An improved Iterative Physical Optics (IPO) image approximation method has been presented to dramatically increase the accuracy of the approximation and extend its applicability to PEC surfaces with smaller radii or larger curvatures. Starting from the first-order conventional PO image approximation, the IPO image approximation method iteratively correct the surface current to compensate the deviation of the electric field boundary condition on the PEC surfaces, making use of the local plane wave approximation. Numerical validations with two popular PEC surfaces, i.e., the parabolic dish antennas and the PEC spheres, are carried out and the results show that the IPO approximation method increases the surface current accuracy by more than two orders of magnitude, compared to the conventional PO image approximation method.

Accurate ground-state energies are the focus of most electronic structure calculations. Such energies can, in principle, be extracted from a sequence of density functional calculations of conditional probabilities (CP-DFT), without approximating the energy directly. Simple CP approximations yield usefully accurate results for a broad range of systems: two-electron ions, the hydrogen dimer, and the uniform gas at all temperatures. CP-DFT has no self-interaction error for one electron, and correctly dissociates H$_2$, both major challenges in standard density functional theory. Orbital free CP-DFT may be ideal for warm dense matter simulations

The novel corona virus (COVID-19) has slowed down a lot of human activities in the world. A lockdown for a period of 2 months, due to the pandemic, was enough to cause a drop of 7% of the anthropogonic CO2 in the atmosphere. In addition to the world in general, the excess of the anthropogonic CO2 emission in the atmosphere has always been a threat to the oceans as well. Oceans play a key role to buffer the greenhouse effect, but in the process, it becomes warmer, more acidic, and less oxygenated. While there have already been investigations done on the effect of pandemic on atmosphere, the question what happens to oceans during the pandemic remains unanswered. The aim of this paper is to study the pandemic's effect and the resultant reduction in CO2 emissions on the productivity of the global oceans. Often Chlorophyll-a (Chl-a), Particulate organic and inorganic carbon (PIC:POC) and sea surface temperature(SST), are used to indicate the productivity of oceans. Herein, satellite-derived estimates of the aforementioned parameters are used. Based on these estimates, a drop in Chl-a (0.5 mgm-3) is observed off Alaska, North Europe,South China and Southeast USA during the pandemic. CO2 reduction of 123 MtCO2 during the pandemic in China might have caused reduction in mean Chl-a by around 5% (2.5 to 1.6 mgm-3). Reduction of Chl-a during the pandemic is mostly associated with the reduction of PIC:POC. The pandemic demonstrates noticeable effect on Chl-a and/or SST. A cooling response of 0.5 oC in mean SST is observed over most of the coastal areas, especially off Alaska,north Indian ocean and eastern Pacific. The decrease in the CO2 emissions in India by 30% during the pandemic translates into a drop of mean SST in the north Indian ocean by 5% (from 29.95 to 28.46 oC). All these suggest that maintaining global activities as sustainable as the pandemic period, can help to recover the oceans.

This work aims at identifying and quantifying uncertainties related to elastic and viscoelastic parameters, which characterize the arterial wall behavior, in one-dimensional modeling of the human arterial hemodynamics. The chosen uncertain parameters are modeled as random Gaussian-distributed variables, making stochastic the system of governing equations. The proposed methodology is initially discussed for a model equation, presenting a thorough convergence study which confirms the spectral accuracy of the stochastic collocation method and the second-order of accuracy of the IMEX finite volume scheme chosen to solve the mathematical model. Then, univariate and multivariate uncertain quantification analyses are applied to the a-FSI blood flow model, concerning baseline and patient-specific single-artery test cases. A different sensitivity is depicted when comparing the variability of flow rate and velocity waveforms to the variability of pressure and area, the latter ones resulting much more sensitive to the parametric uncertainties underlying the mechanical characterization of vessel walls. Simulations performed considering both the simple elastic and the more realistic viscoelastic constitutive law show that including viscoelasticity in the FSI model consistently improves the reliability of pressure waveforms prediction. Results of the patient-specific tests suggest that the proposed methodology could be a valuable tool for improving cardiovascular diagnostics and the treatment of diseases.

Three weakly nonlinear but fully dispersive Whitham-Boussinesq systems for uneven bathymetry are studied. The derivation and discretization of one system is presented. The numerical solutions of all three are compared with wave gauge measurements from a series of laboratory experiments conducted by Dingemans. The results show that although the models are mathematically similar, their accuracy varies dramatically.

Mobile devices, climate science, and autonomous vehicles all require advanced microwave antennas for imaging, radar, and wireless communications. The cost, size, and power consumption of existing technology, however, has hindered the ubiquity of electronically steered systems. Here, we propose a metasurface antenna design paradigm that enables electronic beamsteering from a passive lightweight circuit board with varactor-tuned elements. Distinct from previous metasurfaces (which require dense element spacing), the proposed design uses Nyquist spatial sampling of half a wavelength. We detail the design of this Nyquist metasurface antenna and experimentally validate its ability to electronically steer in two directions. Nyquist metasurface antennas can realize high performance without costly and power hungry phase shifters, making them a compelling technology for future antenna hardware.

Many high power electronic devices operate in a regime where the current they draw is limited by the self-fields of the particles. This space-charge-limited current poses particular challenges for numerical modeling where common techniques like over-emission or Gauss Law are computationally inefficient or produce nonphysical effects. In this paper we show an algorithm using the value of the electric field in front of the surface instead of attempting to zero the field at the surface, making the algorithm particularly well suited to both electromagnetic and parallel implementations of the PIC algorithm. We show how the algorithm is self-consistent within the framework of finite difference (for both electrostatics and electromagnetics). We show several 1D and 2D benchmarks against both theory and previous computational results. Finally we show application in 3D to high power microwave generation in a 13 GHz magnetically insulated line oscillator.

Exact density functionals for the exchange and correlation energies are approximated in practical calculations for the ground-state electronic structure of a many-electron system. An important exact constraint for the construction of approximations is to recover the correct non-relativistic large-$Z$ expansions for the corresponding energies of neutral atoms with atomic number $Z$ and electron number $N=Z$, which are correct to leading order ($-0.221 Z^{5/3}$ and $-0.021 Z \ln Z$ respectively) even in the lowest-rung or local density approximation. We find that hydrogenic densities lead to $E_x(N,Z) \approx -0.354 N^{2/3} Z$ (as known before only for $Z \gg N \gg 1$) and $E_c \approx -0.02 N \ln N$. These asymptotic estimates are most correct for atomic ions with large $N$ and $Z \gg N$, but we find that they are qualitatively and semi-quantitatively correct even for small $N$ and for $N \approx Z$. The large-$N$ asymptotic behavior of the energy is pre-figured in small-$N$ atoms and atomic ions, supporting the argument that widely-predictive approximate density functionals should be designed to recover the correct asymptotics.

The impact of liquid drops on a rigid surface is central in cleaning, cooling and coating processes in both nature and industrial applications. However, it is not clear how details of pores, roughness and texture on the solid surface influence the initial stages of the impact dynamics. Here, we experimentally study drop impacting at low velocities onto surfaces textured with asymmetric (tilted) ridges. % We define the line-friction capillary number $Ca_f = \mu_f V_0/\sigma$ (where $\mu_f$, $V_0$ and $\sigma$ are the line friction, impact velocity and surface tension, respectively) as a measure of the importance of the topology of surface textures for the dynamics of droplet impact. We show that when $Ca_f \ll 1$, the contact line speed in the direction against the inclination of the ridges is set by line-friction, whereas in the direction with inclination the contact line is pinned at acute corners of the ridge. When $Ca_f \sim 1$, the pinning is only temporary as inertia pushes the liquid-gas interface to next ridge where a new contact line is formed. Finally, when $Ca_f\gg 1$, impact inertia of the droplet entirely governs spreading and the geometric details of non-smooth surfaces play little role.

