p>A formal optimization procedure is reported for an external-compression supersonic intake with the twin objectives of maximizing the total pressure recovery while simultaneously minimizing the intake pressure drag. Prior to that, two key design modifications are introduced to the supersonic intake. First, a small cowl offset distance is applied, deliberately violating the shock-on-lip condition. This ensures an attached external shock at the cowl, which is beneficial, in return for a small, controlled flow spillage. Second, in a novel development, an internal wedge angle is introduced at the cowl lip, which forces the terminal shock to be a strong oblique shock. This also helps anchor the terminal shock at the cowl lip for a range of intake back-pressure values, and reduces the cowl external angle with respect to the free stream. The optimization problem is formulated based on axiomatic design theory with the two design parameters innovatively selected as the Oswatitsch ramp angle triplets and the cowl internal wedge angle, respectively. A multi-objective genetic algorithm (MOGA), assisted by a Kriging meta-model with infilling, is run in tandem with a RANS solver, to iteratively compute the Pareto front. The optimal design yields ramp angles that are somewhat smaller than the theoretical Oswatitsch values, yet returns a total pressure recovery very close to the Oswatitsch optimum while reducing the intake pressure drag significantly. </p>

<p>It was recently discovered that the time correlations of repeating fast radio bursts (FRBs) are similar to the properties of earthquake aftershocks. Motivated by the association between FRBs and magnetars, here we report two-point correlation function analyses in the time-energy space for the 563 periodic radio pulses detected by FAST and the 579 X-ray short bursts detected by NICER from the magnetar SGR 1935+2154, which is known to have generated FRBs. Although radio pulses are concentrated near the fixed phase of the rotational cycle, we find that when multiple pulses occur within a single cycle, their correlation properties (aftershock production probability, aftershock rate decaying in power of time, and more) are similar to those of extragalactic FRBs and earthquakes. A possible interpretation is that the radio pulses are produced by rupture of the neutron star crust, and the first pulse within one cycle is triggered by external force or torque periodically exerted on the crust. The source of the periodic external force may be the interaction of the magnetosphere with the material ejected in an outburst. For X-ray bursts, we found no significant correlation signal. The similarity in the aftershock nature between the periodic radio pulsation and FRBs is surprising, given that the two are energetically very different, and therefore the energy sources would be different. This suggests that the essence of FRB-like phenomena is starquakes, regardless of the energy source, and it is important to search for FRB-like bursts from neutron stars with various properties or environments. </p>

<p>Quantum metaphotonics has emerged as a cutting-edge subfield of meta-optics employing subwavelength resonators and their planar structures such as metasurfaces to generate, manipulate, and detect quantum states of light. It holds a great potential for the miniaturization of current bulky quantum optical elements by developing a design of on-chip quantum systems for various applications of quantum technologies. Over the past few years, this field has witnessed a surge of intriguing theoretical ideas, groundbreaking experiments, and novel application proposals. This perspective paper aims to summarize the most recent advancements and also provide a perspective on the further progress in this rapidly developing field of research. </p>

<p>In this paper, we investigate the possibility of explaining nonclassical correlations between two quantum systems in terms of quantum interferences between collective states of the two systems. We achieve this by mapping the relations between different measurement contexts in the product Hilbert space of a pair of two-level systems onto an analogous sequence of interferences between paths in a single-particle interferometer. The paradoxical relations between different measurement outcomes can then be traced to the distribution of probability currents in the interferometer. We show that the relation between probability currents and correlations can be represented by continuous conditional (quasi)probability currents through the interferometer, given by weak values; the violation of the noncontextual assumption is expressed by negative conditional currents in some of the paths. Since negative conditional currents correspond to the assignment of negative conditional probabilities to measurements results in different measurement contexts, the necessity of such negative probability currents represents a failure of noncontextual local realism. Our results help to explain the meaning of nonlocal correlations in quantum mechanics, and support Feynman's claim that interference is the origin of all quantum phenomena. </p>

<p>Despite the ongoing progress in integrated optical frequency comb technology, compact sources of short bright pulses in the mid-infrared wavelength range from 3 {\mu}m to 12 {\mu}m so far remained beyond reach. The state-of-the-art ultrafast pulse emitters in the mid-infrared are complex, bulky, and inefficient systems based on the downconversion of near-infrared or visible pulsed laser sources. Here we show a purely DC-driven semiconductor laser chip that generates one picosecond solitons at the center wavelength of 8.3 {\mu}m at GHz repetition rates. The soliton generation scheme is akin to that of passive nonlinear Kerr resonators. It relies on a fast bistability in active nonlinear laser resonators, unlike traditional passive mode-locking which relies on saturable absorbers or active mode-locking by gain modulation in semiconductor lasers. Monolithic integration of all components - drive laser, active ring resonator, coupler, and pump filter - enables turnkey generation of bright solitons that remain robust for hours of continuous operation without active stabilization. Such devices can be readily produced at industrial laser foundries using standard fabrication protocols. Our work unifies the physics of active and passive microresonator frequency combs, while simultaneously establishing a technology for nonlinear integrated photonics in the mid-infrared. </p>

<p>Complex field imaging, which captures both the amplitude and phase information of input optical fields or objects, can offer rich structural insights into samples, such as their absorption and refractive index distributions. However, conventional image sensors are intensity-based and inherently lack the capability to directly measure the phase distribution of a field. This limitation can be overcome using interferometric or holographic methods, often supplemented by iterative phase retrieval algorithms, leading to a considerable increase in hardware complexity and computational demand. Here, we present a complex field imager design that enables snapshot imaging of both the amplitude and quantitative phase information of input fields using an intensity-based sensor array without any digital processing. Our design utilizes successive deep learning-optimized diffractive surfaces that are structured to collectively modulate the input complex field, forming two independent imaging channels that perform amplitude-to-amplitude and phase-to-intensity transformations between the input and output planes within a compact optical design, axially spanning ~100 wavelengths. The intensity distributions of the output fields at these two channels on the sensor plane directly correspond to the amplitude and quantitative phase profiles of the input complex field, eliminating the need for any digital image reconstruction algorithms. We experimentally validated the efficacy of our complex field diffractive imager designs through 3D-printed prototypes operating at the terahertz spectrum, with the output amplitude and phase channel images closely aligning with our numerical simulations. We envision that this complex field imager will have various applications in security, biomedical imaging, sensing and material science, among others. </p>

<p>Recent advances in electron microscopy allowed the generation of high-energy electron wave packets of ultrashort duration. Here we present a non-perturbative S-matrix theory for scattering of ultrashort electron wave packets by atomic targets. We apply the formalism to a case of elastic scattering and derive a generalized optical theorem for ultrashort wave-packet scattering. By numerical simulations with 1-fs wave packets, we find in angular distributions of electrons on a detector one-fold and anomalous two-fold azimuthal asymmetries. We discuss how the asymmetries relate to the coherence properties of the electron beam, and to the magnitude and phase of the scattering amplitude. The essential role of the phase of the exact scattering amplitude is revealed by comparison with results obtained using the first-Born approximation. Our work paves a way for controlling electron-matter interaction by the lateral and transversal coherence properties of pulsed electron beams. </p>

<p>Monolayers of molybdenum disulfide (MoS2) are the most studied two-dimensional (2D) transition-metal dichalcogenides (TMDs), due to its exceptional optical, electronic, and opto-electronic properties. Recent studies have shown the possibility of incorporating a small amount of magnetic transition metals (e.g., Fe, Co, Mn, V) into MoS2 to form a 2D dilute magnetic semiconductor (2D-DMS). However, the origin of the observed ferromagnetism has remained elusive, due to the presence of randomly generated sulfur vacancies during synthesis that can pair with magnetic dopants to form complex dopant-vacancy configurations altering the magnetic order induced by the dopants. By combining high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) imaging with first-principles density functional theory (DFT) calculations and magnetometry data, we demonstrate the critical effects of sulfur vacancies and their pairings with vanadium atoms on the magnetic ordering in V-doped MoS2 (V-MoS2) monolayers. Additionally, we fabricated a series of field effect transistors on these V-MoS2 monolayers and observed the emergence of p-type behavior as the vanadium concentration increased. Our study sheds light on the origin of ferromagnetism in V-MoS2 monolayers and provides a foundation for future research on defect engineering to tune the electronic and magnetic properties of atomically thin TMD-based DMSs. </p>

<p>We present an interband cascade laser (ICL) emitting at 5.2 {\mu}m consisting of an 8-stage active region and a hybrid cladding composed of outer plasmon-enhanced InAs_0.915 Sb_0.085 and inner InAs/AlSb superlattice claddings. The hybrid cladding architecture shows a theoretical improvement in mode-confinement in the active region by 11.2 % according to the simulation. This is a consequence of a significantly lower refractive index of plasmon-enhanced claddings. The threshold current density is 242 A/cm^2 in pulsed operation at room temperature. This is the lowest value reported so far for ICLs emitting at wavelengths longer than 5 {\mu}m. We also report close to record value threshold power density of 840 W/cm^2 for ICLs at such wavelengths and a high voltage efficiency of 97.8 %. For broad area devices, pulsed operation is observed up to 65 C. </p>

<p>Accelerating the oxygen reduction reaction (ORR) is a main subject of electrocatalysis research.A critical step of ORR is the formation of the hydroperoxyl functional group (OOH*) intermediate. In this study, we investigate the influence of defects on facilitating the creation of OOH* in a zirconia-based cathode under hydroxyl group (-OH) adsorption. Simulations involve tetragonal pristine ZrO2 (111) surfaces with introduced oxygen vacancy (t-ZrO2-x) and nitrogen dopant (ZrO2-xNx). Density functional theory (DFT) is used to calculate the competitive -OH adsorption energies on pristine and defective surfaces. It reveals that oxynitride t-ZrO2-xNx and under-stoichiometric oxide t-ZrO2-x exhibit the lowest and highest susceptibility to -OH adsorption, respectively. Additionally, we have determined the Minimum Energy Pathway (MEP) for OOH* formation on t-ZrO2, t-ZrO2-x, and t-ZrO2-xNx with adsorbed-OH using the Nudged Elastic Band (NEB) approach with the COMB3 potential. Our results highlight the significant influence of defects on tuning the barrier energy of OOH* formation. The trend in the barrier energy formation of OOH* decreases in the order of t-ZrO2-x &gt; pristine t-ZrO2 &gt; t-ZrO2-xNx. We demonstrate that ZrO2-xNx is a promising candidate for accelerating ORR due to its lower barrier energy for OOH* creation. The findings from this study offer crucial insights for experimentalists aiming to develop optimal non-platinum-based cathode materials. </p>

<p>The realization of semiconductor structures with stable excitons at room temperature is crucial for the development of excitonics and polaritonics. Quantum confinement has commonly been employed for enhancing excitonic effects in semiconductor heterostructures. Dielectric confinement, which is potentially much stronger, has proven to be more difficult to achieve because of the rapid nonradiative surface/interface recombination in hybrid dielectric-semiconductor structures. Here, we demonstrate intense excitonic emission from bare GaN nanowires with diameters down to 6 nm. The large dielectric mismatch between the nanowires and vacuum greatly enhances the Coulomb interaction, with the thinnest nanowires showing the strongest dielectric confinement and the highest radiative efficiency at room temperature. In situ monitoring of the fabrication of these structures allows one to accurately control the degree of dielectric enhancement. These ultrathin nanowires may constitute the basis for the fabrication of advanced low-dimensional structures with an unprecedented degree of confinement. </p>

<p>Considerable attention has been given to the use of a nonlinear energy sink (NES) as a nonlinear vibration absorber. The NES is an efficient passive control device, that has been the focus of extensive research. In this paper, the modal interactions between a linear oscillator subjected to a harmonically external excitation and a grounded NES are studied. By applying the complexification-averaging method, the system is reduced from the four-dimensional (4D) real vector fields to the two-dimensional (2D) complex vector fields, namely the fast-slow system. Based on the fast-slow analysis, the fast subsystem, a one-dimensional (1D) complex vector field, is obtained from the fast-slow system, in which the linear oscillator's complex amplitude can be considered a bifurcation parameter. With the change of the bifurcation parameter, the critical manifold, obtained from the fast subsystem, presents distinct structures, that capture diverse types of modal interactions between the linear oscillator and the NES, verified by the numerical simulation results. The results indicate that the critical manifold can well predict the modal interactions on multiple time scales. The Hilbert spectrums verify that there is energy transfer at different time scales in the system. Additionally, the two special types of oscillations, namely the point-type oscillations and the ring-type oscillations, cannot be captured by the critical manifold. </p>

