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



In this study, we connect concepts that have been recently developed in thermoacoustics, specifically, (i) high-order spectral perturbation theory, (ii) symmetry induced degenerate thermoacoustic modes, (iii) intrinsic thermoacoustic modes, and (iv) exceptional points. Their connection helps gain physical insight into the behaviour of the thermoacoustic spectrum when parameters of the system are varied. First, we extend high-order adjoint-based perturbation theory of thermoacoustic modes to the degenerate case. We provide explicit formulae for the calculation of the eigenvalue corrections to any order. These formulae are valid for self-adjoint, non-self-adjoint or even non-normal systems; therefore, they can be applied to a large range of problems, including fluid dynamics. Second, by analysing the expansion coefficients of the eigenvalue corrections as a function of a parameter of interest, we accurately estimate the radius of convergence of the power series. Third, we connect the existence of a finite radius of convergence to the existence of singularities in parameter space. We identify these singularities as exceptional points, which correspond to defective thermoacoustic eigenvalues, with infinite sensitivity to infinitesimal changes in the parameters. At an exceptional point, two eigenvalues and their associated eigenvectors coalesce. Close to an exceptional point, strong veering of the eigenvalue trajectories is observed. As demonstrated in recent work, exceptional points naturally arise in thermoacoustic systems due to the interaction between modes of acoustic and intrinsic origin. The role of exceptional points in thermoacoustic systems sheds new light on the physics and sensitivity of thermoacoustic stability, which can be leveraged for passive control by small design modifications.

The dynamics of initially truncated and bent line solitons for the Kadomtsev-Petviashvili (KPII) equation modelling internal and surface gravity waves are analysed using modulation theory. In contrast to previous studies on obliquely interacting solitons that develop from acute incidence angles, this work focuses on initial value problems for the obtuse incidence of two or three partial line solitons, which propagate away from one another. Despite counterpropagation, significant residual soliton interactions are observed with novel physical consequences. The initial value problem for a truncated line soliton---describing the emergence of a quasi-one-dimensional soliton from a wide channel---is shown to be related to the weak interaction of oblique solitons. Analytical descriptions for the development of weak and strong interactions are obtained in terms of interacting simple wave solutions of modulation equations for the local soliton amplitude and slope. In the weak interaction case, the long-time evolution of truncated and large obtuse angle solitons exhibits a decaying, parabolic wave profile with temporally increasing focal length that asymptotes to a cylindrical Korteweg-de Vries soliton. In contrast, the resonant case of slightly obtuse interacting solitons evolves into a steady, one-dimensional line soliton with amplitude reduced by an amount proportional to the incidence slope. This strong interaction is identified with the "Mach expansion" of a soliton with an expansive corner, contrasting with the well-known Mach reflection of a soliton with a compressive corner. Interestingly, the critical angles for Mach expansion and reflection are the same. Numerical simulations of the KPII equation quantitatively support the analytical findings.

A model for the wave motion of an internal wave in the presence of current in the case of intermediate long wave approximation is studied. The lower layer is considerably deeper, with a higher density than the upper layer. The flat surface approximation is assumed. The fluids are incompressible and inviscid. The model equations are obtained from the Hamiltonian formulation of the dynamics in the presence of a depth-varying current. It is shown that an appropriate scaling leads to the integrable Intermediate Long Wave Equation (ILWE). Two limits of the ILWE leading to the integrable Benjamin-Ono and KdV equations are presented as well.

The aim of this paper is to assess the effectiveness of nonlinear viscoelastic damping in controlling base-excited vibrations. Specifically, the focus is on investigating the robustness of the nonlinear base isolation performance in controlling the system response due to a wide set of possible excitation spectra. The dynamic model is derived to study a simple structure whose base isolation is provided via a Rubber-Layer Roller Bearing (RLRB) (rigid cylinders rolling on rigid plates with highly damping rubber coatings) equipped with a nonlinear cubic spring, thus presenting both nonlinear damping and stiffness. We found that, under periodic loading, due to the non-monotonic bell-shaped viscoelastic damping arising from the viscoelastic rolling contacts, different dynamic regimes occur mostly depending on whether the damping peak is overcome or not. Interestingly, in the former case, poorly damped self-excited vibrations may be triggered by the steep damping decrease. Moreover, in order to investigate the robustness of the isolation performance, we consider a set of real seismic excitations, showing that tuned nonlinear RLRB provide loads isolation in a wider range of excitation spectra, compared to generic linear isolators. This is peculiarly suited for applications (such as seismic and failure engineering) in which the specific excitation spectrum is unknown a priori, and blind design on statistical data has to be employed.

In this work, we present the experimental optical trap of microparticles with an Airy beams array using a holographic optical tweezers. The Airy beams array are attractive for optical manipulation of particles owing to their non--diffracting and autofocusing properties. An Airy beams array is composed of N Airy beams which accelerate mutually and symmetrically in opposite direction, for different ballistic trajectories, that is, with different initial launch angles. Based on this, we developed a holographic optical tweezers system for the generation of non-diffracting beams and with it, we investigate the distribution of optical forces acting on microparticles of an Airy beams array. The results show that the gradient and scattering force of array on microparticles can be controlled through a launch angle parameter of Airy beams. In addition, it's possible to obtain greater stability for optical trap using an Airy beams array, with interesting possibilities for trapping and guiding of microparticles in a controllable way that can be applied in optical, biological and atmospheric sciences.

Solar wind measurements in the heliosphere are predominantly comprised of protons, alphas, and minor elements in a highly ionized state. The majority of low charge states, such as He$^{+}$, measured in situ are often attributed to pick up ions of non-solar origin. However, through inspection of the velocity distribution functions of near Earth measurements, we find a small but significant population of He$^+$ ions in the normal solar wind whose properties indicate that it originated from the Sun and has evolved as part of the normal solar wind. Current ionization models, largely governed by electron impact and radiative ionization and recombination processes, underestimate this population by several orders of magnitude. Therefore, to reconcile the singly ionized He observed, we investigate recombination of solar He$^{2+}$ through charge exchange with neutrals from circumsolar dust as a possible formation mechanism of solar He$^{+}$. We present an empirical profile of neutrals necessary for charge exchange to become an effective vehicle to recombine He$^{2+}$ to He$^{+}$ such that it meets observational He$^{+}$ values. We find the formation of He$^{+}$ is not only sensitive to the density of neutrals but also to the inner boundary of the neutral distribution encountered along the solar wind path. However, further observational constraints are necessary to confirm that the interaction between solar $\alpha$ particles and dust neutrals is the primary source of the He$^{+}$ observations.

To study axonal microstructure with diffusion MRI, axons are typically modeled as straight impermeable cylinders, whereby the transverse diffusion MRI signal can be made sensitive to the cylinder's inner diameter. However, the shape of a real axon varies along the axon direction, which couples the longitudinal and transverse diffusion of the overall axon direction. Here we develop a theory of the intra-axonal diffusion MRI signal based on coarse-graining of the axonal shape by 3d diffusion. We demonstrate how the estimate of the inner diameter is confounded by the diameter variations (beading), and by the local variations in direction (undulations) along the axon. We analytically relate diffusion MRI metrics, such as time-dependent radial diffusivity D(t) and kurtosis K(t), to the axonal shape, and validate our theory using Monte Carlo simulations in synthetic undulating axons with randomly positioned beads, and in realistic axons reconstructed from electron microscopy images of mouse brain white matter. We show that (i) In the narrow pulse limit, the inner diameter from D(t) is overestimated by about twofold due to a combination of axon caliber variations and undulations (each contributing a comparable effect size); (ii) The narrow-pulse kurtosis K$_{t\to\infty}$ deviates from that in an ideal cylinder due to caliber variations; we also numerically calculate the fourth-order cumulant for an ideal cylinder in the wide pulse limit, which is relevant for inner diameter overestimation; (iii) In the wide pulse limit, the axon diameter overestimation is mainly due to undulations at low diffusion weightings b; and (iv) The effect of undulations can be considerably reduced by directional averaging of high-b signals, with the apparent inner diameter given by a combination of the axon caliber (dominated by the thickest axons), caliber variations, and the residual contribution of undulations.

Photonic topological edge states in one-dimensional dimer chains have long been thought to be robust to structural perturbations by mapping the topological Su-Schrieffer-Heeger model of a solid-state system. However, the edge states at the two ends of a finite topological dimer chain will interact as a result of near-field coupling. This leads to deviation from topological protection by the chiral symmetry from the exact zero energy, weakening the robustness of the topological edge state. With the aid of non-Hermitian physics, the splitting frequencies of edge states can be degenerated again and topological protection recovered by altering the gain or loss strength of the structure. This point of coalescence is known as the exceptional point (EP). The intriguing physical properties of EPs in topological structures give rise to many fascinating and counterintuitive phenomena. In this work, based on a finite non-Hermitian dimer chain composed of ultra-subwavelength resonators, we propose theoretically and verify experimentally that the sensitivity of topological edge states is greatly affected when the system passes through the EP. Using the EP of a non-Hermitian dimer chain, we realize a new sensor that is sensitive to perturbation at the end of the structure and yet topologically protected from internal perturbation. Our demonstration of a non-Hermitian topological structure with an EP paves the way for the development of novel sensors that are not sensitive to internal manufacturing errors but are highly sensitive to changes in the external environment.

An introductory Astronomy survey course is often taken to satisfy a college graduation requirement for non-science majors at colleges around the United States. In this course, material that can be broadly categorized into topics related to "the sky", "the Solar System", "the Galaxy", and "cosmology" is discussed. Even with the wide variety of topics in these categories, though, students may not be 100% interested in the course content, and it is almost certain that a specific topic about which a student wishes to learn is not covered. To at least partly address these issues, to appeal to all of the students in this class, and to allow students to explore topics of their choice, a video project has been assigned to students at Albion College as a class activity. In this assignment, students are asked to create a video of a famous (or not) astronomer, astronomical object or discovery, or telescope observatory to present to the class. Students work in pairs to create a video that is original and imaginative and includes accurate scientific content. For this project, then, students use a familiar technology and exercise their creativity while learning a little (or a lot of) science along the way. Herein data on types and topics of videos, examples of videos, assignment requirements and grading rubrics, lessons learned, and student comments will be discussed and shared.

The concept of an embodied intelligent agent is a key concept in modern AI and robotics. Physically, an agent---like a Turing machine---is an open system embedded in an environment which it interacts with through sensors and actuators. It contains a learning algorithm that correlates the sensor and actuator results by learning features about its environment. The sensor-actuator system is similar to a measurement based control system. Quantum mechanics enables new measurement and control protocols capable of exceeding what can be achieved classically. We demonstrate how quantum optical sensors and actuators can dramatically improve an agent's ability to learn in a thermal environment. Furthermore we use the Jarzynski equality to show that learning maximises the exchange in free energy $\Delta F$ between the agent's sensor and actuator when considered as a stochastic feedback cycle.

All three motional modes of a charged dielectric nanoparticle in a Paul trap are cooled by direct feedback to temperatures of a few mK. We test two methods, one based on electrical forces and the other on optical forces; for both methods, we find similar cooling efficiencies. Cooling is characterized for both feedback forces as a function of feedback parameters, background pressure, and the particle's position.

Solving large complex partial differential equations (PDEs), such as those that arise in computational fluid dynamics (CFD), is a computationally expensive process. This has motivated the use of deep learning approaches to approximate the PDE solutions, yet the simulation results predicted from these approaches typically do not generalize well to truly novel scenarios. In this work, we develop a hybrid (graph) neural network that combines a traditional graph convolutional network with an embedded differentiable fluid dynamics simulator inside the network itself. By combining an actual CFD simulator (run on a much coarser resolution representation of the problem) with the graph network, we show that we can both generalize well to new situations and benefit from the substantial speedup of neural network CFD predictions, while also substantially outperforming the coarse CFD simulation alone.

Many social and biological systems are characterized by enduring hierarchies, including those organized around prestige in academia, dominance in animal groups, and desirability in online dating. Despite their ubiquity, the general mechanisms that explain the creation and endurance of such hierarchies are not well understood. We introduce a generative model for the dynamics of hierarchies using time-varying networks in which new links are formed based on the preferences of nodes in the current network and old links are forgotten over time. The model produces a range of hierarchical structures, ranging from egalitarianism to bistable hierarchies, and we derive critical points that separate these regimes in the limit of long system memory. Distinctively, our model supports statistical inference, allowing for a principled comparison of generative mechanisms using data. We apply the model to study hierarchical structures in empirical data on hiring patterns among mathematicians, dominance relations among parakeets, and friendships among members of a fraternity, observing several persistent patterns as well as interpretable differences in the generative mechanisms favored by each. Our work contributes to the growing literature on statistically grounded models of time-varying networks.