Lithium-ion batteries are recognised as a key technology to power electric vehicles and integrate grid-connected renewable energy resources. The economic viability of these applications is affected by the battery degradation during its lifetime. This study presents an extensive experimental degradation data for lithium-ion battery cells from three different manufactures (Sony, BYD and Samsung). The Sony and BYD cells are of LFP chemistry while the Samsung cell is of NMC. The capacity fade and resistance increase of the battery cells are quantified due to calendar and cycle aging. The charge level and the temperature are considered as the main parameters to affect calendar aging while the depth of discharge, current rate and temperature for cycle aging. It is found that the Sony and BYD cells with LFP chemistry has calendar capacity loss of nearly 5% and 8% after 30 months respectively. Moreover, the Samsung NMC cell reached 80% state of health after 3000 cycles at 35C and 75% discharge depth suggesting a better cycle life compared to the other two battery cells with the same conditions

Free-falling objects impacting onto water pools experience a very high initial impact force, greatest at the moment when breaking through the free surface. Many have intuitively wondered whether throwing another object in front of an important object (like oneself) before impacting the water surface may reduce this high impact force. Here, we test this idea experimentally by allowing two spheres to consecutively enter the water and measuring the forces on the trailing sphere. We find that the impact acceleration reduction on the trailing sphere depends on the dynamics of the cavity created by the first sphere and the relative timing of the second sphere impact. These combined effects are captured by the non-dimensional `Matryoshka' number, which classifies the observed phenomena into four major regimes. In three of these regimes, we find that the impact acceleration on the second sphere is reduced by up to 78\% relative to impact on a quiescent water surface. Surprisingly, in one of the regimes, the force on the trailing sphere is dramatically increased by more than 400\% in the worst case observed. We explain how the various stages of cavity evolution result in the observed alterations in impact force in this multi-body water entry problem.

Purpose To alleviate the spatial encoding limitations of single-shot EPI by developing multi-shot segmented EPI for ultra-high-resolution fMRI with reduced ghosting artifacts from subject motion and respiration. Methods Segmented EPI can reduce readout duration and reduce acceleration factors, however, the time elapsed between segment acquisitions (on the order of seconds) can result in intermittent ghosting, limiting its use for fMRI. Here, "FLEET" segment ordering--where segments are looped over before slices--was combined with a variable flip angle progression (VFA-FLEET) to improve inter-segment fidelity and maximize signal for fMRI. Scaling a sinc pulse's flip angle for each segment (VFA-FLEET-Sinc) produced inconsistent slice profiles and ghosting, therefore, a recursive Shinnar-Le Roux (SLR) RF pulse design was developed (VFA-FLEET-SLR) to generate unique pulses for every segment that together produce consistent slice profiles and signals. Results The temporal stability of VFA-FLEET-SLR was compared against conventional-segmented EPI and VFA-FLEET-Sinc at 3 T and 7 T. VFA-FLEET-SLR showed reductions in both intermittent and stable ghosting compared to conventional-segmented and VFA-FLEET-Sinc, resulting in improved image quality with a minor trade-off in temporal SNR. Combining VFA-FLEET-SLR with acceleration, we achieved a 0.6-mm isotropic acquisition at 7 T--without zoomed imaging or partial Fourier--demonstrating reliable detection of BOLD responses to a visual stimulus. To counteract the increased repetition time from segmentation, simultaneous multi-slice VFA-FLEET-SLR was demonstrated using RF-encoded controlled aliasing. Conclusions VFA-FLEET with a recursive RF pulse design supports acquisitions with low levels of artifact and spatial blur, enabling fMRI at previously inaccessible spatial resolutions with a "full-brain" field of view.

Aligned, densely-packed carbon nanotube metamaterials prepared using vacuum filtration are an emerging infrared nanophotonic material. We report multiple hyperbolic plasmon resonances, together spanning the mid-infrared, in individual resonators made from aligned and densely-packed carbon nanotubes. In the first near-field scanning optical microscopy (NSOM) imaging study of nanotube metamaterial resonators, we observe distinct deeply-subwavelength field profiles at the fundamental and higher-order resonant frequencies. The wafer-scale area of the nanotube metamaterials allows us to combine this near-field imaging with a systematic far-field spectroscopic study of the scaling properties of many resonator arrays. Thorough theoretical modeling agrees with these measurements and identifies the resonances as higher-order Fabry-P\'erot (FP) resonances of hyperbolic waveguide modes. Nanotube resonator arrays show broadband extinction from 1.5-10 {\mu}m and reversibly switchable extinction in the 3-5 {\mu}m atmospheric transparency window through the coexistence of multiple modes in individual ribbons. Broadband carbon nanotube metamaterials supporting multiple resonant modes are a promising candidate for ultracompact absorbers, tunable thermal emitters, and broadband sensors in the mid-infrared.

We present in this work the first experimental observation of oscillations in Parity-Time symmetric ZRC dimers. The system obtained is of first order ordinary differential equation due to the use of imaginary resistors. The coupled cells must share the same type of frequency: positive or negative. We observed the real and imaginary parts of the voltage across the components of a ZRC cell. Exceptional points are well identified. This work may be very useful in the generation of new type of oscillators. It can also be used in the design of new optoelectronic devices for major applications in the transport of information and the mimics of two-level systems for quantum computing.

This paper deals with different image theorems, i.e., Love's equivalence principle, the induction equivalence principle and the physical optics equivalence principle, in the spherical geometry. The deviation of image theorem approximation is quantified by comparing the modal expansion coefficients between the electromagnetic field obtained from the image approximation and the exact electromagnetic field for the spherical geometry. Two different methods, i.e., the vector potential method through the spherical addition theorem and the dyadic Green's function method, are used to do the analysis. Applications of the spherical imaging theorems include metal mirror design and other electrically-large object scattering.

Garay-Avenda\~no \& Zamboni-Rached (2014) defined two classes of axisymmetric solutions of the free Maxwell equations. We prove that the linear combinations of these two classes of solutions cover all totally propagating time-harmonic axisymmetric free Maxwell fields -- and hence, by summation on frequencies, all totally propagating axisymmetric free Maxwell fields. It provides an explicit representation for these fields. This will be important, e.g., to have the interstellar radiation field in a disc galaxy modelled as an exact solution of the free Maxwell equations. Keywords: Maxwell equations; axial symmetry; exact solutions; electromagnetic duality

A mechanical model of a quasi-elastic body (aether) which reproduces Maxwell's equations with charges and currents is presented. In MacCullagh's model [31], a quasi-elastic body with antisymmetrical stress tensor was considered but it did not include any charges or currents. Indeed, any presence of charges or currents appeared to contradict the continuity equation of the aether and it remained a mystery as to where the aether goes and whence it comes. We present here a solution to this mystery. In the model here presented, the amount of aether is conserved even in the presence of charges and currents. It turns out that the charges themselves appear to be moving with the same local aethereal velocity. In other words, the charges appear to be part of the aether itself, a kind of singularities in the aether. The positive (negative) charge seems to blast away (draw in) aether with a rate equal to the amount of charge, the electric field is interpreted as flux of the aether and the magnetic field as a torque per unit volume. In addition it is shown that the model is consistent with the theory of relativity, provided that Lorentz-Poincare interpretation of relativity theory is used instead of the relativistic or Minkowskian interpretation (three very different but empirically equivalent interpretations). Within the framework of the Lorentz-Poincare interpretation a statistical-mechanical interpretation of the Lorentz transformations is provided. It turns out that the length of a body is contracted by the electromagnetic field acting back on the body produced by the constituent particles of this same body. This self-interaction causes also delay of all the processes.