<p>In this paper, we study the dynamic behavior of a Rubber-Layer Roller Bearing (RLRB) interposed between a spring-mass elemental superstructure and a vibrating base. Thanks to the viscoelastic rolling contact between the rigid rollers and the rubber layers, the RLRB is able to provide a nonlinear damping behavior. The effect of the RLRB geometric and material parameters is investigated under periodic base excitation, showing that both periodic and aperiodic responses can be achieved. Specifically, since the viscoelastic damping is non-monotonic (bell shaped), there exist systemdynamic conditions involving the decreasing portion of the damping curve in which a strongly nonlinear behavior is experienced. In the second part of the paper, we investigate the effectiveness of the nonlinear device in terms of seismic isolation. Focusing on the mean shock of the Central Italy 2016 earthquake, we opportunely tune the material and geometrical RLRB parameters, showing that a significant reduction of both the peak and root-mean-square value of the inertial force acting on the superstructure is achieved, compared to the best performance of a linear base isolation system. </p>

<p>Muography is an innovative imaging technique using naturally produced elementary particles -- atmospheric muons -- like the X-rays of medical imaging. The modification of the particles flux -- by scattering or absorption --, reflects the contrasts in density within the medium and therefore offers the possibility for an image of the crossed volumes. The imaging process is based on the tracking of the particles which accounts for the absorption or the scattering of the muons trajectories. Neither the energy nor the identity of the particles (the so-called PID) is exploited since this information traditionally relies on the use of calorimeters and/or high intensity magnetic fields. Both these techniques hinder detector portability which in the case of muography is important and this renders them impractical for its purpose. In this paper we characterize the performance of a simple and small water Cherenkov detector capable on the one hand of providing some insights on energy and PID and on the other hand of improving the background rejection for a muon telescope. We tested a prototype of such water Cherenkov detector in combination with two small muon hodoscopes. Both systems are using the same opto-electronics chain -- optical fibers and pixellized photosensors -- and the same data acquisition (DAQ) readout system which ensures an easy integration and implementation within presently running systems. This article presents the test setup, the detector response to cosmic muons and its performance evaluation against a basic simulation of its geometry and detection principle. </p>

<p>We demonstrate the channeling of fluorescence photons from quantum dots (QDs) into guided modes of an optical nanofiber tip (ONFT). We deposit QDs on the ONFT using micro/nano fluidic technology. We measure the photon-counting and emission spectrum of fluorescence photons that are channeled into guided modes of the ONFT. The measured emission spectrum confirms the deposition of QDs on the ONFT. We perform numerical simulations to determine channeling efficiency ({\eta}) for the ONFT and a single dipole source (SDS) system. For the radially oriented SDS at the center of the facet of the ONFT, we found the maximum {\eta}-value of 44% at the fiber size parameter of 7.16, corresponding to the ONFT radius of 0.71 {\mu}m for the emission wavelength at 620 nm. Additionally, we investigate the SDS position dependence in transverse directions on the facet of the ONFT in view of keeping experimental ambiguities. The present fiber inline platform may open new avenues in quantum technologies. </p>

<p>The dynamical Franz-Keldysh effect, indicative of the transient light-matter interaction regime between quantum and classical realms, is widely recognized as an essential signature in wide bandgap condensed matter systems such as dielectrics. In this study, we applied the time-resolved transient absorption spectroscopy to investigate ultrafast optical responses in graphene, a zero-bandgap system. We observed in the gate-tuned graphene that the massless Dirac materials notably enhance intraband light-driven transitions, significantly leading to the giant dynamical Franz-Keldysh effect compared to the massive Dirac materials, a wide bandgap system. In addition, employing the angle-resolved spectroscopy, it is found that the perpendicular polarization orientation for the pump and the probe further pronounces the optical spectra to exhibit the complete fishbone structure, reflecting the unique pseudospin nature of Dirac cones. Our findings expand the establishment of emergent transient spectroscopy frameworks into not only zero-bandgap systems but also pseudospin-mediated quantum phenomena, moving beyond dielectrics. </p>

<p>Lightsails using Earth-based lasers for propulsion require passive stabilization to stay within the beam. This can be achieved through the sail's scattering properties, creating optical restoring forces and torques. Undamped restoring forces produce uncontrolled oscillations, which could jeopardize the mission, but it is not obvious how to achieve damping in the vacuum of space. Using a simple two-dimensional model we show that the Doppler effect and relativistic aberration of the propelling laser beam create damping terms in the optical forces and torques. The effect is similar to the Poynting-Robertson effect causing loss of orbital momentum of dust particles around stars, but can be enhanced by design of the sail's geometry. </p>

<p>The LOw Frequency ARray (LOFAR) was used to track the propagation of a TID containing embedded plasma structures which generated type 1 asymmetric quasi periodic scintillations (QPS: Maruyama, 1991) over a distance of &gt;1200 km across Northern Europe. Broadband trans ionospheric radio scintillation observations of these phenomena are, to our knowledge, unreported in the literature as is the ability to track asymmetric QPS generating plasma structures over such a distance. Type 1 asymmetric QPS are characterised by an initial broadband signal fade and enhancement which is then followed by 'ringing pattern' interference fringes. These are caused by diffractive fringing as the radio signal transitions through regions of relatively steep plasma density gradient at the trailing edge of the plasma structures. That the QPS retained their characteristics consistently over the full observing window implies that the plasma structures generating them likewise held their form for several hours, and over the full 1200 km distance. The most likely TID propagation altitude of 110 km was consistent with a persistent and non blanketing sporadic E region detected by the Juliusruh ionosondes, and direct measurements from co-located medium frequency radar. Co-temporal GNSS data was used to establish that these plasma density variations were very small, with a maximum likely amplitude of no more than +/- 0.02 TECu deviation from the background average. The observations were made between 0430-0800 UT on 17 December 2018 under very quiet geophysical conditions which possibly indicated a terrestrial source. Given the TID propagation direction, the source was likely located at high-latitude. </p>

<p>Here, we investigate the linear spatial stability of a parallel two-dimensional compressible boundary layer on an adiabatic plate by considering 2D and 3D disturbances. We employ the Compound Matrix Method for the first time for compressible flows, which, unlike other conventional techniques, can efficiently eliminate the stiffness of the original equation. Our study explores flow Mach numbers ranging from low subsonic to supersonic cases, to investigate the effects of flow compressibility and spanwise variation of disturbances. We get some interesting results depending on the flow Mach number. Mack (AGARD Report No. 709, 1984) reported the existence of two unstable modes for Mach number greater than 3 from viscous calculations (the so-called second mode) that subsequently fuse to create only one unstable zone when Mach number increases. Our calculations show a series of unstable modes for a Mach number greater than 3. The number of such modes is much more than two (unlike what Mack reports). The number and the frequency extent of the corresponding unstable zones increase with an increase in M, which is significantly higher than subsonic or low-supersonic cases. While the shape of the neutral curves for the second unstable mode for a Mach number greater than 4 is similar to the fused neutral curve shown by Mack for a Mach number of 4.8, the characteristics of higher-order spatially unstable modes considering the viscous stability of supersonic boundary layers remain unreported to the best of our knowledge. The last one is the most novel element in the reported results. </p>

<p>Three-dimensional CP-DNS of reacting iron particle dust clouds in a turbulent mixing layer are conducted. The simulation approach considers the Eulerian transport equations for the reacting gas phase and resolves all scales of turbulence, whereas the particle boundary layers are modelled employing the Lagrangian point-particle framework for the dispersed phase. The CP-DNS employs an existing sub-model for iron particle combustion that considers the oxidation of iron to FeO and that accounts for both diffusion- and kinetically-limited combustion. At first, the particle sub-model is validated against experimental results for single iron particle combustion considering various particle diameters and ambient oxygen concentrations. Subsequently, the CP-DNS approach is employed to predict iron particle cloud ignition and combustion in a turbulent mixing layer. The upper stream of the mixing layer is initialised with cold particles in air, while the lower stream consists of hot air flowing in the opposite direction. Simulation results show that turbulent mixing induces heating, ignition and combustion of the iron particles. Significant increases in gas temperature and oxygen consumption occur mainly in regions where clusters of iron particles are formed. Over the course of the oxidation, the particles are subjected to different rate-limiting processes. While initially particle oxidation is kinetically-limited it becomes diffusion-limited for higher particle temperatures and peak particle temperatures are observed near the fully-oxidised particle state. Comparing the present non-volatile iron dust flames to general trends in volatile-containing solid fuel flames, non-vanishing particles at late simulation times and a stronger limiting effect of the local oxygen concentration on particle conversion is found for the present iron dust flames in shear-driven turbulence. </p>

<p>The X-ray absorption (XA) spectra of aqueous ammonia and ammonium are computed using a combination of coupled cluster singles and doubles (CCSD) with different quantum mechanical and molecular mechanical embedding schemes. Specifically, we compare frozen Hartree--Fock (HF) density embedding, polarizable embedding (PE), and polarizable density embedding (PDE). Integrating CCSD with frozen HF density embedding is possible within the CC-in-HF framework, which circumvents the conventional system-size limitations of standard coupled cluster methods. We reveal similarities between PDE and frozen HF density descriptions, while PE spectra differ significantly. By including approximate triple excitations, we also investigate the effect of improving the electronic structure theory. The spectra computed using this approach show an improved intensity ratio compared to CCSD-in-HF. Charge transfer analysis of the excitations shows the local character of the pre-edge and main-edge, while the post-edge is formed by excitations delocalized over the first solvation shell and beyond. </p>

<p>We analyse the deformations of a cylindrical elastic body resulting from displacements in a varying gravitational field. </p>

<p>We analyze and present applications of a recently proposed empirical tight-binding scheme for investigating the effects of alloy disorder on various electronic and optical properties of semiconductor alloys, such as the band gap variation, the localization of charge carriers, and the optical transitions. The results for a typical antimony-containing III-V alloy, GaAsSb, show that the new scheme greatly improves the accuracy in reproducing the experimental alloy band gaps compared to other widely used schemes. The atomistic nature of the empirical tight-binding approach paired with a reliable parameterization enables more detailed physical insights into the effects of disorder in alloyed materials. </p>

<p>The Finite Fourier Series (FFS) Shape-Based (SB) trajectory approximation method has been used to rapidly generate initial trajectories that satisfy the dynamics, trajectory boundary conditions, and limitation on maximum thrust acceleration. The FFS SB approach solves a nonlinear programming problem (NLP) in searching for feasible trajectories. This paper extends the development of the FFS SB approach to generate sub optimal solutions. Specifically, the objective function of the NLP problem is modified to include also a measure for the time of flight. Numerical results presented in this paper show several solutions that differ from those of the original FFS SB ones. The sub-optimal trajectories generated using a time of flight minimization are shown to be physically feasible trajectories and potential candidates for direct solvers. </p>

<p>We report on the conception, fabrication and characterization of a new concept of optical fiber enabling a precise control of the ratio between the 2nd and 4th-order of chromatic dispersion (respectively \b{eta}2 and \b{eta}4) at 1.55 micro-meter which is at the heart of the Four-Wave-Mixing (FWM) generation. For conventional highly nonlinear fiber the sensitivity of this ratio to fiber geometry fluctuations is very critical, making the fabrication process challenging. The new design fiber reconciles the accurate control of chromatic dispersion properties and fabrication by standard stack and draw method, allowing a robust and reliable method against detrimental fluctuations parameters during the fabrication process. Experimental frequency conversion with FWM in the new design fiber is demonstrated. </p>