Power storage devices such as batteries are a crucial part of modern technology. The development and use of batteries has accelerated in the past decades, yet there are only a few techniques that allow gathering vital information from battery cells in a nonivasive fashion. A widely used technique to investigate batteries is electrical impedance spectroscopy (EIS), which provides information on how the impedance of a cell changes as a function of the frequency of applied alternating currents. Building on recent developments of inside-out MRI (ioMRI), a technique is presented here which produces spatially-resolved maps of the oscillating magnetic fields originating from the alternating electrical currents distributed within a cell. The technique works by using an MRI pulse sequence synchronized with a gated alternating current applied to the cell terminals. The approach is benchmarked with a current-carrying wire coil, and demonstrated with commercial and prototype lithium-ion cells. Marked changes in the fields are observed for different cell types.

Since we still lack a theory of classical turbulence, attention has focused on the conceptually simpler turbulence in quantum fluids. Can such systems of identical singly-quantized vortices provide a physically accessible "toy model" of the classical counterpart? That said, we have hitherto lacked detectors capable of the real-time, non-invasive probing of the wide range of length scales involved in quantum turbulence. However, we demonstrate here the real-time detection of quantum vortices by a nanoscale resonant beam in superfluid $^4$He at 10 mK. The basic idea is that we can trap a single vortex along the length of a nanobeam and observe the transitions as a vortex is either trapped or released, which we observe through the shift in the resonant frequency of the beam. With a tuning fork source, we can control the ambient vorticity density and follow its influence on the vortex capture and release rates. But, most important, we show that these devices are capable of probing turbulence on the micron scale.

Purpose: The goal is to provide a sufficient condition on the invertibility of a multi-energy (ME) X-ray transform. The energy-dependent X-ray attenuation profiles can be represented by a set of coefficients using the Alvarez-Macovski (AM) method. An ME X-ray transform is a mapping from $N$ AM coefficients to $N$ noise-free energy-weighted measurements, where $N\geq2$.

Methods: We apply a general invertibility theorem which tests whether the Jacobian of the mapping $J(\mathbf A)$ has zero values over the support of the mapping. The Jacobian of an arbitrary ME X-ray transform is an integration over all spectral measurements. A sufficient condition of $J(\mathbf A)\neq0$ for all $\mathbf A$ is that the integrand of $J(\mathbf A)$ is $\geq0$ (or $\leq0$) everywhere. Note that the trivial case of the integrand equals to zero everywhere is ignored. With symmetry, we simplified the integrand of the Jacobian into three factors that are determined by the total attenuation, the basis functions, and the energy-weighting functions, respectively. The factor related to total attenuation is always positive, hence the invertibility of the X-ray transform can be determined by testing the signs of the other two factors. Furthermore, we use the Cramer-Rao lower bound (CRLB) to characterize the noise-induced estimation uncertainty and provide a maximum-likelihood (ML) estimator.

Conclusions: We have provided a framework to study the invertibility of an arbitrary ME X-ray transform and proved the global invertibility for four types of systems.

Quantum mechanics in the Wigner-von Neumann interpretation is presented. This is characterized by 1) a quantum dualism between matter and consciousness unified within an informational neutral monism, 2) a quantum perspectivism which is extended to a complementarity between the Copenhagen interpretation and the many-worlds formalism, 3) a psychophysical causal closure akin to Leibniz parallelism and 4) a quantum solipsism, i.e. a reality in which classical states are only potentially-existing until a conscious observation is made.

Poincar\'e maps for toroidal magnetic fields are routinely employed to study gross confinement properties in devices built to contain hot plasmas. In most practical applications, evaluating a Poincar\'e map requires numerical integration of a magnetic field line, a process that can be slow and that cannot be easily accelerated using parallel computations. We show that a novel neural network architecture, the H\'enonNet, is capable of accurately learning realistic Poincar\'e maps from observations of a conventional field-line-following algorithm. After training, such learned Poincar\'e maps evaluate much faster than the field-line integration method. Moreover, the H\'enonNet architecture exactly reproduces the primary physics constraint imposed on field-line Poincar\'e maps: flux preservation. This structure-preserving property is the consequence of each layer in a H\'enonNet being a symplectic map. We demonstrate empirically that a H\'enonNet can learn to mock the confinement properties of a large magnetic island by using coiled hyperbolic invariant manifolds to produce a sticky chaotic region at the desired island location. This suggests a novel approach to designing magnetic fields with good confinement properties that may be more flexible than ensuring confinement using KAM tori.

Elucidating mechanisms of a selective chemical reaction is fundamental towards control over its outcome. For molecules colliding on a surface, accelerating the molecule towards the surface has not been considered as a means to attain a selective reaction. Here we show bond-selective reaction of a molecule induced by its translational kinetic energy towards a surface. We use electrospray ion beam deposition to collide the molecule at low, hyperthermal translational energy (2 - 50 eV) with a Cu(100) surface and image the outcome at single-molecule level using Scanning Tunneling Microscopy (STM). A large mechanical impulse generated from the collision compresses the molecule and bends specific bonds within, making them react selectively. The compression-induced dynamics leads to reaction products that are inaccessible by thermal pathways since the compression timescale (sub-picoseconds) is much shorter than the thermalization timescale (nanoseconds or longer). The bond-selective, compression-induced chemistry, exemplified here by an organic dye molecule (Reichardt's Dye, C41H30NO+) colliding on a Cu-surface allows the exploration of mechanochemistry, especially for large molecules possessing complex chemical functionality that may have limited thermal stability.

We propose a state-sensitive scheme to optically detect a single molecule without a closed transition, through strong coupling to a high-Q whispering-gallery mode high-Q resonator. A background-free signal can be obtained by detecting a molecule-induced transparency in a photon bus waveguide that is critically coupled to the resonator, with a suppressed depumping rate to other molecular states by the cooperativity parameter $C$. We numerically calculate the dynamics of the molecule-resonator coupled system using Lindblad master equations, and develop analytical solutions through the evolution of quasi-steady states in the weak-driving regime. Using Rb$_2$ triplet ground state molecules as an example, we show that high fidelity state readout can be achieved using realistic resonator parameters. We further discuss the case of multiple molecules collectively coupled to a resonator, demonstrating near-unity detection fidelity and negligible population loss.

The brain may be thought of as a many-body architecture with a spatio-temporal dynamics described by neuronal structures. The oscillatory nature of brain activity allows these structures (nodes) to be described as a set of coupled oscillators forming a network where the node dynamics, and that of the network topology can be studied. Quantifying its dynamics at various scales is an issue that claims to be explored for several brain activities, e.g., activity at rest. The resting-state associates the underlying brain dynamics of healthy subjects that are not actively compromised with sensory or cognitive processes. Studying its dynamics is highly non-trivial but opens the door to understand the general principles of brain functioning. We hypothesize about how could be the spatio-temporal dynamics of cortical fluctuations for healthy subjects at resting-state. We retrieve the alphabet that reconstructs the dynamics (entropy/complexity) of magnetoencephalograpy signals. We assemble the cortical connectivity to elicit the network's dynamics. We depict an order relation between entropy/complexity for frequency bands. We unveiled that the posterior cortex conglomerates nodes with both stronger dynamics and high clustering for {\alpha} band. The existence of these order relations suggests an emergent phenomenon of each band. Interestingly, we find that the posterior cortex plays a cardinal role in both the dynamics and structure regarding the resting-state. To the best of our knowledge, this is the first study with magnetoencephalograpy involving information theory and network science to better understand the dynamics and structure of brain activity at rest for different bands and scales.

One of the goals of current particle physics research is to obtain evidence for new physics, that is, physics beyond the Standard Model (BSM), at accelerators such as the Large Hadron Collider (LHC) at CERN. The searches for new physics are often guided by BSM theories that depend on many unknown parameters, which, in some cases, makes testing their predictions difficult. In this paper, machine learning is used to model the mapping from the parameter space of the phenomenological Minimal Supersymmetric Standard Model (pMSSM), a BSM theory with 19 free parameters, to some of its predictions. Bayesian neural networks are used to predict cross sections for arbitrary pMSSM parameter points, the mass of the associated lightest neutral Higgs boson, and the theoretical viability of the parameter points. All three quantities are modeled with average percent errors of 3.34% or less and in a time significantly shorter than is possible with the supersymmetry codes from which the results are derived. These results are a further demonstration of the potential for machine learning to model accurately the mapping from the high dimensional spaces of BSM theories to their predictions.

Biphasic chemical reactions compartmentalized in small droplets offer advantages, such as streamlined procedures for chemical analysis, enhanced chemical reaction efficiency and high specificity of conversion. In this work, we experimentally and theoretically investigate the rate for biphasic chemical reactions between acidic nanodroplets on a substrate surface and basic reactants in a surrounding bulk flow. The reaction rate is measured by droplet shrinkage as the product is removed from the droplets by the flow. In our experiments, we determine the dependence of the reaction rate on the flow rate and the solution concentration. The theoretical analysis predicts that the life time $\tau$ of the droplets scales with Peclet number $Pe$ and the reactant concentration in the bulk flow $c_{re,bulk}$ as $\tau\propto Pe^{-3/2}c_{re,bulk}^{-1}$, in good agreement with our experimental results. Furthermore, we found that the product from the reaction on an upstream surface can postpone the droplet reaction on a downstream surface, possibly due to the adsorption of interface-active products on the droplets in the downstream. The time of the delay decreases with increasing $Pe$ of the flow and also with increasing reactant concentration in the flow, following the scaling same as that of the reaction rate with these two parameters. Our findings provide insight for the ultimate aim to enhance droplet reactions under flow conditions.

We present a sawtooth model that explains observations where the central safety factor, $q_0$, stays well below one, which is irreconcilable with current models that predict a reset to $q_0=1$ after the crash. We identify the structure of the field around the magnetic axis with elements of the Lie group $\mathrm{SL}(2,\mathbb{R})$ and find a transition to an alternating-hyperbolic geometry when $q_0=2/3$. This transition is driven by an ideal MHD instability and leads to a chaotic magnetic field near the axis.

We present a microscopic model for exciton-induced transparency (ExIT) in a hybrid system comprised of an emitter resonantly coupled to a surface plasmon in a metal-dielectric structure. We obtain an effective optical polarizability of such a system with coupling between the system components expressed in terms of energy transfer rates. We demonstrate that, in the weak coupling regime, the underlying mechanism of ExIT is the energy exchange imbalance between the plasmon and the emitter in a narrow frequency region. We derive in analytic form a frequency-dependent function that accurately describes the shape and amplitude of the transparency window in scattering spectra, supported by numerical calculations.

We designed a nanoscale light extractor (NLE) for the efficient outcoupling and beaming of broadband light emitted by shallow, negatively charged nitrogen-vacancy (NV) centers in bulk diamond. The NLE consists of a patterned silicon layer on diamond and requires no etching of the diamond surface. Our design process is based on adjoint optimization using broadband time-domain simulations, and yields structures that are inherently robust to positioning and fabrication errors. Our NLE functions like a transmission antenna for the NV center, enhancing the optical power extracted from an NV center positioned 10 nm below the diamond surface by a factor of more than 35, and beaming the light into a 30{\deg} cone in the far field. This approach to light extraction can be readily adapted to other solid-state color centers.

Collections of cells exhibit coherent migration during morphogenesis, cancer metastasis, and wound healing. In many cases, bigger clusters split, smaller sub-clusters collide and reassemble, and gaps continually emerge. The connections between cell-level adhesion and cluster-level dynamics, as well as the resulting consequences for cluster properties such as migration velocity, remain poorly understood. Here we investigate collective migration of one- and two-dimensional cell clusters that collectively track chemical gradients using a mechanism based on contact inhibition of locomotion. We develop both a minimal description based on the lattice gas model of statistical physics, and a more realistic framework based on the cellular Potts model which captures cell shape changes and cluster rearrangement. In both cases, we find that cells have an optimal adhesion strength that maximizes cluster migration speed. The optimum negotiates a tradeoff between maintaining cell-cell contact and maintaining cluster fluidity, and we identify maximal variability in the cluster aspect ratio as a revealing signature. Our results suggest a collective benefit for intermediate cell-cell adhesion.

Small-scale magnetic flux ropes (SFRs) are a type of structures in the solar wind that possess helical magnetic field lines. In a recent report (Chen & Hu 2020), we presented the radial variations of the properties of SFR from 0.29 to 8 au using in situ measurements from the Helios, ACE/Wind, Ulysses, and Voyager spacecraft. With the launch of the Parker Solar Probe (PSP), we extend our previous investigation further into the inner heliosphere. We apply a Grad-Shafranov-based algorithm to identify SFRs during the first two PSP encounters. We find that the number of SFRs detected near the Sun is much less than that at larger radial distances, where magnetohydrodynamic (MHD) turbulence may act as the local source to produce these structures. The prevalence of Alfvenic structures significantly suppresses the detection of SFRs at closer distances. We compare the SFR event list with other event identification methods, yielding a dozen well-matched events. The cross-section maps of two selected events confirm the cylindrical magnetic flux rope configuration. The power-law relation between the SFR magnetic field and heliocentric distances seems to hold down to 0.16 au.