We show that for the optimized angle of incidence, the SPR based optical sensors exhibit dual resonance in the near-infrared region around which the sensor becomes exceptionally high sensitive. Both the resonances show opposite spectral shift with an ambient refractive index, increasing the differential shift by many folds. The physical reason behind the dual resonance and opposite spectral shifts are also explained using the modal analysis and the phase-matching condition. The presence of dual resonance is highly susceptible to the angle of incidence, which facilitates the sensors to work in a wide range from gaseous specimen to biological ones with extremely high sensitivity of 460 um/RIU and 290 um/RIU, respectively. The considered sensor has broader prospects for the detection of bio-chemicals and gases without changing its geometrical parameters.

Objectives: Precise segmentation of total extraocular muscles (EOM) and optic nerve (ON) is essential to assess anatomical development and progression of thyroid-associated ophthalmopathy (TAO). We aim to develop a semantic segmentation method based on deep learning to extract the total EOM and ON from orbital CT images in patients with suspected TAO. Materials and Methods: A total of 7,879 images obtained from 97 subjects who underwent orbit CT scans due to suspected TAO were enrolled in this study. Eighty-eight patients were randomly selected into the training/validation dataset, and the rest were put into the test dataset. Contours of the total EOM and ON in all the patients were manually delineated by experienced radiologists as the ground truth. A three-dimensional (3D) end-to-end fully convolutional neural network called semantic V-net (SV-net) was developed for our segmentation task. Intersection over Union (IoU) was measured to evaluate the accuracy of the segmentation results, and Pearson correlation analysis was used to evaluate the volumes measured from our segmentation results against those from the ground truth. Results: Our model in the test dataset achieved an overall IoU of 0.8207; the IoU was 0.7599 for the superior rectus muscle, 0.8183 for the lateral rectus muscle, 0.8481 for the medial rectus muscle, 0.8436 for the inferior rectus muscle and 0.8337 for the optic nerve. The volumes measured from our segmentation results agreed well with those from the ground truth (all R>0.98, P<0.0001). Conclusion: The qualitative and quantitative evaluations demonstrate excellent performance of our method in automatically extracting the total EOM and ON and measuring their volumes in orbital CT images. There is a great promise for clinical application to assess these anatomical structures for the diagnosis and prognosis of TAO.

Identifying important nodes is one of the central tasks in network science, which is crucial for analyzing the structure of a network and understanding the dynamical processes on a network. Most real-world systems are time-varying and can be well represented as temporal networks. Motivated by the classic gravity model in physics, we propose a temporal gravity model to identify influential nodes in temporal networks. Two critical elements in the gravity model are the masses of the objects and the distance between two objects. In the temporal gravity model, we treat nodes as the objects, basic node properties, such as static and temporal properties, as the nodes' masses. We define temporal distances, i.e., fastest arrival distance and temporal shortest distance, as the distance between two nodes in our model. We utilize our model as well as the baseline centrality methods on important nodes identification. Experimental results on ten real-world datasets show that the temporal gravity model outperforms the baseline methods in quantifying node structural influence. Moreover, when we use the temporal shortest distance as the distance between two nodes, our model is robust and performs the best in quantifying node spreading influence compared to the baseline methods.

The tailoring of plasmonic near-fields is central to the field of nanophotonics. The detailed knowledge of the field distribution is crucial for a design and fabrication of plasmonic sensors, detectors, photovoltaics, plasmon-based cicuits, nanomanipulators, electrooptic plasmonic modulators and atomic devices. We report on a fully quantitative comparison between near field observation and numerical calculations, considering the intensity distribution for TM and TE polarisations, necessary for the construction of devices in all these areas. We present the near field scanning microscopy (NSOM) results of Surface Plasmon Polaritons (SPPs), excited by linearly polarized illumination on a gold, nanofabricated transmission grating. The optimization process is performed for infrared light, for future applications in cold atoms trapping and plasmonic sensing. We show the in situ processes of build up and propagation of SPPs and confirm that the out of plane component is not coupled to the aperture-type NSOM probe.

The airline industry was severely hit by the COVID-19 crisis with an average demand decrease of about $64\%$ (IATA, April 2020) which triggered already several bankruptcies of airline companies all over the world. While the robustness of the world airline network (WAN) was mostly studied as an homogeneous network, we introduce a new tool for analyzing the impact of a company failure: the `airline company network' where two airlines are connected if they share at least one route segment. Using this tool, we observe that the failure of companies well connected with others has the largest impact on the connectivity of the WAN. We then explore how the global demand reduction affects airlines differently, and provide an analysis of different scenarios if its stays low and does not come back to its pre-crisis level. Using traffic data from the Official Aviation Guide (OAG) and simple assumptions about customer's airline choice strategies, we find that the local effective demand can be much lower than the average one, especially for companies that are not monopolistic and share their segments with larger companies. Even if the average demand comes back to $60\%$ of the total capacity, we find that between $46\%$ and $59\%$ of the companies could experience a reduction of more than $50\%$ of their traffic, depending on the type of competitive advantage that drives customer's airline choice. These results highlight how the complex competitive structure of the WAN weakens its robustness when facing such a large crisis.

I describe a simple method to calculate Earth dimensions using only local measurements and observations. I used modern technology (a digital photo camera and Google Earth) but the exact same method can be used without any aid, with naked eye observations and distances measured by walking, and so it was perfectly accessible to Ancient Greek science.

We present a kinetic model for optical pumping in Lu$^+$ and Lr$^+$ ions as well as a theoretical approach to calculate the transport properties of Lu$^+$ in its ground $^1S_0$ and metastable $^3D_1$ states in helium background gas. Calculations of the initial ion state populations, the field and temperature dependence of the mobilities and diffusion coefficients, and the ion arrival time distributions demonstrate that the ground- and metastable-state ions can be collected and discriminated efficiently under realistic macroscopic conditions.

In this work, we study magnetization switching induced by spin-orbit torque in heterostructures with variable thickness of heavy-metal layers W and Pt, perpendicularly magnetized Co layer and an antiferromagnetic NiO layer. Using current-driven switching, magnetoresistance and anomalous Hall effect measurements, perpendicular and in-plane exchange bias field were determined. Several Hall-bar devices possessing in-plane exchange bias from both systems were selected and analyzed in relation to our analytical switching model of critical current density as a function of Pt and W thickness, resulting in estimation of effective spin Hall angle and effective perpendicular magnetic anisotropy. Approximately one order of magnitude smaller critical switching current densities in W- than Pt-based Hall-bar devices were found due to a higher effective spin Hall angle in W structures. The current switching stability and training process are discussed in detail.

Optical spectroscopy constitutes the historical path to accumulate basic knowledge on the atom and its structure. Former work based on fluorescence and resonance ionization spectroscopy enabled identifying optical spectral lines up to element 102, nobelium. The new challenges faced in this research field are the refractory nature of the heavier elements and the decreasing production yields. A new concept of ion-mobility-assisted laser spectroscopy is proposed to overcome the sensitivity limits of atomic structure investigations persisting in the region of the superheavy elements. The concept offers capabilities of both broadband-level searches and high-resolution hyperfine spectroscopy of synthetic elements beyond nobelium.

Reduced-order models of flame dynamics can be used to predict and mitigate the emergence of thermoacoustic oscillations in the design of gas turbine and rocket engines. This process is hindered by the fact that these models, although often qualitatively correct, are not usually quantitatively accurate. As automated experiments and numerical simulations produce ever-increasing quantities of data, the question arises as to how this data can be assimilated into physics-informed reduced-order models in order to render these models quantitatively accurate. In this study, we develop and test a physics-based reduced-order model of a ducted premixed flame in which the model parameters are learned from high speed videos of the flame. The experimental data is assimilated into a level-set solver using an ensemble Kalman filter. This leads to an optimally calibrated reduced-order model with quantified uncertainties, which accurately reproduces elaborate nonlinear features such as cusp formation and pinch-off. The reduced-order model continues to match the experiments after assimilation has been switched off. Further, the parameters of the model, which are extracted automatically, are shown to match the first order behavior expected on physical grounds. This study shows how reduced-order models can be updated rapidly whenever new experimental or numerical data becomes available, without the data itself having to be stored.