<p>An algorithm for efficiently calculating the expected size of single-seed cascade dynamics on networks is proposed and tested. The expected size is a time-dependent quantity and so enables the identification of nodes who are the most influential early or late in the spreading process. The measure is accurate for both critical and subcritical dynamic regimes and so generalises the nonbacktracking centrality that was previously shown to successfully identify the most influential single spreaders in a model of critical epidemics on networks. </p>

<p>The trajectories of a single bubble rising in the vicinity of a vertical solid wall are experimentally investigated. Distinct initial wall-bubble distances are considered for three different bubble rising regimes, i.e. rectilinear, planar zigzag, and spiral. The problem is defined by three control parameters, namely the Galilei number, $Ga$, the Bond number, $Bo$, and the initial dimensionless distance between the bubble centroid and the wall, $L$. We focus on high-Bond numbers, varying $L$ from 1 to 4, and compare the results with the corresponding unbounded case, $L \rightarrow \infty$. In all cases, the bubble deviates from the expected unbounded trajectory and migrates away from the wall as it rises due to the overpressure generated in the gap between the bubble and the wall. This repulsion is more evident as the initial wall-bubble distance decreases. Moreover, in the planar zigzagging regime, the wall is found to impose a preferential zigzagging plane perpendicular to it when $L$ is small enough. Only slight wall effects are observed in the velocity or the oscillation amplitude and frequency. The wall migration effect is more evident for the planar zigzagging case and less relevant for the rectilinear one. Finally, the influence of the vertical position of the wall is also investigated. When the wall is not present upon release, the bubbles have the expected behavior for the unbounded case and experience the migration only instants before reaching the wall edge. This repulsion is, in general, more substantial than in the initially-present-wall case. </p>

<p>Understanding the nature of the photoexcitation and ultrafast charge dynamics pathways in organic halide perovskite superlattices is key for their potential applications as tunable light emitters, photon harvesting materials and light-amplification systems. In this work we apply two-dimensional coherent electronic spectroscopy (2DES) to track in real time the formation of near-infrared optical excitons and their ultrafast decay into bi-excitons in CH(NH2)2PbI3 nanocube superlattices. On the picosecond timescale, the strong coupling between localized charges and specific lattice distortions leads to the progressive formation of long-lived localized trap states. The analysis of the temperature dependence of the excitonic intrinsic linewidth, as extracted by the anti-diagonal components of the 2D spectra, unveils a dramatic change of the excitonic coherence time across the cubic to tetragonal structural transition. Our results offer a new way to control and enhance the ultrafast coherent dynamics of photocarrier generation in hybrid halide perovskite synthetic solids. </p>

<p>Various types of measurement techniques, such as Light Detection and Ranging devices, anemometers, and wind vanes, are extensively utilized in wind energy to characterize the inflow. However, these methods typically gather data at limited points within local wind fields, capturing only a fraction of the wind field's characteristics at wind turbine sites, thus hindering detailed wind field analysis. This study introduces a framework using Physics-informed Neural Networks (PINNs) to assimilate diverse sensor data types. This includes line-of-sight wind speed, velocity magnitude and direction, velocity components, and pressure. Moreover, the Reynolds Averaged Navier-Stokes equations are integrated as physical constraints, ensuring that the neural networks accurately represent atmospheric flow dynamics. The framework accounts for the turbulent nature of atmospheric boundary layer flow by including turbulence eddy viscosity in the network outputs, enhancing the model's ability to learn and accurately depict large-scale flow structures. The reconstructed flow field and the effective wind speed are in good agreement with the actual data. Furthermore, a transfer learning strategy is employed for the online deployment of pre-trained PINN, which requires less time than that of the actual physical flow. This capability allows the framework to reconstruct wind flow fields in real time based on live data. In the demo cases, the maximum error between the effective wind speed reconstructed online and the actual value at the wind turbine site is only 3.7%. The proposed data assimilation framework provides a universal tool for reconstructing spatiotemporal wind flow fields using various measurement data. Additionally, it presents a viable approach for the online assimilation of real-time measurements. To facilitate the utilization of wind energy, our framework's source code is openly accessible. </p>

<p>In the present work we describe the design, construction, and testing of the optical prototype developed for the BOLDPET project, with the objective of creating a PET detection module with high spatial and time resolution. The BOLDPET technology uses an innovative detection liquid, trimethylbismuth, for detecting 511 keV $\gamma$-quanta resulting from positron annihilation. The optical signal is exclusively produced through the Cherenkov mechanism, and the produced photons are detected using Planacon microchannel-plate photomultiplier. We achieve an excellent time resolution of 150 ps (FWHM) within a sizable detection volume measuring 55 mm x 55 mm x 25 mm. Through detailed Geant4 simulations, we examine the limiting factors affecting time resolution and explore potential avenues for improvement. Furthermore, we demonstrate the feasibility of coarse 2D localization of interactions using the optical signal alone, achieving a precision of about 5-8 mm (FWHM) within the homogeneous detection volume. </p>

<p>Second order perturbation solutions of profiles of bubbles suspended in liquid and liquid gas interfaces when liquid all sinks in the bottom under different accelerations are derived. Six procedures are developed based on these solutions, and they are divided into two types. One takes coordinates of endpoints of profiles as inputs, and the other takes liquid volume or gas volume as inputs. Numerical simulation are performed with the Volume of Fluid method and numerical results are in good agreement with predictions of these procedures. Besides, the bigger the acceleration, the more flatter the bubble will be until all liquid sinks to the bottom. Effects of accelerations on bubbles shape must be considered. When liquid all sinks to the bottom, predictions of liquid volume with the same liquid meniscus height as inputs differs a lot under different accelerations. The most significant change of liquid volume is when Bond is much smaller than 1. Effects of accelerations and liquid contact angle on liquid gas interfaces must be considered during evaluating liquid residue, and these findings will be great helpful for liquid residue measurement and fine management in space. </p>

<p>Deep-learning electronic structure calculations show great potential for revolutionizing the landscape of computational materials research. However, current neural-network architectures are not deemed suitable for widespread general-purpose application. Here we introduce a framework of equivariant local-coordinate transformer, designed to enhance the deep-learning density functional theory Hamiltonian referred to as DeepH-2. Unlike previous models such as DeepH and DeepH-E3, DeepH-2 seamlessly integrates the simplicity of local-coordinate transformations and the mathematical elegance of equivariant neural networks, effectively overcoming their respective disadvantages. Based on our comprehensive experiments, DeepH-2 demonstrates superiority over its predecessors in both efficiency and accuracy, showcasing state-of-the-art performance. This advancement opens up opportunities for exploring universal neural network models or even large materials models. </p>

<p>It is shown that all spherical symmetric potentials are capable of producing dynamical symmetries in classical one-body motions, thanks to the inevitable existence of symmetry axes associated with turning points for corresponding trajectories. This will definitely expand the class of maximally superintegrable one-body motions in central potentials that until now was considered to include only the Newtonian and Hookean cases. A simple method is proposed to identify and characterize these dynamical symmetries. </p>

<p>Accurately characterizing the intensity and duration of strong-field femtosecond pulses within the interaction volume is crucial for attosecond science. However, this remains a major bottleneck, limiting accuracy of the strong-field, and in particular, high harmonic generation experiments. We present a novel scheme for the in situ measurement and control of spatially resolved strong-field femtosecond pulse intensity and duration within the interaction focal region. Our approach combines conjugate focal imaging with in situ ion measurements using gas densities pertinent to attosecond science experiments. Independent measurements in helium and argon, accompanied by a fitting to a strong field ionization dynamic model, yield accurate and consistent results across a wide range of gas densities and underscores the significance of double ionization, as well as barrier suppression ionization. Direct spatially resolved characterization of the driving laser is a critical step towards resolving the averaging problem in the interaction volume, paving the way for more accurate and reliable attosecond experiments. </p>

<p>The structure of data organization is widely recognized as having a substantial influence on the efficacy of machine learning algorithms, particularly in binary classification tasks. Our research provides a theoretical framework suggesting that the maximum potential of binary classifiers on a given dataset is primarily constrained by the inherent qualities of the data. Through both theoretical reasoning and empirical examination, we employed standard objective functions, evaluative metrics, and binary classifiers to arrive at two principal conclusions. Firstly, we show that the theoretical upper bound of binary classification performance on actual datasets can be theoretically attained. This upper boundary represents a calculable equilibrium between the learning loss and the metric of evaluation. Secondly, we have computed the precise upper bounds for three commonly used evaluation metrics, uncovering a fundamental uniformity with our overarching thesis: the upper bound is intricately linked to the dataset's characteristics, independent of the classifier in use. Additionally, our subsequent analysis uncovers a detailed relationship between the upper limit of performance and the level of class overlap within the binary classification data. This relationship is instrumental for pinpointing the most effective feature subsets for use in feature engineering. </p>

<p>This study investigates the role of spatial segregation, prompted by competition avoidance, as a key mechanism for emergent coexistence within microbial communities. Recognizing these communities as complex adaptive systems, we challenge the sufficiency of pairwise interaction models and consider the impact of spatial dynamics. We developed an individual-based spatial simulation depicting bacterial movement through a pattern of random walks influenced by competition avoidance, leading to the formation of spatially segregated clusters. This model was integrated with a Lotka-Volterra metapopulation framework focused on competitive interactions. Our findings reveal that spatial segregation alone can lead to emergent coexistence in microbial communities, offering a new perspective on the formation of stable, coexisting microbe clusters that differ significantly from their behavior in isolated pairwise interactions. This study underscores the importance of considering spatial factors in understanding the dynamics of microbial ecosystems. </p>

<p>The assembly of the ATLAS Inner Tracker requires the construction of 19,000 silicon strip sensor detector modules in eight different geometries. Modules will be assembled and tested at 31 institutes on four continents from sensors, readout chips, and flexes. In order to adhere to the module specifications defined for sufficient tracking performance, a rigorous programme of quality control (QC) was established to cover components at every stage of assembly. This contribution presents an overview of the QC programme for ITk strip tracker modules, issues encountered during the pre-production phase (5% of the production volume), and their solutions. </p>

<p>The study of neutrino oscillation at accelerators is limited by systematic uncertainties, in particular on the neutrino flux, cross-section, and energy estimates. These systematic uncertainties could be eliminated by a novel experimental technique: neutrino tagging. This technique relies on a new type of neutrino beamline and its associated instrumentation which would enable the kinematical reconstruction of the neutrinos produced in $\pi^{\pm} \to \mu^{\pm} \nu_\mu$ and $K^{\pm} \to \mu^{\pm} \nu_\mu$ decays. This article presents a proof-of-concept study for such a tagged beamline, aiming to serve a long baseline neutrino experiment exploiting a megaton scale natural water Cherenkov detector. After optimizing the target and the beamline optics to first order, a complete Monte Carlo simulation of the beamline has been performed. The results show that the beamline provides a meson beam compatible with the operation of the spectrometer, and delivers a neutrino flux sufficient to collect neutrino samples with a size comparable with similar experiments and with other un-tagged long-baseline neutrino experimental proposals. </p>

<p>We recently found wall-bounded turbulence to suppress and control bipolar triboelectric charging of particles of identical material. This control is due to fluid modifying the motion of light particles. Thus, the particles' charge distribution depends on their Stokes number distribution. More specifically, fluid forces narrow the bandwidth of the charge distribution, and bipolar charging reduces dramatically. Consequently, not the smallest but mid-sized particles collect the most negative charge. However, the influence of the Reynolds number or particle concentration on bipolar charging of polydisperse particles is unknown. This paper presents the charging simulations of same-material particles the in different wall-bounded flows. In a comprehensive study, we vary the Reynolds number from $Re_\tau=$ $150$ to $210$ and the particle number density from $4 \times 10^9 \ \mathrm{m}^{-3}$ to $1 \times 10^{10} \ \mathrm{m}^{-3}$ to further explore the influence of the carrier flow on bipolar charging. We model charge transfer based on the balance of transferable charge species. Such species can represent adsorbed ions transferred during collisions or free electrons captured into a lower energy state on the other surface. The turbulent flow is modeled via Direct Numerical Simulations (DNS) and is coupled to the particulate phase modeled via the Discrete Element Method (DEM). Overall, our multiphysics approach couples the fluid dynamics, electric field, triboelectric charging, and particle momentum into one complex simulation. </p>