In this paper, we model the trajectory of the cumulative confirmed cases and deaths of COVID-19 (in log scale) via a piecewise linear trend model. The model naturally captures the phase transitions of the epidemic growth rate via change-points and further enjoys great interpretability due to its semiparametric nature. On the methodological front, we advance the nascent self-normalization (SN) technique (Shao, 2010) to testing and estimation of a single change-point in the linear trend of a nonstationary time series. We further combine the SN-based change-point test with the NOT algorithm (Baranowski et al., 2019) to achieve multiple change-point estimation. Using the proposed method, we analyze the trajectory of the cumulative COVID-19 cases and deaths for 30 major countries and discover interesting patterns with potentially relevant implications for effectiveness of the pandemic responses by different countries. Furthermore, based on the change-point detection algorithm and a flexible extrapolation function, we design a simple two-stage forecasting scheme for COVID-19 and demonstrate its promising performance in predicting cumulative deaths in the U.S.

Liquid electricity generator and hydrovoltaic technology have received numerous attentions, which can be divided into horizontal movement generator and vertical movement generator. The horizontal movement generator is limited for powering the integrated and miniaturized energy chip as the current output direction is depending on the moving direction of the water droplet, which means a sustainable and continuous direct current output can be hardly achieved because of the film of limited length. On the other hand, the existing vertical movement generators include triboelectricity or humidity gradient-based liquid electricity generator, where the liquid or water resource must be sustainably supplied to ensure continuous current output. Herein, we have designed an integratable vertical generator by sandwiching water droplets with semiconductor and metal, such as graphene or aluminum. This generator, named as polarized liquid molecular generator (PLMG), directly converts the lateral kinetic energy of water droplet into vertical direct-electricity with an output voltage of up to ~1.0 V from the dynamic water-semiconductor interface. The fundamental discovery of PLMG is related to the non-symmetric structure of liquid molecules, such as water and alcohols, which can be polarized under the guidance of built-in field caused by the Fermi level difference between metal and semiconductor, while the symmetric liquid molecules cannot produce any electricity on the opposite. Integratable PLMG with a large output power of ~90 nW and voltage of ~2.7 V has been demonstrated, meanwhile its small internal resistance of ~250 kilohm takes a huge advantage in resistance matching with the impedance of electron components. The PLMG shows potential application value in the Internet of Things after proper miniaturization and integration.

A novel ultra-sensitive Parity-Time symmetry based Graphene FET (PTS-GFET) sensor is studied for gas concentration detection. The PTS-GFET sensor effectively integrates the sensitivity of the PT symmetry around its Exceptional Point (EP) and the tunability of the GFET conductance. The change of GFET conductance with the gas concentration can be brought back to the EP of the PTS-GFET by tuning the gate voltage on the GFET. Thus, the applied gate voltage indicates the gas concentration. The minimum detectable gas concentration has been derived and estimated based on the experimental data, which shows that PTS-GFET can detect gas concentration below 50 ppb.

Coronal Mass Ejections (CMEs) often show different features in different band-passes. By combining data in white-light (WL) and ultraviolet (UV) bands, we have applied different techniques to derive plasma temperatures, electron density, internal radial speed, etc, within a fast CME. They serve as extensive tests of the diagnostic capabilities, developed for the observations provided by future multi-channel coronagraphs (such as Solar Orbiter/Metis, ASO-S/LST, PROBA-3/ASPIICS). The involved data include WL images acquired by SOHO/LASCO coronagraphs, and intensities measured by SOHO/UVCS at 2.45 R$_{\odot}$ in the UV (H I Ly$\alpha$ and O VI 1032 {AA} lines) and WL channels. Data from the UVCS WL channel have been employed for the first time to measure the CME position angle with polarization-ratio technique. Plasma electron and effective temperatures of the CME core and void are estimated by combining UV and WL data. Due to the CME expansion and the possible existence of prominence segments, the transit of the CME core results in decreases of the electron temperature down to $10^{5}$ K. The front is observed as a significant dimming in the Ly$\alpha$ intensity, associated with a line broadening due to plasma heating and flows along the line-of-sight. The 2D distribution of plasma speeds within the CME body is reconstructed from LASCO images and employed to constrain the Doppler dimming of Ly$\alpha$ line, and simulate future CME observations by Metis and LST.

We investigate the effect of solute drag on grain growth (GG) kinetics in olivine-rich rocks through full field and mean field modelling. Considering a drag force exerted by impurities on grain boundary migration allows reconciling laboratory and natural constraints on olivine GG kinetics. Solute drag is implemented in a full field level-set framework and on a mean field model, which explicitly accounts for a grain size distribution. After calibration of the mean field model on full field results, both models are able to both reproduce laboratory GG kinetics and to predict grain sizes consistent with observations in peridotite xenoliths from different geological contexts.

Attempts to control the epidemic spread of COVID19 in the different countries often involve imposing restrictions to the mobility of citizens. Recent examples demonstrate that the effectiveness of these policies strongly depends on the willingness of the population to adhere them. And this is a parameter that it is difficult to measure and control. We demonstrate in this manuscript a systematic way to check the mood of a society and a way to incorporate it into dynamical models of epidemic propagation. We exemplify the process considering the case of Spain although the results and methodology can be directly extrapolated to other countries.

Intense ultrashort laser pulses propagating through an underdense plasma are able to drive relativistic plasma waves, creating accelerating structures with extreme gradients. These structures represent a new type of compact sources for generating ultrarelativistic, ultrashort electron beams. This chapter covers the theoretical background behind the process of LWFA. Starting from the basic description of electromagnetic waves and their interaction with particles, the main aspects of the LWFA are presented. These include the excitation of plasma waves, description of the acceleration phase and injection mechanisms. These considerations are concluded by a discussion of the fundamental limits on the energy gain and scaling laws.

We report the spectral features of a phase-shifted parity and time ($\mathcal{PT}$)-symmetric fiber Bragg grating (PPTFBG) and demonstrate its functionality as a demultiplexer in the unbroken $\mathcal{PT}$-symmetric regime. The length of the proposed system is of the order of millimeters and the lasing spectra in the broken $\mathcal{PT}$-symmetric regime can be easily tuned in terms of intensity, bandwidth and wavelength by varying the magnitude of the phase shift in the middle of the structure. Surprisingly, the multi-modal lasing spectra are suppressed by virtue of judiciously selected phase and the gain-loss value. Also, it is possible to obtain sidelobe-less spectra in the broken $\mathcal{PT}$-symmetric regime, without a need for an apodization profile, which is a traditional way to tame the unwanted sidelobes. The system is found to show narrow band single-mode lasing behavior for a wide range of phase shift values for given values of gain and loss. Moreover, we report the intensity tunable reflection and transmission characteristics in the unbroken regime via variation in gain and loss. At the exceptional point, the system shows unidirectional wave transport phenomenon independent of the presence of phase shift in the middle of the grating. For the right light incidence direction, the system exhibits zero reflection wavelengths within the stopband at the exceptional point. We also investigate the role of multiple phase shifts placed at fixed locations along the length of the FBG and the variations in the spectra when the phase shift and gain-loss values are tuned. In the broken $\mathcal{PT}$-symmetric regime, the presence of multiple phase shifts aids in controlling the number of reflectivity peaks besides controlling their magnitude.

Material thermal properties characterization at nanoscales remains a challenge even if progresses were done in developing specific characterization techniques like the Scanning Thermal Microscopy (SThM). In the present work, we propose a detailed procedure based on the combined use of a SThM probe characterization and its Finite Element Modeling (FEM) to recover in-operando 3omega measurements achieved under high vacuum. This approach is based on a two-step methodology: (i) a fine description of the probe s electrical and frequency behaviors in out of contact mode to determine intrinsic parameters of the SThM tip, (b) a minimization of the free parameter of our model, i.e. the contact thermal resistance, by comparing 3omega measurements to our simulations of the probe operating in contact mode. Such an approach allows us to accurately measure thermal interface resistances of the probe as a function of the strength applied between the tip and the surface for three different materials (silicon, silica and gold). In addition, FEM modeling provides insights about the 3omega-SThM technique sensitivity, as a function of probe / sample interface resistance to measure material thermal conductivity, paving the way to quantitative SThM measurements.

The bandgap tunability of mixed-halide perovskites makes them promising candidates for light emitting diodes and tandem solar cells. However, illuminating mixed-halide perovskites results in the formation of segregated phases enriched in a single-halide. This segregation occurs through ion migration, which is also observed in single-halide compositions, and whose control is thus essential to enhance the lifetime and stability. Using pressure-dependent transient absorption spectroscopy, we find that the formation rates of both iodide- and bromide-rich phases in MAPb(BrxI1-x)3 reduce by two orders of magnitude on increasing the pressure to 0.3 GPa. We explain this reduction from a compression-induced increase of the activation energy for halide migration, which is supported by first-principle calculations. A similar mechanism occurs when the unit cell volume is reduced by incorporating a smaller cation. These findings reveal that stability with respect to halide segregation can be achieved either physically through compressive stress or chemically through compositional engineering.

Traditional methods for black box optimization require a considerable number of evaluations which can be time consuming, unpractical, and often unfeasible for many engineering applications that rely on accurate representations and expensive models to evaluate. Bayesian Optimization (BO) methods search for the global optimum by progressively (actively) learning a surrogate model of the objective function along the search path. Bayesian optimization can be accelerated through multifidelity approaches which leverage multiple black-box approximations of the objective functions that can be computationally cheaper to evaluate, but still provide relevant information to the search task. Further computational benefits are offered by the availability of parallel and distributed computing architectures whose optimal usage is an open opportunity within the context of active learning. This paper introduces the Resource Aware Active Learning (RAAL) strategy, a multifidelity Bayesian scheme to accelerate the optimization of black box functions. At each optimization step, the RAAL procedure computes the set of best sample locations and the associated fidelity sources that maximize the information gain to acquire during the parallel/distributed evaluation of the objective function, while accounting for the limited computational budget. The scheme is demonstrated for a variety of benchmark problems and results are discussed for both single fidelity and multifidelity settings. In particular we observe that the RAAL strategy optimally seeds multiple points at each iteration allowing for a major speed up of the optimization task.

We report on a recently developed laser-based diagnostic which allows direct measurements of ray-deflection angles in one axis, whilst retaining imaging capabilities in the other axis. This allows us to measure the spectrum of angular deflections from a laser beam which passes though a turbulent high-energy-density plasma. This spectrum contains information about the density fluctuations within the plasma, which deflect the probing laser over a range of angles. The principle of this diagnostic is described, along with our specific experimental realisation. We create synthetic diagnostics using ray-tracing to compare this new diagnostic with standard shadowgraphy and schlieren imaging approaches, which demonstrates the enhanced sensitivity of this new diagnostic over standard techniques. We present experimental data from turbulence behind a reverse shock in a plasma and demonstrate that this technique can measure angular deflections between 0.05 and 34 mrad, corresponding to a dynamic range of over 500.

An overexpanded jet in a truncated ideally contoured nozzle is found to feature a tonal behavior. The flow field is investigated to understand its origin and show how it modifies side-load properties. The temporal and spatial organization of wall pressure and jet velocity field are first experimentally characterized based on synchronized acquisition of both wall-pressure along rings of pressure probes located within the nozzle and high-rate time-resolved PIV velocity fields measured in a plane section crossing the jet downstream of the nozzle exit. The external jet aerodynamics and internal wall pressure field are first shown to be clearly linked, but only at this frequency peak for which a significant coherence emerges between first azimuthal mode of fluctuating wall pressure and first azimuthal mode of fluctuating external velocity field. A Delayed Detached Eddy Simulation is carried out and validated against experimental results in order to reproduce this tonal flow dynamics. The analysis of simulation data shows that the tonal flow behaviour of first azimuthal mode is indeed more largely felt within the whole flow structure where both upstream and downstream propagating waves are shown to co-exist, even far downstream of the nozzle exit. The analysis shows that both waves possess support in the jet core and have a non negligible pressure signature in the separated region. The Spectral Proper Orthogonal Decomposition of fluctuating pressure field at this tonal frequency reveals that the nature and intensity of lateral pressure forces is directed by the resonance related to the upstream- and downstream-propagating coherent structures, which imposes the shock-waves network to respond and modulate the pressure levels on the nozzle internal surface.

Multimode optical fibers has emerged as the platform that will bridge the gap between nonlinear optics in bulk media and in single-mode fibers. However, the understanding of the transition between these two research fields still remains incomplete despite numerous investigations of intermodal nonlinear phenomena and spatiotemporal coupling. Some of the striking phenomena observed in bulk media with ultrashort and ultra-intense pulses (i.e., conical emission, harmonic generation and light bullets) require a deeper insight to be possibly unveiled in multimode fibers. Here we generalize the concept of conical waves described in bulk media towards structured media, such as multimode optical fibers, in which only a discrete and finite number of modes can propagate. The modal distribution of optical fibers provides a quantization of conical emission (e.g., quantized X-waves) through phase-matched resonant radiations (i.e., dispersive waves) seeded by optical shocks or ultrashort wave structures during spatiotemporal compression stages. Such quantized dispersion- and diffraction-free waves are generated when a rather intense short pulse propagates nonlinearly in a multimode waveguide, whatever the dispersion regime and waveguide geometry. Future nonlinear experiments in commercially-available multimode fibers could reveal different forms of conical emission and an easy control of supercontinuum light bullets.