We perform simulations of structural balance evolution on a triangular lattice using the heat-bath algorithm. In contrast to similar approaches -- but applied to analysis of complete graphs -- the triangular lattice topology successfully prevents the occurrence of even partial Heider's balance. Starting with the state of Heider's paradise, it is just a matter of time when the evolution of the system leads to an unbalanced and disordered state. The time of the system relaxation does not depend on the system size. The lack of any signs of balanced state was not observed in earlier investigated systems dealing with structural balance

We advance here an algorithm of the synthesis of lossless electric circuits such that their evolution matrices have the prescribed Jordan canonical forms subject to natural constraints. Every synthesized circuit consists of a chain-like sequence of LC-loops coupled by gyrators. All involved capacitances, inductances and gyrator resistances are either positive or negative with values determined by explicit formulas. A circuit must have at least one negative capacitance or inductance for having a nontrivial Jordan block for the relevant matrix.

Most of the opinion dynamics models in sociophysics have their historic origin in studies two-dimensional magnetization phenomena. This metaphor has proven quite useful, as it allowed to use well known techniques, relating individual behaviours of single spins and their interactions, to large scale properties, such as magnetization or magnetic domains creation. These physical properties were then ``mapped'' to social concepts: spin orientation to a person's views on a specific issue, magnetization to global opinion on the issue, etc. During the past 20 years, the models were significantly expanded, using more complex individual agent characteristics and even more complex types of the interactions, but the power of the metaphor remained unchanged. In the current paper we propose to use a new physical system as the basis for new ideas in sociophysics. We shall argue that the concepts and tools devoted to studies of High Entropy Alloys (HEAs) could significantly broaden the range of social concepts ``addressable'' by sociophysics, by focusing on a wider range of global phenomena, arising from atomic properties, interactions and arrangements. We illustrate the new idea by calculating a few characteristics of a simple HEA system and their possible ``mapping'' into social concepts.

Due to immature treatment and rapid transmission of COVID-19, mobility interventions play a crucial role in containing the outbreak. Among various non-pharmacological interventions, community infection control is considered to be a quite promising approach. However, there is a lack of research on improving community-level interventions based on a community's real conditions and characteristics using real-world observations. Our paper aims to investigate the different responses to mobility interventions between communities in the United States with a specific focus on different income levels. We produced six daily mobility metrics for all communities using the mobility location data from over 100 million anonymous devices on a monthly basis. Each metric is tabulated by three performance indicators: "best performance," "effort," and "consistency." We found that being high-income improves social distancing behavior after controlling multiple confounding variables in each of the eighteen scenarios. In addition to the reality that it is more difficult for low-income communities to comply with social distancing, the comparisons between scenarios raise concerns on the employment status, working condition, accessibility to life supplies, and exposure to the virus of low-income communities.

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.

Laser decoherence limits the stability of optical clocks by broadening the observable resonance linewidths and adding noise during the dead time between clock probes. Correlation spectroscopy avoids these limitations by measuring correlated atomic transitions between two ensembles, which provides a frequency difference measurement independent of laser noise. Here, we apply this technique to perform stability measurements between two independent clocks based on the $^1S_0\leftrightarrow{}^3P_0$ transition in $^{27}$Al$^+$. By stabilizing the dominant sources of differential phase noise between the two clocks, we observe coherence between them during synchronous Ramsey interrogations as long as 8 s at a frequency of $1.12\times10^{15}$ Hz. The observed contrast in the correlation spectroscopy signal is consistent with the 20.6 s $^3P_0$ state lifetime and supports a measurement instability of $(1.8\pm0.5)\times 10^{-16}/\sqrt{\tau/\textrm{s}}$ for averaging periods longer than the probe duration when deadtime is negligible.

Demand for low-noise, continuous-wave, frequency-tunable lasers based on semiconductor integrated photonics has been advancing in support of numerous applications. In particular, an important goal is to achieve narrow spectral linewidth, commensurate with bulk-optic or fiber-optic laser platforms. Here, we report on laser-frequency-stabilization experiments with a heterogeneously integrated III/V-Si widely tunable laser and a high-finesse, thermal-noise-limited photonic resonator. This hybrid architecture offers a chip-scale optical-frequency reference with an integrated linewidth of 60 Hz and a fractional frequency stability of 2.5e-13 at 1-second integration time. We explore the potential for stabilization with respect to a resonator with lower thermal noise by characterizing laser-noise contributions such as residual amplitude modulation and photodetection noise. Widely tunable, compact and integrated, cost effective, stable and narrow linewidth lasers are envisioned for use in various fields, including communication, spectroscopy, and metrology.

Over the past decade, artificially engineered optical materials and nanostructured thin films have revolutionized the area of photonics by employing novel concepts of metamaterials and metasurfaces where spatially varying structures yield tailorable, "by design" effective electromagnetic properties. The current state-of-the-art approach to designing and optimizing such structures relies heavily on simplistic, intuitive shapes for their unit cells or meta-atoms. Such approach can not provide the global solution to a complex optimization problem where both meta-atoms shape, in-plane geometry, out-of-plane architecture, and constituent materials have to be properly chosen to yield the maximum performance. In this work, we present a novel machine-learning-assisted global optimization framework for photonic meta-devices design. We demonstrate that using an adversarial autoencoder coupled with a metaheuristic optimization framework significantly enhances the optimization search efficiency of the meta-devices configurations with complex topologies. We showcase the concept of physics-driven compressed design space engineering that introduces advanced regularization into the compressed space of adversarial autoencoder based on the optical responses of the devices. Beyond the significant advancement of the global optimization schemes, our approach can assist in gaining comprehensive design "intuition" by revealing the underlying physics of the optical performance of meta-devices with complex topologies and material compositions.

The power spectrum of water optical turbulence is shown to vary with its average temperature $\left\langle T \right\rangle$ and average salinity concentration $\left\langle S \right\rangle$, as well as with light wavelength $\lambda$. This study explores such variations for $\left\langle T \right\rangle \in \left[ {0\ ^\circ\rm{C},30\ ^\circ\rm{C}} \right]$, $\left\langle S \right\rangle \in \left[ {0\ \rm{ppt},40\ \rm{ppt}} \right]$ covering most of the possible natural water conditions within the Earth's boundary layer and for visible electromagnetic spectrum, $\lambda \in \left[400\ nm, 700\ nm \right]$. For illustration of the effects of these parameters on propagating light we apply the developed power spectrum model for estimation of the scintillation index of a plane wave (the Rytov variance) and the threshold between weak and strong turbulence regimes.

On their way to an academic career in physics, Ph.D. students have to overcome difficulties at many levels. Beyond the intellectual challenge, there are also psychological, social and economic barriers. We studied the difficulties experienced by physics Ph.D. students in the Israeli universities, with special attention to gender-related issues. Among the hurdles that are much more significant for women than for men -- that we call ``the glass hurdles" -- we find gender-related discrimination, sexual harassment, physiological and psychological health issues, and challenges related to pregnancy and parenthood. We make recommendations for ways to confront and remove these barriers in order to provide female physicists with an equal opportunity to succeed.

The analytical solution of neutron transport equation has fascinated mathematicians and physicists alike since the Milne half-space problem was introduce in 1921 [1]. Numerous numerical solutions exist, but understandably, there are only a few analytical solutions, with the prominent one being the singular eigenfunction expansion (SEE) introduced by Case [2] in 1960. For the half-space, the method, though yielding, an elegant analytical form resulting from half-range completeness, requires numerical evaluation of complicated integrals. In addition, one finds closed form analytical expressions only for the infinite medium and half-space cases. One can find the flux in a slab only iteratively. That is to say, in general one must expend a considerable numerical effort to get highly precise benchmarks from SEE. As a result, investigators have devised alternative methods, such as the CN [3], FN [4] and Greens Function Method (GFM) [5] based on the SEE have been devised. These methods take the SEE at their core and construct a numerical method around the analytical form. The FN method in particular has been most successful in generating highly precise benchmarks. No method yielding a precise numerical solution has yet been based solely on a fundamental discretization until now. Here, we show for the albedo problem with a source on the vacuum boundary of a homogeneous medium, a precise numerical solution is possible via Lagrange interpolation over a discrete set of directions.

