## Physics (physics) updates on the arXiv.org e-print archive



The importance of computing in astronomy continues to increase, and so is its impact on the environment. When analyzing data or performing simulations, most researchers raise concerns about the time to reach a solution rather than its impact on the environment. Luckily, a reduced time-to-solution due to faster hardware or optimizations in the software generally also leads to a smaller carbon footprint. This is not the case when the reduced wall-clock time is achieved by overclocking the processor, or when using supercomputers.

The increase in the popularity of interpreted scripting languages, and the general availability of high-performance workstations form a considerable threat to the environment. A similar concern can be raised about the trend of running single-core instead of adopting efficient many-core programming paradigms.

In astronomy, computing is among the top producers of green-house gasses, surpassing telescope operations. Here I hope to raise the awareness of the environmental impact of running non-optimized code on overpowered computer hardware.

Analysing greenhouse gas emissions of an astronomical institute is a first step in reducing its environmental impact. Here, we break down the emissions of the Max Planck Institute for Astronomy in Heidelberg and propose measures for reductions.

This thesis deals with the systematic treatment of quantum-mechanical systems in post-Newtonian gravitational fields. Starting from clearly spelled-out assumptions, employing a framework of geometric background structures defining the notion of a post-Newtonian expansion, our systematic approach allows to properly derive the post-Newtonian coupling of quantum-mechanical systems to gravity based on first principles. This sets it apart from more heuristic approaches that are commonly employed, for example, in the description of quantum-optical experiments under gravity.

Regarding single particles, we compare simple canonical quantisation of a free particle in curved spacetime to formal expansions of the minimally coupled Klein-Gordon equation, which may be motivated from QFT in curved spacetimes. Specifically, we develop a general WKB-like post-Newtonian expansion of the KG equation to arbitrary order in $c^{-1}$. Furthermore, for stationary spacetimes, we show that the Hamiltonians arising from expansions of the KG equation and from canonical quantisation agree up to linear order in particle momentum, independent of any expansion in $c^{-1}$.

Concerning composite systems, we perform a fully detailed systematic derivation of the first order post-Newtonian quantum Hamiltonian describing the dynamics of an electromagnetically bound two-particle system situated in external electromagnetic and gravitational fields, the latter being described by the Eddington-Robertson PPN metric.

In the last, independent part of the thesis, we prove two uniqueness results characterising the Newton--Wigner position observable for Poincar\'e-invariant classical Hamiltonian systems: one is a direct classical analogue of the quantum Newton--Wigner theorem, and the other clarifies the geometric interpretation of the Newton--Wigner position as `centre of spin', as proposed by Fleming in 1965.

Network structures in a wide array of systems such as social networks, transportation, power and water distribution infrastructures, and biological and ecological systems can exhibit critical thresholds or tipping points beyond which there are disproportionate losses in the system functionality. There is growing concern over tipping points and failure tolerance of such systems as tipping points can lead to an abrupt loss of intended functionality and possibly non-recoverable states. While attack tolerance of networked systems has been intensively studied for the disruptions originating from a single point of failure, there have been instances where real-world systems are subject to simultaneous or sudden onset of concurrent disruption at multiple locations. Using open-source data from the United States Airspace Airport network and Indian Railways Network, and random networks as prototype class of systems, we study their responses to synthetic attack strategies of varying sizes. For both types of networks, we observe the presence of warning regions, which serve as a precursor to the tipping point. Further, we observe the statistically significant relationships between network robustness and size of simultaneous distribution, which generalizes to the networks with different topological attributes for random failures and targeted attacks. We show that our approach can determine the entire robustness characteristics of networks of disparate architecture subject to disruptions of varying sizes. Our approach can serve as a paradigm to understand the tipping point in real-world systems, and the principle can be extended to other disciplines to address critical issues of risk management and resilience.

The annual meeting of the European Astronomical Society took place in Lyon, France, in 2019, but in 2020 it was held online only due the COVID-19 pandemic. The carbon footprint of the virtual meeting was roughly 3,000 times smaller than the face-to-face one, providing encouragement for more ecologically minded conferencing.

Gas sensors built using two-dimensional (2D) MoS2 have conventionally relied on a change in field-effect-transistor (FET) channel resistance or a change in Schottky contact/pn homojunction barrier. This report demonstrates, for the first time, an NO2 gas sensor that leverages a gate tunable type II WSe2 (p)/MoS2 (n) heterojunction to realize a 4x enhancement in sensitivity, 8x lower limit of detection and improved dynamic response when compared to an MoS2 FET sensor on the same flake. Comprehensive sensing measurements over a range of analyte concentrations, gate biases and MoS2 flake thicknesses indicate a novel two-fold electrical response to NO2 exposure underlying the enhanced sensitivity of the heterojunction- (i) a series resistance change that leads to an exponential change in thermionic current at high bias, and, (ii) a carrier concentration change that leads to a linear change in interlayer recombination current near zero bias. The heterojunction diode also exhibits fast and tunable recovery under negative gate biasing. All-electrical (gate controlled) sensing and recovery operation at room temperature makes this a simple, low-overhead sensor. The ability to sense tri-nitro toluene (TNT) molecules down to a concentration of 80PPB highlights its potential as a comprehensive chemical sensing platform.

Reaction-diffusion waves have long been used to describe the growth and spread of populations undergoing a spatial range expansion. Such waves are generally classed as either pulled, where the dynamics are driven by the very tip of the front and stochastic fluctuations are high, or pushed, where cooperation in growth or dispersal results in a bulk-driven wave in which fluctuations are suppressed. These concepts have been well studied experimentally in populations where the cooperation leads to a density-dependent growth rate. By contrast, relatively little is known about experimental populations that exhibit a density-dependent dispersal rate. Using bacteriophage T7 as a test organism, we present novel experimental measurements that demonstrate that the diffusion of phage T7, in a lawn of host E. coli, is hindered by the physical presence of the host bacteria cells. The coupling between host density, phage dispersal and cell lysis caused by viral infection results in an effective density-dependent diffusion rate akin to cooperative behavior. Using a system of reaction-diffusion equations, we show that this effect can result in a transition from a pulled to pushed expansion. Moreover, we find that a second independent density-dependent effect on phage dispersal spontaneously emerges as a result of the viral incubation period, during which phage is trapped inside the host unable to disperse. Our results indicate both that bacteriophage can be used as a controllable laboratory population to investigate the impact of density-dependent dispersal on evolution, and that the genetic diversity and adaptability of expanding viral populations could be much greater than is currently assumed.

Directed Energy Deposition (DED) processes offer one of the most versatile current techniques to additively manufacture and repair metallic components that have generatively designed complex geometries, and with compositional control. When compared to powder bed fusion (PBF), its applicability and adoption has been limited because several issues innate to the process are yet to be suitably understood and resolved. This work catalogs and delineates these issues and anomalies in the DED process along with their causes and solutions, based on a state-of-the-art literature review. This work also serves to enumerate and associate the underlying causes to the detrimental effects which manifest as undesirable part/process outcomes. These DED-specific anomalies are categorized under groups related to the part, process, material, productivity, safety, repair, and functional gradients. Altogether, this primer acts as a guide to best prepare for and mitigate the problems that are encountered in DED, and also to lay the groundwork to inspire novel solutions to further advance DED into mainstream manufacturing.

As a result of the spread of COVID-19 during spring 2020, many colleges and universities across the US, and beyond, were compelled to move entirely to remote, online instruction, or shut down. Due to the rapidity of this transition, instructors had to significantly -- if not completely -- change their instructional style on very short notice. Our purpose with this paper is to report on student experiences and reactions to the switch to emergency remote learning at two large, land-grant, research intensive universities. We aimed to explore how students have received and dealt with the shift to remote learning that began in March 2020, specifically in introductory physics and astronomy courses. By providing timely student feedback, we hope to help instructors tune their efforts to build a more effective remote learning environment.

The ab-initio theory of low-field electronic transport properties such as carrier mobility in semiconductors is well-established. However, an equivalent treatment of electronic fluctuations about a non-equilibrium steady state, which are readily probed experimentally, remains less explored. Here, we report a first-principles theory of electronic noise for warm electrons in semiconductors. In contrast with typical numerical methods used for electronic noise, no adjustable parameters are required in the present formalism, with the electronic band structure and scattering rates calculated from first-principles. We demonstrate the utility of our approach by applying it to GaAs and show that spectral features in AC transport properties and noise originate from the disparate time scales of momentum and energy relaxation, despite the dominance of optical phonon scattering. Our formalism enables a parameter-free approach to probe the microscopic transport processes that give rise to electronic noise in semiconductors.

Quantum-optical technologies based on the effect of parametric light down-conversion are not yet applied in the terahertz frequency range. This is owing to the absence of terahertz single-photon detectors and the strong entanglement of modes of optical-terahertz biphotons. This study investigates the angular structure of scattered radiation generated by strongly non-degenerate parametric down-conversion. It demonstrates that under certain approximations, it is possible to obtain azimuthal eigenmodes for the nonlinear-interaction operator. The solution of the evolution equations for the field operators in these eigenmodes has the form of the Bogolyubov transformation, which allows a scattering matrix to be obtained for arbitrary values of the parametric gain. This scattering matrix can describe both the production of biphoton pairs and the generation of intense fluxes of correlated optical-terahertz fields that form a macroscopic quantum state of radiation in two spectral ranges.

Chemical interaction and changes in local electronic structure of Cr, Fe, Co, Ni and Cu transition metals (TMs) upon formation of an $Al_{8}Co_{17}Cr_{17}Cu_{8}Fe_{17}Ni_{33}$ compositionally complex alloy (CCA) have been studied by X-ray absorption spectroscopy and X-ray photoelectron spectroscopy. It was found that upon CCA formation, occupancy of the Cr, Co and Ni 3d states changes and the maximum of the occupied and empty Ni 3d states density shifts away from Fermi level ($E_f$) by 0.5 and 0.6 eV, respectively, whereas the Cr 3d empty states maximum shifts towards $E_f$ by 0.3 eV, compared to the corresponding pure metals. The absence of significant charge transfer between the elements was established, pointing to the balancing of the 3d states occupancy change by involvement of delocalized 4s and 4p states into the charge redistribution. Despite the expected formation of strong Al-TMs covalent bonds, the Al role in the transformation of the TMs 3d electronic states is negligible. The work demonstrates a decisive role of Cr in the Ni local electronic structure transformation and suggests formation of directional Ni-Cr bonds with covalent character. These findings can be helpful for tuning deformation properties and phase stability of the CCA.

In the Noisy Intermediate-Scale Quantum (NISQ) era, solving the electronic structure problem from chemistry is considered as the "killer application" for near-term quantum devices. In spite of the success of variational hybrid quantum/classical algorithms in providing accurate energy profiles for small molecules, careful considerations are still required for the description of complicated features of potential energy surfaces. Because the current quantum resources are very limited, it is common to focus on a restricted part of the Hilbert space (determined by the set of active orbitals). While physically motivated, this approximation can severely impact the description of these complicated features. A perfect example is that of conical intersections (i.e. a singular point of degeneracy between electronic states), which are of primary importance to understand many prominent reactions. Designing active spaces so that the improved accuracy from a quantum computer is not rendered useless is key to finding useful applications of these promising devices within the field of chemistry. To answer this issue, we introduce a NISQ-friendly method called "State-Averaged Orbital-Optimized Variational Quantum Eigensolver" (SA-OO-VQE) which combines two algorithms: (1) a state-averaged orbital-optimizer, and (2) a state-averaged VQE. To demonstrate the success of the method, we classically simulate it on a minimal Schiff base model (namely the formaldimine molecule CH2NH) relevant also for the photoisomerization in rhodopsin -- a crucial step in the process of vision mediated by the presence of a conical intersection. We show that merging both algorithms fulfil the necessary condition to describe the molecule's conical intersection, i.e. the ability to treat degenerate (or quasi-degenerate) states on the same footing.

When testing and calibrating particle detectors in a test beam, accurate tracking information independent of the detector being tested is extremely useful during the offline analysis of the data. A general-purpose Silicon Beam Tracker (SBT) was constructed with an active area of 32.0 x 32.0 mm2 to provide this capability for the beam calibration of the Cosmic Ray Energetics And Mass (CREAM) calorimeter. The tracker consists of two modules, each comprised of two orthogonal layers of 380 {\mu}m thick silicon strip sensors. In one module each layer is a 64-channel AC-coupled single-sided silicon strip detector (SSD) with a 0.5 mm pitch. In the other, each layer is a 32-channel DC-coupled single-sided SSD with a 1.0 mm pitch. The signals from the 4 layers are read out using modified CREAM hodoscope front-end electronics with a USB 2.0 interface board to a Linux DAQ PC. In this paper, we present the construction of the SBT, along with its performance in radioactive source tests and in a CERN beam test in October 2006.