<p>We present a highly-optimized thread-safe lattice Boltzmann model in which the non-equilibrium part of the distribution function is locally reconstructed via recursivity of Hermite polynomials. Such a procedure allows the explicit incorporation of non-equilibrium moments of the distribution up to the order supported by the lattice. Thus, the proposed approach increases accuracy and stability at low viscosities without compromising performances and amenability to parallelization with respect to standard lattice Boltzmann models. The high-order thread-safe version, successfully employed here to simulate the flow in a smooth straight channel at $Re_{\tau}=180$ and the axisymmetric turbulent jet at $Re=7000$, a) achieves peak performances ($\sim 5 \; TeraFlop/s$ and an arithmetic intensity of $\sim 7\; FLOP/byte$ on single GPU) by significantly reducing the memory footprint, b) retains the algorithmic simplicity of standard lattice Boltzmann computing and c) allows to perform stable simulations at vanishingly low viscosities. Our findings open attractive prospects for high-performance simulations of realistic turbulent flows on GPU-based architectures. Such expectations are confirmed by the excellent agreement among lattice Boltzmann, experimental, and DNS reference data. </p>

<p>The electronic structure and magnetic properties of a newly predicted stable ternary compound La$_{18}$Co$_{28}$Pb$_{3}$ are studied using electronic structure analysis. The ground state of this compound is ferromagnetic, with three positions of nonequivalent magnetic Co atoms. A strong dependence of magnetic properties on volume shows that this system is situated near the point of magnetic instability. A coexistence of high- and low-spin ferromagnetic states as a function of volume near equilibrium was discovered. A corresponding spin tunneling splitting was estimated. The stability of the theoretically predicted magnetic ground state was tested by varying the Hubbard parameter. The thermal spin fluctuations were added to estimate the paramagnetic moment and a Curie temperature. The necessity of experimental verification of the obtained results is emphasized. </p>

<p>We report mainly on the global flagship outreach activity in particle physics: the International Particle Physics Masterclasses. It is illustrated on the example of Slovakia and the Czech Republic. The Masterclasses are described and their long-term impact is studied with the help of a survey among former participants. The positive effect of Masterclasses in shifting the attitude towards science is shown. We also discuss the modification of Masterclasses for a pandemic situation. Finally, we present CASCADE projects as a way to foster the interest in a field which has been strongly enhanced by previous experience, e.g., at Masterclasses. </p>

<p>Why does the Sun have a radius around 696000~km? We will see in this article that dimensional arguments can be used to understand the size of the Sun and of a few other things along the way. These arguments are not new and can be found scattered in textbooks. They are presented here in a succinct way in order to better confront the kinematic and mechanical viewpoints on size. We derive and compare a number of expressions for the size of the Sun and relate large and small scales. We hope that such presentation will be useful to students, instructors and researchers alike. </p>

<p>Biomolecular condensates help organize the cell cytoplasm and nucleoplasm into spatial compartments with different chemical compositions. A key feature of such compositional patterning is the local enrichment of enzymatically active biomolecules which, after transient binding via molecular interactions, catalyze reactions among their substrates. Thereby, biomolecular condensates provide a spatial template for non-uniform concentration profiles of substrates. In turn, the concentration profiles of substrates, and their molecular interactions with enzymes, drive enzyme fluxes which can enable novel non-equilibrium dynamics. To analyze this generic class of systems, with a current focus on self-propelled droplet motion, we here develop a self-consistent sharp interface theory. In our theory, we diverge from the usual bottom-up approach, which involves calculating the dynamics of concentration profiles based on a given chemical potential gradient. Instead, reminiscent of control theory, we take the reverse approach by deriving the chemical potential profile and enzyme fluxes required to maintain a desired condensate form and dynamics. The chemical potential profile and currents of enzymes come with a corresponding power dissipation rate, which allows us to derive a thermodynamic consistency criterion for the passive part of the system (here, reciprocal enzyme-enzyme interactions). As a first use case of our theory, we study the role of reciprocal interactions, where the transport of substrates due to reactions and diffusion is, in part, compensated by redistribution due to molecular interactions. More generally, our theory applies to mass-conserved active matter systems with moving phase boundaries. </p>

<p>Construction of ohmic contact is a long-standing challenge encountered by two-dimensional (2D) device fabrication and integration. van der Waals contacts, as a new solution for 2D contact construction, can effectively eliminate issues, such as Fermi-level pining and formation of Schottky barrier. Nevertheless, current research primarily considers energy band alignment, while ignoring the transverse momentum conservation of charge carriers during the quantum tunneling across the van der Waals contacts. In this study, by comparing the IV characteristics and tunneling spectra of graphene-silicon tunneling junctions with various interfacial transverse momentum distribution, we demonstrate the importance of charge carrier momentum in constructing high-performance 2D contact. Further, by conditioning the van der Waals contacts and minimizing the momentum mismatch, we successfully enhanced the quantum tunneling current with more than three orders of magnitude and obtain ohmic-like contact. Our study provide and effective method for the construction of direction 2D-3D contact with low resistance and can potentially benefit the heterogeneous of integration of 2D materials in post-CMOS architectures. </p>

<p>Quantum computing shows great potential, but errors pose a significant challenge. This study explores new strategies for mitigating quantum errors using artificial neural networks (ANN) and the Yang-Baxter equation (YBE). Unlike traditional error correction methods, which are computationally intensive, we investigate artificial error mitigation. The manuscript introduces the basics of quantum error sources and explores the potential of using classical computation for error mitigation. The Yang-Baxter equation plays a crucial role, allowing us to compress time dynamics simulations into constant-depth circuits. By introducing controlled noise through the YBE, we enhance the dataset for error mitigation. We train an ANN model on partial data from quantum simulations, demonstrating its effectiveness in correcting errors in time-evolving quantum states. </p>

<p>In the limit of sufficiently fast rotation, rotating mirror traps are known to be stable against the loss-cone modes associated with conventional (non-rotating) mirrors. This paper calculates how quickly a mirror configuration must rotate in order for several of these modes to be stabilized (in particular, the high-frequency convective loss cone, drift cyclotron loss cone, and Dory-Guest-Harris modes). Commonalities in the stabilization conditions for these modes then motivate a modified formulation of the Gardner free energy and diffusively accessible free energy to be used for systems in which the important modes have wave vectors that are orthogonal or nearly orthogonal to the magnetic field, as well as a modification to include the effects of a loss region in phase space. </p>

<p>Constant-potential molecular dynamics (MD) simulations are indispensable for understanding the capacitance, structure, and dynamics of electrical double layers (EDLs) at the atomistic level. However, the classical constant-potential method, relying on the so-called 'floating charges' to keep electrode equipotential, overlooks quantum effects on the electrode and always underestimates EDL capacitance for typical electrochemical systems featuring metal electrodes in aqueous electrolytes. Here, we propose a universal theoretical framework as moment-tensor-based constant potential method (mCPM) to capture electronic structure variations with electric moments. For EDLs at Au(111) electrodes, mCPM-based MD reveals bell-shaped capacitance curves in magnitude and shape both quantitatively consistent with experiments. It further unveils the potential-dependent local electric fields, agreeing with experimental observations of redshift vibration of interfacial water under negative polarization and predicting a blueshift under positive polarization, and identifies geometry dependence of two time scales during EDL formation. </p>

<p>Flocking, as paradigmatically exemplified by birds, is the coherent collective motion of active agents. As originally conceived, flocking emerges through alignment interactions between the agents. Here, we report that flocking can also emerge through interactions that turn agents away from each other. Combining simulations, kinetic theory, and experiments, we demonstrate this mechanism of flocking in self-propelled Janus colloids with stronger repulsion on the front than on the rear. The polar state is stable because particles achieve a compromise between turning away from left and right neighbors. Unlike for alignment interactions, the emergence of polar order from turn-away interactions requires particle repulsion. At high concentration, repulsion produces flocking Wigner crystals. Whereas repulsion often leads to motility-induced phase separation of active particles, here it combines with turn-away torques to produce flocking. Therefore, our findings bridge the classes of aligning and non-aligning active matter. Our results could help to reconcile the observations that cells can flock despite turning away from each other via contact inhibition of locomotion. Overall, our work shows that flocking is a very robust phenomenon that arises even when the orientational interactions would seem to prevent it. </p>

<p>This study employs gyrokinetic simulations to investigate ion temperature gradient (ITG) turbulence in realistic fusion plasmas featuring reverse magnetic shear. Negative magnetic shear is found to suppress the ITG instability due to the scarcity of mode rational surfaces, as evidenced by a comparison of instabilities for different magnetic shears. This suppression effect remains observable in nonlinear turbulence with zonal flow artificially eliminated, where the emergence of turbulence solitons aligns with mode rational surface peaks. However, the suppression effect diminishes in the presence of self-consistently generated zonal flow, along with the occurance of turbulence solitons. The zonal flow is found to originated from a force driven process by the primary instability, instead of the conventional modulational instability. The study further reveals a remarkable phenomenon that the Dimits shift no longer exists for negative magnetic shear, which are attributed to the weakness of zonal flow around marginal stability. However, away from marginal stability, the turbulent transport is primarily regulated by the zonal flow regardless of different magnetic shears. </p>

<p>About a hundred years ago the Russian biologist A. Gurwitsch, based on his experiments with onion plants by measuring their growth rate, made the hypothesis that plants emitted a weak electromagnetic field which somehow influenced cell growth. This interesting observation remained fundamentally ignored by the scientific community and only in the 1950s the electromagnetic emission from some plants was measured using a photomultiplier used in single counting mode. Later, in the 80s several groups in the world started some extensive work to understand the origin and role of this ultra-weak emission, hereby called biophotons, coming from living organisms. Biophotons are an endogenous very small production of photons in the visible energy range in and from cells and organism, and this emission is characteristic of alive organisms. Today there is no doubt that biophotons really exist, this emission has in fact been measured by many groups and on many different living organisms, from humans to bacteria. On the contrary, the origin of biophotons and whether organisms use them in some way to exchange information is not yet well known; no model proposed since now is really capable of reproducing and interpreting the great variety of experimental data coming from the many different living systems measured so far. In this brief review we present our experimental work on biophotons coming from germinating seeds, the main experimental results and some methods we are using to analyze the data in order to open the door for interpretative models of this phenomenon and clarifying its function in the regulation and communication between cells and living organisms. We also discuss some ideas on how to increase the signal-to-noise ratio of the measured signal to have new experimental possibilities that allow the measurement and the characterization of currently unmeasurable quantities. </p>

<p>This paper presents the experimental results on research of growth processes of GaAs layers on silicon substrates by molecular beam epitaxy. The formation of buffer Si layer in a single growth process has been found to significantly improve the crystalline quality of the GaAs layers formed on its surface, as well as to prevent the formation of anti-phase domains both on offcutted towards the [110] direction and on singular Si(100) substrates. It has been demonstrated that the use of cyclic thermal annealing at temperatures 350-660{\deg}C in the flow of arsenic atoms makes it possible to reduce the number of threading dislocations and increase the smoothness of the GaAs layers surface. At the same time, the article considers possible mechanisms that lead to an improvement in the quality of the surface layers of GaAs. It is shown that the thus obtained GaAs layers of submicron thickness on the singular Si(100) substrates have a mean square value of surface roughness 1.9 nm. The principal possibility of using thin GaAs layers on silicon as templates for forming on them light-emitting semiconductor heterostructures with active area based on self-organizing InAs quantum dots and InGaAs quantum well is presented. They are shown to exhibit photoluminescence at 1.2 um at room temperature. </p>

<p>Green's function characterizes a partial differential equation (PDE) and maps its solution in the entire domain as integrals. Finding the analytical form of Green's function is a non-trivial exercise, especially for a PDE defined on a complex domain or a PDE with variable coefficients. In this paper, we propose a novel boundary integral network to learn the domain-independent Green's function, referred to as BIN-G. We evaluate the Green's function in the BIN-G using a radial basis function (RBF) kernel-based neural network. We train the BIN-G by minimizing the residual of the PDE and the mean squared errors of the solutions to the boundary integral equations for prescribed test functions. By leveraging the symmetry of the Green's function and controlling refinements of the RBF kernel near the singularity of the Green function, we demonstrate that our numerical scheme enables fast training and accurate evaluation of the Green's function for PDEs with variable coefficients. The learned Green's function is independent of the domain geometries, forcing terms, and boundary conditions in the boundary integral formulation. Numerical experiments verify the desired properties of the method and the expected accuracy for the two-dimensional Poisson and Helmholtz equations with variable coefficients. </p>