Context. Evaporative (sublimation) cooling of icy interstellar grains occurs when the grains have been suddenly heated by a cosmic-ray (CR) particle or other process. It results in thermal desorption of icy species, affecting the chemical composition of interstellar clouds. Aims. We investigate details on sublimation cooling, obtaining necessary knowledge before this process is considered in astrochemical models. Methods. We employed a numerical code that describes the sublimation of molecules from an icy grain, layer by layer, also considering a limited diffusion of bulk-ice molecules toward the surface before they sublimate. We studied a grain, suddenly heated to peak temperature T, which cools via sublimation and radiation. Results. A number of questions were answered. The choice of grain heat capacity C has a limited effect on the number of sublimated molecules N, if the grain temperature T > 40K. For grains with different sizes, CR-induced desorption is most efficient for rather small grains with a core radius of a ~ 0.02 micron. CR-induced sublimation of CO2 ice can occur only from small grains if their peak temperature is T > 80K and there is a lack of other volatiles. The presence of H2 molecules on grain surface hastens their cooling and thus significantly reduces N for other sublimated molecules for T < 30K. Finally, if there is no diffusion and subsequent sublimation of bulk-ice molecules (i.e., sublimation occurs only from the surface layer), sublimation yields do not exceed 1-2 monolayers and, if T > 50K, N does not increase with increasing T. Conclusions. Important details regarding the sublimation cooling of icy interstellar grains were clarified, which will enable a proper consideration of this process in astrochemical modeling.

Alloying metals with other elements is often done to improve the material strength or hardness. A key microscopic mechanism is precipitation hardening, where precipitates impede dislocation motion, but the role of such obstacles in determining the nature of collective dislocation dynamics remains to be understood. Here, three-dimensional discrete dislocation dynamics simulations of FCC single crystals are performed with fully coherent spherical precipitates from zero precipitate density upto $\rho_p = 10^{21}\,\text{m}^{-3}$ and at various dislocation-precipitate interaction strengths. When the dislocation-precipitate interactions do not play a major role the yielding is qualitatively as for pure crystals, i.e., dominated by "dislocation jamming", resulting in glassy dislocation dynamics exhibiting critical features at any stress value. We demonstrate that increasing the precipitate density and/or the dislocation-precipitate interaction strength creates a true yield or dislocation assembly depinning transition, with a critical yield stress. This is clearly visible in the statistics of dislocation avalanches observed when quasistatically ramping up the external stress, and is also manifested in the response of the system to constant applied stresses. The scaling of the yielding with precipitates is discussed in terms of the Bacon-Kocks-Scattergood relation.

We propose geometric tools for studying the behavior of a billiard trajectory in a homogeneous force field. Two examples are considered: a vertical plane with an open top and with a parabolic or right angle boundary at the bottom. In either case, we derive equations of the envelopes of a trajectory, which agree with the equations obtained earlier with the use of other calculation methods. In addition, some new geometric properties of trajectories will be presented. We show that in the case of a parabolic boundary the sequence of trajectory collision points can be easily built by multiple reflection of a single ellipse.

Density matrix perturbation theory (DMPT) is known as a promising alternative to the Rayleigh-Schr\"odinger perturbation theory, in which the sum-over-state (SOS) is replaced by algorithms with perturbed density matrices as the input variables. In this article, we formulate and discuss three genre of DMPT, with two of them based only on density matrices: the approach of Kussmann and Ochsenfeld [J. Chem. Phys.127, 054103 (2007)] is reformulated via the Sylvester equation, and the recursive DMPT of A.M.N. Niklasson and M. Challacombe [Phys. Rev. Lett. 92, 193001 (2004)] is extended to the hole-particle canonical purification (HPCP) from [L.A. Truflandier, R.M. Dianzinga and D.R. Bowler, 144, 091102 (2016)]. Comparison of the computational performances shows that the aformentioned methods outperform the standard SOS. The HPCP-DMPT demonstrate stable convergence profiles but at a higher computational cost when compared to the original recursive polynomial method

We found that small perturbations of the optical vortex core in the Laguerre-Gaussian (LG) beams generate a fine structure of the Hermite-Gauss (HG) mode spectrum. Such perturbations can be easily simulated by weak variations of amplitudes and phases of the HG modes in the expansion of the LG beam field. We also theoretically substantiated and experimentally implemented a method for measuring the topological charge of LG beams with an arbitrary number of ring dislocations. Theoretical discussion and experimental studies were accompanied by simple examples of estimating the orbital angular momentum and the topological charge of perturbed LG beams.

Redlining is the discriminatory practice whereby institutions avoided investment in certain neighborhoods due to their demographics. Here we explore the lasting impacts of redlining on the spread of COVID-19 in New York City (NYC). Using data available through the Home Mortgage Disclosure Act, we construct a redlining index for each NYC census tract via a multi-level logistical model. We compare this redlining index with the COVID-19 statistics for each NYC Zip Code Tabulation Area. Accurate mappings of the pandemic would aid the identification of the most vulnerable areas and permit the most effective allocation of medical resources, while reducing ethnic health disparities.

The phenomenon of Many-Body Stark Localization of bosons in tilted optical lattice is studied. Despite the fact that no disorder is necessary for Stark localization to occur, it is very similar to well known many body localization (MBL) in sufficiently strong disorder. Not only the mean gap ratio reaches poissonian value as characteristic for localized situations but also the eigenstates reveal multifractal character as in standard MBL. Stark localization enables a coexistence of spacially separated thermal and localized phases in the harmonic trap similarly to fermions. Stark localization may also lead to spectacular trapping of particles in a reversed harmonic field which naively might be considered as an unstable configuration.

Surface Plasmon Polaritons (SPP) are exploited due to their intriguing properties for photonic circuits fabrication and miniaturization, for surface enhanced spectroscopies and imaging beyond the diffraction limit. However, the excitation of these plasmonic modes by direct illumination is forbidden by energy/momentum conservation rules. One strategy to overcome this limitation relies on diffraction gratings to match the wavevector of the incoming photons with that of propagating SPP excitations. The main limit of the approaches so far reported in literature is that they rely on highly ordered diffraction gratings fabricated by means of demanding nano-lithographic processes. In this work we demonstrate that an innovative, fully self-organized method based on wrinkling-assisted Ion Beam Sputtering can be exploited to fabricate large area (cm^2 scale) nano-rippled soda-lime templates which conformally support ultrathin Au films deposited by physical deposition. The self-organized patterns act as quasi-1D gratings characterized by a remarkably high spatial order which matches properly the transverse photon coherence length. The gratings can thus enable the excitation of hybrid SPP modes confined at the Au/dielectric interfaces, with a resonant wavelength which can be tuned either by modifying the grating period, photon incidence angle or, potentially, the choice of the thin film conductive material. Surface Enhanced Raman Scattering experiments show promising gains in the range of 10^3 which are competitive, even before a systematic optimization of the sample fabrication parameters, with state-of-the art lithographic systems, demonstrating the potential of such templates for a broad range of optoelectronic applications aiming at plasmon-enhanced photon harvesting for molecular or bio-sensing.

Recent advances in the asymptotic analysis of energy levels of potentials produce relative errors in eigenvalue sums of order $10^{-34}$, but few non-trivial potentials have been solved numerically to such accuracy. We solve the general quartic potential (arbitrary linear combination of $x^2$ and $x^4$ ) beyond this level of accuracy using a basis of several hundred oscillator states. We list the lowest 20 eigenvalues for 9 such potentials. We confirm the known asymptotic expansion for the levels of the pure quartic oscillator, and extract the next 2 terms in the asymptotic expansion. We give analytic formulas for expansion in up to 3 even basis states. We confirm the virial theorem for the various energy components to similar accuracy. The sextic oscillator levels are also given. These benchmark results should be useful for extreme tests of approximations in several areas of chemical physics and beyond.

The Cassie-Baxter state droplet has many local energy minima on the textured surface, while the amount of the energy barrier between them can be affected by the gravity. When the droplet cannot find any local energy minimum point on the surface, the droplet starts to slide. Based on the Laplace pressure equation, the shape of a two-dimensional Cassie-Baxter droplet on a textured surface is predicted. Then the stability of the droplet is examined by considering the interference between the liquid and the surface microstructure as well as analyzing the free energy change upon the de-pinning. Afterward, the theoretical analysis is validated against the line-tension based front tracking method simulation (LTM), that seamlessly captures the attachment and detachment between the liquid and the substrate. We answer to the open debates on the sliding research field: (i) Whether the sliding initiates with the front end slip or the rear end slip, and (ii) whether the advancing and receding contact angles measured on the horizontal surface are comparable with the front and rear contact angle of the droplet at the onset of sliding. Additionally, a new droplet translation mechanism promoted by cycle of condensation and evaporation is suggested.

The following notes are intended to provide a brief primer in plasma physics, introducing common definitions, basic properties and processes typically found in plasmas. These concepts are inherent in contemporary plasma-based accelerator schemes, and thus build foundation for the more advanced lectures which follow in this volume. No prior knowledge of plasma physics is required, but the reader is assumed to be familiar with basic electrodynamics and fluid mechanics.

In this paper, we show that bending of spaghetti beams and columns exposed to hot steam reveals the time evolution of young modulus, the diffusion coefficient of water molecules penetrating the spaghetti, the partial Fickian behavior of water diffusion, and a logistic-like evolution of column bending angle. The bending geometries were timely recorded and the Young moduli were obtained by processing the images. We applied two equations proposed by us previously, one equation was applied for beam bending and the other for column bending, to estimate the Young moduli. The experiment was conducted by exposing the freely-hung cantilever spaghetti beams and columns using hot steam from boiling water so that the images were recorded in realtime while the beam or column bent undisturbedly. Surprisingly, the estimated diffusion coefficient of water molecules matched well the experimental data reported by others. This method may become an alternative for estimating the diffusion coefficient of vapor molecules penetrating the materials.

Over the past decade, a number of algorithms for full-field elastic strain estimation from neutron and X-ray measurements have been published. Many of the recently published algorithms rely on modelling the unknown strain field as a Gaussian Process (GP) - a probabilistic machine-learning technique. Thus far, GP-based algorithms have assumed a high degree of smoothness and continuity in the unknown strain field. In this paper, we propose three modifications to the GP approach to improve performance, primarily when this is not the case (e.g. for high-gradient or discontinuous fields); hyperparameter optimisation using k-fold cross-validation, a radial basis function approximation scheme, and gradient-based placement of these functions.

Medical instrument detection is essential for computer-assisted interventions since it would facilitate the surgeons to find the instrument efficiently with a better interpretation, which leads to a better outcome. This article reviews medical instrument detection methods in the ultrasound-guided intervention. First, we present a comprehensive review of instrument detection methodologies, which include traditional non-data-driven methods and data-driven methods. The non-data-driven methods were extensively studied prior to the era of machine learning, i.e. data-driven approaches. We discuss the main clinical applications of medical instrument detection in ultrasound, including anesthesia, biopsy, prostate brachytherapy, and cardiac catheterization, which were validated on clinical datasets. Finally, we selected several principal publications to summarize the key issues and potential research directions for the computer-assisted intervention community.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), is a threat to the global healthcare system and economic security. As of July 2020, no specific drugs or vaccines are yet available for COVID-19, fast and accurate diagnosis for SARS-CoV-2 is essential in slowing down the spread of COVID-19 and for efficient implementation of control and containment strategies. Magnetic immunoassay is a novel and emerging topic representing the frontiers of current biosensing and magnetics areas. The past decade has seen rapid growth in applying magnetic tools for biological and biomedical applications. Recent advances in magnetic materials and nanotechnologies have transformed current diagnostic methods to nanoscale and pushed the detection limit to early stage disease diagnosis. Herein, this review covers the literatures of magnetic immunoassay platforms for virus and pathogen detections, before COVID-19. We reviewed the popular magnetic immunoassay platforms including magnetoresistance (MR) sensors, magnetic particle spectroscopy (MPS), and nuclear magnetic resonance (NMR). Magnetic Point-of-Care (POC) diagnostic kits are also reviewed aiming at developing plug-and-play diagnostics to manage the SARS-CoV-2 outbreak as well as preventing future epidemics. In addition, other platforms that use magnetic materials as auxiliary tools for enhanced pathogen and virus detections are also covered. The goal of this review is to inform the researchers of diagnostic and surveillance platforms for SARS-CoV-2 and their performances.