Plasmonic lasers provide a paradigm-changing approach for the generation of coherent light at the nanoscale. In addition to the usual properties of coherent radiation, the emission of plasmonic lasers can feature high sensitivity to the surrounding environment, which makes this technology attractive for developing high-performance and highly-integrated sensing devices. Here, we investigate a plasmonic laser architecture based on a high-Q plasmonic crystal consisting of a periodic arrangement of nanoholes on a thin gold film cladded with an organic-dye-doped SiO$_2$ gain layer as the gain material. We report an extensive full-wave numerical analysis of the device's lasing performance and its application as a biochemical sensor, showing that the proposed design features excellent figures of merit for surface sensing that in principle can be over an order of magnitude larger than those of previously reported high-performance plasmonic biosensor architectures.

Electrically-tunable optical properties in materials are desirable for many applications ranging from displays to lasing and optical communication. In most two-dimensional thin-films and other quantum confined materials, these constants have been measured accurately. However, the optical constants of single wall nanotubes (SWCNT) as a function of electrostatic tuning are yet to be measured due to lack of electronic purity and spatial homogeneity over large areas. Here, we measure the basic optical constants of ultrathin high-purity (>99%) semiconducting single wall carbon nanotube (s-SWCNT) films with spectroscopic ellipsometry. We extract the gate-tunable complex refractive index of s-SWCNT films and observe giant modulation of the real refractive index (~11.2% or an absolute value of >0.2) and extinction coefficient (~11.6%) in the near-infrared (IR) region (1.3-1.55 {\mu}m) induced by the applied electric field significantly higher than all existing electro-optic semiconductors in this wavelength range. We further design a multilayer IR reflection phase modulator stack by combining s-SWCNT and monolayer MoS2 heterostructures that can attain >45{\deg} reflection phase modulation at 1600 nm wavelength for < 200 nm total stack thickness. Our results highlight s-SWCNT as a promising material system for infrared photonics and electro-optics in telecommunication applications.

Nonlinear dynamics of spiking neural networks has recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by collective spiking dynamics of neurons, the fine control of spiking dynamics is desirable for neuromorphic devices. Here we show that photonic spiking neurons implemented with paired nonlinear optical oscillators can be controlled to generate two modes of bio-realistic spiking dynamics by changing the optical pump amplitude. When they are coupled in a network, we found that the interaction between the photonic neurons induces an effective change in the pump amplitude depending on the order parameter that characterizes synchronization. The experimental results show that the effective change causes spontaneous modification of the spiking modes and firing rates of clustered neurons, and such collective dynamics can be utilized to realize efficient heuristics for solving NP-hard combinatorial optimization problems.

Developing a suitable production method for three-dimensional periodic nanostructures with high aspect ratios is a subject of growing interest. For mass production, Talbot lithography offers many advantages. However, one disadvantage is that the minimum period of the light intensity distribution is limited by the period of the diffraction grating used. To enhance the aspect ratio of fabricated nanostructures, in the present study we focus on multi-wave interference between diffracted waves created using the Talbot effect. We propose a unique exposure method to generate multi-wave interference between adjacent diffraction orders by controlling the angle of incidence of an ultraviolet (UV) light source. Using finite-difference time-domain simulations, we obtain fringe patterns with a sub-wavelength period using a one-dimensional periodic grating mask. Moreover, we demonstrate the practical application of this approach by using UV lithography to fabricate sub-wavelength periodic structures with an aspect ratio of 30 in millimeter-scale areas, indicating its suitability for mass production.

Controlling the contact angles of the wettability is an important issue especially in industrial applications. Establishing its {\it ab initio} predictions is hence a topic of great interest. For the predictions, it is required to setup a model of the adsorption structure of liquid molecules on a surface. The appropriate setting is expected to depend on whether the surface is of insulating or metallic materials, the latter of which is the target of the present study while all preceding {\it ab initio} studies have worked on the former. Since the feasibility of {\it ab initio} evaluations relies on the approximation of the liquid-gas interface energy evaluated roughly by the crystal ice, it would be a natural choice to take the periodic honeycomb array of the water molecules as the adsorbing model of water on the surface. Although the periodic model have successfully been used for the preceding treatments of insulating surfaces, we found for the case with metallic surfaces that the periodic model gives worse prediction to reproduce experimental values. Rather than that, the models with isolated water multimers are found to give better predictions. The ambiguity of the models about the size of multimers and the coverage is found to be small ($\sim\pm 10^{\circ}$), and is averaged over to give a plausible value based on the Boltzmann weight with the adsorbing energies. The procedure we are providing can generally be applicable to any of wettability on the surfaces of metallic materials.

Model discovery based on existing data has been one of the major focuses of mathematical modelers for decades. Despite tremendous achievements of model identification from adequate data, how to unravel the models from limited data is less resolved. In this paper, we focus on the model discovery problem when the data is not efficiently sampled in time. This is common due to limited experimental accessibility and labor/resource constraints. Specifically, we introduce a recursive deep neural network (RDNN) for data-driven model discovery. This recursive approach can retrieve the governing equation in a simple and efficient manner, and it can significantly improve the approximation accuracy by increasing the recursive stages. In particular, our proposed approach shows superior power when the existing data are sampled with a large time lag, from which the traditional approach might not be able to recover the model well. Several widely used examples of dynamical systems are used to benchmark this newly proposed recursive approach. Numerical comparisons confirm the effectiveness of this recursive neural network for model discovery.

In a neutrino-less double-beta-decay ($0\nu\beta\beta$) experiment, an irremovable two-neutrino double-beta-decay ($2\nu\beta\beta$) background surrounds the Q-value of the double beta decay isotope. The energy resolution must be improved to differentiate between $0\nu\beta\beta$ and $2\nu\beta\beta$ events. CAlcium fluoride for studies of Neutrino and Dark matters by Low Energy Spectrometer (CANDLES) discerns the $0\nu\beta\beta$ of $^{48}$Ca using a CaF$_2$ scintillator as the detector and source. Photomultiplier tubes (PMTs) collect scintillation photons. Ideally, the energy resolution should equal the statistical fluctuation of the number of photoelectrons. At the Q-value of $^{48}$Ca, the current energy resolution (2.6%) exceeds this fluctuation (1.6%). Because of CaF$_2$'s long decay constant of 1000 ns, a signal integration in 4000 ns is used to calculate the energy. The baseline fluctuation ($\sigma_{\rm baseline}$) is accumulated in the signal integration, degrading the energy resolution. Therefore, this paper studies $\sigma_{\rm baseline}$ in the CANDLES detector, which has a severe effect (1%) at the Q-value of $^{48}$Ca. To avoid $\sigma_{\rm baseline}$, photon counting can be used to obtain the number of photoelectrons in each PMT; however, a significant photoelectron signal overlapping probability in each PMT causes missing photoelectrons in counting and reduces the energy resolution. "Partial photon counting" reduces $\sigma_{\rm baseline}$ and minimizes photoelectron loss. We thus obtain improved energy resolutions of 4.5--4.0% at 1460.8 keV ($\gamma$-ray of $^{40}$K), and 3.3--2.9% at 2614.5 keV ($\gamma$-ray of $^{208}$Tl). The energy resolution at the Q-value shows an estimated improvement of 2.2%, with improved detector sensitivity by factor 1.09 for the $0\nu\beta\beta$ half-life of $^{48}$Ca.

We emphasize the role of temperature in explaining the IV ovonic threshold switching curve of amorphous phase change materials. The Poole-Frankel conduction model is supplemented by considering effects of temperature on the conductivity in amorphous materials and we find agreement with a wide variety of available data. This leads to a simple explanation of the snapback in threshold switching. We also argue that low frequency current noise in the amorphous state originates from trains of moving charge carriers derailing and restarting due to the different local structures within the amorphous material.

The "proton radius puzzle" was recently solved by reducing the four-standard deviation discrepancy between the results for electronic hydrogen ($H$) and muonic hydrogen ($\mu H$) atoms to $3.3$ value. The value of the root-mean-square radius of the proton ($r_p$), extracted from experiments on measuring the one-photon $2s-4p$ transition and the Lamb shift in hydrogen, is now $0.8335(95)$ fm, that is in good agreement with the muonic hydrogen experiments, $0.84087(39)$ fm. Even so, these values deviate significantly from the CODATA value, which is determined as the average using the results for various spectral lines including two-photon transitions in the hydrogen atom. The solution of the proton radius puzzle was realized by taking into account the influence of interference effect in one-photon scattering processes. The importance of interfering effects in atomic frequencies measurements gives an impetus to the study of experiments based on two-photon spectroscopy with the suchlike thoroughness. It is shown here that the effect of interfering pathways for two-photon $2s-nd$ transitions in a hydrogen atom is also significant in determining the proton charge radius and Rydberg constant.

The electric field grading of dielectric permittivity gradient devices is an effective way of enhancing their insulation properties. The in-situ electric field-driven assembly is an advanced method for the fabrication of insulation devices with adaptive permittivity gradients, however, there is no theoretical guidance for design. In this work, an analytical model with a time constant is developed to determine the transient permittivity of uncured composites under an applied AC electric field. This model is based on optical image and dielectric permittivity monitoring, which avoids the direct processing of complex electrodynamics. For a composite with given components, the increased filler content and electric field strength can accelerate the transient process. Compared with the finite element method (FEM) based on differential equations, this statistical model is simple but efficient, and can be applied to any low-viscosity uncured composites, which may contain multiple fillers. More importantly, when a voltage is applied to an uncured composite insulating device, the proposed model can be used to analyse the spatiotemporal permittivity characteristics of this device and optimise its permittivity gradient for electric field grading.

Tip enhanced IR spectra and imaging have been widely used in cutting-edge studies for the in-depth understanding of the composition, structure and function of interfaces at the nanoscale. However, molecular monolayer sensitivity has only been demonstrated on solid/gas interfaces. In aqueous environment, the reduced sensitivity due to strong damping of the cantilever oscillation and background IR absorption extremely limits the practical applications of tip enhanced IR nanospectroscopy. Here, we demonstrate hypersensitive nanoscale IR spectra and imaging in aqueous environment with the combination of photoinduced force (PiF) microscopy and resonant antennas. The highly confined electromagnetic field inbetween the tip end and antenna extremely amplifies the photoinduced force to the detectable level, while the excitation via plasmon internal reflection mode minimizes the environmental absorption. A polydimethylsiloxane (PDMS) layer (~1-2 nm thickness) functionalized on the AFM tip has been successfully identified in water with antennas of different sizes. Sampling volume of ~604 chemical bonds from PDMS was demonstrated with sub-10 nm spatial resolution confirmed by electric (E) field distribution mapping on antennas, which strongly suggests the desired requirements for interfacial spectroscopy. This platform demonstrates for the first time the application of photoinduced force microscopy in aqueous environments, providing a brand-new configuration to achieve highly enhanced nanoscale IR signals, which is extremely promising for future research of interfaces and nanosystems in aqueous environments.

Rubrene, a superstar in organic semiconductors, has achieved unprecedented achievements in the application of electronic devices, and research based on its various photoelectric properties is still in progress. In this review, we introduced the preparation of rubrene crystal, summarized the applications in organic optoelectronic devices with the latest research achievements based on rubrene semiconductors. An outlook of future research directions and challenges of rubrene semiconductor for applications is also provided.

The interaction of supersonic laser-driven plasma jets with a secondary gas target was studied experimentally. The plasma parameters of the jet, and resulting shock, were characterized using a combination of multi-frame interferometry/shadowgraphy and X-ray diagnostics, allowing for a detailed study of their structure and evolution. The velocity was obtained with an X-ray streak camera, and filtered X-ray pinhole imaging was used to infer the electron temperature in the jet and shock. The density and topology of the background plasma was found to have a significant effect on the jet and shock formation, as well as their radiation characteristics. The experimental results were compared with radiation hydrodynamic simulations, and qualitative agreement was seen between the two.

We estimated the residual entropy of ice Ih by the recently developed simulation protocol, namely, the combination of Replica-Exchange Wang-Landau algorithm and Multicanonical Replica-Exchange Method. We employed a model with the nearest neighbor interactions on the three-dimensional hexagonal lattice, which satisfied the ice rules in the ground state. The results showed that our estimate of the residual entropy is found to be within 0.038 % of series expansion estimate by Nagle and within 0.000077 % of PEPS algorithm by Vanderstraeten. In this article, we not only give our latest estimate of the residual entropy of ice Ih but also discuss the importance of the uniformity of a random number generator in MC simulations.