A novel planar device having doped silicon regions (tubs) under the source and drain of an FDSOI MOSFET is reported at 20 nm gate length. The doped silicon regions result in formation of potential wells (PW) in the source and drain regions of FDSOI MOSFET and thus, the device being called as Potential Well Based FDSOI MOSFET (PWFDSOI MOSFET). Simulation and device physics study on PWFDSOI MOSFET showed reduction in the OFF current of the device by orders of magnitude. A low IOF F of 22 pA/um, high ION /IOF F ratio of 1.5 x 107 and subthreshold swing of 76 mV/decade were achieved in 20 nm gate length PWFDSOI MOSFET. The study was performed on devices with unstrained silicon channel.

On the base of logic discrete equations system mathematical modeling of COVID-19 epidemic spread was carried out in the world and in the countries with the largest number of infected people such as the USA, Brasil, Russia and India in the first half of 2020. It was shown that for the countries with strong restrictive measures the spread of COVID-19 fit on a single wave with small capacity as for a number of countries with violation of restrictive measures the spread of the epidemic fit on a waves superposition. For countries with large population mixing, the spread of the epidemic today also fits into a single wave, but with a huge capacity value (for Brazil - 80 million people, for India - 40 million people). We estimated that the epidemic spread in the world today fits into 5 waves. The first two waves are caused by the epidemic spread in China (the first - in Wuhan), the third - by the epidemic spread in European countries, the fourth mainly by the epidemic spread in Russia and the USA, the fifth wave is mainly caused by the epidemic spread in Latin America and South Asia. It was the fifth wave that led to the spread of the coronavirus epidemic COVID-19 entering a new phase, with an increase in the number of infected more than 100 thousand inhabitants. For all the studied countries and the world, for each of the superposition waves, the wave capacities and growth indicators were calculated. The local peaks of the waves and their ending times are determined. It was the fifth wave that led to the fact that COVID-19 spread is entering a new phase, with the increase in the number of infected people being more than 100 thousand inhabitants. For all the countries being examined and for the whole world, for each of the superposition waves we calculated the waves capacities and index of infected people growth.

A Hamiltonian six-field gyrofluid model is constructed, based on closure relations derived from the so-called "quasi-static" gyrokinetic linear theory where the fields are assumed to propagate with a parallel phase velocity much smaller than the parallel particle thermal velocities. The main properties of this model, primarily aimed at exploring basic phenomena of interest for space plasmas such as the solar wind, are its ability to provide a reasonable agreement with kinetic theory for linear low-frequency modes, and at the same time to ensure a Hamiltonian structure in the absence of explicit dissipation. The model accounts for equilibrium temperature anisotropy, ion and electron finite Larmor radius corrections, electron inertia, magnetic fluctuations along the direction of a strong guide field, and parallel Landau damping. Remarkably, the quasi-static closure leads to exact expressions for the nonlinear terms involving gyroaveraged electromagnetic perturbations. One of the consequences is that a rather natural identification of the Hamiltonian structure of the model becomes possible when Landau damping is neglected. A slight variant of the model consists of a four-field Hamiltonian reduction of the original six-field model, which we use for the subsequent linear analysis. In the latter, the dispersion relations of kinetic Alfv\'en waves and the firehose instability are shown to be correctly reproduced, relatively far in the sub-ion range (depending on the plasma parameters), while the spectral range where the slow-wave dispersion relation and the field-swelling instabilities are precisely described is less extended. This loss of accuracy originates from the breaking of the condition of small phase velocity, relative to the parallel thermal velocity of the electrons (for kinetic Alfv\'en waves and firehose instability) or of the ions (in the case of the field-swelling instabilities).

Hybrid-halide perovskite (HHP) films exhibit exceptional photo-electric properties. These materials are utilized for highly efficient solar cells and photoconductive technologies. Both ion migration and polarization have been proposed as the source of enhanced photoelectric activity, but the exact origin of these advantageous device properties has remained elusive. Here, we combined microscale and device-scale characterization to demonstrate that polarization-assisted conductivity governs photoconductivity in thin HHP films. Conductive atomic force microscopy under light and variable temperature conditions showed that the photocurrent is directional and is suppressed at the tetragonal-to-cubic transformation. It was revealed that polarization-based conductivity is enhanced by light, whereas dark conductivity is dominated by non-directional ion migration, as was confirmed by large-scale device measurements. Following the non-volatile memory nature of polarization domains, photoconductive memristive behavior was demonstrated. Understanding the origin of photoelectric activity in HHP allows designing devices with enhanced functionality and lays the grounds for photoelectric memristive devices.

Many prior studies have found a gender gap between male and female students' performance on conceptual assessments such as the Force Concept Inventory (FCI) and the Conceptual Survey of Electricity and Magnetism (CSEM) with male students performing better than female students. Prior studies have also found that activation of a negative stereotype about a group or stereotype threat, e.g., asking test-takers to indicate their ethnicity before taking a test, can lead to deteriorated performance of the stereotyped group. Here, we describe two studies in which we investigated the gender gap on the FCI and CSEM. In the first study, we investigated whether asking students to indicate their gender immediately before taking hte CSEM increased the gender gap compared to students who were not asked for this information. In the second study, conducted with over 1100 introductory physics students, we investigated the prevalence of the belief that men generally perform better in physics than women and the extent to which this belief is correlated with the performance of both the female and male students on the FCI.

The doped silicon regions (tubs) in PWFDSOI MOSFET cause significant reduction in OFF current by reducing the number of carriers contributing to the OFF current. The emphasis of the simulation and device physics study on PWFDSOI MOSFET presented in this paper is on the scalability of the device to 10 nm gate length and its related information. A high ION /IOFF ratio of 7.6 x 10^5 and subthreshold swing of 87 mV/decade were achieved in 10 nm gate length PWFDSOI MOSFET. The study was performed on devices with unstrained silicon channel.

Ultrawide-angle electromagnetic wave absorbers with excellent mechanical properties are required in many diverse applications such as sensing, and stealth technologies. Here, a novel 3D reconfigurable metamaterial absorber (MMA) consisting of honeycomb and VO2 films is proposed. The proposed MMA exhibits a strong absorptivity above 90\% in the widest incident angle up to $87^\circ$ for TM- and TE- polarized oblique incidences for THz wave propagating in yoz-plane. According to simulation results, under normal incidence, when VO2 films are in the insulating state, the proposed absorber exhibits high absorptivity in the frequency band of 1-4 THz. By increasing the temperature of the whole structure, the structural transformation of VO2 occurs and turns into the metallic phase. We have shown that under oblique incidence, the ohmic losses of VO2 films especially those parallel to the direction of the incident electric field are the most important absorption principles of the proposed MMA. Furthermore, to understand the physical mechanism of absorption, the induced electric field as well as the power loss density of the proposed structure are investigated. In addition, it is shown that the presented VO2 based honeycomb absorber retains its full-coverage incident angle characteristics for TM-polarized incidences propagating in the xoz-plane. Due to the ultra wide-angle absorption (angular stability) and mechanical performance, it is expected that the presented MMA may find potential applications, such as camouflage technologies, electromagnetic interference, imaging, and sensing. To the best knowledge of authors, the proposed MMA configuration exhibits the absorptivity in the widest incident angle ever reported.