<p>A theoretical formulation of lattice Boltzmann models on a general curvilinear coordinate system is presented. It is based on a volumetric representation so that mass and momentum are exactly conserved as in the conventional lattice Boltzmann on a Cartesian lattice. In contrast to some previously existing approaches for arbitrary meshes involving interpolation approximations among multiple neighboring cells, the current formulation preserves the fundamental one-to-one advection feature of a standard lattice Boltzmann method on a uniform Cartesian lattice. The new approach is built on the concept that a particle is moving along a curved path. A discrete space-time inertial force is derived so that the momentum conservation is exactly ensured for the underlying Euclidean space. We theoretically show that the new scheme recovers the Navier-Stokes equation in general curvilinear coordinates in the hydrodynamic limit, along with the correct mass continuity equation. </p>

<p>Using smartphones for mobile self-testing could provide easy access to speech intelligibility testing for a large proportion of the world population. The matrix sentence test (MST) is an ideal candidate in this context, as it is a repeatable and accurate speech test currently available in 20 languages. In clinical practice, an experimenter uses professional audiological equipment and supervises the MST, which is infeasible for smartphone-based self-testing. Therefore, it is crucial to investigate the feasibility of self-conducting the MST on a smartphone, given its restricted screen size. </p> <p>We compared the traditional closed matrix user interface, displaying all 50 words of the MST in a 10x5 matrix, and three alternative, newly-developed interfaces (slide, type, wheel) regarding SRT consistency, user preference, and completion time, across younger normal hearing (N=15) and older hearing impaired participants (N=14). </p> <p>The slide interface is most suitable for mobile implementation. While the traditional matrix interface works well for most participants, not every participant could perform the task with this interface. The newly-introduced slide interface could serve as a plausible alternative on the small screen of a smartphone. This might be more attractive for elderly patients that may exhibit more tactile and visual impairments than our test subjects employed here. </p>

<p>Synthetic aperture radar (SAR) utilizes an aircraft-carried antenna to emit electromagnetic pulses and detect the returning echoes. As the aircraft travels across a designated area, it synthesizes a large virtual aperture to improve image resolution. Inspired by SAR, we introduce synthetic aperture ptycho-endoscopy (SAPE) for micro-endoscopic imaging beyond the diffraction limit. SAPE operates by hand-holding a lensless fiber bundle tip to record coherent diffraction patterns from specimens. The fiber cores at the distal tip modulate the diffracted wavefield within a confined area, emulating the role of the 'airborne antenna' in SAR. The handheld operation introduces positional shifts to the tip, analogous to the aircraft's movement. These shifts facilitate the acquisition of a ptychogram and synthesize a large virtual aperture extending beyond the bundle's physical limit. We mitigate the influences of hand motion and fiber bending through a low-rank spatiotemporal decomposition of the bundle's modulation profile. Our tests on various samples demonstrate the ability to resolve a 548-nm linewidth and achieve a depth of field exceeding 2 cm. Notably, the aperture synthesizing process surpasses the diffraction limit set by the bundle's maximum collection angle. Requiring no interferometric measurements, SAPE heralds new opportunities for super-resolution endoscopic imaging beyond traditional optical constraints. </p>

<p>The effect of substrate topography on the settlement of coral larvae in wave-driven oscillatory flow is investigated using computational fluid dynamics coupled to a 2D agent-based simulation of individual larvae. Substrate topography modifies the boundary layer flow by generating vortices within roughness features that can be ejected into the bulk flow, directly influencing larval transport and settlement. In agreement with recent experimental findings, millimeter-scale ridged topographies were found to increase settlement compared to sub-mm feature heights. At this length scale, ridge spacing-to-height ratios of 10 to 20, spacings of more than 30 coral larval body lengths, resulted in the highest settlement rates. These optimal topographies produce a high averaged vertical velocity variance in the bulk flow, indicating that vertical larval movement to benthic surfaces is dominated by passive transport driven by recirculatory flow structures. Indeed, larval settlement was found to be positively correlated with mean vertical velocity variance, and settlement results with substrates comprising complex multiscale roughness were quantitatively similar to those with a simple rectangular model. Our findings reveal how substrates can be designed with surface features to promote larval settlement in natural flow conditions above shallow coral reefs independent of biological cues and substrate material composition. </p>

<p>We show theoretically that the mean turbulent dynamics can be described by a kinetic theory representation with a single free relaxation time that depends on space and time. A proper kinetic equation is constructed from averaging the Klimontovich-type equation for fluid elements satisfying the Navier-Stokes hydrodynamics exactly. The turbulent kinetic energy plays the role of temperature in standard molecular thermodynamics. We show that the dynamics of turbulent fluctuations resembles a collision process that asymptotically drives the mean distribution towards a Gaussian (Maxwell-Boltzmann) equilibrium form. Non-Gaussianity arises directly from non-equilibrium shear effects. The present framework overcomes the bane of most conventional turbulence models and theoretical frameworks arising from the lack of scale separation between the mean and fluctuating scales of the Navier-Stokes equation with an eddy viscous term. An averaged turbulent flow in the present framework behaves more like a flow of finite Knudsen number with finite relaxation time, and is thus more suitably described in a kinetic theory representation. </p>

<p>As quantum technologies continue to advance, the simulation of open quantum dynamics using quantum algorithms has garnered increasing attention. In this paper, we present a universal and compact theory, the dissipaton-embedded quantum master equation in second quantization (DQME-SQ), for simulating non-Markovian open quantum dynamics. The DQME-SQ theory is not only inprinciple exact for both bosonic and fermionic environments that satisfy Gaussian statistics, but also possesses a compact form that facilitates quantum simulations. To demonstrate the practicality of the DQME-SQ theory, we conduct digital quantum simulations of spin-boson and Anderson impurity models, highlighting the significant non-Markovian dynamical effects. The proposed theoretical framework establishes a solid foundation for the accurate and efficient simulation of complex open quantum systems. </p>

<p>Space missions that use low-thrust propulsion technology are becoming increasingly popular since they utilize propellant more efficiently and thus reduce mission costs. However, optimizing continuous-thrust trajectories is complex, time-consuming, and extremely sensitive to initial guesses. Hence, generating approximate trajectories that can be used as reliable initial guesses in trajectory generators is essential. This paper presents a semi-analytic approach for designing planar and three-dimensional trajectories using Hills equations. The spacecraft is assumed to be acted upon by a constant thrust acceleration magnitude. The proposed equations are employed in a Nonlinear Programming Problem (NLP) solver to obtain the thrust directions. Their applicability is tested for various design scenarios like orbit raising, orbit insertion, and rendezvous. The trajectory solutions are then validated as initial guesses in high-fidelity optimal control tools. The usefulness of this method lies in the preliminary stages of low-thrust mission design, where speed and reliability are key. </p>

<p>Dark matter (DM) with masses of order an electronvolt or below can have a non-zero coupling to electromagnetism. In these models, the ambient DM behaves as a new classical source in Maxwell's equations, which can excite potentially detectable electromagnetic (EM) fields in the laboratory. We describe a new proposal for using integrated photonics to search for such DM candidates with masses in the 0.1 eV - few eV range. This approach offers a wide range of wavelength-scale devices like resonators and waveguides that can enable a novel and exciting experimental program. In particular, we show how refractive index-modulated resonators, such as grooved or periodically-poled microrings, or patterned slabs, support EM modes with efficient coupling to DM. When excited by the DM, these modes can be read out by coupling the resonators to a waveguide that terminates on a micron-scale-sized single photon detector, such as a single pixel of an ultra-quiet charge-coupled device or a superconducting nanowire. We then estimate the sensitivity of this experimental concept in the context of axion-like particle and dark photon models of DM, showing that the scaling and confinement advantages of nanophotonics may enable exploration of new DM parameter space. </p>

<p>Superconducting transition-edge sensors (TES) are extremely sensitive microcalorimeters used as photon detectors with unparalleled energy resolution. They have found application from measuring astronomical spectra through to determining the quantum property of photon-number, $\hat{n} {=} \hat{a}^{\dag} \hat{a}$, for energies from 0.6-2.33eV. However, achieving optimal energy resolution requires considerable data acquisition -- on the order of 1GB/min -- followed by post-processing, which does not allow access to energy information in real time. Here we use a custom hardware processor to process TES pulses while new detections are still being registered, allowing photon-number to be measured in real time as well as reducing data requirements by orders-of-magnitude. We resolve photon number up to n=16 -- achieving up to parts-per-billion discrimination for low photon numbers on the fly -- providing transformational capacity for applications of TES detectors from astronomy through to quantum technology. </p>

<p>We study the interaction of two counter-propagating electromagnetic waves in vacuum in the Born-Infeld electrodynamics. First we investigate the Born case for linearly polarized beams, ${\bf E}\cdot{\bf B}=0$, i. e. $\mathfrak{G}^2=0$ (crossed field configuration), which is identical for Born-Infeld and Born electrodynamics; subsequently we study the general Born-Infeld case for beams which are nonlinearly polarized, $\mathfrak{G}^2\neq0$. In both cases, we show that the nonlinear field equations decouple using self-similar solutions and investigate the shock wave formation. We show that the only nonlinear solutions are exceptional travelling wave solutions which propagate with constant speed and which do not turn into shocks for our approximation. We obtain two types of exceptional wave solutions, then we numerically analyze which phase velocities correspond to the counter- or co-propagating beams and subsequently we determine the direction of propagation of the exceptional waves. </p>

<p>The interaction between the supersonic jet and background can influence the process of star formation, and this interaction also results in a change of the jet's velocity, direction and density through shock waves. However, due to the limitations of current astronomical facilities, the fine shock structure and the detailed interaction process still remain unclear. Here we investigate the plasma dynamics under different collision states through laser-driven experiments. A double-shock structure is shown in the optical diagnosis for collision case, but the integrated self-emitting X-ray characteristic is different. For solid plastic hemisphere obstacle, two-layer shock emission is observed, and for the relatively low-density laser-driven plasma core, only one shock emission is shown. And the plasma jets are deflected by $50 ^{\circ}$ through the interaction with the high-density background in both cases. For collisionless cases, filament structures are observed, and the mean width of filaments is roughly the same as the ion skin depth. High-energy electrons are observed in all interaction cases. We present the detailed process of the shock formation and filament instability through 2D/3D hydrodynamic simulations and particle-in-cell simulations respectively. Our results can also be applied to explain the shock structure in the Herbig-Haro (HH) 110/270 system, and the experiments indicate that the impact point may be pushed into the inside part of the cloud. </p>

<p>A statistical emulator can be used as a surrogate of complex physics-based calculations to drastically reduce the computational cost. Its successful implementation hinges on an accurate representation of the nonlinear response surface with a high-dimensional input space. Conventional "space-filling" designs, including random sampling and Latin hypercube sampling, become inefficient as the dimensionality of the input variables increases, and the predictive accuracy of the emulator can degrade substantially for a test input distant from the training input set. To address this fundamental challenge, we develop a reliable emulator for predicting complex functionals by active learning with error control (ALEC). The algorithm is applicable to infinite-dimensional mapping with high-fidelity predictions and a controlled predictive error. The computational efficiency has been demonstrated by emulating the classical density functional theory (cDFT) calculations, a statistical-mechanical method widely used in modeling the equilibrium properties of complex molecular systems. We show that ALEC is much more accurate than conventional emulators based on the Gaussian processes with "space-filling" designs and alternative active learning methods. Besides, it is computationally more efficient than direct cDFT calculations. ALEC can be a reliable building block for emulating expensive functionals owing to its minimal computational cost, controllable predictive error, and fully automatic features. </p>