The output signal of classical symmetrical Hall plates is an odd function of the magnetic field component acting perpendicular to the plate. At weak magnetic field the Hall plate output is linearly proportional to the perpendicular magnetic field. Magnetic field components parallel to the plate may also contribute to the output signal via the planar Hall effect. It leads to even order terms of the in-plane magnetic field in the output signal. At moderate magnetic field the planar Hall effect adds to the output signal a term proportional to the square of the in-plane magnetic field. This paper reports on linear terms of the in-plane magnetic field component to the output signal of Hall-plates, when they are subjected to mechanical shear stress. The effect is small for Hall plates but large for Vertical Hall devices in (100)-silicon. It is fully described by piezo-resistance and piezo-Hall tensors. We present results of numerical simulations and measurements. Thin devices are less affected than thick devices. If magnetic angle sensors are made of Vertical Hall devices, in-plane shear stress leads to a small orthogonality error which - in contrast to the planar Hall effect - cannot be cancelled out by spinning current schemes. We propose a compensation circuit to eliminate this shear-stress induced orthogonality error.

This paper describes a novel technique that allows separation and quantification of different sources of convection in the high-latitude ionosphere. To represent the ionospheric convection electric field, we use the Spherical Elementary Convection Systems representation. We demonstrate how this technique can separate and quantify the contributions from different magnetospheric source regions to the overall ionospheric convection pattern. The technique is in particular useful for distinguishing the contributions of high-latitude reconnection associated with lobe cells from the low-latitude reconnection associated with Dungey two-cell circulation. The results from the current paper are utilized in a companion paper (Reistad et al., 2019, https://doi.org/10.1029/2019JA026641) to quantify how the dipole tilt angle influences lobe convection cells. We also describe a relation bridging other representations of the ionospheric convection electric field or potential to the Spherical Elementary Convection Systems description, enabling a similar separation of convection sources from existing models.

Helium atom scattering studies have the potential for making numerous breakthroughs in the study of processes on surfaces. As this field remains active, there will frequently be new young researchers entering the field. The transition from student to researcher is often met with difficulty, consequently wasting limited time available for a PhD or masters level research. Addressing this issue, we present an educational package for emerging research students in the field of helium atom scattering. We hope that this package serves as sufficient material to significantly accelerate the progress made by new postgraduate students.

Safeguarding the disposal of spent nuclear fuel in a geological repository needs an effective, efficient, reliable and robust non-destructive assay (NDA) system to ensure the integrity of the fuel prior to disposal. In the context of the Finnish geological repository, Passive Gamma Emission Tomography (PGET) will be a part of such an NDA system. We report here on the results of PGET measurements at the Finnish nuclear power plants during the years 2017-2020. Gamma activity profiles are recorded from all angles by rotating the detector arrays around the fuel assembly that has been inserted into the center of the torus. Image reconstruction from the resulting tomographic data is defined as a constrained minimization problem with a data fidelity term and regularization terms. The activity and attenuation maps, as well as detector sensitivity corrections, are the variables in the minimization process. The regularization terms ensure that prior information on the (possible) locations of fuel rods and their diameter are taken into account. Fuel rod classification, the main purpose of the PGET method, is based on the difference of the activity of a fuel rod from its immediate neighbors, taking into account its distance from the assembly center. The classification is carried out by a support vector machine. We report on the results for ten different fuel types with burnups between 5.72 and 55.0 GWd/tU, cooling times between 1.87 and 34.6 years and initial enrichments between 1.9 and 4.4%. For all fuel assemblies measured, missing fuel rods, partial fuel rods and water channels were correctly classified. Burnable absorber fuel rods were classified as fuel rods. On rare occasions, a fuel rod that is present was falsely classified as missing. We conclude that the combination of the PGET device and our image reconstruction method provides a reliable base for fuel rod classification.

One believed path to Interstellar Complexes Organic Molecules (iCOMs) formation inside the Interstellar Medium (ISM) is through chemical recombination at the surface of amorphous solid water (ASW) mantle covering the silicate-based core of the interstellar grains. The study of these iCOMs formation and their binding energy to the ASW, using computational chemistry, depends strongly on the ASW models used, as different models may exhibit sites with different adsorbing features. ASW extended models are rare in the literature because large sizes require very large computational resources when quantum mechanical methods based on DFT are used. To circumvent this problem, we propose to use the newly developed GFN-xTB Semi-empirical Quantum Mechanical (SQM) methods from the Grimme's group. These methods are, at least, two orders of magnitude faster than conventional DFT, only require modest central memory, and in this paper we aim to benchmark their accuracy against rigorous and resource hungry quantum mechanical methods. We focused on 38 water structures studied by MP2 and CCSD(T) approaches comparing energetic and structures with three levels of GFN-xTB parametrization (GFN0, GFN1, GFN2) methods. The extremely good results obtained at the very cheap GFN-xTB level for both water cluster structures and energetic paved the way towards the modeling of very large AWS models of astrochemical interest.

The initial detection and identification of suspicious lesions and the precise delineation of tumour mar-gins are essential for successful tumour resection, with progression-free survival linked to rates of complete resection. However, post-surgical positive margin rates remain high for many cancers and despite numerous advances in intraoperative imaging and diagnostic technologies, there exists no single modality that can adequately perform both tumoural detection and delineation. Here, we demonstrate a multimodal computer vision-based diagnostic system capable of both the gross detection and identification of suspicious lesions and the precise delineation of disease margins. We first show that through visual tracking of a spectroscopic probe, we enable real-time tumour margin delineation both for ex vivo human tumour biopsies and for an in vivo tumour xenograft mouse model. We then demonstrate that the combination of Raman spectroscopic diagnoses with protoporphyrin IX (PPIX) fluorescence imaging enables fluorescence-guided Raman spectroscopic margin delineation. Our fluorescence-guided Raman spectroscopic system achieves superior margin delineation accuracy to fluorescence imaging alone, demonstrating the potential for our system to achieve improved clinical outcomes for tumour resection surgeries.

This paper is an attempt to study the effects of surface topography on the flow of a droplet (or a bubble) in a low Reynolds number flow regime. Multiphase flows through a constricted passage find many interesting applications in chemistry and biology. The main parameters which determine the flow properties such as flow rate and pressure drop, and govern the complex multiphase phenomena such as drop coalescence, break-up and snap-off in a straight channel flow are the viscosity ratio, droplet size and ratio of the viscous forces to the surface tension forces (denoted by Capillary number). But in flow through a constricted passage, various other parameters such as constriction ratio, length and shape of the constriction, phase angle, and spacing between the constrictions also start playing an important role. An attempt has been made to review and summarize the present knowledge on these aspects and by mentioning what all lacks in the literature that could be studied further.

This paper analyzes the human and financial costs of the COVID-19 pandemic on 92 countries. We compare country-by-country equity market dynamics to cumulative COVID-19 case and death counts and new case trajectories. First, we examine the multivariate time series of cumulative cases and deaths, particularly regarding their changing structure over time. We reveal similarities between the case and death time series, and key dates that the structure of the time series changed. Next, we classify new case time series, demonstrate five characteristic classes of trajectories, and quantify discrepancy between them with respect to the behavior of waves of the disease. Finally, we show there is no relationship between countries' equity market performance and their success in managing COVID-19. Each country's equity index has been unresponsive to the domestic or global state of the pandemic. Instead, these indices have been highly uniform, with most movement in March.

Photosystem I is a light-driven electron transfer device. Available X-ray crystal structure from Thermosynechococcus elongatus, showed that electron transfer pathways consist of two nearly symmetric branches of cofactors converging at the first iron sulfur cluster FX, which is followed by two terminal iron sulfur clusters FA and FB. Experiments have shown that Fx has lower oxidation potential than FA and FB, which facilitate the electron transfer reaction. Here, we use Density Functional Theory and Multi-Conformer Continuum Electrostatics to explain the differences in the midpoint Em potentials of the Fx, FA and FB clusters. Our calculations show that Fx has the lowest oxidation potential compared to FA and FB due strong pair-wise electrostatic interactions with surrounding residues. These interactions are shown to dominated by the bridging sulfurs and cysteine ligands, which may be attributed to the shorter average bond distances between the oxidized Fe ion and ligating sulfurs for FX compared to FA and FB. Moreover, the electrostatic repulsion between the 4Fe-4S clusters and the positive potential of the backbone atoms is least for FX compared to both of FA and FB. These results agree with the experimental measurements from the redox titrations of low-temperature EPR signals and of room temperature recombination kinetics.

We present a method for accelerating discrete ordinates radiative transfer calculations for radiative transfer. Our method works with nonlinear positivity fixes, in contrast to most acceleration schemes. The method is based on the dynamic mode decomposition (DMD) and using a sequence of rank-one updates to compute the singular value decomposition needed for DMD. Using a sequential method allows us to automatically determine the number of solution vectors to include in the DMD acceleration. We present results for slab geometry discrete ordinates calculations with the standard temperature linearization. Compared with positive source iteration, our results demonstrate that our acceleration method reduces the number of transport sweeps required to solve the problem by a factor of about 3 on a standard diffusive Marshak wave problem and a factor of 20 improvement in a multimaterial radiating shock problem.

The Mu3e experiment aims to find or exclude the lepton flavour violating decay $\mu \rightarrow eee$ at branching fractions above $10^{-16}$. A first phase of the experiment using an existing beamline at the Paul Scherrer Institute (PSI) is designed to reach a single event sensitivity of $2\cdot 10^{-15}$. We present an overview of all aspects of the technical design and expected performance of the phase~I Mu3e detector. The high rate of up to $10^{8}$ muon decays per second and the low momenta of the decay electrons and positrons pose a unique set of challenges, which we tackle using an ultra thin tracking detector based on high-voltage monolithic active pixel sensors combined with scintillating fibres and tiles for precise timing measurements.

Carbon dioxide Capture and Storage (CCS) is an important strategy in mitigating anthropogenic CO$_2$ emissions. In order for CCS to be successful, large quantities of CO$_2$ must be stored and the storage site conformance must be monitored. Here we present a deep learning method to reconstruct pressure fields and classify the flux out of the storage formation based on the pressure data from Above Zone Monitoring Interval (AZMI) wells. The deep learning method is a version of a semi conditional variational auto-encoder tailored to solve two tasks: reconstruction of an incremental pressure field and leakage rate classification. The method, predictions and associated uncertainty estimates are illustrated on the synthetic data from a high-fidelity heterogeneous 2D numerical reservoir model, which was used to simulate subsurface CO$_2$ movement and pressure changes in the AZMI due to a CO$_2$ leakage.

The Poisson-Boltzmann equation is a widely used model to study the electrostatics in molecular solvation. Its numerical solution using a boundary integral formulation requires a mesh on the molecular surface only, yielding accurate representations of the solute, which is usually a complicated geometry. Here, we utilize adjoint-based analyses to form two goal-oriented error estimates that allows us to determine the contribution of each discretization element (panel) to the numerical error in the solvation free energy. This information is useful to identify high-error panels to then refine them adaptively to find optimal surface meshes. We present results for spheres and real molecular geometries, and see that elements with large error tend to be in regions where there is a high electrostatic potential. We also find that even though both estimates predict different total errors, they have similar performance as part of an adaptive mesh refinement scheme. Our test cases suggest that the adaptive mesh refinement scheme is very effective, as we are able to reduce the error one order of magnitude by increasing the mesh size less than 20\%. This result sets the basis towards efficient automatic mesh refinement schemes that produce optimal meshes for solvation energy calculations.

In recent years, metasurfaces have shown extremely powerful abilities for manipulation of electromagnetic waves. However, the local electromagnetic response of conventional metasurfaces yields to an intrinsic performance limitation in terms of efficiency, minimizing their implementation in real-life applications. The efficiency of reconfigurable metasurfaces further decreases because of the high density of meta-atoms, reaching 74 meta-atoms per $\lambda^2$ area, incorporating lossy tunable elements. To address these problems, we implement strong electromagnetic non-local features in a \textit{sparse} metasurface composed of electronically reconfigurable meta-atoms. As a proof-of-concept demonstration, a dynamic sparse metasurface having as few as $8$ meta-atoms per $\lambda^2$ area is experimentally realized in the microwave domain to control wavefronts in both near-field and far-field regions for focusing and beam-forming, respectively. The proposed metasurface with its sparsity not only facilitates design and fabrication, but also opens the door to high-efficiency real-time reprogrammable functionalities in beam manipulations, wireless power transfer and imaging holography.