Original GLM (Gel'fand-Levitan-Marchenko) theory is for scattering potential recovery of Schr\"odinger equation. In this paper, we formulate the GLM impedance solution of oblique incidence for simultaneous inversion of velocity and density including boundary jumps based on acoustic wave equation. In addition to the use of reflection amplitude, traveltime information of reflection arrivals is also utilized for inversion based on the focusing principle. Numerical tests demonstrate the recovery of velocity and density, verified the validity of the theory and method. The theory of Schr\"odinger impedance inverse-scattering studied in this paper is closely related to the direct envelope inversion.

Quantitative phase microscopy (QPM) is a label-free technique that enables to monitor morphological changes at subcellular level. The performance of the QPM system in terms of spatial sensitivity and resolution depends on the coherence properties of the light source and the numerical aperture (NA) of objective lenses. Here, we propose high space-bandwidth QPM using partially spatially coherent optical coherence microscopy (PSC-OCM) assisted with deep neural network. The PSC source synthesized to improve the spatial sensitivity of the reconstructed phase map from the interferometric images. Further, compatible generative adversarial network (GAN) is used and trained with paired low-resolution (LR) and high-resolution (HR) datasets acquired from PSC-OCM system. The training of the network is performed on two different types of samples i.e. mostly homogenous human red blood cells (RBC) and on highly heterogenous macrophages. The performance is evaluated by predicting the HR images from the datasets captured with low NA lens and compared with the actual HR phase images. An improvement of 9 times in space-bandwidth product is demonstrated for both RBC and macrophages datasets. We believe that the PSC-OCM+GAN approach would be applicable in single-shot label free tissue imaging, disease classification and other high-resolution tomography applications by utilizing the longitudinal spatial coherence properties of the light source.

Most capacitors of practical use deviate from the assumption of a constant capacitance. They exhibit memory and are often described by a time-varying capacitance. It is shown that a direct implementation of the classical relation, $Q\left(t\right)=CV\left(t\right)$, that relates the charge, $Q\left(t\right)$, with the constant capacitance, $C$, and the voltage, $V\left(t\right)$, is not applicable when the capacitance is time-varying. The resulting equivalent circuit that emerges from the substitution of, $C$, by, $C\left(t\right)$, is found to be inconsistent. Since, $C\left(t\right)$, leads to a time-variant system, the current, $\dot{Q}$, that is obtained from the product rule of the differentiation is not valid either. The search for a solution to this problem led to the expression for the charge, that is given by the convolution of the time-varying capacitance with the first-order derivative of the voltage, as, $Q\left(t\right)=C\left(t\right)\ast\dot{V}\left(t\right)$. Coincidentally, this equation also corresponds to the charge-voltage relation for a fractional-capacitor which is probably \textit{first} reported in this Letter.

In recent years, the first author has developed three successful numerical methods to solve the 1D radiative transport equation yielding highly precise benchmarks. The second author has shown a keen interest in novel solution methodologies and an ability for their implementation. Here, we combine talents to generate yet another high precision solution, the Matrix Riccati Equation Method (MREM). MREM features the solution to two of the four matrix Riccati ODEs that arise from the interaction principle of particle transport. Through interaction coefficients, the interaction principle describes how particles reflect from- and transmit through- a single slab. On combination with Taylor series and doubling, a high quality numerical benchmark, to nearly seven places, is established.

Despite the negative stereotypes still overshadowing community colleges, scores of freshmen nationwide are deliberately beginning their college careers at these institutions, and the numbers are increasing more than twice as fast as those of four-year schools. Approximately 300,000 of these students take introductory astronomy each year as the last formal exposure to science most of them will ever have, and at least one-third of these students do so at a community or two-year college. The importance of investing in and devoting resources and training to serve this population - everyone, demographically speaking - cannot be overstated. Yet the overwhelming majority of those who do serve this population are lacking in both areas. The community colleges' heavy emphasis on teaching and student success creates both challenges and opportunities that educators must meet head-on using a variety of methods and innovative strategies, teamwork and faculty support systems, and clever workarounds. Here, we introduce both the student and faculty populations, examine some characteristics of both populations, and offer some advice for those looking to teach introductory astronomy at a community college.

Despite widespread interest, ultrathin and highly flexible light-emitting devices that can be seamlessly integrated and used for flexible displays, wearables, and as bioimplants remain elusive. Organic light-emitting diodes (OLEDs) with $\mu$m-scale thickness and exceptional flexibility have been demonstrated but show insufficient stability in air and moist environments due to a lack of suitable encapsulation barriers. Here, we demonstrate an efficient and stable OLED with a total thickness of $\approx$12 $\mu$m that can be fully immersed in water or cell nutrient media for weeks without suffering substantial degradation. The active layers of the device are embedded between conformal barriers formed by alternating layers of parylene-C and metal oxides that are deposited through a low temperature chemical vapour process. These barriers also confer stability of the OLED to repeated bending and to extensive postprocessing, e.g. via reactive gas plasmas, organic solvents, and photolithography. This unprecedented robustness opens up a wide range of novel possibilities for ultrathin OLEDs.

A milestone revision of the International System of Units (SI) was made at the 26th General Conference on Weights and Measures that four of the seven SI base units, i.e. kilogram, ampere, kelvin, and mole, are redefined by fundamental physical constants of nature. The SI base unit founding the electrical measurement activities, i.e. ampere, is defined by fixing the numerical value of the elementary charge to $e=1.602\,176\,634\times10^{-19}$C. For electrical measurement, several major adjustments, mostly positive, are involved in this SI revision. In this paper, the main impacts of the new SI for electrical measurement activities are surveyed under the new framework.

Our investigation of 353 faculty-produced multiple-choice Think-Pair-Share questions leads to key insights into faculty members' ideas about the discipline representations and intellectual tasks that could engage learners on key topics in physics and astronomy. The results of this work illustrate that, for many topics, there is a lack of variety in the representations featured, intellectual tasks posed, and levels of complexity fostered by the questions faculty develop. These efforts motivated and informed the development of two frameworks: (1) a curriculum characterization framework that allows us to systematically code active learning strategies in terms of the discipline representations, intellectual tasks, and reasoning complexity that an activity offers the learner; and (2) a curriculum development framework that guides the development of activities deliberately focused on increasing learners' discipline fluency. We analyze the faculty-produced Think-Pair-Share questions with our curriculum characterization framework, then apply our curriculum development framework to generate (1) Fluency-Inspiring Questions, a more pedagogically powerful extension of a well-established instructional strategy, and (2) Student Representation Tasks, a brand new type of instructional activity in astronomy that shifts the responsibility for generating appropriate representations onto the learners. We explicitly unpack and provide examples of Fluency-Inspiring Questions and Student Representation Tasks, detailing their usage of Pedagogical Discipline Representations coupled with novel question and activity formats.

Coherent laser beams in the 3 to 20 {\mu}m region of the spectrum are most applicable for chemical sensing by addressing the strongest vibrational absorption resonances of the media. Broadband frequency combs in this spectral range are of special interest since they can be used as a powerful tool for molecular spectroscopy offering dramatic gains in speed, sensitivity, precision, and massive parallelism of data collection. Here we show that a frequency comb realized through subharmonic generation in an optical parametric oscillator (OPO) based on orientation-patterned gallium phosphide (OP-GaP) pumped by a Kerr-lens mode-locked 2.35-{\mu}m laser can reach a continuous wavelength span of 3-12 {\mu}m, thus covering most of the molecular 'signature' region. The key to achieving such a broad spectrum is to use a low-dispersion cavity entailing all gold-coated mirrors, minimally dispersive and optically thin intracavity elements, and a specially designed pump injector. The system features a smooth ultra-broadband spectral output that is phase coherent to the pump laser comb, 245-mW output power with high (>20%) optical conversion efficiency, and a possibility to reach close to unity conversion from a mode-locked drive, thanks to the non-dissipative downconversion processes and photon recycling.