<p>Magnetic reconnection drives multi-species particle acceleration broadly in space and astrophysics. We perform the first 3D hybrid simulations (fluid electrons, kinetic ions) that contain sufficient scale separation to produce nonthermal heavy-ion acceleration, with fragmented flux ropes critical for accelerating all species. We demonstrate the acceleration of all ion species (up to Fe) into power-law spectra with similar indices, by a common Fermi acceleration mechanism. The upstream ion velocities influence the first Fermi reflection for injection. The subsequent onsets of Fermi acceleration are delayed for ions with lower charge-mass ratios (Q/M), until growing flux ropes magnetize them. This leads to a species-dependent maximum energy/nucleon $\propto(Q/M)^\alpha$. These findings are consistent with in-situ observations in reconnection regions, suggesting Fermi acceleration as the dominant multi-species ion acceleration mechanism. </p>

<p>Presently under construction in Lund, Sweden, the European Spallation Source (ESS) will be the world's brightest neutron source. As such, it has the potential for a particle physics program with a unique reach and which is complementary to that available at other facilities. This paper describes proposed particle physics activities for the ESS. These encompass the exploitation of both the neutrons and neutrinos produced at the ESS for high precision (sensitivity) measurements (searches). </p>

<p>Transport networks, such as vasculature or river networks, provide key functions in organisms and the environment. They usually contain loops whose significance for the stability and robustness of the network is well documented. However, the dynamics of their formation is usually not considered. The growth of such structures is often driven by the gradient of an external field. During network evolution, extending branches compete for the available flux, which leads to effective repulsion between them and screening of the shorter ones. Yet, in remarkably diverse processes, from unstable fluid flows to the canal system of jellyfish, loops suddenly form near the breakthrough when the longest branch reaches the boundary of the system. We provide a physical explanation for this universal behavior. Using a 1D model, we explain that the appearance of effective attractive forces results from the field drop inside the leading finger as it approaches the outlet. Furthermore, we numerically study the interactions between two fingers, including screening in the system and its disappearance near the breakthrough. Finally, we perform simulations of the temporal evolution of the fingers to show how revival and attraction to the longest finger leads to dynamic loop formation. We compare the simulations to the experiments and find that the dynamics of the shorter finger is well reproduced. Our results demonstrate that reconnection is a prevalent phenomenon in systems driven by diffusive fluxes, occurring both when the ratio of the mobility inside the growing structure to the mobility outside is low and near the breakthrough. </p>

<p>By providing mathematical estimates, this paper answers a fundamental question -- "what leads to Stokes drift"? Although overwhelmingly understood for water waves, Stokes drift is a generic mechanism that stems from kinematics and occurs in any non-transverse wave in fluids. To showcase its generality, we undertake a comparative study of the pathline equation of sound (1D) and intermediate-depth water (2D) waves. Although we obtain a closed-form solution $\mathbf{x}(t)$ for the specific case of linear sound waves, a more generic and meaningful approach involves the application of asymptotic methods and expressing variables in terms of the Lagrangian phase $\theta$. We show that the latter reduces the 2D pathline equation of water waves to 1D. Using asymptotic methods, we solve the respective pathline equation for sound and water waves, and for each case, we obtain a parametric representation of particle position $\mathbf{x}(\theta)$ and elapsed time $t(\theta)$. Such a parametric description has allowed us to obtain second-order-accurate expressions for the time duration, horizontal displacement, and average horizontal velocity of a particle in the crest and trough phases. All these quantities are of higher magnitude in the crest phase in comparison to the trough, leading to a forward drift, i.e. Stokes drift. We also explore particle trajectory due to second-order Stokes waves and compare it with linear waves. While finite amplitude waves modify the estimates obtained from linear waves, the understanding acquired from linear waves is generally found to be valid. </p>

<p>Social network structures play an important role in the lives of animals by affecting individual fitness, and the spread of disease and information. Nevertheless, we still lack a good understanding of how these structures emerge from the behaviour of individuals. Generative network models based on empirical knowledge about animal social systems provide a powerful approach that can help close this gap. In this study: 1) we develop a general model for the emergence of social structures based on a key generative process of real animal social networks, namely social preferences for traits (such as the age, sex, etc. of social partners); 2) we use this model to investigate how different trait preferences affect social network structure and function. We find that the preferences used in a population can have far-reaching consequences for the population, via effects on the transmission of disease and information and the robustness of the social network against fragmentation when individuals disappear. The study thus shows that social preferences can have consequences that go far beyond direct benefits individuals gain from social partner selection. It also shows that these consequences depend both on the preference types, and on the types of traits they are used with. We discuss the implications of the results for social evolution. </p>

<p>We investigate turbulence in magnetic reconnection jets in the Earth's magnetotail using data from the Magnetospheric Multiscale spacecraft. We show that signatures of a limited inertial range are observed in many reconnection jets. The observed turbulence develops on the time scale of a few ion gyroperiods, resulting in intermittent multifractal energy cascade from the characteristic scale of the jet down to the ion scales. We show that at sub-ion scales, the fluctuations are close to mono-fractal and predominantly kinetic Alfv\'en waves. The observed energy transfer rate across the inertial range is $\sim 10^8~\mathrm{J}~\mathrm{kg}^{-1}~\mathrm{s}^{-1}$, which is the largest reported for space plasmas so far. </p>

<p>The microwave radio dynamic spectra of the Crab pulsar interpulse contain fine structures represented via narrowband quasiharmonic stripes. The pattern significantly constrains any potential emission mechanism. Similar to the zebra patterns observed, for example, in type IV solar radio bursts or decameter and kilometer Jupiter radio emission, the double plasma resonance (DPR) effect of the cyclotron maser instability may allow for interpretion of observations of pulsar radio zebras. We present electromagnetic relativistic particle-in-cell (PIC) simulations of the electron-positron cyclotron maser for cyclotron frequency smaller than the plasma frequency. In four distinct simulation cycles, we focused on the effects of varying the plasma parameters on the instability growth rate and saturation energy. The physical parameters were the ratio between the plasma and cyclotron frequency, the density ratio of the "hot" loss-cone to the "cold" background plasma, the loss-cone characteristic velocity, and comparison with electron-proton plasma. In contrast to the results obtained from electron-proton plasma simulations, we find that the pulsar electron-positron maser instability does not generate distinguishable X and Z modes. On the contrary, a singular electromagnetic XZ mode was generated in all studied configurations close to or above the plasma frequency. For low density ratios, the highest peak of the XZ mode is at double the frequency of the highest peak of the Bernstein modes, indicating that the radio emission is produced by a coalescence of two Bernstein modes with the same frequency and opposite wave numbers. Our estimate of the radiative flux generated from the simulation is up to $\sim$30 mJy from an area of 100 km$^2$ for an observer at 1 kpc distance without the inclusion of relativistic beaming effects, which may account for multiple orders of magnitude. </p>

<p>Intergranular normal stresses (INS) are critical in the initiation and evolution of grain boundary damage in polycrystalline materials. To model the effects of such microstructural damage on a macroscopic scale, knowledge of INS is usually required statistically at each representative volume element subjected to various loading conditions. However, calculating INS distributions for different stress states can be cumbersome and time-consuming. This study proposes a new method to extend the existing INS distributions to arbitrary loading conditions using the symmetries of a polycrystalline material composed of randomly oriented linear-elastic grains with arbitrary lattice symmetry. The method relies on a fact that INS distributions can be accurately reproduced from the first (typically) ten statistical moments, which depend trivially on just three stress invariants and a few material invariants due to assumed isotropy and material linearity of the polycrystalline model. While these material invariants are complex averages, they can be extracted numerically from a few existing INS distributions and tabulated for later use. Practically, only three such INS distributions at properly selected loadings are required to provide all relevant material invariants for the first 11 statistical moments, which can then be used to reconstruct the INS distribution for arbitrary loading conditions. The proposed approach is demonstrated to be accurate and feasible for an arbitrarily selected linear-elastic material under various loading conditions. </p>

<p>In the same silicon photonic integrated circuit, we compare two types of integrated degenerate photon-pair sources (microring resonators or waveguides) by means of Hong-Ou-Mandel (HOM) interference experiments. Two nominally identical microring resonators are coupled to two nominally identical waveguides which form the arms of a Mach-Zehnder interferometer. This is pumped by two lasers at two different wavelengths to generate, by spontaneous four-wave mixing, degenerate photon pairs. In particular, the microring resonators can be thermally tuned in or out of resonance with the pump wavelengths, thus choosing either the microring resonators or the waveguides as photon-pair sources, respectively. In this way, an on-chip HOM visibility of 94% with microring resonators and 99% with straight waveguides is measured upon filtering. We compare our experimental results with theoretical simulations of the joint spectral intensity and the purity of the degenerate photon pairs. We verify that the visibility is connected to the sources' indistinguishability, which can be quantified by the overlap between the joint spectral amplitudes (JSA) of the photon pairs generated by the two sources. We estimate a JSAs overlap of 98% with waveguides and 89% with microring resonators. </p>

<p>Recently the photonic golden rule, which predicts that the spontaneous emission rate of an atom depends on the projected local density of states (LDOS), was shown to fail in an optical medium with a linear gain amplifier. We present a classical light-matter theory to fix this widely used spontaneous emission rate, fully recovering the quantum mechanical rate reported in Franke et al., Phys. Rev. Lett. 127, 013602 (2021). The corrected classical Purcell factor, for media containing linear amplifiers, is obtained in two different forms, both of which can easily be calculated in any standard classical Maxwell solver. We also derive explicit analytical results in terms of quasinormal modes, which are useful for studying practical cavity structures in an efficient way, including the presence of local field effects for finite-size dipole emitters embedded inside lossy or gain materials (using a real cavity model). Finally, we derive a full classical correspondence from the viewpoint of quantized quasinormal modes in the bad cavity limit. Example numerical calculations are shown for coupled loss-gain microdisk resonators, showing excellent agreement between few mode expansions and full numerical dipole simulations. </p>

<p>Common criteria used for measuring performance of vibrating systems have one thing in common: they do not depend on initial conditions of the system. In some cases it is assumed that the system has zero initial conditions, or some kind of averaging is used to get rid of initial conditions. The aim of this paper is to initiate rigorous study of the dependence of vibrating systems on initial conditions in the setting of optimal damping problems. We show that, based on the type of initial conditions, especially on the ratio of potential and kinetic energy of the initial conditions, the vibrating system will have quite different behavior and correspondingly the optimal damping coefficients will be quite different. More precisely, for single degree of freedom systems and the initial conditions with mostly potential energy, the optimal damping coefficient will be in the under-damped regime, while in the case of the predominant kinetic energy the optimal damping coefficient will be in the over-damped regime. In fact, in the case of pure kinetic initial energy, the optimal damping coefficient is $+\infty$! Qualitatively, we found the same behavior in multi degree of freedom systems with mass proportional damping. We also introduce a new method for determining the optimal damping of vibrating systems, which takes into account the peculiarities of initial conditions and the fact that, although in theory these systems asymptotically approach equilibrium and never reach it exactly, in nature and in experiments they effectively reach equilibrium in some finite time. </p>

<p>The full instrument response of a superminiaturised CsI(Tl)-PiN photodiode radioactivity detector, intended for deployment on a meteorological radiosonde, has been modelled by combining a physics-based model of the sensor with the detector circuit response, obtained via an LTspice simulation. The model uses the incident energy of a gamma ray as an input, and produces the pulse expected from the detector. The detector response was verified by comparing the simulated energy calibration with a laboratory source. The measurement circuit is found to control the minimum detectable energy of 26 keV, and the maximum detectable energy is ~10 MeV. The energy sensitivity of the PiN detector is 0.29 +- 0.02 mV/keV in the 0-800 keV range. The simulation and laboratory calibrations were consistent to better than 5% over the calibration range of the instrument. </p>

<p>In this paper, we introduce an all-fibered dual-comb spectrometer based on a new design of highly nonlinear fiber to efficiently convert frequency combs from 1.55 micron to 2 micron We show that our spectrometer can be used to measure absorption profiles of rovibrational transitions of CO2 and N2O molecules, and especially their collisional self-broadening coefficients. The results show very good agreement with the HITRAN database and thus further measurements have been performed on a mixture CO2 /N2O to measure the broadening of the CO2 absorption lines resulting from the presence of N2O. </p>