The COVID-19 pandemic poses challenges for continuing economic activity while reducing health risk to individuals and preventing uncontrolled outbreaks. These challenges can be mitigated by extensive testing. We study testing policies that optimize a fixed budget of tests within a single institution (e.g., business, school, nursing home, etc.) by varying the number of batches that the tests are split into. We prove that, in an exponential spread model and for reasonable parameter values, the expected size of an outbreak at initial detection is smaller when random subgroups of the population are tested frequently, as opposed to periodic testing of the entire population. We also simulate the effect of different policies in a network SEIR model taking into account factors such as variable connectivity between individuals, incubation period, and inaccurate testing results. We show that under a broad set of early-outbreak scenarios, given a certain budget of tests, increasing testing frequency of random samples of the population will reduce the societal risk, defined as the number of infection opportunities until first detection. For example, testing a quarter of the institution members every week is generally better than testing the entire institution every month. In fact, in many settings, sufficiently frequent testing (combined with mitigation once an outbreak is detected) can decrease the risk even compared to the baseline when the institution is closed and testing is not conducted. The bottom-line is a simple policy prescription for institutions: distribute the total tests over several batches instead of using them all at once.

Entropy is being used in physics, mathematics, informatics and in related areas to describe equilibration, dissipation, maximal probability states and optimal compression of information. The Gini index on the other hand is an established measure for social and economical inequalities in a society. In this paper we explore the mathematical similarities and connections in these two quantities and introduce a new measure that is capable to connect these two at an interesting analogy level. This supports the idea that a generalization of the Gibbs--Boltzmann--Shannon entropy, based on a transformation of the Lorenz curve, can properly serve in quantifying different aspects of complexity in socio- and econo-physics.

In this essay, I outline a personal vision of how I think Numerical Weather Prediction (NWP) should evolve in the years leading up to 2030 and hence what it should look like in 2030. By NWP I mean initial-value predictions from timescales of hours to seasons ahead. Here I want to focus on how NWP can better help save lives from increasingly extreme weather in those parts of the world where society is most vulnerable. Whilst we can rightly be proud of many parts of our NWP heritage, its evolution has been influenced by national or institutional politics as well as by underpinning scientific principles. Sometimes these conflict with each other. It is important to be able to separate these issues when discussing how best meteorological science can serve society in 2030; otherwise any disruptive change - no matter how compelling the scientific case for it - becomes impossibly difficult.

A novel plasma equilibrium in the high-$\beta$, Hall regime that produces centrally-peaked, high Mach number Couette flow is described. Flow is driven using a weak, uniform magnetic field and large, cross field currents. Large magnetic field amplification (factor 20) due to the Hall effect is observed when electrons are flowing radially inward, and near perfect field expulsion is observed when the flow is reversed. A dynamic equilibrium is reached between the amplified (removed) field and extended density gradients.

We present the design of a Velocity Map Imaging apparatus tailored to the demands of high-resolution crossed molecular beam experiments employing Stark or Zeeman decelerators. The key requirements for these experiments consist of the combination of a high relative velocity resolution for large ionization volumes and a broad range of relatively low lab-frame velocities. The SIMION software package was employed to systematically optimize the electrode geometries and electrical configuration. The final design consists of a stack of 16 tubular electrodes, electrically connected with resistors, which is divided into three electric field regions. The resulting apparatus allows for an inherent velocity blurring of less than 1.1 m/s for NO$^+$ ions originating from a 3x3x3 mm ionization volume, which is negligible in a typical crossed beam experiment. The design was recently employed in several state of the art crossed-beam experiments, allowing the observation of fine details in the velocity distributions of the scattered molecules.

We present a theory for the interaction between motile particles in an elastic medium on a substrate, relying on two arguments: a moving particle creates a strikingly fore-aft asymmetric distortion in the elastic medium; this strain field reorients other particles. We show that this leads to sensing, attraction and pursuit, with a non-reciprocal character, between a pair of motile particles. We confirm the predicted distortion fields and non-mutual trail-following in our experiments and simulations on polar granular rods made motile by vibration, moving through a dense monolayer of beads in its crystalline phase. Our theory should be of relevance to the interaction of motile cells in the extracellular matrix or in a supported layer of gel or tissue.

This paper focuses on a survey of experimental data related to radiation into CO$_2$ plasma flows, which are encountered during Mars and Venus entries. The review emphasizes on VUV and IR radiation, since recent experimental efforts has been devoted to these wavelength ranges. The main objective of the study is to identify the most attractive datasets for future cross-check comparisons with the results obtained during future test campaigns with ESTHER shock-tube. The survey accounts for the results obtained in shock-tubes, expansion tube and plasma arc-jets for Mars and Venus test campaigns. The experimental results obtained for propulsion related studies have also been considered.

Nonlinear topological photonics, which explores topics common to the fields of topological phases and nonlinear optics, is expected to open up a new paradigm in topological photonics. Here, we demonstrate second-harmonic generation via nonlinear interaction of double topological valley-Hall kink modes in all-dielectric photonic crystals. We first show that two topological frequency bandgaps can be created around a pair of frequencies, $\omega_0$ and $2\omega_0$, by gapping out the corresponding Dirac points in two-dimensional honeycomb photonic crystals. Valley-Hall kink modes along a kink-type domain wall interface between two photonic crystals placed together in a mirror-symmetric manner are generated within the two frequency bandgaps. Importantly, through full-wave simulations and mode dispersion analysis, we demonstrate that tunable, bi-directional phase-matched second-harmonic generation via nonlinear interaction of the valley-Hall kink modes within the two frequency bandgaps could be achieved. Our work opens up new avenues towards topologically protected nonlinear frequency mixing in optics using all-dielectric materials.

In this work we extend low frequency impulsive stimulated Raman microspectroscopy to the pre-electronic resonance regime. We use a broadband two color collinear pump probe scheme which can be readily extended to imaging. We discuss the difficulties unique to this type of measurements in the form of competing resonant two-photon processes and the means to overcome them. We successfully reduce the noise which arises due to those competing processes by eliminating the detected spectral components which do not contribute to the vibrational signature of the sample though introduce most of the noise. Finally, we demonstrate low-frequency spectroscopy of crystalline samples under near-resonant pumping showing both enhancement and spectral modification due to coupling with the electronic degree of freedom.

The nonlinear dynamics of a recently derived generalized Lorenz model (Macek and Strumik, Phys. Rev. E 82, 027301, 2010) of magnetoconvection is studied. A bifurcation diagram is constructed as a function of the Rayleigh number where attractors and nonattracting chaotic sets coexist inside a periodic window. The nonattracting chaotic sets, also called chaotic saddles, are responsible for fractal basin boundaries with a fractal dimension near the dimension of the phase space, which causes the presence of very long chaotic transients. It is shown that the chaotic saddles can be used to infer properties of chaotic attractors outside the periodic window, such as their maximum Lyapunov exponent.

Stress analysis of heterogeneous media, like composite materials, using finite element method (FEM) has become commonplace in design and analysis. However, calculating stresses and determining stress distributions in heterogeneous media using FEM can be computationally expensive in situations like optimization and multi-scaling, where several design iterations are required to be tested iteratively until convergence. In this paper, we utilize deep learning and develop a set of Difference-based Neural Network (DNN) frameworks based on engineering and statistics knowledge to determine stress distribution in heterogeneous media with special focus on discontinuous domains that manifest high stress concentrations. To evaluate the performance of DNN frameworks, we consider four different types of geometric models that are commonly used in the analysis of composite materials: plate with circular cutout, square packed fiber reinforced, hexagonal packed fiber reinforced and hollow particle reinforced models. The proposed DNN structure consists of a normalization module (DNN-N) for all geometries considered, while we additionally introduce a clean module with DNN-N, named DNN-NC, for geometries with discontinuities. Results show that the DNN structures (DNN-N and DNN-NC) significantly enhance the accuracy of stress prediction compared to existing structures for all four models considered, especially when localized high stress concentrations are present in the geometric models.

Avalanche photodiodes (APDs) are well-suited for single-photon detection on quantum communication satellites as they are a mature technology with high detection efficiency without requiring cryogenic cooling. They are, however, prone to significantly increased thermal noise caused by in-orbit radiation damage. Previous work demonstrated that a one-time application of thermal annealing reduces radiation-damage-induced APD thermal noise. Here we examine the effect of cyclical proton irradiation and thermal annealing, emulating the realistic operating profile of a satellite in low-Earth-orbit over a two-year life span. We show that repeated thermal annealing is effective in maintaining thermal noise of silicon APDs within a range suitable for quantum key distribution throughout the nominal mission life, and beyond. We examine two strategies---annealing at a fixed period of time, and annealing only when the thermal noise exceeds a pre-defined limit---and find that the latter exhibits lower thermal noise at end-of-life for most samples. We also observe that afterpulsing probability of the detector increases with cumulative proton irradiation. This knowledge helps guide design and tasking decisions for future space-borne quantum communication applications.

The flourishing of fake news is favored by recommendation algorithms of online social networks which, based on previous users activity, provide content adapted to their preferences and so create filter bubbles. We introduce an analytically tractable voter model with personalized information, in which an external field tends to align the agent opinion with the one she held more frequently in the past. Our model shows a surprisingly rich dynamics despite its simplicity. An analytical mean-field approach, confirmed by numerical simulations, allows us to build a phase diagram and to predict if and how consensus is reached. Remarkably, polarization can be avoided only for weak interaction with the personalized information and if the number of agents is below a threshold. We analytically compute this critical size, which depends on the interaction probability in a strongly non linear way.

Electroconvection and its coupling with a morphological instability are important in many applications, including electrodialysis, batteries and fuel cells. In this work, we study the effects of a two-dimensional channel flow on the electroconvective and morphological instabilities using two approaches. In the bulk analysis, we consider the instability of the electroneutral bulk region driven by a second kind electroosmosis slip velocity boundary condition and derive the asymptotic solutions for small and large wavenumbers. In the full analysis, we consider the entire region of the liquid electrolyte and use the ultraspherical spectral method to numerically solve the eigenvalue problems. Both studies show that the imposed flow significantly affects the electroconvective instability. The imposed flow generates a shielding effect by deforming the perturbed ion concentration field and hinders the ion transfer from low- to high- concentration regions which causes the instability. It fully suppresses the electroconvective instability at small wavenumbers and reduces the growth rate of the perturbations at large wavenumbers. The direct effect of the flow on the morphological instability is minor, while the suppression of the electroconvective instability may change the wavenumber of the most unstable mode of the coupled instabilities. For the electroconvective instability, the bulk analysis is qualitatively different from the full analysis at high wavenumbers. For the morphological instability, good agreement is found between the two studies at both small and large wavenumbers.

Metal-organic frameworks (MOFs) can provide exceptional porosity for molecular guest encapsulation useful for emergent applications in sensing, gas storage, drug delivery and optoelectronics. Central to the realisation of such applications however is the successful incorporation of the guest material within the host framework. Here we demonstrate, for the first time, the feasibility of scattering-type scanning near-field optical microscopy (s-SNOM) and nano-Fourier transform infrared (nanoFTIR) spectroscopy, in concert with density functional theory (DFT) calculations to reveal the vibrational characteristics of the Guest@MOF systems. Probing individual MOF crystals, we pinpoint the local molecular vibrations and thus, shed new light on the host-guest interactions at the nanoscale. Our strategy not only confirms the successful encapsulation of luminescent guest molecules in the porous host framework in single crystals, but further provides a new methodology for nanoscale-resolved physical and chemical identification of wide-ranging framework materials and designer porous systems for advanced applications.

In an ideal accelerator, the single-particle dynamics can be decoupled into transverse motion -- the betatron oscillations -- and longitudinal motion -- the synchrotron oscillations. Chromatic and dispersive effects introduce a coupling between these dynamics, the so-called synchro-betatron coupling. We present an analysis of the fully coupled dynamics over a single synchrotron oscillation that leads to a stroboscopic invariant with synchro-betatron coupling in a generic lattice. This invariant is correct to $\mathcal{O}(\nu_s)$, where $\nu_s$ is the synchrotron tune. We apply this analysis to a design for a rapid cycling synchrotron built using the integrable optics described by Danilov and Nagaitsev, showing that although there is fairly complex behavior over the course of a synchrotron oscillation, the predicted invariants are nevertheless periodic with the synchrotron motion.

Acoustic devices play an important role in classical information processing. The slower speed and lower losses of mechanical waves enable compact and efficient elements for delaying, filtering, and storing of electric signals at radio and microwave frequencies. Discovering ways of better controlling the propagation of phonons on a chip is an important step towards enabling larger scale phononic circuits and systems. We present a platform, inspired by decades of advances in integrated photonics, that utilizes the strong piezoelectric effect in a thin film of lithium niobate on sapphire to excite guided acoustic waves immune from leakage into the bulk due to the phononic analogue of index-guiding. We demonstrate an efficient transducer matched to 50 ohm and guiding within a 1-micron wide mechanical waveguide as key building blocks of this platform. Putting these components together, we realize acoustic delay lines, racetrack resonators, and meander line waveguides for sensing applications. To evaluate the promise of this platform for emerging quantum technologies, we characterize losses at low temperature and measure quality factors on the order of 50,000 at 4 kelvin. Finally, we demonstrate phononic four-wave mixing in these circuits and measure the nonlinear coefficients to provide estimates of the power needed for relevant parametric processes.