Brain network is remarkably cost-efficient while the fundamental physical mechanisms underlying its economical optimization in network structure and dynamics are not clear. Here we study intricate cost-efficient interplay between structure and dynamics in biologically plausible spatial modular neuronal network models. We find that critical avalanche states from excitation-inhibition balance, under modular network topology with less wiring cost, can also achieve less costs in firing, but with strongly enhanced response sensitivity to stimuli. We derived mean-field equations that govern the macroscopic network dynamics through a novel approximate theory. The mechanism of low firing cost and stronger response in the form of critical avalanche is explained as a proximity to a Hopf bifurcation of the modules when increasing their connection density. Our work reveals the generic mechanism underlying the cost-efficient modular organization and critical dynamics widely observed in neural systems, providing insights to brain-inspired efficient computational designs.

A combined density and first-order reduced-density-matrix (1RDM) functional method is proposed for the calculation of potential energy curves (PECs) of molecular multibond dissociation. Its 1RDM functional part, a pair density functional, efficiently approximates the ab initio pair density of the complete active space self-consistent-field (CASSCF) method. The corresponding approximate on top pair density {\Pi} is employed to correct for double counting a correlation functional of density functional theory (DFT). The proposed ELS-DM{\Pi}DFT method with the extended L\"owdin-Shull (ELS) 1RDM functional with dispersion and multibond (DM) corrections augmented with the {\Pi}DFT functional closely reproduces PECs of multibond dissociation in the paradigmatic N_2 , H_2O, and H_2CO molecules calculated with the recently proposed CAS{\Pi}DFT (CASSCF augmented with a {\Pi} based scaled DFT correlation correction) method. Furthermore, with the additional M-correction, ELS-DM{\Pi}DFT+M reproduces well the benchmark PEC of the N_2 molecule by Lie and Clementi.

The ExB electron drift instability, present in many plasma devices, is an important agent in cross-field particle transport. In presence of a resulting low frequency electrostatic wave, the motion of a charged particle becomes chaotic and generates a stochastic web in phase space. We define a scaling exponent to characterise transport in phase space and we show that the transport is anomalous, of super-diffusive type. Given the values of the model parameters, the trajectories stick to different kinds of islands in phase space, and their different sticking time power-law statistics generate successive regimes of the super-diffusive transport.

Steady two-dimensional Rayleigh--B\'enard convection between stress-free isothermal boundaries is studied via numerical computations. We explore properties of steady convective rolls with aspect ratios $\pi/5\le\Gamma\le4\pi$, where $\Gamma$ is the width-to-height ratio for a pair of counter-rotating rolls, over eight orders of magnitude in the Rayleigh number, $10^3\le Ra\le10^{11}$, and four orders of magnitude in the Prandtl number, $10^{-2}\le Pr\le10^2$. At large $Ra$, where steady rolls are typically unstable, the computed rolls display $Ra \rightarrow \infty$ asymptotic scaling. In the asymptotic regime, the Nusselt number $Nu$ that measures heat transport scales like $Ra^{1/3}$ uniformly in $Pr$. The prefactor of this asymptotic scaling depends on $\Gamma$ and is largest at $\Gamma \approx 1.9$. The Reynolds number $Re$ for large-$Ra$ rolls scales like $Pr^{-1} Ra^{2/3}$ with a prefactor that is largest at $\Gamma \approx 4.5$. All of these large-$Ra$ features agree quantitatively with the semi-analytical asymptotic solutions constructed by Chini & Cox (2009). Convergence of $Nu$ and $Re$ to their asymptotic scalings occurs more slowly when $Pr$ is larger and when $\Gamma$ is smaller.

We analytically and numerically study the temporal intensity pattern emerging from the linear or nonlinear evolutions of a single or double phase jump in an optical fiber. The results are interpreted in terms of interferences of the well-known diffractive patterns of a straight edge, strip and slit and a complete analytical framework is provided in terms of Fresnel integrals for the case of purely dispersive evolution. When Kerr nonlinearity affects the propagation, various coherent nonlinear structures emerge according to the regime of dispersion.

In this study, the impact of non-inertial effects, caused by rotational motion, on the cylindrical perfect cloak is simulated. Also, the interactions between plane waves, Gaussian sine, and Gaussian pulse are investigated. it is shown that non-inertial perfect cloak could be detectable with the Sagnac and magnetoelectric effects.at low frequency of gyration, the distortion of waveform pattern is humble and negligible, however when the rotational frequency increases, the pattern distortion becomes huge and wavelets are formed and their intensity grows up. the scattering pattern can be influenced by the direction of rotation, thus, the direction of rotation could be identified with the scattering pattern analysis. Also, a method for measuring rotational velocity can be prepared concerning the electric field phase retardation. the simulation is computed using the FDTD methods by transforming the Maxwell's equations from non-inertial frameworks to the lab framework.

Spherical gaseous time projection chamber detectors, known also as spherical proportional counters, are widely used today for the search of rare phenomena such as weakly interacting massive particles. In principle such a detector exhibits a number of essential features for the search of neutrinoless double beta decay ($\beta\beta0\nu$). A ton scale experiment using a spherical gaseous time projection chamber could cover a region of parameter space relevant for the inverted mass hierarchy in just a few years of data taking. In this context, the first point to be addressed, and the major goal of the R2D2 R\&D effort, is the energy resolution. The first results of the prototype, filled with argon at pressures varying from 0.2 to 1.1 bar, yielded an energy resolution as good as 1.1\% FWHM for 5.3~MeV $\alpha$ tracks having ranges from 3 to 15~cm. This is a milestone that paves the way for further studies with xenon gas, and the possible use of this technology for $\beta\beta0\nu$ searches.

We show that turbulent dynamics that arise in simulations of the three-dimensional Navier--Stokes equations in a triply-periodic domain under sinusoidal forcing can be described as transient visits to the neighborhoods of unstable time-periodic solutions. Based on this description, we reduce the system with more than $10^5$ degrees of freedom to an 18-node Markov chain where each node corresponds to the neighborhood of a periodic orbit. The model accurately reproduces long-term averages of the system's observables as weighted sums over the periodic orbits.

We describe the Hybrid seeding, a standalone pattern recognition algorithm aiming at finding charged particle trajectories for the LHCb upgrade. A significant improvement to the charged particle reconstruction efficiency is accomplished by exploiting the knowledge of the LHCb magnetic field and the position of energy deposits in the scintillating fibre tracker detector. Moreover, we achieve a low fake rate and a small contribution to the overall timing budget of the LHCb real-time data processing.

Indirect imaging problems in biomedical optics generally require repeated evaluation of forward models of radiative transport, for which Monte Carlo is accurate yet computationally costly. We develop a novel approach to reduce this bottleneck which has significant implications for quantitative tomographic imaging in a variety of medical and industrial applications. Using Monte Carlo we compute a fully stochastic gradient of an objective function for a given imaging problem. Leveraging techniques from the machine learning community we then adaptively control the accuracy of this gradient throughout the iterative inversion scheme, in order to substantially reduce computational resources at each step. For example problems of Quantitative Photoacoustic Tomography and Ultrasound Modulated Optical Tomography, we demonstrate that solutions are attainable using a total computational expense that is comparable to (or less than) that which is required for a single high accuracy forward run of the same Monte Carlo model. This approach demonstrates significant computational savings when approaching the full non-linear inverse problem of optical property estimation using stochastic methods.

The averaged absorbed power density (APD) and temperature rise in body models with nonplanar surfaces were computed for electromagnetic exposure above 6 GHz. Different calculation schemes for the averaged APD were investigated. Additionally, a novel compensation method for correcting the heat convection rate on the air/skin interface in voxel human models was proposed and validated. The compensation method can be easily incorporated into bioheat calculations and does not require information regarding the normal direction of the boundary voxels, in contrast to a previously proposed method. The APD and temperature rise were evaluated using models of a two-dimensional cylinder and a three-dimensional partial forearm. The heating factor, which was defined as the ratio of the temperature rise to the APD, was calculated using different APD averaging schemes. Our computational results revealed different frequency and curvature dependences. For body models with curvature radii of >30 mm and at frequencies of >20 GHz, the differences in the heating factors among the APD schemes were small.