Heat and fluid flow in low Prandtl number melting pools during laser processing of materials are sensitive to the prescribed boundary conditions, and the responses are highly nonlinear. Previous studies have shown that fluid flow in melt pools with surfactants can be unstable at high Marangoni numbers. In numerical simulations of molten metal flow in melt pools, surface deformations and its influence on the energy absorbed by the material are often neglected. However, this simplifying assumption may reduce the level of accuracy of numerical predictions with surface deformations. In the present study, we carry out three-dimensional numerical simulations to realise the effects of surface deformations on thermocapillary flow instabilities in laser melting of a metallic alloy with surfactants. Our computational model is based on the finite-volume method and utilises the volume-of-fluid (VOF) method for gas-metal interface tracking. Additionally, we employ a dynamically adjusted heat source model and discuss its influence on numerical predictions of the melt pool behaviour. Our results demonstrate that including free surface deformations in numerical simulations enhances the predicted flow instabilities and, thus, the predicted solid-liquid interface morphologies.

Magnetic winding is a fundamental topological quantity that underpins magnetic helicity and measures the entanglement of magnetic field lines. Like magnetic helicity, magnetic winding is also an invariant of ideal magnetohydrodynamics. In this article we give a detailed description of what magnetic winding describes, how to calculate it and how to interpret it in relation to helicity. We show how magnetic winding provides a clear topological description of magnetic fields (open or closed) and we give examples to show how magnetic winding and helicity can behave differently, thus revealing different and imporant information about the underlying magnetic field.

The paper "Physics without determinism: Alternative interpretations of classical physics" [Phys. Rev. A, 100:062107, Dec 2019] defines finite information quantities (FIQ). A FIQ expresses the available information about the value of a physical quantity. We show that a change in the measurement unit does not preserve the information carried by a FIQ, and therefore that the definition provided in the paper is not complete.

Magnetic helicity is an invariant of ideal magnetohydrodynamics (MHD) that encodes information on the topology of magnetic field lines. It has long been appreciated that magnetic topology is an important constraint for the evolution of magnetic fields in MHD. In applications to the solar atmosphere, understanding magnetic topology is crucial for following the evolution and eruption of magnetic fields. At present, magnetic helicity flux can be measured in solar observations but the interpretation of results is difficult due to the combination of confounding factors. We propose that a renormalization of helicity flux, the \emph{magnetic winding}, can be used to detect more detailed topological features in magnetic fields and thus provide a more reliable signature for predicting the onset of solar eruptions.

Due to the lockdown measures during the 2019 novel coronavirus (COVID-19) pandemic, the economic activities and the associated emissions have significantly declined. This reduction in emissions has created a natural experiment to assess the impact of the emitted precursor control policy on ozone (O$_3$) pollution, which has become a public concern in China during the last decade. In this study, we utilized comprehensive satellite, ground-level observations, and source-oriented chemical transport modeling to investigate the O$_3$ variations during the COVID-19 in China. Here we found that the O$_3$ formation regime shifted from a VOC-limited regime to a NOx-limited regime due to the lower NOx during the COVID-19 lockdown. However, instead of these changes of the O$_3$ formation region, the significant elevated O$_3$ in the North China Plain (40%) and Yangtze River Delta (35%) were mainly attributed to the enhanced atmospheric oxidant capacity (AOC) in these regions, which was different from previous studies. We suggest that future O$_3$ control policies should comprehensively consider the synergistic effects of O$_3$ formation regime and AOC on the O$_3$ elevation.

Nonlinear optics is an increasingly important field for scientific and technological applications, owing to its relevance and potential for optical and optoelectronic technologies. Currently, there is an active search for suitable nonlinear material systems with efficient conversion and small material footprint. Ideally, the material system should allow for chip-integration and room-temperature operation. Two-dimensional materials are highly interesting in this regard. Particularly promising is graphene, which has demonstrated an exceptionally large nonlinearity in the terahertz regime. Yet, the light-matter interaction length in two-dimensional materials is inherently minimal, thus limiting the overall nonlinear-optical conversion efficiency. Here we overcome this challenge using a metamaterial platform that combines graphene with a photonic grating structure providing field enhancement. We measure terahertz third-harmonic generation in this metamaterial and obtain an effective third-order nonlinear susceptibility with a magnitude as large as 3$\cdot$10$^{-8}$m$^2$/V$^2$, or 21 esu, for a fundamental frequency of 0.7 THz. This nonlinearity is 50 times larger than what we obtain for graphene without grating. Such an enhancement corresponds to third-harmonic signal with an intensity that is three orders of magnitude larger due to the grating. Moreover, we demonstrate a field conversion efficiency for the third harmonic of up to $\sim$1% using a moderate field strength of $\sim$30 kV/cm. Finally we show that harmonics beyond the third are enhanced even more strongly, allowing us to observe signatures of up to the 9$^{\rm th}$ harmonic. Grating-graphene metamaterials thus constitute an outstanding platform for commercially viable, CMOS compatible, room temperature, chip-integrated, THz nonlinear conversion applications.

This work aims to advance computational methods for projection-based reduced order models (ROMs) of linear time-invariant (LTI) dynamical systems. For such systems, current practice relies on ROM formulations expressing the state as a rank-1 tensor (i.e., a vector), leading to computational kernels that are memory bandwidth bound and, therefore, ill-suited for scalable performance on modern many-core and hybrid computing nodes. This weakness can be particularly limiting when tackling many-query studies, where one needs to run a large number of simulations. This work introduces a reformulation, called rank-2 Galerkin, of the Galerkin ROM for LTI dynamical systems which converts the nature of the ROM problem from memory bandwidth to compute bound. We present the details of the formulation and its implementation, and demonstrate its utility through numerical experiments using, as a test case, the simulation of elastic seismic shear waves in an axisymmetric domain. We quantify and analyze performance and scaling results for varying numbers of threads and problem sizes. Finally, we present an end-to-end demonstration of using the rank-2 Galerkin ROM for a Monte Carlo sampling study. We show that the rank-2 Galerkin ROM is one order of magnitude more efficient than the rank-1 Galerkin ROM (the current practice) and about 970X more efficient than the full order model, while maintaining excellent accuracy in both the mean and statistics of the field.

The ntCT nano tomography system is a geometrically magnifying X-ray microscopy system integrating the recent Excillum NanoTube nano-focus X-ray source and a CdTe photon counting detector from Dectris. The system's modulation transfer function (MTF) and corresponding point spread function (PSF) are characterized by analyzing the contrast visibility of periodic structures of a star pattern featuring line width from 150nm to 1.5$\mu$m. The results, which can be attributed to the characteristics of the source spot, are crosschecked by scanning the source's electron focus over an edge of the structured transmission target in order to obtain an independent measurement of its point spread function. For frequencies above 1000 linepairs/mm, the MTF is found to correspond to a Gaussian PSF of 250nm full width at half maximum (FWHM). The lower frequency range down to 340 linepairs/mm shows an additional Gaussian contribution of 1$\mu$m FWHM. The resulting resolution ranges at 3200 linepairs/mm, which is consistent with the visual detectability of the smallest 150nm structures within the imaged star pattern.

Engineering projects are notoriously hard to complete on-time, with project delays often theorised to propagate across interdependent activities. Here, we use a novel dataset consisting of activity networks from 14 diverse, large-scale engineering projects to uncover network properties that impact timely project completion. We provide the first empirical evidence of the infectious nature of activity deviations, where perturbations in the delivery of a single activity can impact up to 4 activities downstream, leading to large perturbation cascades. We further show that perturbation clustering significantly affects project overall delays. Finally, we find that poorly performing projects have their highest perturbations in high reach nodes, which can lead to largest cascades, while well performing projects have perturbations in low reach nodes, resulting in localised cascades. Altogether, these findings pave the way for a network-science framework that can materially enhance the delivery of large-scale engineering projects.

We theoretically study an impulsively excited quantum bouncer (QB) - a particle bouncing off a surface in the presence of gravity. A pair of time-delayed pulsed excitations is shown to induce a wave-packet echo effect - a partial rephasing of the QB wave function appearing at twice the delay between pulses. In addition, an appropriately chosen observable [here, the population of the ground gravitational quantum state (GQS)] recorded as a function of the delay is shown to contain the transition frequencies between the GQSs, their populations, and partial phase information about the wave packet quantum amplitudes. The wave-packet echo effect is a promising candidate method for precision studies of GQSs of ultra-cold neutrons, atoms, and anti-atoms confined in closed gravitational traps.

Janus phoretic colloids (JPs) self-propel as a result of self-generated chemical gradients and exhibit spontaneous nontrivial dynamics within phoretic suspensions, on length scales much larger than the microscopic swimmer size. Such collective dynamics arise from the competition of (i) the self-propulsion velocity of the particles, (ii) the attractive/repulsive chemically-mediated interactions between particles and (iii) the flow disturbance they introduce in the surrounding medium. These three ingredients are directly determined by the shape and physico-chemical properties of the colloids' surface. Owing to such link, we adapt a recent and popular kinetic model for dilute suspensions of chemically-active JPs where the particles' far-field hydrodynamic and chemical signatures are intrinsically linked and explicitly determined by the design properties. Using linear stability analysis, we show that self-propulsion can induce a wave-selective mechanism for certain particles' configurations consistent with experimental observations. Numerical simulations of the complete kinetic model are further performed to analyze the relative importance of chemical and hydrodynamic interactions in the nonlinear dynamics. Our results show that regular patterns in the particle density are promoted by chemical signaling but prevented by the strong fluid flows generated collectively by the polarized particles, regardless of their chemotactic or antichemotactic nature (i.e. for both puller and pusher swimmers).

This article reports the characterization of two High Purity Germanium detectors performed by extracting and comparing their efficiencies using experimental data and Monte Carlo simulations. The efficiencies were calculated for pointlike $\gamma$-ray sources as well as for extended calibration sources. Characteristics of the detectors such as energy linearity, energy resolution, and full energy peak efficiencies are reported from measurements performed on surface laboratories. The detectors will be deployed in a $\gamma$-ray assay facility that will be located in the first underground laboratory in Mexico, Laboratorio Subterr\'aneo de Mineral del Chico (LABChico), in the Comarca Minera UNESCO Global Geopark

Soft corals, such as the bipinnate sea plume Antillogorgia bipinnata, are colony building animals that feed by catching food particles brought by currents. With their flexible skeleton, they bend and sway back and forth when a surface wave passes over. In addition to this low frequency sway of the whole colony, branches of A. bipinnata vibrate at high frequency with small amplitude and transverse to the flow as the wave flow speed peaks. We explain the origin of these yet unexplained vibrations and investigate their effect on soft corals. Estimation of dynamical variables along with finite element implementation of the wake-oscillator model favour vortex-induced vibrations (VIV) as the most probable origin of the observed rapid dynamics. To assess the impact of these dynamics on filter feeding, we simulated particles advected by flows around a circular cylinder and calculated the capture rate with an in-house monolithic fluid-structure interaction (FSI) finite element solver and Python code. We found that vibrating cylinders can capture up to 40% more particles than fixed ones at frequency lock-in. Thence, VIV plausibly offer soft corals better food capture.

This paper investigates the impact of cell body (soma) size and branching of cellular projections on diffusion MR imaging (dMRI) and spectroscopy (dMRS) signals for both standard single diffusion encoding (SDE) and more advanced double diffusion encoding (DDE) measurements using numerical simulations. The aim is to study the ability of dMRI/dMRS to characterize the complex morphology of brain grey matter, focusing on these two distinctive features. To this end, we employ a recently developed framework to create realistic meshes for Monte Carlo simulations, covering a wide range of soma sizes and branching orders of cellular projections, for diffusivities reflecting both water and metabolites. For SDE sequences, we assess the impact of soma size and branching order on the signal b-value dependence as well as the time dependence of the apparent diffusion coefficient (ADC). For DDE sequences, we assess their impact on the mixing time dependence of the signal angular modulation and of the estimated microscopic anisotropy, a promising contrast derived from DDE measurements. The SDE results show that soma size has a measurable impact on both the b-value and diffusion time dependence, for both water and metabolites. On the other hand, branching order has little impact on either, especially for water. In contrast, the DDE results show that soma size has a measurable impact on the signal angular modulation at short mixing times and the branching order significantly impacts the mixing time dependence of the signal angular modulation as well as of the derived microscopic anisotropy, for both water and metabolites. Our results confirm that soma size can be estimated from SDE based techniques, and most importantly, show for the first time that DDE measurements show sensitivity to the branching of cellular projections, paving the way for non-invasive characterization of grey matter morphology.

Climate change is affecting and will increasingly affect astronomical observations. In this paper, we investigated the role some key weather parameters play in the quality of astronomical observations, and analysed their long-term trends (longer than 30 years) in order to grasp the impact of climate change on current and future observations. In this preliminary study, we specifically analysed four parameters, the temperature, the surface layer turbulence, the wind speed at the jetstream layer and the humidity. The analyses is conducted with data from the Very Large Telescope (VLT), operated by the European Southern Observatory (ESO), located at Cerro Paranal in the Atacama desert, Chile, which is one of the driest places on Earth. To complete the data from the various sensors installed at Paranal, we used the fifth generation and 20th century European Centre Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate, ERA5 (from 1980 to now) and ERA20C (from 1900 to 2010), which we interpolated at the Paranal observatory location. In addition, we also explored climate projections in this region, using the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble, under the worst-case climate change Shared Socio-Economic Pathways (SSP5-8.5) scenario. Further investigation is needed to better understand the underlying mechanisms of change, as well as to assess the severity of the impact.