<p>Simulating turbulent flows is crucial for a wide range of applications, and machine learning-based solvers are gaining increasing relevance. However, achieving temporal stability when generalizing to longer rollout horizons remains a persistent challenge for learned PDE solvers. In this work, we analyze if fully data-driven fluid solvers that utilize an autoregressive rollout based on conditional diffusion models are a viable option to address this challenge. We investigate accuracy, posterior sampling, spectral behavior, and temporal stability, while requiring that methods generalize to flow parameters beyond the training regime. To quantitatively and qualitatively benchmark the performance of a range of flow prediction approaches, three challenging scenarios including incompressible and transonic flows, as well as isotropic turbulence are employed. We find that even simple diffusion-based approaches can outperform multiple established flow prediction methods in terms of accuracy and temporal stability, while being on par with state-of-the-art stabilization techniques like unrolling at training time. Such traditional architectures are superior in terms of inference speed, however, the probabilistic nature of diffusion approaches allows for inferring multiple predictions that align with the statistics of the underlying physics. Overall, our benchmark contains three carefully chosen data sets that are suitable for probabilistic evaluation alongside various established flow prediction architectures. </p>

<p>We study how external magnetic fields from 0 to 40 T influence positive streamers in atmospheric pressure air, using 3D PIC-MCC (particle-in-cell, Monte Carlo collision) simulations. When a magnetic field $\vec{B}$ is applied perpendicular to the background electric field $\vec{E}$, the streamers deflect towards the $+\vec{B}$ and $-\vec{B}$ directions which results in a branching into two main channels. With a stronger magnetic field the angle between the branches increases, and for the 40 T case the branches grow almost parallel to the magnetic field. Due to the $\vec{E}\times\vec{B}$ drift of electrons we also observe a streamer deviation in the opposite $-\vec{E}\times\vec{B}$ direction, where the minus sign appears because positive streamers propagate opposite to the electron drift velocity. The deviation due to this $\vec{E}\times\vec{B}$ effect is smaller than the deviation parallel to $\vec{B}$. In both cases of $\vec{B}$ perpendicular and parallel to $\vec{E}$, the streamer radius decreases with the magnetic field strength. We relate our observations to the effects of electric and magnetic fields on electron transport and reaction coefficients. </p>

<p>The existence and properties of envelope solitary waves on a periodic, traveling wave background, called traveling breathers, are investigated numerically in representative nonlocal dispersive media. Using a fixed point computational scheme, a space-time boundary value problem for bright traveling breather solutions is solved for the weakly nonlinear Benjamin-Bona-Mahony equation, a nonlocal, regularized shallow water wave model, and the strongly nonlinear conduit equation, a nonlocal model of viscous core-annular flows. Curves of unit-mean traveling breather solutions within a three-dimensional parameter space are obtained. Resonance due to nonconvex, rational linear dispersion leads to a nonzero oscillatory background upon which traveling breathers propagate. These solutions exhibit a topological phase jump, so act as defects within the periodic background. For small amplitudes, traveling breathers are well-approximated by bright soliton solutions of the nonlinear Schr\"odinger equation with a negligibly small periodic background. These solutions are numerically continued into the large amplitude regime as elevation defects on cnoidal or cnoidal-like periodic traveling wave backgrounds. This study of bright traveling breathers provides insight into systems with nonconvex, nonlocal dispersion that occur in a variety of media such as internal oceanic waves subject to rotation and short, intense optical pulses. </p>

<p>In this work we investigate quantum interference in a four-level atom coupled to a negative index meta-material (NIMM) plasmonic reservoir that supports both TE and TM polarized surface plasmons (SP). This provides more options to control SP interaction with emitters and hence more control of spontaneous emission decays and spectrum. The spectrum depends critically on parameters like the reservoir parameters, mode frequency, frequency dependent electric permittivity and magnetic permeability, and the location of the atom. We report orders of magnitude enhancement in the reservoir-modified decays and spectrum compared to free space case. The rich atomic and plasmonic parameters provide a wide range of flexibility and more options to control emission spectrum that suits practical applications. </p>

<p>We characterize the performance of two pixelated neutron detectors: a PMT-based array that utilizes Anger logic for pixel identification and a SiPM-based array that employs individual pixel readout. The SiPM-based array offers improved performance over the previously developed PMT-based detector both in terms of uniformity and neutron detection efficiency. Each detector array uses PSD-capable plastic scintillator as a detection medium. We describe the calibration and neutron efficiency measurement of both detectors using a $^{137}$Cs source for energy calibration and a $^{252}$Cf source for calibration of the neutron response. We find that the intrinsic neutron detection efficiency of the SiPM-based array is ($30.2 \ \pm \ 1.7$)\%, which is almost twice that of the PMT-based array, which we measure to be ($16.9 \pm 0.2$)\%. </p>

<p>The post-Newtonian orbital effects induced by the mass quadrupole and spin octupole moments of an isolated, oblate spheroid of constant density that is rigidly and uniformly rotating on the motion of a test particle are analytically worked out for an arbitrary orbital configuration and without any preferred orientation of the body's spin axis. The resulting expressions are specialized to the cases of (a) equatorial and (b) polar orbits. The opportunity offered by a hypothetical new spacecraft moving around Jupiter along a Juno-like highly elliptical, polar orbit to measure them is preliminarily studied. Although more difficult to be practically implemented, also the case of a less elliptical orbit is considered since it yields much larger figures for the relativistic effects of interest. The possibility of using the S stars orbiting the supermassive black hole in Sgr A$^\ast$ at the Galactic Center as probes to potentially constrain some parameters of the predicted extended mass distribution surrounding the hole by means of the aforementioned orbital effects is briefly examined. </p>

<p>Quantum chemical calculations of the ground-state properties of positron-molecule complexes are challenging. The main difficulty lies in employing an appropriate basis set for representing the coalescence between electrons and a positron. Here, we tackle this problem with the recently developed Fermionic neural network (FermiNet) wavefunction, which does not depend on a basis set. We find that FermiNet produces highly accurate, in some cases state-of-the-art, ground-state energies across a range of atoms and small molecules with a wide variety of qualitatively distinct positron binding characteristics. We calculate the binding energy of the challenging non-polar benzene molecule, finding good agreement with the experimental value, and obtain annihilation rates which compare favourably with those obtained with explicitly correlated Gaussian wavefunctions. Our results demonstrate a generic advantage of neural network wavefunction-based methods and broaden their applicability to systems beyond the standard molecular Hamiltonian. </p>

<p>Low-temperature cryogenics open the door for a range of interesting technologies based on features like superconductivity and superfluidity, low-temperature phase transitions or the low heat capacity of non-metals in the milli-Kelvin range. Devices based on these technologies are often sensitive to small energy depositions as can be caused by environmental radiation. The Cryogenic Underground TEst facility (CUTE) at SNOLAB is a platform for testing and operating cryogenic devices in an environment with low levels of background. The large experimental chamber ($\mathcal{O}$(10) L) reaches a base temperature of $\sim$12 mK; it can hold a payload of up to $\sim$20 kg and provides a radiogenic background event rate as low as a few events/kg/keV/day in the energy range below about 100 keV, as well as a negligible muon rate ($\mathcal{O}$(1)/month). CUTE was designed and built in the context of the Super Cryogenic Dark Matter Search experiment (SuperCDMS) which uses cryogenic detectors to search for interactions of dark matter particles with ordinary matter. The facility has been used to test SuperCDMS detectors since its commissioning in 2019. In 2021, it was handed over to SNOLAB to become a SNOLAB user facility after the completion of the testing of detectors for SuperCDMS. The facility will be available for projects that benefit from these special conditions, based on proposals assessed for their scientific and technological merits. This article describes the main design features and operating parameters of CUTE. </p>

<p>Graph Neural Networks (GNNs), especially message-passing neural networks (MPNNs), have emerged as powerful architectures for learning on graphs in diverse applications. However, MPNNs face challenges when modeling non-local interactions in graphs such as large conjugated molecules, and social networks due to oversmoothing and oversquashing. Although Spectral GNNs and traditional neural networks such as recurrent neural networks and transformers mitigate these challenges, they often lack generalizability, or fail to capture detailed structural relationships or symmetries in the data. To address these concerns, we introduce Matrix Function Neural Networks (MFNs), a novel architecture that parameterizes non-local interactions through analytic matrix equivariant functions. Employing resolvent expansions offers a straightforward implementation and the potential for linear scaling with system size. The MFN architecture achieves stateof-the-art performance in standard graph benchmarks, such as the ZINC and TU datasets, and is able to capture intricate non-local interactions in quantum systems, paving the way to new state-of-the-art force fields. </p>

<p>The growing computing power over the years has enabled simulations to become more complex and accurate. While immensely valuable for scientific discovery and problem-solving, however, high-fidelity simulations come with significant computational demands. As a result, it is common to run a low-fidelity model with a subgrid-scale model to reduce the computational cost, but selecting the appropriate subgrid-scale models and tuning them are challenging. We propose a novel method for learning the subgrid-scale model effects when simulating partial differential equations augmented by neural ordinary differential operators in the context of discontinuous Galerkin (DG) spatial discretization. Our approach learns the missing scales of the low-order DG solver at a continuous level and hence improves the accuracy of the low-order DG approximations as well as accelerates the filtered high-order DG simulations with a certain degree of precision. We demonstrate the performance of our approach through multidimensional Taylor-Green vortex examples at different Reynolds numbers and times, which cover laminar, transitional, and turbulent regimes. The proposed method not only reconstructs the subgrid-scale from the low-order (1st-order) approximation but also speeds up the filtered high-order DG (6th-order) simulation by two orders of magnitude. </p>

<p>Molecular dynamics simulations are utilized to study the microwave heating of methane hydrate by the five-body rotation coordinate system with the TIP5P-Ewald model. The structure I of methane hydrate is constructed, and the ice and free methane or methane hydrate are exposed to microwave electric fields of 10 GHz.Provisional methane hydrate of the normal density and a temperature of 273 K is dynamically unstable and collapses after some periods of irradiation. The period of a collapse time is $1.7 \times 10^{6} \tau $ and the temperature increase is $\Delta T \cong 61$ deg, with the external electric field $3 \times 10^{7} \rm{V/cm}$ (i.e. 0.3 V/\AA) and $\tau = 1 \times 10^{-14}$ s. For the ice and free methane of the temperature 193 K and the pressure 1 atm, the system is stable while it is heated under microwave irradiation. About the temperature of 273 K, high density methane hydrate becomes stable, whereas the density of 0.93 g/cm$^{3}$ is marginally stable but is heated when microwaves are present. </p>

<p>COSINE-100 is a dark matter direct detection experiment with 106 kg NaI(Tl) as the target material. 210Pb and daughter isotopes are a dominant background in the WIMP region of interest and are detected via beta decay and alpha decay. Analysis of the alpha channel complements the background model as observed in the beta/gamma channel. We present the measurement of the quenching factors and Monte Carlo simulation results and activity quantification of the alpha decay components of the COSINE-100 NaI(Tl) crystals. The data strongly indicate that the alpha decays probabilistically undergo two possible quenching factors but require further investigation. The fitted results are consistent with independent measurements and improve the overall understanding of the COSINE-100 backgrounds. Furthermore, the half-life of 216Po has been measured to be 143.4 +/- 1.2 ms, which is consistent with and more precise than recent measurements. </p>

<p>High-throughput computing (HTC) is a pivotal asset in many scientific fields, such as biology, material science and machine learning. Applying HTC to the complex physics-based degradation models of lithium-ion batteries enables efficient parameter identification and sensitivity analysis, which further leads to optimal battery design and operating conditions. However, running physics-based degradation models comes with pitfalls, as solvers can crash or get stuck in infinite loops due to numerical errors. Also, how to pipeline HTC for degradation models has seldom been discussed. To fill these gaps, we have created ParaSweeper, a Python script tailored for HTC, designed to streamline parameter sweeping by running as many ageing simulations as computational resources allow, each with different parameters. We have demonstrated the capability of ParaSweeper based on the open-source platform PyBaMM, and the approach can also apply to other numerical models which solve partial differential equations. ParaSweeper not only manages common solver errors, but also integrates various methods to accelerate the simulation. Using a high-performance computing platform, ParaSweeper can run millions of charge/discharge cycles within one day. ParaSweeper stands to benefit both academic researchers, through expedited model exploration, and industry professionals, by enabling rapid lifetime design, ultimately contributing to the prolonged lifetime of batteries. </p>