Hubble's law, which states a linear increase in velocities with distances, can physically be understood in terms of an acceleration cH. This work proposes a connection between this "universal" acceleration seen in the solar system and the anomalous acceleration acting on the Pioneer 10/11 spacecraft, in which the Hubble constant inferred from Pioneer 10/11 data is ~ 87 km/s/Mpc. Its physical implication is discussed in relation with Mach's principle.

A fluid flow is described by fictitious particles hopping on homogeneously distributed nodes with a given finite set of discrete velocities. We emphasize that the existence of a fictitious particle having a discrete velocity among the set in a node is given by a probability. We describe a compressible thermal flow of the level of accuracy of the Navier-Stokes equation by 25 or 33 discrete velocities for two-dimensional space and perform simulations for investigating internal structural evolution of a shock wave.

This paper is a revised version of the original paper of same title--published in Applied Mathematics Letters 89--containing some corrections and clarifications to the original text. We derive non-singular Green's functions for the unbounded Poisson equation in one, two and three dimensions, using a cut-off function in the Fourier domain to impose a smallest length scale when deriving the Green's function. The resulting non-singular Green's functions are relevant to applications which are restricted to a minimum resolved length scale (e.g. a mesh size h) and thus cannot handle the singular Green's function of the continuous Poisson equation. We furthermore derive the gradient vector of the non-singular Green's function, as this is useful in applications where the Poisson equation represents potential functions of a vector field.

We present a comparative modelling study of fluid-structure interactions in microchannels. Through a mathematical analysis based on plate theory and the lubrication approximation for low-Reynolds-number flow, we derive models for the flow rate-pressure drop relation for long shallow microchannels with both thin and thick deformable top walls. These relations are tested against full three-dimensional two-way-coupled fluid-structure interaction simulations. Three types of microchannels, representing different elasticity regimes and having been experimentally characterized previously, are chosen as benchmarks for our theory and simulations. Good agreement is found in most cases for the predicted, simulated and measured flow rate-pressure drop relationships. The numerical simulations performed allow us to also carefully examine the deformation profile of the top wall of the microchannel in any cross section, showing good agreement with the theory. Specifically, the prediction that span-wise displacement in a long shallow microchannel decouples from the flow-wise deformation is confirmed, and the predicted scaling of the maximum displacement with the hydrodynamic pressure and the various material and geometric parameters is validated.

Understanding the localization properties of eigenvectors of complex networks is important to get insight into various structural and dynamical properties of the corresponding systems. Here, we analytically develop a scheme to construct a highly localized network for a given set of networks parameters that is the number of nodes and the number of interactions. We find that the localization behavior of the principal eigenvector (PEV) of such a network is sensitive against a single edge rewiring. We find evidences for eigenvalue crossing phenomena as a consequence of the single edge rewiring, in turn providing an origin to the sensitive behavior of the PEV localization. These insights were then used to analytically construct the highly localized network for a given set of networks parameters. The analysis provides fundamental insight into relationships between the structural and the spectral properties of networks for PEV localized networks. Further, we substantiate the existence of the eigenvalue crossing phenomenon by considering a linear-dynamical process, namely the ribonucleic acid (RNA) neutral network population dynamical model. The analysis presented here on model networks aids in understanding the steady-state behavior of a broad range of linear-dynamical processes, from epidemic spreading to biochemical dynamics associated with the adjacency matrices.

High index dielectric nanoantennas excited at Mie-type resonances have exhibited enormous enhancement of optical nonlinearity. Such nanostructures have been actively studied by researchers in the last years. The present work provides the first numerical analysis study of the optical Kerr effect of nanocomposites consisting of high refractive index (GaP) spheres at the wavelength of 532~nm. This is done by means of three-dimensional finite-difference time-domain (FDTD) simulations. The effective nonlinear refractive index of $0.8$~$\mu$m thick nanocomposites and metasurfaces is evaluated. It is shown that the optical Kerr nonlinearity of the nanocomposites rises by orders in proximity to Mie resonances and may exceed the second-order refractive index of the bulk material. It is revealed that the sign of the effective optical Kerr coefficient is inverted near the Mie resonances. This effect may be of interest in developing nonlinear optical metadevices.

The classical stability for a dynamical system consisting of two coupled oscillators is discussed, restricted to the case of two ions confined in a 3D Radio-Frequency (RF) trap. The electric potential is considered to be a general solution of the Laplace equation, built using spherical harmonic functions with time dependent coefficients. A well known model from the literature is used to describe the system, depending on two control parameters: the axial angular moment and the ratio between the radial and axial trap frequencies. We extend this model by using the Hessian matrix of the potential to characterize the critical points of the system, implicitly the system stability. We show the degenerate critical points compose the bifurcation set whose image in the control parameter space establishes the catastrophe set of equations which defines the separatrix, and we obtain the bifurcation diagram associated with the system. Then, we extend the Hessian matrix based model previously introduced to investigate semi-classical stability for many-body systems consisting of $N$ identical ions and supply a method to identify the critical points for the system. We propose an alternative approach to provide insight into the associated many-body dynamics in combined (Paul and Penning) traps. The approach we suggest can be very useful in generalizing the parameters of different types of traps in a unified manner.

The DeeMe experiment to search for muon-to-electron conversions with a sensitivity 10--100 times better than those achieved by previous experiments is in preparation at the Japan Proton Accelerator Research Complex. The magnetic spectrometer used by the DeeMe experiment consists of an electromagnet and four multiwire proportional chambers (MWPCs). The newly developed MWPCs are operated with a high voltage (HV) switching technique and have good burst-hit tolerance. In this article, the final designs of the MWPCs, amplifiers for readout, and HV switching modules are described. Additionally, some results of MWPC performance evaluation are presented.

The most common species in liquid water, next to neutral H$_2$O molecules, are the H$_3$O$^+$ and OH$^-$ ions. In a dynamic picture, their exact concentrations depend on the time scale at which these are probed. Here, using a spectral-weight analysis, we experimentally resolve the fingerprints of the elusive fluctuations-born short-living H$_3$O$^+$, DH$_2$O$^+$, HD$_2$O$^+$, and D$_3$O$^+$ ions in the IR spectra of light (H$_2$O), heavy (D$_2$O), and semi-heavy (HDO) water. We find that short-living ions, with concentrations reaching $\sim 2\%$ of the content of water molecules, coexist with long-living pH-active ions on the picosecond timescale, thus making liquid water an effective ionic liquid in femtochemistry.

A new resistance bridge has been built at the Laboratoire national de m\'etrologie et d'essais (LNE) to improve the ohm realization in the $Syst\`eme International$ (SI) of units from the quantum Hall effect. We describe the instrument, the performance of which relies on two synchronized and noise-filtered current sources, an accurate and stable current divider and a cryogenic current comparator (CCC) having a low noise of $\mathrm{80~pA.t/Hz^{1/2}}$. The uncertainty budget for the measurement of the 100 $\Omega/(R_\mathrm{K}/2)$ ratio, where $R_\mathrm{K}$ is the von Klitzing constant, amounts to a few parts in $10^{10}$ only.

A relativistic version of the effective charge model for computation of observable characteristics of multi-electron atoms and ions is developed. A complete and orthogonal Dirac hydrogen basis set, depending on one parameter -- effective nuclear charge $Z^{*}$ -- identical for all single-electron wave functions of a given atom or ion, is employed for the construction of the secondary-quantized representation. The effective charge is uniquely determined by the charge of the nucleus and a set of electron occupation numbers for a given state. We thoroughly study the accuracy of the leading-order approximation for the total binding energy and demonstrate that it is independent of the number of electrons of a multi-electron atom. In addition, it is shown that the fully analytical leading-order approximation is especially suited for the description of highly charged ions since our wave functions are almost coincident with the Dirac-Hartree-Fock ones for the complete spectrum. Finally, we evaluate various atomic characteristics, such as scattering factors and photoionization cross-sections, and thus envisage that the effective charge model can replace other models of comparable complexity, such as the Thomas-Fermi-Dirac model for all applications where it is still utilized.

Mixing iodide and bromide in halide perovskite semiconductors is an effective strategy to tune their bandgap, therefore mixed-halide perovskites hold great promise for color-tunable LEDs and tandem solar cells. However, the bandgap of mixed-halide perovskites is unstable under (sun-)light, since the halides segregate into domains of different bandgaps. Using pressure-dependent ultrafast transient absorption spectroscopy, we show that high external pressure increases the range of thermodynamically stable halide mixing ratios. Chemical pressure, by inserting a smaller cation, has the same effect, which means that any iodide-to-bromide ratio can be thermodynamically stabilized by tuning the crystal volume and compressibility. We interpret this stabilization by an alteration of the Helmholtz free energy via the largely overlooked PdeltaV term.

Weyl points are robust point degeneracies in the band structure of a periodic material, which act as monopoles of Berry curvature. They have been at the forefront of research in three-dimensional topological materials (whether photonic, electronic or otherwise) as they are associated with novel behavior both in the bulk and on the surface. Here, we present the experimental observation of a charge-2 photonic Weyl point in a low-index-contrast photonic crystal fabricated by two-photon polymerization. The reflection spectrum obtained via Fourier Transform Infrared (FTIR) spectroscopy closely matches simulations and shows two bands with quadratic dispersion around a point degeneracy. This work provides a launching point towards all-dielectric, low-contrast three-dimensional photonic topological devices.

Contemporary Niche Theory is a useful framework for understanding how organisms interact with each other and with their shared environment. Its graphical representation, popularized by Tilman's Resource Ratio Hypothesis, facilitates the analysis of the equilibrium structure of complex dynamical models including species coexistence. This theory has been applied primarily to resource competition since its early beginnings. Here, we integrate mutualism into niche theory by expanding Tilman's graphical representation to the analysis of consumer-resource dynamics of plant-pollinator networks. We graphically explain the qualitative phenomena previously found by numerical simulations, including the effects on community dynamics of nestedness, adaptive foraging, and pollinator invasions. Our graphical approach promotes the unification of niche and network theories, and deepens the synthesis of different types of interactions within a consumer-resource framework.

Calculating the yield limit $Y_c$ (the critical ratio of the yield stress to the driving stress), of a viscoplastic fluid flow is a challenging problem, often needing iteration in the rheological parameters to approach this limit, as well as accurate computations that account properly for the yield stress and potentially adaptive meshing. For particle settling flows, in recent years calculating $Y_c$ has been accomplished analytically for many antiplane shear flow configurations and also computationally for many geometries, under either two dimensional (2D) or axisymmetric flow restrictions. Here we approach the problem of 3D particle settling and how to compute the yield limit directly, i.e. without iteratively changing the rheology to approach the yield limit. The presented approach develops tools from optimization theory, taking advantage of the fact that $Y_c$ is defined via a minimization problem. We recast this minimization in terms of primal and dual variational problems, develop the necessary theory and finally implement a basic but workable algorithm. We benchmark results against accurate axisymmetric flow computations for cylinders and ellipsoids, computed using adaptive meshing. We also make comparisons of accuracy in calculating $Y_c$ on comparable fixed meshes. This demonstrates the feasibility and benefits of directly computing $Y_c$ in multiple dimensions. Lastly, we present some sample computations for complex 3D particle shapes.

Traffic evacuation plays a critical role in saving lives in devastating disasters such as hurricanes, wildfires, floods, earthquakes, etc. An ability to evaluate evacuation plans in advance for these rare events, including identifying traffic flow bottlenecks, improving traffic management policies, and understanding the robustness of the traffic management policy are critical for emergency management. Given the rareness of such events and the corresponding lack of real data, traffic simulation provides a flexible and versatile approach for such scenarios, and furthermore allows dynamic interaction with the simulated evacuation. In this paper, we build a traffic simulation pipeline to explore the above problems, covering many aspects of evacuation, including map creation, demand generation, vehicle behavior, bottleneck identification, traffic management policy improvement, and results analysis. We apply the pipeline to two case studies in California. The first is Paradise, which was destroyed by a large wildfire in 2018 and experienced catastrophic traffic jams during the evacuation. The second is Mill Valley, which has high risk of wildfire and potential traffic issues since the city is situated in a narrow valley.

Neutrinos are particles that interact rarely, so identifying them requires large detectors which produce lots of data. Processing this data with the computing power available is becoming more difficult as the detectors increase in size to reach their physics goals. In liquid argon time projection chambers (TPCs) the charged particles from neutrino interactions produce ionization electrons which drift in an electric field towards a series of collection wires, and the signal on the wires is used to reconstruct the interaction. The MicroBooNE detector currently collecting data at Fermilab has 8000 wires, and planned future experiments like DUNE will have 100 times more, which means that the time required to reconstruct an event will scale accordingly. Modernization of liquid argon TPC reconstruction code, including vectorization, parallelization and code portability to GPUs, will help to mitigate these challenges. The liquid argon TPC hit finding algorithm within the \texttt{LArSoft}\xspace framework used across multiple experiments has been vectorized and parallelized. This increases the speed of the algorithm on the order of ten times within a standalone version on Intel architectures. This new version has been incorporated back into \texttt{LArSoft}\xspace so that it can be generally used. These methods will also be applied to other low-level reconstruction algorithms of the wire signals such as the deconvolution. The applications and performance of this modernized liquid argon TPC wire reconstruction will be presented.