Spatiotemporal control over the intensity of a laser pulse has the potential to enable or revolutionize a wide range of laser-based applications that currently suffer from the poor flexibility offered by conventional optics. Specifically, these optics limit the region of high intensity to the Rayleigh range and provide little to no control over the trajectory of the peak intensity. Here, we introduce a nonlinear technique for spatiotemporal control, the "self-flying focus," that produces an arbitrary trajectory intensity peak that can be sustained for distances comparable to the focal length. The technique combines temporal pulse shaping and the inherent nonlinearity of a medium to customize the time and location at which each temporal slice within the pulse comes to its focus. As an example of its utility, simulations show that the self-flying focus can form a highly uniform, meter-scale plasma suitable for advanced plasma-based accelerators.

In this proceedings we demonstrate how to implement and construct the PineAPPL grids, designed for fast-interpolation of Monte Carlo simulation with electroweak and QCD corrections, using the VegasFlow framework for Monte Carlo simulation on hardware accelerators. We provide an example of synchronous and asynchronous filling operations of PineAPPL grids from Monte Carlo events generated by VegasFlow. We compare the performance of this procedure on multithreading CPU and GPU.

Compressional Alfv\'en eigenmodes (CAE) driven by energetic ions have been observed in magnetic fusion experiments. In this paper, we show that the modes can also be driven by runaway electrons formed in post-disruption plasma, which may explain kinetic instabilities observed in DIII-D disruption experiments with massive gas injection. The mode-structure is calculated, as are the frequencies which are in agreement with experimental observations. Using a runaway electron distribution function obtained from a kinetic simulation, the mode growth rates are calculated and found to exceed the collisional damping rate when the runaway electron density exceeds a threshold value. The excitation of CAE poses a new possible approach to mitigate seed runaway electrons during the current quench and surpassing the avalanche.

Recent breakthroughs in photonics-based quantum, neuromorphic and analogue processing have pointed out the need for new schemes for fully programmable nanophotonic devices. Universal optical elements based on interferometer meshes are underpinning many of these new technologies, however this is achieved at the cost of an overall footprint that is very large compared to the limited chip real estate, restricting the scalability of this approach. Here, we propose an ultracompact platform for low-loss programmable elements using the complex transmission matrix of a multi-port multimode waveguide. Our approach allows the design of arbitrary transmission matrices using patterns of weakly scattering perturbations, which is successfully achieved by means of a deep learning inverse network. The demonstrated platform allows control over both the intensity and phase in a multiport device at a four orders reduced device footprint compared to conventional technologies, thus opening the door for large-scale integrated universal networks.

Charge state distributions in hot, dense plasmas are a key ingredient in the calculation of spectral quantities like the opacity. However, they are challenging to calculate, as models like Saha-Boltzmann become unreliable for dense, quantum plasmas. Here we present a new variational model for the charge state distribution, along with a simple model for the energy of the configurations that includes the orbital relaxation effect. Comparison with other methods reveals generally good agreement with average atom based calculations, the breakdown of the Saha-Boltzmann method, and mixed agreement with a chemical model. We conclude that the new model gives a relatively inexpensive, but reasonably high fidelity method of calculating the charge state distribution in hot dense plasmas, in local thermodynamic equilibrium.

The recent detection of phosphine in the atmosphere of Venus has reignited interest in the possibility of life aloft in this environment. If the cloud decks of Venus are indeed an abode of life, it should reside in the "habitable zone" between ~50 to ~60 km altitude, roughly coincident with the middle cloud deck, where the temperature and pressure (but not the atmospheric composition) are similar to conditions at the Earth's surface. We outline a precursor astrobiological mission to search for such putative lifeforms in situ with instrument balloons, which could be delivered to Venus via launch opportunities in 2022-2023. This mission would collect aerosol and dust samples on small balloons floating in the Venusian cloud deck and directly scrutinize whether they include any apparent biological materials and, if so, their shapes, sizes and motility. Our balloon mission would also be equipped with a miniature mass spectrometer that ought to permit the detection of complex organic molecules. The mission is augmented by contextual cameras that will be used to search for macroscopic signs of life in the Venusian atmospheric habitable zone. Finally, mass and power constraints permitting, radio interferometric determinations of the motion of the balloons in Venusian winds, together with in situ temperature and pressure measurements, will provide valuable insight into the poorly understood meteorology of the middle cloud region.

We consider an approach for community detection in time-varying networks. At its core, this approach maintains a small sketch graph to capture the essential community structure found in each snapshot of the full network. We demonstrate how the sketch can be used to explicitly identify six key community events which typically occur during network evolution: growth, shrinkage, merging, splitting, birth and death. Based on these detection techniques, we formulate a community detection algorithm which can process a network concurrently exhibiting all processes. One advantage afforded by the sketch-based algorithm is the efficient handling of large networks. Whereas detecting events in the full graph may be computationally expensive, the small size of the sketch allows changes to be quickly assessed. A second advantage occurs in networks containing clusters of disproportionate size. The sketch is constructed such that there is equal representation of each cluster, thus reducing the possibility that the small clusters are lost in the estimate. We present a new standardized benchmark based on the stochastic block model which models the addition and deletion of nodes, as well as the birth and death of communities. When coupled with existing benchmarks, this new benchmark provides a comprehensive suite of tests encompassing all six community events. We provide a set of numerical results demonstrating the advantages of our approach both in run time and in the handling of small clusters.

Micro-bending attenuation in an optical waveguide can be modeled by a Fokker-Planck equation. It is shown that a supersymmetric transformation applied to the Fokker-Planck equation is equivalent to a change in the refractive index profile, resulting in a larger or smaller attenuation. For a broad class of monomial index profiles, it is always possible to obtain an index profile with a larger micro-bending attenuation using a supersymmetric transformation. However, obtaining a smaller attenuation is not always possible and is restricted to a subset of index profiles.

Convection is a fundamental fluid transport phenomenon, where the large-scale motion of a fluid is driven, for example, by a thermal gradient or an electric potential. Modeling convection has given rise to the development of chaos theory and the reduced-order modeling of multiphysics systems; however, these models have been limited to relatively simple thermal convection phenomena. In this work, we develop a reduced-order model for chaotic electroconvection at high electric Rayleigh number. The chaos in this system is related to the standard Lorenz model obtained from Rayleigh-Benard convection, although our system is driven by a more complex three-way coupling between the fluid, the charge density, and the electric field. Coherent structures are extracted from temporally and spatially resolved charge density fields via proper orthogonal decomposition (POD). A nonlinear model is then developed for the chaotic time evolution of these coherent structures using the sparse identification of nonlinear dynamics (SINDy) algorithm, constrained to preserve the symmetries observed in the original system. The resulting model exhibits the dominant chaotic dynamics of the original high-dimensional system, capturing the essential nonlinear interactions with a simple reduced-order model.

We introduce a family of unsupervised, domain-free, and (asymptotically) model-independent algorithms based on the principles of algorithmic probability and information theory designed to minimize the loss of algorithmic information, including a lossless-compression-based lossy compression algorithm. The methods can select and coarse-grain data in an algorithmic-complexity fashion (without the use of popular compression algorithms) by collapsing regions that may procedurally be regenerated from a computable candidate model. We show that the method can preserve the salient properties of objects and perform dimension reduction, denoising, feature selection, and network sparsification. As validation case, we demonstrate that the method preserves all the graph-theoretic indices measured on a well-known set of synthetic and real-world networks of very different nature, ranging from degree distribution and clustering coefficient to edge betweenness and degree and eigenvector centralities, achieving equal or significantly better results than other data reduction and some of the leading network sparsification methods. The methods (InfoRank, MILS) can also be applied to applications such as image segmentation based on algorithmic probability.

An approximate solution is presented for simple harmonic motion in the presence of damping by a force which is a general power-law function of the velocity. The approximation is shown to be quite robust, allowing for a simple way to investigate amplitude decay in the presence of general types of weak, nonlinear damping.

Matter-wave interferometry and spectroscopy of optomechanical resonators offer complementary advantages. Interferometry with cold atoms is employed for accurate and long-term stable measurements, yet it is challenged by its dynamic range and cyclic acquisition. Spectroscopy of optomechanical resonators features continuous signals with large dynamic range, however it is generally subject to drifts. In this work, we combine the advantages of both devices. Measuring the motion of a mirror and matter waves interferometrically with respect to a joint reference allows us to operate an atomic gravimeter in a seismically noisy environment otherwise inhibiting readout of its phase. Our method is applicable to a variety of quantum sensors and shows large potential for improvements of both elements by quantum engineering.

Flexible filaments and fibres are essential components of important complex fluids that appear in many biological and industrial settings. Direct simulations of these systems that capture the motion and deformation of many immersed filaments in suspension remain a formidable computational challenge due to the complex, coupled fluid--structure interactions of all filaments, the numerical stiffness associated with filament bending, and the various constraints that must be maintained as the filaments deform. In this paper, we address these challenges by describing filament kinematics using quaternions to resolve both bending and twisting, applying implicit time-integration to alleviate numerical stiffness, and using quasi-Newton methods to obtain solutions to the resulting system of nonlinear equations. In particular, we employ geometric time integration to ensure that the quaternions remain unit as the filaments move. We also show that our framework can be used with a variety of models and methods, including matrix-free fast methods, that resolve low Reynolds number hydrodynamic interactions. We provide a series of tests and example simulations to demonstrate the performance and possible applications of our method. Finally, we provide a link to a MATLAB/Octave implementation of our framework that can be used to learn more about our approach and as a tool for filament simulation.

Network embedding is a method to learn low-dimensional representation vectors for nodes in complex networks. In real networks, nodes may have multiple tags but existing methods ignore the abundant semantic and hierarchical information of tags. This information is useful to many network applications and usually very stable. In this paper, we propose a tag representation learning model, Tag2Vec, which mixes nodes and tags into a hybrid network. Firstly, for tag networks, we define semantic distance as the proximity between tags and design a novel strategy, parameterized random walk, to generate context with semantic and hierarchical information of tags adaptively. Then, we propose hyperbolic Skip-gram model to express the complex hierarchical structure better with lower output dimensions. We evaluate our model on the NBER U.S. patent dataset and WordNet dataset. The results show that our model can learn tag representations with rich semantic information and it outperforms other baselines.

In this paper, we explore the connection between the curvature of the background De Sitter space-time with the spectroscopic study of entanglement of two atoms. Our set up is in the context of an Open Quantum System (OQS), where the two atoms, each having two energy levels and represented by Pauli spin tensor operators projected along any arbitrary direction. The system mimics the role of a pair of freely falling Unruh De-Witt detectors, which are allowed to non-adiabatically interact with a conformally coupled massless probe scalar field which has the role of background thermal bath. The effective dynamics of this combined system takes into account of the non-adiabatic interaction, which is commonly known as the Resonant Casimir Polder Interaction (RCPI) with the thermal bath. Our analysis reveals that the RCPI of two stable entangled atoms in the quantum vacuum states in OQS depends on the de Sitter space-time curvature relevant to the temperature of the thermal bath felt by the static observer. We also find that, in OQS, RCPI produces a new significant contribution appearing in the effective Hamiltonian of the total system and thermal bath under consideration. We find that the Lamb Shift is characterized by a decreasing inverse square power-law behavior, $L^{-2}$, when inter atomic Euclidean distance, $L$, is much larger than a characteristic length scale, $k$, which is the inverse surface gravity of the background De Sitter space. If the background space-time would have been Minkowskian this shift decreases as, $L^{-1}$, and is independent of temperature. Thus, we establish a connection between the curvature of the De Sitter space-time with the Lamb Shift spectroscopy.

In many cases, Neural networks can be mapped into tensor networks with an exponentially large bond dimension. Here, we compare different sub-classes of neural network states, with their mapped tensor network counterpart for studying the ground state of short-range Hamiltonians. We show that when mapping a neural network, the resulting tensor network is highly constrained and thus the neural network states do in general not deliver the naive expected drastic improvement against the state-of-the-art tensor network methods. We explicitly show this result in two paradigmatic examples, the 1D ferromagnetic Ising model and the 2D antiferromagnetic Heisenberg model, addressing the lack of a detailed comparison of the expressiveness of these increasingly popular, variational ans\"atze.