<p>We utilize the reconstruction of attosecond beating by interference of two-photon transitions (RABBIT) technique to study the phase of a Rabi-cycling atom using circularly polarized extreme ultraviolet and infrared (IR) fields, where the IR field induces Rabi oscillations between the 2s and 2p states of lithium. Autler-Townes splittings are observed in sidebands of the photoelectron spectra and the relative phases of outgoing electron wave packets are retrieved from the azimuthal angle. In this RABBIT scheme, more ionization pathways beyond the usual two-photon pathways are required. Our results show that the polar-angle-integrated and polar-angle-resolved RABBIT phases have different behaviors when the XUV and IR fields have co- and counter-rotating circular polarizations, which are traced back to the different ionization channels according to the selection rules in these two cases and their competition relying on the propensity rule in laser-assisted photoionization. </p>

<p>Selected configuration interaction (SCI) methods have emerged as state-of-the-art methodologies for achieving high accuracy and generating benchmark reference data for ground and excited states in small molecular systems. However, their precision relies heavily on extrapolation procedures to produce a final estimate of the exact result. Using the structure of the exact electronic energy landscape, we provide a rationale for the common linear extrapolation of the variational energy as a function of the second-order perturbative correction. In particular, we demonstrate that the energy gap and the coupling between the so-called internal and external spaces are the key factors determining the rate at which the linear regime is reached. Starting from first principles, we also derive a new non-linear extrapolation formula that improves the post-processing of data generated from SCI methods and can be applied to both ground- and excited-state energies. </p>

<p>Studies of the dynamics of a quantum system coupled to a bath are typically performed by utilizing the Nakajima-Zwanzig memory kernel (${\mathcal{K}}$) or the influence functions ($\mathbf{{I}}$), especially when the dynamics exhibit memory effects (i.e., non-Markovian). Despite their significance, the formal connection between the memory kernel and the influence functions has not been explicitly made. We reveal their relation through the observation of a diagrammatic structure underlying the system propagator, $\mathbf{{I}}$, and ${\mathcal{K}}$. Based on this, we propose a non-perturbative, diagrammatic approach to construct ${\mathcal{K}}$ from $\mathbf{{I}}$ for (driven) systems interacting with harmonic baths without the use of any projection-free dynamics inputs required by standard approaches. With this construction, we also show how approximate path integral methods can be understood in terms of approximate memory kernels. Furthermore, we demonstrate a Hamiltonian learning procedure to extract the bath spectral density from a set of reduced system trajectories obtained experimentally or by numerically exact methods, opening new avenues in quantum sensing and engineering. The insights we provide in this work will significantly advance the understanding of non-Markovian dynamics, and they will be an important stepping stone for theoretical and experimental developments in this area. </p>

<p>Recent advances in far-infrared detector technology have led to increases in raw sensitivity of more than an order of magnitude over previous state-of-the-art detectors. With such sensitivity, photon noise becomes the dominant noise component, even when using cryogenically cooled optics, unless a method of restricting the spectral bandpass is employed. The leading instrument concept features reflecting diffraction gratings which post-disperse the light that has been modulated by a polarizing Fourier transform spectrometer (FTS) onto a detector array, thereby reducing the photon noise on each detector. This paper discusses the development of a cryogenic (4 K) diffraction grating spectrometer which operates over the wavelength range from 285 - 500 $\mu$m and was used to post-disperse the output from a room-temperature polarizing FTS. Measurements of the grating spectral response and diffraction efficiency are presented as a function of both wavelength and polarization to characterize the instrumental performance. </p>

<p>Conventional heterodyne readout schemes are now under reconsideration due to the realization of techniques to evade its inherent 3 dB signal-to-noise penalty. The application of high-frequency, spectrally entangled, two-mode squeezed states can further improve the readout sensitivity of audio-band signals. In this paper, we experimentally demonstrate quantum-enhanced heterodyne readout of two spatially distinct interferometers with direct optical signal combination, circumventing the 3 dB heterodyne signal-to-noise penalty. Applying a high-frequency, spectrally entangled, two-mode squeezed state, we show further signal-to-noise improvement of an injected audio band signal of 3.5 dB. This technique is applicable for quantum-limited high-precision experiments, with application to searches for quantum gravity, gravitational wave detection and wavelength-multiplexed quantum communication. </p>

<p>Due to the ability of liquid crystals to self-assemble into complex structures, their strong response to the electric field, integrability into complex optical systems, and recently also considerable second-order optical nonlinearity, they are a base for various linear and nonlinear optical devices. However, their use as sources of quantum states of light has not been explored so far. Here, we demonstrate an efficient electric-field tunable broadband source of entangled photons based on spontaneous parametric down-conversion in a ferroelectric nematic liquid crystal. The emission rate and the polarization state of the photon pairs can be drastically altered by either applying a few volts or twisting the molecular orientation along the sample, enabling the generation of almost any polarization state. The concepts developed here could be extended to complex topological structures and multi-pixel devices generating quantum light. </p>

<p>Study Objectives: Polysomnography (PSG) currently serves as the benchmark for evaluating sleep disorders. Its discomfort, impracticality for home-use, and introduction of bias in sleep quality assessment necessitate the exploration of less invasive, cost-effective, and portable alternatives. One promising contender is the in-ear-EEG sensor, which offers advantages in terms of comfort, fixed electrode positions, resistance to electromagnetic interference, and user-friendliness. This study aims to establish a methodology to assess the similarity between the in-ear-EEG signal and standard PSG. </p> <p>Methods: We assess the agreement between the PSG and in-ear-EEG derived hypnograms. We extract features in the time- and frequency- domain from PSG and in-ear-EEG 30-second epochs. We only consider the epochs where the PSG-scorers and the in-ear-EEG-scorers were in agreement. We introduce a methodology to quantify the similarity between PSG derivations and the single-channel in-ear-EEG. The approach relies on a comparison of distributions of selected features -- extracted for each sleep stage and subject on both PSG and the in-ear-EEG signals -- via a Jensen-Shannon Divergence Feature-based Similarity Index (JSD-FSI). </p> <p>Results: We found a high intra-scorer variability, mainly due to the uncertainty the scorers had in evaluating the in-ear-EEG signals. We show that the similarity between PSG and in-ear-EEG signals is high (JSD-FSI: 0.61 +/- 0.06 in awake, 0.60 +/- 0.07 in NREM and 0.51 +/- 0.08 in REM), and in line with the similarity values computed independently on standard PSG-channel-combinations. </p> <p>Conclusions: In-ear-EEG is a valuable solution for home-based sleep monitoring, however further studies with a larger and more heterogeneous dataset are needed. </p>

<p>We consider conservation of momentum in AQUAL, a field-theoretic extension to Modified Newtonian Dynamics (MOND). We show that while there is a sense in which momentum is conserved, it is only if momentum is attributed to the gravitational field, and thus Newton's third law fails as usually understood. We contrast this situation with that of Newtonian gravitation on a field theoretic formulation. We then briefly discuss the situation in TeVeS, a relativistic theory that has AQUAL as a classical limit. </p>

<p>How predictable are turbulent flows? Here we use theoretical estimates and shell model simulations to argue that Eulerian spontaneous stochasticity, a manifestation of the non-uniqueness of the solutions to the Euler equation that is conjectured to occur in Navier-Stokes turbulence at high Reynolds numbers, leads to universal statistics at finite times, not just at infinite time as for standard chaos. These universal statistics are predictable, even though individual flow realizations are not. Any small-scale noise vanishing slowly enough with increasing Reynolds number can trigger spontaneous stochasticity and here we show that thermal noise alone, in the absence of any larger disturbances, would suffice. If confirmed for Navier-Stokes turbulence, our findings would imply that intrinsic stochasticity of turbulent fluid motions at all scales can be triggered even by unavoidable molecular noise, with implications for modeling in engineering, climate, astrophysics and cosmology. </p>

<p>In this work it is shown that there are symmetries beyond the Euclidean group $E\left(3\right)$ in 3-body problem, and by extension in many-body problem, with inverse squared distance inter particle force. The symmetries in 3-body problem form a group: $SO\left(4\times3,2\times3\right)/\left(C\left(3\times2\right)\right)$, where $C\left(n\right)$ is the planar translation group in n dimensions, which forms its Spectrum-Generating group. Some of these quantities commute with the Hamiltonian. The existence of these conserved quantities was verified by calculating energy spectrum of the Helium atom. This method can also be used to find symmetries in many-body problem, and to calculate energy levels, and wave-functions of more complicated systems, which include every possible atomic and molecular systems in chemistry. </p>

<p>A new concept, the Triplet Track Trigger (TTT), is proposed for stand-alone tracking at the first trigger level of the FCC-hh detector. The concept is based on a highly scalable monolithic pixel sensor technology and uses a very simple and fast track reconstruction algorithm that can be easily implemented in hardware processors. The goal is to suppress the enormous pileup of ~1000 minimum bias collisions expected at the FCC-hh experiment and to identify the hard-interaction vertex and the corresponding tracks as a basis for a trigger decision. In the barrel region, the TTT consists of three closely stacked, highly granular pixel detector layers at radii of ~1m. An extension of the TTT to the endcap region increases the geometrical acceptance. </p> <p>We present full Geant4 simulations and reconstruction performance of a modified FCC-hh reference tracker that includes TTT barrel and endcap detector layers. The stacking of TTT layers results in excellent track purity, and the large lever arm ensures very good momentum resolution. Additionally, sub-mm $z$-vertex resolution is achieved, which allows for very efficient pileup suppression. By reconstructing pileup suppressed track-jets, the primary vertex of the hard interaction is successfully identified, even at a pileup rate of $\langle\mu\rangle=1000$ and at trigger level. </p> <p>The multi-jet signature, pp -&gt; HH -&gt; 4b, is used as a showcase to study the trigger performance of the TTT and compare it to an emulated calorimeter trigger (calo-trigger). The TTT allows for significantly lower trigger thresholds and higher trigger efficiencies than a calo-trigger. Furthermore, the TTT is very robust against fluctuations in the pileup rate compared to the calo-trigger. As a result, a significant gain of sensitivity for measuring the trilinear Higgs self-coupling ($\lambda$) is expected with the TTT at the FCC-hh. </p>

<p>Simulating realistic time-domain observations of gravitational waves (GWs) and GW detector glitches can help in advancing GW data analysis. Simulated data can be used in downstream tasks by augmenting datasets for signal searches, balancing data sets for machine learning, and validating detection schemes. In this work, we present Conditional Derivative GAN (cDVGAN), a novel conditional model in the Generative Adversarial Network framework for simulating multiple classes of time-domain observations that represent gravitational waves (GWs) and detector glitches. cDVGAN can also generate generalized hybrid samples that span the variation between classes through interpolation in the conditioned class vector. cDVGAN introduces an additional player into the typical 2-player adversarial game of GANs, where an auxiliary discriminator analyzes the first-order derivative time-series. Our results show that this provides synthetic data that better captures the features of the original data. cDVGAN conditions on three classes, two denoised from LIGO blip and tomte glitch events from its 3rd observing run (O3), and the third representing binary black hole (BBH) mergers. Our proposed cDVGAN outperforms 4 different baseline GAN models in replicating the features of the three classes. Specifically, our experiments show that training convolutional neural networks (CNNs) with our cDVGAN-generated data improves the detection of samples embedded in detector noise beyond the synthetic data from other state-of-the-art GAN models. Our best synthetic dataset yields as much as a 4.2% increase in area-under-the-curve (AUC) performance compared to synthetic datasets from baseline GANs. Moreover, training the CNN with hybrid samples from our cDVGAN outperforms CNNs trained only on the standard classes, when identifying real samples embedded in LIGO detector background (4% AUC improvement for cDVGAN). </p>