One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material effects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filter-based methods for highly parallel, many-core SIMD and SIMT architectures that are now prevalent in high-performance hardware. Previously we observed significant parallel speedups, with physics performance comparable to CMS standard tracking, on Intel Xeon, Intel Xeon Phi, and (to a limited extent) NVIDIA GPUs. While early tests were based on artificial events occurring inside an idealized barrel detector, we showed subsequently that our mkFit software builds tracks successfully from complex simulated events (including detector pileup) occurring inside a geometrically accurate representation of the CMS-2017 tracker. Here, we report on advances in both the computational and physics performance of mkFit, as well as progress toward integration with CMS production software. Recently we have improved the overall efficiency of the algorithm by preserving short track candidates at a relatively early stage rather than attempting to extend them over many layers. Moreover, mkFit formerly produced an excess of duplicate tracks; these are now explicitly removed in an additional processing step. We demonstrate that with these enhancements, mkFit becomes a suitable choice for the first iteration of CMS tracking, and eventually for later iterations as well. We plan to test this capability in the CMS High Level Trigger during Run 3 of the LHC, with an ultimate goal of using it in both the CMS HLT and offline reconstruction for the HL-LHC CMS tracker.

We report the observation of microwave coherent control of rotational states of ultracold $^{85}$Rb$^{133}$Cs molecules formed in their vibronic ground state by short-range photoassociation. Molecules are formed in the single rotational state $X(v=0,J=1)$ by exciting pairs of atoms to the short-range state $(2)^{3}\Pi_{0^{-}} (v=11, J=0)$, followed by spontaneous decay. We use depletion spectroscopy to record the dynamic evolution of the population distribution and observe clear Rabi oscillations while irradiating on a microwave transition between coupled neighbouring rotational levels. A density-matrix formalism that accounts for longitudinal and transverse decay times reproduces both the dynamic evolution during the coherent process and the equilibrium population. The coherent control reported here is valuable both for investigating coherent quantum effects and for applications of cold polar molecules produced by continuous short-range photoassociation.

Here we present datasets provided by a SCINDA GNSS receiver installed in the Lisbon airport area from November of 2014 to July of 2019. The installed equipment is a NovAtel EURO4 with a JAVAD Choke-Ring antenna. The data are in an archived format and include the general messages on quality of records (*.msg), RANGE files (*.rng), raw observables as the signal-to-noise (S/N) ratios, pseudoranges and phases (*.obs), receiver position information (*.psn), ionosphere scintillations monitor (ISMRB; *.ism) and ionospheric parameters: total electron content (TEC), rate of change of TEC index (ROTI), and the scintillation index S4 (*.scn). The presented data cover the full 2015 year. The raw data are of 1-minute resolution and available for each of the receiver-satellite pairs. The processing and the analysis of the ionosphere scintillation datasets can be done using a specific "SCINDA-Iono" toolbox for the MATLAB developed by T. Barlyaeva (2019) and available online via MathWorks File Exchange system. The toolbox calculates 1-hour means for ionospheric parameters for each of the available receiver-satellite pairs and averaged over all available satellites during the analyzed hour. Here we present the processed data for the following months in 2015: March, June, October, and December. The months were selected as containing most significant geomagnetic events of 2015. The 1-hour means for other months can be obtained from the raw data using the aforementioned toolbox. The provided datasets are interesting for the GNSS and ionosphere based scientific communities.

Environmental changes greatly influence the evolution of populations. Here, we study the dynamics of a population of two strains, one growing slightly faster than the other, competing for resources in a time-varying binary environment modeled by a carrying capacity switching either randomly or periodically between states of abundance and scarcity. The population dynamics is characterized by demographic noise (birth and death events) coupled to a varying environment. We elucidate the similarities and differences of the evolution subject to a stochastically- and periodically-varying environment. Importantly, the population size distribution is generally found to be broader under intermediate and fast random switching than under periodic variations, which results in markedly different asymptotic behaviors between the fixation probability of random and periodic switching. We also determine the detailed conditions under which the fixation probability of the slow strain is maximal.

Magnetospheric Multiscale (MMS) encountered the primary low-latitude magnetopause reconnection site when the inter-spacecraft separation exceeded the upstream ion inertial length. Classical signatures of the ion diffusion region (IDR), including a sub-ion-Alfv\'enic de-magnetized ion exhaust, a super-ion-Alfv\'enic magnetized electron exhaust, and Hall electromagnetic fields, are identified. The opening angle between the magnetopause and magnetospheric separatrix is $30^\circ\pm5^\circ$. The exhaust preferentially expands sunward, displacing the magnetosheath. Intense pileup of reconnected magnetic flux occurs between the magnetosheath separatrix and the magnetopause in a narrow channel intermediate between the ion and electron scales. The strength of the pileup (normalized values of 0.3-0.5) is consistent with the large angle at which the magnetopause is inclined relative to the overall reconnection coordinates. MMS-4, which was two ion inertial lengths closer to the X-line than the other three spacecraft, observed intense electron-dominated currents and kinetic-to-electromagnetic-field energy conversion within the pileup. MMS-1, 2, and 3 did not observe the intense currents nor the particle-to-field energy conversion but did observe the pileup, indicating that the edge of the generation region was contained within the tetrahedron. Comparisons with particle-in-cell simulations reveal that the electron currents and large inclination angle of the magnetopause are interconnected features of the asymmetric Hall effect. Between the separatrix and the magnetopause, high-density inflowing magnetosheath electrons brake and turn into the outflow direction, imparting energy to the normal magnetic field and generating the pileup. The findings indicate that electron dynamics are likely an important influence on the magnetic field structure within the ion diffusion region.

Techniques to manipulate the individual constituents of an ultracold mixture are key to investigating impurity physics. In this work, we confine a mixture of the hyperfine ground states of Rb-87 in a double-well potential. The potential is produced by dressing the atoms with multiple radiofrequencies. The amplitude and phase of each frequency component of the dressing field are individually controlled to independently manipulate each species. Furthermore, we verify that our mixture of hyperfine states is collisionally stable, with no observable inelastic loss.

Temporal networks are widely used to represent a vast diversity of systems, including in particular social interactions, and the spreading processes unfolding on top of them. The identification of structures playing important roles in such processes remains largely an open question, despite recent progresses in the case of static networks. Here, we consider as candidate structures the recently introduced concept of span-cores: the span-cores decompose a temporal network into subgraphs of controlled duration and increasing connectivity, generalizing the core-decomposition of static graphs. To assess the relevance of such structures, we explore the effectiveness of strategies aimed either at containing or maximizing the impact of a spread, based respectively on removing span-cores of high cohesiveness or duration to decrease the epidemic risk, or on seeding the process from such structures. The effectiveness of such strategies is assessed in a variety of empirical data sets and compared to baselines that use only static information on the centrality of nodes and static concepts of coreness, as well as to a baseline based on a temporal centrality measure. Our results show that the most stable and cohesive temporal cores play indeed an important role in epidemic processes on temporal networks, and that their nodes are likely to represent influential spreaders.

Opinion dynamics have attracted the interest of researchers from different fields. Local interactions among individuals create interesting dynamics for the system as a whole. Such dynamics are important from a variety of perspectives. Group decision making, successful marketing, and constructing networks (in which consensus can be reached or prevented) are a few examples of existing or potential applications. The invention of the Internet has made the opinion fusion faster, unilateral, and on a whole different scale. Spread of fake news, propaganda, and election interferences have made it clear there is an essential need to know more about these dynamics.

The emergence of new ideas in the field has accelerated over the last few years. In the first quarter of 2020, at least 50 research papers have emerged, either peer-reviewed and published or on pre-print outlets such as arXiv. In this paper, we summarize these ground-breaking ideas and their fascinating extensions and introduce newly surfaced concepts.

The annual modulation signal observed by the DAMA experiment is a long-standing question in the community of dark matter direct detection. This necessitates an independent verification of its existence using the same detection technique. The COSINE-100 experiment has been operating with 106~kg of low-background NaI(Tl) detectors providing interesting checks on the DAMA signal. However, due to higher backgrounds in the NaI(Tl) crystals used in COSINE-100 relative to those used for DAMA, it was difficult to reach final conclusions. Since the start of COSINE-100 data taking in 2016, we also have initiated a program to develop ultra-pure NaI(Tl) crystals for COSINE-200, the next phase of the experiment. The program includes efforts of raw powder purification, ultra-pure NaI(Tl) crystal growth, and detector assembly techniques. After extensive research and development of NaI(Tl) crystal growth, we have successfully grown a few small-size (0.61$-$0.78 kg) thallium-doped crystals with high radio-purity. A high light yield has been achieved by improvements of our detector assembly technique. Here we report the ultra-pure NaI(Tl) detector developments at the Institute for Basic Science, Korea. The technique developed here will be applied to the production of NaI(Tl) detectors for the COSINE-200 experiment.

Fe-gluconate, Fe(C_6H_11O_7_2xH_2O is a well-known material widely used for iron supplementation. On the other hand, it is used in food industry as a coloring agent, in cosmetic industry for skin and nail conditioning and metallurgy. Despite of wide range of applications its physical properties were not studied extensively. In this study, Fe-gluconate with three different amount of water viz. x=2 (fully hydrated, 0 < x < 2 (intermediate) and x=0 (dry) was investigated by means of X-ray diffraction (XRD) and M\"ossbauer spectroscopic (MS) methods. The former in the temperature range of 20-300 K, and the latter at 295 K. Based on the XRD measurements crystallographic structures were determined: monoclinic (space group I2) for the hydrated sample and triclinic (space group P1) for the dry sample. The partially hydrated sample was two-phased. Unit cells parameters for both structures show strong, very complex and non-monotonic temperature dependences. M\"ossbauer spectroscopic measurements gave evidence that iron in all samples exist in form of Fe(II) and Fe(III) ions. The amount of the latter equals to ca.30% in the hydrated sample and to ca.20% in the dry one.

Based on a collective description of electrolytes composed of charge-regulated macro-ions and simple salt ions, we analyze their equilibrium charge state in the bulk and their behavior in the vicinity of an external electrified surface. The mean-field formulation of mobile macro-ions in an electrolyte bathing solution is extended to include interactions between association/dissociation sites. We demonstrate that above a critical concentration of salt, and similar to the critical micelle concentration, a non-trivial distribution of charge states sets in. Such a charge state can eventually lead to a liquid-liquid phase separation based on charge regulation.

In this paper we consider the fractional SIS epidemic model ($\alpha$-SIS model) in the case of constant population size. We provide a representation of the explicit solution to the fractional model and we illustrate the results by numerical schemes. A comparison with the limit case when the fractional order $\alpha \uparrow 1$ (the SIS model) is also given. We analyse the effects of the fractional derivatives by comparing the SIS and the $\alpha$-SIS models.

We show that two-time, second-order correlations of scattered photons from planar arrays and chains of atoms display nonclassical features that can be described by a superatom picture of the canonical single-atom $g_2(\tau)$ resonance fluorescence result. For the superatom, the single-atom linewidth is replaced by the linewidth of the underlying collective low light-intensity eigenmode. Strong light-induced dipole-dipole interactions lead to a correlated response, suppressed joint photon detection events, and dipole blockade that inhibits multiple excitations of the collective atomic state. For targeted subradiant modes, nonclassical nature of emitted light can be dramatically enhanced even compared with that of a single atom.

We study experimentally the longitudinal and transverse wakefields driven by a highly relativistic proton bunch during self-modulation in plasma. We show that the wakefields' growth and amplitude increase with increasing seed amplitude as well as with the proton bunch charge in the plasma. We study transverse wakefields using the maximum radius of the proton bunch distribution measured on a screen downstream from the plasma. We study longitudinal wakefields by externally injecting electrons and measuring their final energy. Measurements agree with trends predicted by theory and numerical simulations and validate our understanding of the development of self-modulation. Experiments were performed in the context of the Advanced Wakefield Experiment (AWAKE).

Using high-resolution, two-dimensional particle-in-cell simulations, we investigate numerically the mechanisms of terahertz (THz) emissions in submicron-thick carbon solid foils driven by ultraintense ($\sim 10^{20}\,\rm W\,cm^{-2}$), ultrashort ($30\,\rm fs$) laser pulses at normal incidence. The considered range of target thicknesses extends down to the relativistic transparency regime that is known to optimize ion acceleration by femtosecond laser pulses. By disentangling the fields emitted by longitudinal and transverse currents, our analysis reveals that, within the first picosecond after the interaction, THz emission occurs in bursts as a result of coherent transition radiation by the recirculating hot electrons and antenna-type emission by the shielding electron currents traveling along the fast-expanding target surfaces.