We analyze an epidemic model on a network consisting of susceptible-infected-recovered equations at the nodes coupled by diffusion using a graph Laplacian. We introduce an epidemic criterion and examine different vaccination/containment strategies: we prove that it is most effective to vaccinate a node of highest degree. The model is also useful to evaluate deconfinement scenarios and prevent a so-called second wave. The model has few parameters enabling fitting to the data and the essential ingredient of importation of infected; these features are particularly important for the current COVID-19 epidemic.

The accurate sampling of protein dynamics is an ongoing challenge despite the utilization of High-Performance Computers (HPC) systems. Utilizing only "brute force" MD simulations requires an unacceptably long time to solution. Adaptive sampling methods allow a more effective sampling of protein dynamics than standard MD simulations. Depending on the restarting strategy the speed up can be more than one order of magnitude. One challenge limiting the utilization of adaptive sampling by domain experts is the relatively high complexity of efficiently running adaptive sampling on HPC systems. We discuss how the ExTASY framework can set up new adaptive sampling strategies, and reliably execute resulting workflows at scale on HPC platforms. Here the folding dynamics of four proteins are predicted with no a priori information.

A new representation of electromagnetic gyrokinetic Vlasov-Maxwell theory is presented in which the gyrocenter equations of motion are expressed solely in terms of the perturbed electric and magnetic fields. In this representation, the gyrocenter symplectic (Poisson-bracket) structure and the gyrocenter Jacobian contain electric and magnetic perturbation terms associated with the standard first-order gyrocenter polarization and magnetization terms that traditionally appear in the gyrokinetic Maxwell equations. In addition, the gyrocenter polarization drift (which includes perturbed magnetic-field corrections) now appears explicitly in the gyrocenter velocity. The symplectic gyrokinetic Vlasov-Maxwell equations are self-consistently derived from a constrained Eulerian variational principle, which yields exact energy-momentum conservation laws (through the Noether method) that are verified explicitly. An exact toroidal canonical angular momentum conservation law is also derived explicitly under the assumption of an axisymmetric background magnetic field.

We present a framework for investigating effective dynamics of SU(3) color charge. Two- and three-body effective interaction terms inspired by the Heisenberg spin model are considered. In particular, a toy model for a three-source "baryon" is constructed and investigated analytically and numerically for various choices of interactions. VPython is used to visualize the nontrivial color charge dynamics. The treatment should be accessible to undergraduate students who have taken a first course in quantum mechanics, and suggestions for independent student projects are proposed.

Driving an open spin system by two strong, nearly degenerate fields enables addressing populations of individual spin states, characterisation of their interaction with thermal bath, and measurements of their relaxation/decoherence rates. With such addressing we observe nested magnetic resonances having nontrivial dependence on microwave field intensity: while the width of one of the resonances undergoes a strong power broadening, the other one exhibits a peculiar field-induced stabilization. We also observe light-induced narrowing of such composite resonances. The observations are explained by the dynamics of bright and dark superposition states and their interaction with reservoir.

[New and updated results were published in Nature Chemistry, doi:10.1038/s41557-020-0544-y.] The electronic Schr\"odinger equation describes fundamental properties of molecules and materials, but can only be solved analytically for the hydrogen atom. The numerically exact full configuration-interaction method is exponentially expensive in the number of electrons. Quantum Monte Carlo is a possible way out: it scales well to large molecules, can be parallelized, and its accuracy has, as yet, only been limited by the flexibility of the used wave function ansatz. Here we propose PauliNet, a deep-learning wave function ansatz that achieves nearly exact solutions of the electronic Schr\"odinger equation. PauliNet has a multireference Hartree-Fock solution built in as a baseline, incorporates the physics of valid wave functions, and is trained using variational quantum Monte Carlo (VMC). PauliNet outperforms comparable state-of-the-art VMC ansatzes for atoms, diatomic molecules and a strongly-correlated hydrogen chain by a margin and is yet computationally efficient. We anticipate that thanks to the favourable scaling with system size, this method may become a new leading method for highly accurate electronic-strucutre calculations on medium-sized molecular systems.

Robotic on-orbit servicing (OOS) is expected to be a key technology and concept for future sustainable space exploration. This paper develops a semi-analytical model for OOS systems analysis, responding to the growing needs and ongoing trend of robotic OOS. An OOS infrastructure system is considered whose goal is to provide responsive services to the random failures of a set of customer modular satellites distributed in space (e.g., at the geosynchronous equatorial orbit). The considered OOS architecture is comprised of a servicer that travels and provides module-replacement services to the customer satellites, an on-orbit depot to store the spares, and a series of launch vehicles to replenish the depot. The OOS system performance is analyzed by evaluating the mean waiting time before service completion for a given failure and its relationship with the depot capacity. Leveraging the queueing theory and inventory management methods, the developed semi-analytical model is capable of analyzing the OOS system performance without relying on computationally costly simulations. The effectiveness of the proposed model is demonstrated using a case study compared with simulation results. This paper is expected to provide a critical step to push the research frontier of analytical/semi-analytical models development for complex space systems design.

We demonstrate that the number of Nambu-Goldstone bosons is always equal to the number of conserved currents inside the scenario of non-Hermitian field theories with spontaneous symmetry breaking. This eliminates the redundancies which normally appears in Hermitian field theories, specifically when the Lagrangian under analysis violates explicitly the Lorentz symmetry.

We present spatial coherence measurements of partially coherent light in the far-field of incoherent sources with an experimental setup based on the Thompson-Wolf and Partanen-Turunen-Tervo experiments, to be performed in the context of a possible solar coherence measurement space instrument. The optical setup consists of a telescope to collimate light from a source, to diffract it by a digital micromirror device implementing a Young double-aperture interferometer in retroreflection mode, and finally to image the source into a two-dimensional sensor. Two multimode optical fibers with different diameters were used as incoherent sources and the results obtained for the spectral degree of coherence are compared to those expected from the van Cittert-Zernike theorem.

If time travel is possible, it seems to inevitably lead to paradoxes. These include consistency paradoxes, such as the famous grandfather paradox, and bootstrap paradoxes, where something is created out of nothing. One proposed class of resolutions to these paradoxes allows for multiple histories (or timelines), such that any changes to the past occur in a new history, independent of the one where the time traveler originated. We introduce a simple mathematical model for a spacetime with a time machine, and suggest two possible multiple-histories models, making use of branching spacetimes and covering spaces respectively. We use these models to construct novel and concrete examples of multiple-histories resolutions to time travel paradoxes, and we explore questions such as whether one can ever come back to a previously visited history and whether a finite or infinite number of histories is required. Interestingly, we find that the histories may be finite and cyclic under certain assumptions, in a way which extends the Novikov self-consistency conjecture to multiple histories and exhibits hybrid behavior combining the two. Investigating these cyclic histories, we rigorously determine how many histories are needed to fully resolve time travel paradoxes for particular laws of physics. Finally, we discuss how observers may experimentally distinguish between multiple histories and the Hawking and Novikov conjectures.

When boiling occurs in a liquid flow field, the phenomenon is known as forced-convection boiling. We numerically investigate such a boiling system on a cylinder in a flow at a saturated condition. To deal with the complicated liquid-vapor phase-change phenomenon, we develop a numerical scheme based on the pseudopotential lattice Boltzmann method (LBM). The collision stage is performed in the space of central moments (CMs) to enhance numerical stability for high Reynolds numbers. The adopted forcing scheme, consistent with the CMs-based LBM, leads to a concise yet robust algorithm. Furthermore, additional terms required to ensure thermodynamic consistency are derived in a CMs framework. The effectiveness of the present scheme is successfully tested against a series of boiling processes, including nucleation, growth, and departure of a vapor bubble for Reynolds numbers varying between 30 and 30000. Our CMs-based LBM can reproduce all the boiling regimes, i.e., nucleate boiling, transition boiling, and film boiling, without any artificial input such as initial vapor phase. We find that the typical boiling curve, also known as the Nukiyama curve, appears even though the focused system is not the pool boiling but the forced-convection system. Also, our simulations support experimental observations of intermittent direct solid-liquid contact even in the film-boiling regime. Finally, we provide quantitative comparison with the semi-empirical correlations for the forced-convection film boiling on a cylinder on the Nu-Ja diagram.

We report on a investigation of turbulent bubbly flows. Bubbles of a size larger than the dissipative scale, cannot be treated as point-wise inclusions, and generate important hydrodynamic fields in the carrier fluid when in motion. Furthermore, when the volume fraction of bubbles is large enough, the bubble motion may induce a collective agitation due to hydrodynamic interactions which display some turbulent-like features. We tackle this complex phenomenon numerically, performing direct numerical simulations (DNS) with a Volume-of-fluid (VOF) method. In the first part of the work, we perform both 2D and 3D tests in order to determine appropriate numerical and physical parameters.

We then carry out a highly-resolved simulation of a 3D bubble column, with a configuration and physical parameters similar to those used in laboratory experiments. This is the largest simulation attempted for such a configuration and is possible only thanks to adaptive grid refinement. Results are compared both with experiments and previous coarse-mesh numerical simulations. In particular, the one-point Probability Density Function (PDF) of the liquid velocity fluctuations is in good quantitative agreement with experiments, notably in the vertical direction, although more extreme events are sampled in the present configuration. The spectra of the liquid kinetic energy show a clear $k^{-3}$ scaling.

The mechanisms underlying the energy transfer and notably the possible presence of a cascade are unveiled by a local scale-by-scale analysis in the physical space. The comparison with previous simulations indicate to what extent simulations not fully resolved may yet give correct results, from a statistical point of view.

Amorphous molybdenum silicide compounds have attracted significant interest for potential device applications, particularly in single-photon detector. In this work, the temperature-dependent resistance and magneto-resistance behaviors were measured to reveal the charge transport mechanism, which is of great importance for applications but is still insufficient. It is found that Mott variable hopping conductivity dominates the transport of sputtered amorphous molybdenum silicide thin films. Additionally, the observed magneto-resistance crossover from negative to positive is ascribed to the interference enhancement and the shrinkage of electron wave function, both of which vary the probability of hopping between localized sites.

In recent times, spatial light modulators have become a common tool in optics laboratories as well as industrial environment to shape the spatial structure of a beam. Although these devices are often easy to use, they usually come at a high cost such that they are far from being implemented in a lot of undergraduate laboratories. However, over the last years, the progress in developing more cost-effective projectors has led to affordable spatial light modulators in the form of so-called Digital Micromirror Devices (DMD). This reduction in price, as well as their simple usage, make such devices increasingly suitable for undergraduate laboratories to demonstrate optical effects and the shaping of light fields. Here, we show one of the most cost-effective ways to make a DMD available, namely turning a projector evaluation module into a computer-controlled spatial light modulator. We explain the underlying functioning and how this low-cost spatial light modulator can be used in undergraduate laboratories. We further characterize the efficiency of the device for the most commonly used laser wavelengths and demonstrate various exemplary optics experiments suitable for undergraduate laboratories ranging from single and multi-slit diffraction, to optical Fourier transformations. Lastly, we show that using amplitude holography, the device can be used to generate transverse spatial modes, e.g. Laguerre-Gaussian beam, which are one of the most commonly used spatially structured beams.

We introduce and study a novel class of sensors whose sensitivity grows exponentially with the size of the device. Remarkably, this drastic enhancement does not rely on any fine-tuning, but is found to be a stable phenomenon immune to local perturbations. Specifically, the physical mechanism behind this striking phenomenon is intimately connected to the anomalous sensitivity to boundary conditions observed in non-Hermitian topological systems. We outline concrete platforms for the practical implementation of these non-Hermitian topological sensors (NTOS) ranging from classical meta-materials to synthetic quantum-materials.

We investigate the absorption and transmission properties of a weak probe field under the influence of a strong control field in a hybrid cavity magnomechanical system in the microwave regime. This hybrid system consists of two ferromagnetic material yttrium iron garnet (YIG) spheres strongly coupled to a single cavity mode. In addition to two magnon-induced transparency (MIT) that arise due to strong photon-magnon interactions, we observe a magnomechanically induced transparency (MMIT) due to the presence of nonlinear phonon-magnon interaction. In addition, we discuss the emergence and tunability of the multiple Fano resonances in our system. We find that due to strong photon-magnon coupling the group delay of the probe field can be enhanced significantly. The subluminal or superluminal propagation depends on the frequency of the magnons, which can be easily tuned by an external bias magnetic field. Besides, the group delay of the transmitted field can also be controlled with the control field power.

The algebraic reformulation of molecular Quantum Electrodynamics (mQED) at finite temperatures is applied to Nuclear Magnetic Resonance (NMR) in order to provide a foundation for the reconstruction of much more detailed molecular structures, than possible with current methods. Conventional NMR theories are based on the effective spin model which idealizes nuclei as fixed point particles in a lattice $L$, while molecular vibrations, bond rotations and proton exchange cause a delocalization of nuclei. Hence, a lot information on molecular structures remain hidden in experimental NMR data, if the effective spin model is used for the investigation.

In this document it is shown how the quantum mechanical probability density $\mid\Psi^\beta(X)\mid^2$ on $\mathbb{R}^{3n}$ for the continuous, spatial distribution of $n$ nuclei can be reconstructed from NMR data. To this end, it is shown how NMR spectra can be calculated directly from mQED at finite temperatures without involving the effective description. The fundamental problem of performing numerical calculations with the infinite-dimensional radiation field is solved by using a purified representation of a KMS state on a $W^*$-dynamical system. Furthermore, it is shown that the presented method corrects wrong predictions of the effective spin model. It is outlined that the presented method can be applied to any molecular system whose electronic ground state can be calculated using a common quantum chemical method. Therefore, the presented method may replace the effective spin model which forms the basis for NMR theory since 1950.

In a concurrent work, Villois et al. 2020 reported the evidence that vortex reconnections in quantum fluids follow an irreversible dynamics, namely vortices separate faster than they approach; such time-asymmetry is explained by using simple conservation arguments. In this work we develop further these theoretical considerations and provide a detailed study of the vortex reconnection process for all the possible geometrical configurations of the order parameter (superfluid) wave function. By matching the theoretical description of incompressible vortex filaments and the linear theory describing locally vortex reconnections, we determine quantitatively the linear momentum and energy exchanges between the incompressible (vortices) and the compressible (density waves) degrees of freedom of the superfluid. We show theoretically and corroborate numerically, why a unidirectional density pulse must be generated after the reconnection process and why only certain reconnecting angles, related to the rates of approach and separations, are allowed. Finally, some aspects concerning the conservation of centre-line helicity during the reconnection process are discussed.

We statistically study vortex reconnections in quantum fluids by evolving different realizations of vortex Hopf links using the Gross--Pitaevskii model. Despite the time-reversibility of the model, we report a clear evidence that the dynamics of the reconnection process is time-irreversible, as reconnecting vortices tend to separate faster than they approach. Thanks to a matching theory devised concurrently in Proment and Krstulovic (arXiv:2005.02047), we quantitatively relate the origin of this asymmetry to the generation of a sound pulse after the reconnection event. Our results have the prospect of being tested in several quantum fluid experiments and, theoretically, may shed new light on the energy transfer mechanisms in both classical and quantum turbulent fluids.

There is renewed interest in using the coherence between beams generated in separate down-converter sources for new applications in imaging, spectroscopy, microscopy and optical coherence tomography (OCT). These schemes make use of continuous wave (CW) pumping in the low parametric gain regime, which generates frequency entanglement between the signal-idler pairs generated in a single source. Is this frequency entanglement a requisite to observe coherence between signal photons generated in separate biphoton sources? We will show that it is not. This might be an advantage for OCT applications. High axial resolution requires a large bandwidth. For CW pumping this requires the use of short nonlinear crystals. This is detrimental since short crystals generate small photon fluxes. We show that the use of ultrashort pump pulses allows improving axial resolution even for long crystal that produce higher photon fluxes.

This work is inspired by the deadlock of conventional theory of unstably-stratified turbulence that, however, plausibly calculates vertical mixing, just sufficient in many applications, and so remains in use. The paradox is explained by irrelevance to the buoyancy-generated part of turbulence of the conventional, presumably universal paradigm "chaos out of order - towards dissipation", copying the Kolmogorov vision of non-stratified shear-generated turbulence. Instead, alternative paradigm defining the buoyancy-generated turbulence, as "order out of chaos - towards self-organization" is invented, demonstrated and proved empirically. Speaking the Thomas Kuhn language, new paradigm launches a "scientific revolution" in theory and modelling of unstably-stratified turbulence and in numerous related phenomena from the atmosphere-Earth surface interaction to stellar convection. The paper is designed for wide readership including potential users of novel theory and all those who are interested in controversial relations between chaos and order.

The measurement of the tunneling time in attosecond experiments, termed as attoclock, offers a fruitful opportunity to understand the role of time in quantum mechanics. It has triggered a hot debate about the tunneling time and the separation into two regimes or processes of different character, the multiphoton ionization and the tunneling (field) ionization. In the present work, we show that our tunneling model presented in previous work, explains the non-adiabatic effects (photon absorption) in the interaction of atoms with strong field as well. Again, as it was the case in the adiabatic field calibration, we reach a very good agreement with the experimental data in the non-adiabatic field calibration of Hofmann et al (J. of Mod. Opt. 66, 1052, 2019). Interestingly, our model offers a clear picture for the multiphoton and tunneling parts. In particular, the tunneling part is now resolve by the non-adiabaticity, which is mainly the absorption of a number of photons that is characteristic for the barrier height. The well known separation of multiphoton and tunneling regimes (usually by Keldysh parameter) is clarified with a more advanced picture. Surprisingly, at a field strength $F < F_a$ the model indicates always a delay time with respect to the quantum limit, which is the ionization time at atomic field strength $F_a$, where the barrier suppression ionization sets up.

Grain boundaries play a critical role in applications of superconducting Nb$_3$Sn: in dc applications, grain boundaries preserve the material's inherently high critical current density by pinning flux, while in ac applications grain boundaries can provide weak points for flux entry and lead to significant dissipation. We present the first $\textit{ab initio}$ study to investigate the physics of different boundary types in Nb$_3$Sn using density functional theory. We identify an energetically favorable selection of tilt and twist grain boundaries of distinct orientations. We find that clean grain boundaries free of point defects reduce the Fermi-level density of states by a factor of two, an effect that decays back to the bulk electronic structure $\sim1-1.5$ nm from the boundary. We further calculate the binding free-energies of tin substitutional defects to multiple boundaries, finding a strong electronic interaction that extends to a distance comparable to that of the reduction of density of states. Associated with this interaction, we discover a universal trend in defect electronic entropies near a boundary. We probe the effects of defect segregation on grain boundary electronic structure and calculate the impact of substitutional impurities on the Fermi-level density of states in the vicinity of a grain boundary, finding that titanium and tantalum have little impact regardless of placement, whereas tin, copper, and niobium defects each have a significant impact but only on sites away from the boundary core. Finally, we consider how all of these effects impact the local superconducting transition temperature $T_\textrm{c}$ as a function of distance from the boundary plane.

High-resolution tunneling electron spin transport properties (longitudinal spin current (LSC) and spin transfer torque (STT) maps) of topologically distinct real-space magnetic skyrmionic textures are reported by employing a 3D-WKB combined scalar charge and vector spin transport theory in the framework of spin-polarized scanning tunneling microscopy (SP-STM). For our theoretical investigation metastable skyrmionic spin structures with various topological charges ($Q=-3,-2,-1,0,1,2$) in the (Pt$_{0.95}$Ir$_{0.05}$)/Fe/Pd(111) ultrathin magnetic film are considered. Using an out-of-plane magnetized SP-STM tip it is found that the maps of the LSC vectors acting on the spins of the magnetic textures and all STT vector components exhibit the same topology as the skyrmionic objects. In contrast, an in-plane magnetized tip generally does not result in spin transport vector maps that are topologically equivalent to the underlying spin structure, except for the LSC vectors acting on the spins of the skyrmionic textures at a specific relation between the spin polarizations of the sample and the tip. The magnitudes of the spin transport vector quantities exhibit close relations to charge current SP-STM images irrespectively of the skyrmionic topologies. Moreover, we find that the STT efficiency (torque/current ratio) acting on the spins of the skyrmions can reach large values up to $\sim$25 meV/$\mu$A ($\sim$0.97 $h/e$) above the rim of the magnetic objects, but it considerably varies between large and small values depending on the lateral position of the SP-STM tip above the topological spin textures. A simple expression for the STT efficiency is introduced to explain its variation. Our calculated spin transport vectors can be used for the investigation of spin-polarized tunneling-current-induced spin dynamics of topologically distinct surface magnetic skyrmionic textures.

This paper presents measurements of the scintillation light yield and time profile for a number of concentration of water-based liquid scintillator, formulated from linear alkylbenzene (LAB) and 2,5-diphenyloxazole (PPO). We find that the scintillation light yield is linear with the concentration of liquid scintillator in water between 1 and 10% with a slope of 127.9+-17.0 ph/MeV/concentration and an intercept value of 108.3+-51.0 ph/MeV, the latter being illustrative of non-linearities with concentration at values less than 1%. This is larger than expected from a simple extrapolation of the pure liquid scintillator light yield. The measured time profiles are consistently faster than that of pure liquid scintillator, with rise times less than 250ps and prompt decay constants in the range of 2.1-2.85ns. Additionally, the separation between Cherenkov and scintillation light is quantified using cosmic muons in the CHESS experiment for each formulation, demonstrating an improvement in separation at the centimeter scale. Finally, we briefly discuss the prospects for large-scale detectors.

We propose a conceptual model which generates abrupt climate changes akin to Dansgaard-Oeschger events. In the model these abrupt climate changes are not triggered by external perturbations but rather emerge in a dynamic self-consistent model through complex interactions of the ocean, the atmosphere and an intermittent process. The abrupt climate changes are caused in our model by intermittencies in the sea-ice cover. The ocean is represented by a Stommel two-box model, the atmosphere by a Lorenz-84 model and the sea-ice cover by a deterministic approximation of correlated additive and multiplicative noise (CAM) process. The key dynamical ingredients of the model are given by stochastic limits of deterministic multi-scale systems and recent results in deterministic homogenisation theory. The deterministic model reproduces statistical features of actual ice-core data such as non-Gaussian $\alpha$-stable behaviour. The proposed mechanism for abrupt millenial-scale climate change only relies on the existence of a quantity, which exhibits intermittent dynamics on an intermediate time scale. We consider as a particular mechanism intermittent sea-ice cover where the intermittency is generated by emergent atmospheric noise. However, other mechanisms such as freshwater influxes may also be formulated within the proposed framework.

Electronic current flowing in a molecular electronic junction dissipates significant amounts of energy to vibrational degrees of freedom, straining and rupturing chemical bonds and often quickly destroying the integrity of the molecular device. The infamous mechanical instability of molecular electronic junctions critically limits performance, lifespan, and raises questions as to the technological viability of single-molecule electronics. Here we propose a practical scheme for cooling the molecular vibrational temperature via application of an AC voltage over a large, static operational DC voltage bias. Using nonequilibrium Green's functions, we computed the viscosity and diffusion coefficient experienced by nuclei surrounded by a nonequilibrium "sea" of periodically driven, current-carrying electrons. The effective molecular junction temperature is deduced by balancing the viscosity and diffusion coefficients. Our calculations show the opportunity of achieving in excess of 40\% cooling of the molecular junction temperature while maintaining the same average current.

In this study a spatio-temporal approach for the solution of the time-dependent Boltzmann (transport) equation is derived. Finding the exact solution using the Boltzmann equation for the general case is generally an open problem and approximate methods are usually used. One of the most common methods is the spherical harmonics method (the $P_N$ approximation), when the exact transport equation is replaced with a closed set of equations for the moments of the density, with some closure assumption. Unfortunately, the classic $P_N$ closure yields poor results with low-order $N$ in highly anisotropic problems. Specifically, the tails of the particle's positional distribution as attained by the $P_N$ approximation, are inaccurate compared to the true behavior. In this work we present a derivation of a linear closure that even for low-order approximation yields a solution that is superior to the classical $P_N$ approximation. This closure, is based on an asymptotic derivation, both for space and time, of the exact Boltzmann equation in infinite homogeneous media. We test this approximation with respect to the one-dimensional benchmark of the full Green function in infinite media. The convergence of the proposed approximation is also faster when compared to (classic or modified) $P_N$ approximation.

Silver benzeneselenolate [AgSePh] is a coordination polymer that hosts a hybrid quantum well structure. The recent advancements in the study of its tightly bound excitons (~300 meV) and photoconductive properties (recently employed in UV photodetection) makes it an interesting representative of a material platform that is an environmentally stable alternative to 2D metal halide perovskites in terms of optoelectronic properties. To this aim, several challenges are to be addressed, among which the lack of control over the metal-organic reaction process in the reported synthesis of the [AgSePh] nanocrystal film (NC). This issue contributed to cast doubts over the origin of its intra-bandgap electronic states. In this article we study all the steps to obtain phase pure [AgSePh] NC films, from thin silver films through its oxidation and reaction via a chemical vapor-solid with benzeneselenol, by means of UV-vis, XRD, SEM, and AFM. Raman and FTIR spectroscopy are also employed to provide vibrational peaks assignment, for the first time on this polymer. Our analysis supports an acid-base reaction scheme based on an acid attacking the metal oxide precursor, generating water as byproduct of the polymeric synthesis, speeding up the reaction by solvating the PhSeH. The reaction readily goes to completion within 30 min in a supersaturated PhSeH / N2 atmosphere at 90 {\deg}C. Our analysis suggests the absence of precursor's leftovers or oxidized species that could contribute to the intra-gap states. By tuning the reaction parameters, we gained control on film morphology to obtain substrate-parallel oriented micro-crystals showing different excitonic absorption intensities. Finally, centimeters size high quality [AgSePh] NC films could be obtained, enabling exploitation of their optoelectronic properties, such as UV photodetection, in large-area applications.