The forward doubly-virtual Compton scattering (VVCS) off the nucleon contains a wealth of information on nucleon structure, relevant to the calculation of the two-photon-exchange effects in atomic spectroscopy and electron scattering. We report on a complete next-to-leading-order (NLO) calculation of low-energy VVCS in chiral perturbation theory ($\chi$PT). Here we focus on the unpolarized VVCS amplitudes $T_1(\nu, Q^2)$ and $T_2(\nu, Q^2)$, and the corresponding structure functions $F_1(x, Q^2)$ and $F_2(x,Q^2)$. Our results are confronted, where possible, with "data-driven" dispersive evaluations of low-energy structure quantities, such as nucleon polarizabilities. We find significant disagreements with dispersive evaluations at very low momentum-transfer $Q$; for example, in the slope of polarizabilities at zero momentum-transfer. By expanding the results in powers of the inverse nucleon mass, we reproduce the known "heavy-baryon" expressions. This serves as a check of our calculation, as well as demonstrates the differences between the manifestly Lorentz-invariant (B$\chi$PT) and heavy-baryon (HB$\chi$PT) frameworks.

LF-Monopix1 and TJ-Monopix1 are depleted monolithic active pixel sensors (DMAPS) in 150 nm LFoundry and 180 nm TowerJazz CMOS technologies respectively. They are designed for usage in high-rate and high-radiation environments such as the ATLAS Inner Tracker at the High-Luminosity Large Hadron Collider (HL-LHC). Both chips are read out using a column-drain readout architecture. LF-Monopix1 follows a design with large charge collection electrode where readout electronics are placed inside. Generally, this offers a homogeneous electrical field in the sensor and short drift distances. TJ-Monopix1 employs a small charge collection electrode with readout electronics separated from the electrode and an additional n-type implant to achieve full depletion of the sensitive volume. This approach offers a low sensor capacitance and therefore low noise and is typically implemented with small pixel size. Both detectors have been characterized before and after irradiation using lab tests and particle beams.

We experimentally demonstrate that electrically neutral particles, neutrons, can be used to directly visualize the electrostatic field inside a target volume that can be isolated or occupied. Electric-field images were obtained using a polychromatic, spin-polarized neutron beam with a sensitive polarimetry scheme. This work may enable new diagnostic power of the structure of electric potential, electric polarization, charge distribution, and dielectric constant by imaging spatially dependent electric fields in objects that cannot be accessed by other conventional probes.

A compartmental epidemic model is proposed to predict the Covid-19 virus spread. It considers: both detected and undetected infected populations, medical quarantine and social sequestration, release from sequestration, plus possible reinfection. The coefficients in the model are evaluated by fitting to empirical data for eight US states: Arizona, California, Florida, Illinois, Louisiana, New Jersey, New York State, and Texas. Together these states make up 43% of the US population; some of these states appear to have handled their initial outbreaks well, while others appear to be emerging hotspots. The evolution of Covid-19 is fairly similar among the states: variations in contact and recovery rates remain below 5%; however, not surprisingly, variations are larger in death rate, reinfection rate, stay-at-home effect, and release rate from sequestration. The results reveal that outbreaks may have been well underway in several states before first detected and that California might have seen more than one influx of the pandemic. Our projections based on the current situation indicate that Covid-19 will become endemic, spreading for more than two years. Should states fully relax stay-at-home orders, most states may experience a secondary peak in 2021. If lockdowns had been kept in place, the number of Covid-19 deaths so far could have been significantly lower in most states that opened up. Additionally, our model predicts that decreasing contact rate by 10%, or increasing testing by approximately 15%, or doubling lockdown compliance (from the current $\sim$ 15% to $\sim$ 30%) will eradicate infections in the state of Texas within a year. Extending our fits for all of the US states, we predict about 11 million total infections (including undetected), 8 million cumulative confirmed cases, and 630,000 cumulative deaths by November 1, 2020.

The COVID-19 pandemic due to the SARS-CoV-2 coronavirus has directly impacted the public health and economy worldwide. To overcome this problem, countries have adopted different policies and non-pharmaceutical interventions for controlling the spread of the virus. This paper proposes the COVID-ABS, a new SEIR (Susceptible-Exposed-Infected-Recovered) agent-based model that aims to simulate the pandemic dynamics using a society of agents emulating people, business and government. Seven different scenarios of social distancing interventions were analyzed, with varying epidemiological and economic effects: (1) do nothing, (2) lockdown, (3) conditional lockdown, (4) vertical isolation, (5) partial isolation, (6) use of face masks, and (7) use of face masks together with 50% of adhesion to social isolation. In the impossibility of implementing scenarios with lockdown, which present the lowest number of deaths and highest impact on the economy, scenarios combining the use of face masks and partial isolation can be the more realistic for implementation in terms of social cooperation. The COVID-ABS model was implemented in Python programming language, with source code publicly available. The model can be easily extended to other societies by changing the input parameters, as well as allowing the creation of a multitude of other scenarios. Therefore, it is a useful tool to assist politicians and health authorities to plan their actions against the COVID-19 epidemic.

We consider the tilting instability of a magnetically confined spheromak using 3D MHD and relativistic PIC calculations with an application to astrophysical plasmas, specifically those occurring in magnetar magnetospheres. The instability is driven by the counter alignment of the spheromak's intrinsic magnetic dipole with the external magnetic field. Initially the spheromak rotates - tilts - trying to lower its magnetic potential energy. As a result a current sheet forms between the internal magnetic field of a spheromak and the confining field. Magnetic reconnection sets in; this leads to the annihilation of the newly counter-aligned magnetic flux of the spheromak. This occurs on few Alfv\'en time scales. In the case of higher order (second order) spheromak, the internal core is first pushed out of the envelope, resulting in formation of two nearly independent tilting spheromaks. Thus, the magnetically twisted outer shell cannot stabilize the inner core. During dissipation, helicity of the initial spheromak is carried away by torsional Alfv\'en waves, violating the assumptions of the Taylor relaxation theorem. In applications to magnetars' giant flares, fast development of tilting instabilities, and no stabilization of the higher order spheromaks, make it unlikely that trapped spheromaks are responsible for the tail emission lasting hundreds of seconds.

Multi-step assembly of individual protein building blocks is key to the formation of essential higher-order structures inside and outside of cells. Optical tweezers is a technique well suited to investigate the mechanics and dynamics of these structures at a variety of size scales. In this mini-review, we highlight experiments that have used optical tweezers to investigate protein assembly and mechanics, with a focus on the extracellular matrix protein collagen. These examples demonstrate how optical tweezers can be used to study mechanics across length scales, ranging from the single-molecule level to fibrils to protein networks. We discuss challenges in experimental design and interpretation, opportunities for integration with other experimental modalities, and applications of optical tweezers to current questions in protein mechanics and assembly.

Penning ionization releases electrons in a state-selected Rydberg gas of nitric oxide entrained in a supersonic molecular beam. Subsequent processes of electron impact avalanche, bifurcation, and quench form a strongly coupled, spatially correlated ultracold plasma of NO$^+$ ions and electrons that exhibits characteristics of self-organized criticality. This plasma contains a residue of nitric oxide Rydberg molecules. A conventional fluid dynamics of ion-electron-Rydberg quasi-equilibrium predicts rapid decay to neutral atoms. Instead, the NO plasma endures for a millisecond or more, suggesting that quenched disorder creates a state of suppressed electron mobility. Supporting this proposition, a 60 MHz radiofrequency field with a peak-to-peak amplitude less than 1 V cm$^{-1}$ acts dramatically to mobilize electrons, causing the plasma to dissipate by dissociative recombination and Rydberg predissociation. An evident density dependence shows that this effect relies on collisions, giving weight to the idea of arrested relaxation as a cooperative property of the ensemble.

We consider a homogeneous mixture of bosons and polarized fermions. We find that long-range and attractive fermion-mediated interactions between bosons have dramatic effects on the properties of the bosons. We construct the phase diagram spanned by boson-fermion mass ratio and boson-fermion scattering parameter. It consists of stable region of mixing and unstable region toward phase separation. In stable mixing phase, the collective long-wavelength excitations can either be well-behaved with infinite lifetime or be finite in lifetime suffered from the Landau damping. We examine the effects of the induced interaction on the properties of weakly interacting bosons. It turns out that the induced interaction not only enhances the repulsion between the bosons against collapse but also enhances the stability of the superfluid state by suppressing quantum depletion.

In a dusty plasma, an impulsively generated shock, i.e., blast wave, was observed to decay less than would be expected due to gas friction alone. In the experiment, a single layer of microparticles was levitated in a radio-frequency glow-discharge plasma. In this layer, the microparticles were self-organized as a 2D solid-like strongly coupled plasma, which was perturbed by the piston-like mechanical movement of a wire. To excite a blast wave, the wire's motion was abruptly stopped, so that the input of mechanical energy ceased at a known time. It was seen that, as it propagated across the layer, the blast wave's amplitude persisted with little decay. This result extends similar findings, in previous experiments with 3D microparticle clouds, to the case of 2D clouds. In our cloud, out-of-plane displacements were observed, lending support to the possibility that an instability, driven by wakes in the ion flow, provides energy that sustains the blast wave's amplitude, despite the presence of gas damping.

In this paper we develop a methodology for the mesoscale simulation of electrolytes. The methodology is an extension of the Fluctuating Immersed Boundary (FIB) approach that treats a solute as discrete Lagrangian particles that interact with Eulerian hydrodynamic and electrostatic fields. In both cases the Immersed Boundary (IB) method of Peskin is used for particle-field coupling. Hydrodynamic interactions are taken to be overdamped, with thermal noise incorporated using the fluctuating Stokes equation, including a "dry diffusion" Brownian motion to account for scales not resolved by the coarse-grained model of the solvent. Long range electrostatic interactions are computed by solving the Poisson equation, with short range corrections included using a novel immersed-boundary variant of the classical Particle-Particle Particle-Mesh (P3M) technique. Also included is a short range repulsive force based on the Weeks-Chandler-Andersen (WCA) potential. The new methodology is validated by comparison to Debye-H{\"u}ckel theory for ion-ion pair correlation functions, and Debye-H{\"u}ckel-Onsager theory for conductivity, including the Wein effect for strong electric fields. In each case good agreement is observed, provided that hydrodynamic interactions at the typical ion-ion separation are resolved by the fluid grid.

The sampling problem lies at the heart of atomistic simulations and over the years many different enhanced sampling methods have been suggested towards its solution. These methods are often grouped into two broad families. On the one hand methods such as umbrella sampling and metadynamics that build a bias potential based on few order parameters or collective variables. On the other hand tempering methods such as replica exchange that combine different thermodynamic ensembles in one single expanded ensemble. We adopt instead a unifying perspective, focusing on the target probability distribution sampled by the different methods. This allows us to introduce a new method that can sample any of the ensembles normally sampled via replica exchange, but does so in a collective-variables-based scheme. This method is an extension of the recently developed on-the-fly probability enhanced sampling method [Invernizzi and Parrinello, J. Phys. Chem. Lett. 11.7 (2020)] that has been previously used for metadynamics-like sampling. The method is thus very general and can be used to achieve different types of enhanced sampling. It is also reliable and simple to use, since it presents only few and robust external parameters and has a straightforward reweighting scheme. Furthermore, it can be used with any number of parallel replicas. We show the versatility of our approach with applications to multicanonical and multithermal-multibaric simulations, thermodynamic integration, umbrella sampling, and combinations thereof.

This paper is devoted to analytical solutions for the base flow and temporal stability of a liquid film driven by gravity over an inclined plane when the fluid rheology is given by the Carreau-Yasuda model, a general description that applies to different types of fluids. In order to obtain the base state and critical conditions for the onset of instabilities, two sets of asymptotic expansions are proposed, from which it is possible to find four new equations describing the reference flow and the phase speed and growth rate of instabilities. These results lead to an equation for the critical Reynolds number, which dictates the conditions for the onset of the instabilities of a falling film. Different from previous works, this paper presents asymptotic solutions for the growth rate, wavelength and celerity of instabilities obtained without supposing a priori the exact fluid rheology, being, therefore, valid for different kinds of fluids. Our findings represent a significant step toward understanding the stability of gravitational flows of non-Newtonian fluids.

A canonical quantization scheme for localized surface plasmons (LSPs) in a metal nanosphere is presented based on a microscopic model composed of electromagnetic fields, oscillators that describe plasmons, and a reservoir that describes excitations other than plasmons. The eigenmodes of this fully quantum electrodynamic theory show a spectrum that includes radiative depolarization and broadening, including redshifting from the quasi-static LSP modes, with increasing particle size. These spectral profiles correctly match those obtained with exact classical electrodynamics (Mie theory). The present scheme provides the electric fields per plasmon in both near- and far-field regions whereby its utility in the fields of quantum plasmonics and nano-optics is demonstrated.