Buoyant, finite-size or inertial particle motion is fundamentally unlike neutrally buoyant, infinitesimally small or Lagrangian particle motion. The de-jure fluid mechanics framework for the description of inertial particle dynamics is provided by the Maxey-Riley equation. Derived from first principles - a result of over a century of research since the pioneering work by Sir George Stokes - the Maxey-Riley equation is a Newton-type-law with several forces including (mainly) flow, added mass, shear-induced lift, and drag forces. In this paper we present an overview of recent efforts to port the Maxey-Riley framework to oceanography. These involved: 1) including the Coriolis force, which was found to explain behavior of submerged floats near mesoscale eddies; 2) accounting for the combined effects of ocean current and wind drag on inertial particles floating at the air-sea interface, which helped understand the formation of great garbage patches and the role of anticyclonic eddies as plastic debris traps; and 3) incorporating elastic forces, which are needed to simulate the drift of pelagic Sargassum. Insight on the nonlinear dynamics of inertial particles in every case was possible to be achieved by investigating long-time asymptotic behavior in the various Maxey-Riley equation forms, which represent singular perturbation problems involving slow and fast variables.

Short-time filtering of the photoionization amplitude extracted straight from the numerical solution of the time-dependent Schr\"{o}dinger equation (TDSE) is used to identify dominant pathways that form photoelectron spectra in strong fields. Thereby, the "black-box nature" of TDSE solvers only giving the final spectrum is overcome, and simpler approaches, e.g., semi-classical based on the strong-field approximation, can be tested and improved. The approach also allows to suppress intercycle quantum interference between pathways removing patterns that are usually washed out in experiments.

The negatively charged silicon monovacancy $V_{Si}^-$ in 4H-silicon carbide (SiC) is a spin-active point defect that has the potential to act as a qubit or quantum memory in solid-state quantum computation applications. Photonic crystal cavities (PCCs) can augment the optical emission of the $V_{Si}^-$, yet fine-tuning the defect-cavity interaction remains challenging. We report on two post-fabrication processes that result in enhancement of the $V_1^{'}$ optical emission from our 1-dimensional PCCs, indicating improved coupling between the ensemble of silicon vacancies and the PCC. One process involves below bandgap illumination at 785 nm and 532 nm wavelengths and above bandgap illumination at 325 nm, carried out at times ranging from a few minutes to several hours. The other process is thermal annealing at $100^o C$, carried out over 20 minutes. Every process except above bandgap irradiation improves the defect-cavity coupling, manifested in augmented Purcell factor enhancement of the $V_1^{'}$ zero phonon line at 77K. The below bandgap laser process is attributed to a modification of charge states, changing the relative ratio of $V_{Si}^0$ (dark state) to $V_{Si}^-$ (bright state), while the thermal annealing process may be explained by diffusion of carbon interstitials, $C_i$, that subsequently recombine with other defects to create additional $V_{Si}^-$s. Above bandgap radiation is proposed to initially convert $V_{Si}^{0}$ to $V_{Si}^-$, but also may lead to diffusion of $V_{Si}^-$ away from the probe area, resulting in an irreversible reduction of the optical signal. Observations of the PCC spectra allow insights into defect modifications and interactions within a controlled, designated volume and indicate pathways to improve defect-cavity interactions.

Electric currents induced in conductive planetary interiors by time-varying magnetospheric and ionospheric current systems have a significant effect on electromagnetic (EM) field observations. Complete characterization of EM induction effects is difficult owing to non-linear interactions between the three-dimensional (3-D) electrical structure of a planet and spatial complexity of inducing current systems. We present a general framework for time-domain modeling of 3-D EM induction effects in heterogeneous conducting planets. Our approach does not assume the magnetic field is potential and allows for an arbitrary distribution of electrical conductivity within a planet and can deal with spatially complex time-varying current systems. The method is applicable to both data measured at stationary observation sites and satellite platforms, and enables the calculation of 3-D EM induction effects in near real-time settings.

We propose a new way to implement Dirichlet boundary conditions for complex shapes using data from a single node only, in the context of the lattice Boltzmann method. The resulting novel method exhibits second-order convergence for the velocity field and shows similar or better accuracy than the well established Bouzidi, Firdaouss, and Lallemand (2001) boundary condition for curved walls, despite its local nature. The method also proves to be suitable to simulate moving rigid objects or immersed surfaces either with or without prescribed motion. The core idea of the new approach is to generalize the description of boundary conditions that combine bounce-back rule with interpolations and to enhance them by limiting the information involved in the interpolation to a close proximity of the boundary.

Kant and Hegel are among the philosophers who are guiding the way in which we reason these days. It is thus of interest to see how physical theories have been developed along the line of Kant and Hegel. Einstein became interested in how things appear to moving observers. Quantum mechanics is also an observer-dependent science. The question then is whether quantum mechanics and relativity can be synthesized into one science. The present form of quantum field theory is a case in point. This theory however is based on the algorithm of the scattering matrix where all participating particles are free in the remote past and in the remote future. We thus need, in addition, a Lorentz-covariant theory of bound state which will address the question of how the hydrogen atom would look to moving observers. The question is then whether this Lorentz-covariant theory of bound states can be synthesized with the field theory into a Lorentz-covariant quantum mechanics. This article reviews the progress made along this line. This integrated Kant-Hegel process is illustrated in terms of the way in which Americans practice their democracy.

Optimal control of turbulent mixed-convection flows has attracted considerable attention from researchers. Numerical algorithms such as Genetic Algorithms (GAs) are powerful tools that allow to perform global optimization. These algorithms are particularly of great interest in complex optimization problems where cost functionals may lack smoothness and regularity. In turbulent flow optimization, the hybridization of GA with high fidelity Computational Fluid Dynamics (CFD) is extremely demanding in terms of computational time and memory storage. Thus, alternative approaches aiming to alleviate these requirements are of great interest. Nowadays, data driven approaches gained attention due to their potential in predicting flow solutions based only on preexisting data. In the present paper, we propose a near-real time data-driven genetic algorithm (DDGA) for inverse parameter identification problems involving turbulent flows. In this optimization framework, the parametrized flow data are used in their reduced form obtained by the POD (Proper Orthogonal Decomposition) and solutions prediction is made by interpolating the temporal and the spatial POD subspaces through a recently developed Riemannian barycentric interpolation. The validation of the proposed optimization approach is carried out in the parameter identification problem of the turbulent mixed-convection flow in a cavity. The objective is to determine the inflow temperature and inflow velocity corresponding to a given temperature distribution in a restricted area of the spatial domain. The results show that the proposed genetic programming optimization framework is able to deliver good approximations of the optimal solutions within less than two minutes.

The Muon $g\textrm{-}2$ Experiment (E989) at Fermilab has a goal of measuring the muon anomaly ($a_\mu$) with unprecedented precision using positive muons. This measurement is motivated by the difference between the previous Brookhaven $a_\mu$ measurement and Standard Model prediction exceeding three standard deviations, which hints at the possibility of physics beyond the Standard Model. Muons are circulated in a storage ring, and the measurement requires a precise determination of the muon anomalous precession frequency (spin precession relative to momentum) from the resulting decay positron time and energy measurements collected with calorimeters. The average magnetic field seen by the muons needs to be known with high precision, and so the storage ring magnetic field is shimmed to be very uniform and is continually monitored with nuclear magnetic resonance (NMR) probes. Detailed Muon Campus beamline and muon storage ring simulations are also required for quantifying beam dynamics and spin-related systematic effects in the determination of the muon anomalous precession frequency, e.g. muon losses during the measurement window. At the time of the conference, the experiment has recently commenced Run-3, and the release of Run-1 physics results is planned for 2020.

Spontaneous locking of the phase of a coherent phonon source to an external reference is demonstrated in an optomechanical oscillator based on a self-triggered free-carrier/temperature limit cycle. Synchronization is observed when the pump laser driving the mechanical oscillator to a self-sustained state is modulated by a radiofrequency tone. We employ a pump-probe phonon detection scheme based on an independent optical cavity to observe only the mechanical oscillator dynamics. The lock range of the oscillation frequency, i.e., the Arnold tongue, is experimentally determined over a range of external reference strengths, evidencing the possibility to tune the oscillator frequency for a range up to 350 kHz. The stability of the coherent phonon source is evaluated via its phase noise, with a maximum achieved suppression of 44 dBc/Hz at 1kHz offset for a 100 MHz mechanical resonator. Introducing a weak modulation in the excitation laser reveals as a further knob to trigger, control and stabilise the dynamical solutions of self-pulsing based optomechanical oscillators, thus enhancing their potential as acoustic wave sources in a single layer silicon platform.

Considerable progress has been made in organic light-emitting diodes (OLEDs) to achieve high external quantum efficiency (EQE), among which the dipole orientation of OLED emitters has a remarkable effect. In most cases, EQE of the OLED emitter is theoretically predicted with only one orientation factor to match with corresponding experiments. Here, we develop a distribution theory with three independent parameters to fully describe the relationship between dipole orientations and power densities. Furthermore, we propose an optimal experiment configuration for measuring such distribution parameters. Measuring the unpolarized spectrum extremely can dig more information of dipole orientation distributions with a rather simple way. Our theory provides a universal plot of the OLED dipole orientation, paving the way for designing more complicated OLED structures.

One desired outcome of introductory physics instruction is that students will be able to reason mathematically about physical phenomena. Little research has been done regarding how students develop the knowledge and skills needed to reason productively about physics quantities, which is different from either conceptual understanding or problem-solving abilities. We introduce the Physics Inventory of Quantitative Literacy (PIQL) as a tool for measuring quantitative literacy (i.e., mathematical reasoning) in the context of introductory physics. We present the development of the PIQL and results showing its validity for use in calculus-based introductory physics courses. As has been the case with many inventories in physics education, we expect large-scale use of the PIQL to catalyze the development of instructional materials and strategies--in this case, designed to meet the course objective that all students become quantitatively literate in introductory physics. Unlike concept inventories, the PIQL is a reasoning inventory, and can be used to assess reasoning over the span of students' instruction in introductory physics.

The scattering matrix, which quantifies the optical reflection and transmission of a photonic structure, is pivotal for understanding the performance of the structure. In many photonic design tasks, it is also desired to know how the structure's optical performance changes with respect to design parameters, that is, the scattering matrix's derivatives (or gradient). Here we address this need. We present a new algorithm for computing scattering matrix derivatives accurately and robustly. In particular, we focus on the computation in semi-analytical methods (such as rigorous coupled-wave analysis). To compute the scattering matrix of a structure, these methods must solve an eigen-decomposition problem. However, when it comes to computing scattering matrix derivatives, differentiating the eigen-decomposition poses significant numerical difficulties. We show that the differentiation of the eigen-decomposition problem can be completely sidestepped, and thereby propose a robust algorithm. To demonstrate its efficacy, we use our algorithm to optimize metasurface structures and reach various optical design goals.

A new application of subspaces interpolation for the construction of nonlinear Parametric Reduced Order Models (PROMs) is proposed. This approach is based upon the Riemannian geometry of the manifold formed by the quotient of the set of full-rank N-by-q matrices by the orthogonal group of dimension q. By using a set of untrained parametrized Proper Orthogonal Decomposition (POD) subspaces of dimension q, the subspace for a new untrained parameter is obtained as the generalized Karcher barycenter which solution is sought after by solving a simple fixed point problem. Contrary to existing PROM approaches, the proposed barycentric PROM is by construction easier to implement and more flexible with respect to change in parameter values. To assess the potential of the barycentric PROM, numerical experiments are conducted on the parametric flow past a circular cylinder and the flow in a lid driven cavity when the value of Reynolds number varies. It is demonstrated that the proposed barycentric PROM approach achieves competitive results with considerably reduced computational cost.

The Photon wave function Formalism provides an alternative description of some quantum optical phenomena in a more intuitive way. We use this formalism to describe the process of correlated Stokes--anti-Stokes Raman scattering. In this process, two photons from a laser beam are inelastically scattered by a phonon created by the first photon (Stokes processes) and annihilated by the second photon (anti-Stokes process), producing a Stokes--anti-Sokes (SaS) photon pair. We arrive at an expression for the two-photon wave function of the scattered SaS photon pair, which is in agreement with a number of experimental results.