We derive the equations of motion for the dynamics of a porous media filled with an incompressible fluid. We use a variational approach with a Lagrangian written as the sum of terms representing the kinetic and potential energy of the elastic matrix, and the kinetic energy of the fluid, coupled through the constraint of incompressibility. As an illustration of the method, the equations of motion for both the elastic matrix and the fluid are derived in the spatial (Eulerian) frame. Such an approach is of relevance e.g. for biological problems, such as sponges in water, where the elastic porous media is highly flexible and the motion of the fluid has a 'primary' role in the motion of the whole system. We then analyze the linearized equations of motion describing the propagation of waves through the media. In particular, we derive the propagation of S-waves and P-waves in an isotropic media. We also analyze the stability criteria for the wave equations and show that they are equivalent to the physicality conditions of the elastic matrix. Finally, we show that the celebrated Biot's equations for waves in porous media are obtained for certain values of parameters in our models.

Many physical systems display quantized energy states. In optics, interacting resonant cavities show a transmission spectrum with split eigenfrequencies, similar to the split energy levels that result from interacting states in bonded multi-atomic, i.e. molecular, systems. Here, we study the nonlinear dynamics of photonic diatomic molecules in linearly coupled microresonators and demonstrate that the system supports the formation of self-enforcing solitary waves when a laser is tuned across a split energy level. The output corresponds to a frequency comb (microcomb) whose characteristics in terms of power spectral distribution are unattainable in single-mode (atomic) systems. Photonic molecule microcombs are coherent, reproducible, and reach high conversion efficiency and spectral flatness whilst operated with a laser power of a few milliwatts. These properties can favor the heterogeneous integration of microcombs with semiconductor laser technology and facilitate applications in optical communications, spectroscopy and astronomy.

Non-Hermitian degeneracies with singularities, called exceptional points (EPs), incorporate unconventional functionalities into photonic devices. However, the radiative response under the EP degeneracy has yet to be experimentally elaborated due to both the limited controllability of pumping and the lifting of degeneracy by carrier-induced mode detuning. Here, we report the spontaneous emission of a second-order EP with two electrically pumped photonic crystal lasers. Systematically tuned and independent current injection to our active heterostructure nanocavities enables us to demonstrate the clear EP phase transition of their spontaneous emission, accompanied with the spectral coalescence of coupled modes and reversed pump dependence of the intensity. Furthermore, we find experimentally and confirm theoretically the peculiar squared Lorentzian emission spectrum very near the exact EP, which indicates the four-fold enhancement of the photonic local density of states induced purely by the degeneracy. Our results open a new pathway to engineer the light-matter interaction with optical non-Hermiticity.

We report on a novel detection system for collinear laser spectroscopy which provides an almost $4\pi$ solid angle for fluorescence photon detection by employing curved surface mirrors. Additional parabolic angular filters offer passive stray light suppression and can be configured to match the experimental conditions. The mirror surfaces have an excellent reflectivity over a broad band of wavelengths in the optical spectrum and can be substituted to expand the wavelength acceptance range even further. Experiments with this system were performed at two collinear laser spectroscopy setups, including the laser spectroscopic investigation of $^{36}$Ca using rates of 25/s at NSCL, MSU.

Polycrystalline PbSe for mid-wave IR (MWIR) photodetector is an attractive material option due to high operating/ambient temperature operation and relatively easy and cheap fabrication process, making it candidate for low-power and small footprint applications such as internet-of-thing (IoT) sensors and deployment on mobile platforms due to reduced/removed active cooling requirements. However, there are many material challenges that reduce the detectivity of these detectors. In this work, we demonstrate that it is possible to improve upon this metric by externally modulating the lifetime of conducting carriers by application of a back-gate voltage that can control the recombination rate of generated carrier. We first describe the physics of $PbSe$ detectors, the mechanisms underlying carrier transport, and long observed lifetimes of conducting carriers. We then discuss the voltage control of these inverted channels using a back-plane gate resulting in modulation of the lifetime of these carriers. This voltage control represents and extrinsic "knob" through which it may be possible to open a pathway for design of high performance IR photodetectors, as shown in this work.

JUNO is a multi-purpose neutrino experiment currently under construction in Jiangmen, China. It is primary aiming to determine the neutrino mass ordering. Moreover, its 20 kt target mass makes it an ideal detector to study neutrinos from various sources, including nuclear reactors, the Earth and its atmosphere, the Sun, and even supernovae. Due to the small cross section of neutrino interactions, the event rate of neutrino experiments is limited. In order to maximize the signal-to noise ratio, it is extremely important to control the background levels. In this paper we discuss the potential of particle identification in a large liquid scintillator detector like JUNO. We discuss the underlying principles of particle identification and its application in the experiment. In order to investigate the potential of event discrimination, several event pairings are analysed, i.e. alpha/beta?, e/p?, e+/e-, and e/gamma. We compare the discrimination performance of advanced analytical techniques based on neural networks and on the topological event reconstruction keeping the standard Gatti filter as a reference. We use the Monte Carlo samples generated in the physically motivated energy intervals. We study the dependence of our cuts on energy, radial position, PMT time resolution, and dark noise. The results show an excellent performance for alpha/beta? and e/p? with the Gatti method and the neural network. Furthermore, e+/e- and e/gamma can partly be distinguished by means of neural network and topological reconstruction on a statistical basis. Especially in the latter case, the topological method proved very successful.

Two independent beam stoppers have been developed for improving the beam separation of the gas-filled recoil ion separator GARIS-II. Performance evaluation of these supplemental beam stoppers was performed by using the 208Pb (18O,3n)223Th reaction. A160-fold enhancement of the signal-to-noise ratio at the GARIS-II focal plane was observed.

Prior research shows that public opinion on climate politics sorts along partisan lines. However, they leave open the question of whether climate politics and other politically salient issues exhibit tendencies for issue alignment, which the political polarization literature identifies as among the most deleterious aspects of polarization. Using a network approach and social media data from the Twitter platform, we study polarization of public opinion toward climate politics and ten other politically salient topics during the 2019 Finnish elections as the emergence of opposing groups in a public forum. We find that while climate politics is not particularly polarized compared to the other topics, it is subject to partisan sorting and issue alignment within the universalist-communitarian dimension of European politics that arose following the growth of right-wing populism. Notably, climate politics is consistently aligned with the immigration issue, and temporal trends indicate that this phenomenon will likely persist.

Single-photon emitting devices have been identified as an important building block for applications in quantum information and quantum communication. They allow to transduce and collect quantum information over a long distance via photons as so called flying qubits. In addition, substrates like silicon carbide provides an excellent material platform for electronic devices. In this work we combine these two features and show that one can drive single photon emitters within a silicon carbide p-i-n-diode. To achieve this, we specifically designed a lateral oriented diode. We find a variety of new color centers emitting non-classical lights in VIS and NIR range. One type of emitter can be electrically excited, demonstrating that silicon carbide can act as an ideal platform for electrically controllable single photon sources.

Geomagnetic activity is often described using summary indices to summarize the likelihood of space weather impacts, as well as when parameterizing space weather models. The geomagnetic index $\text{K}_\text{p}$ in particular, is widely used for these purposes. Current state-of-the-art forecast models provide deterministic $\text{K}_\text{p}$ predictions using a variety of methods -- including empirically-derived functions, physics-based models, and neural networks -- but do not provide uncertainty estimates associated with the forecast. This paper provides a sample methodology to generate a 3-hour-ahead $\text{K}_\text{p}$ prediction with uncertainty bounds and from this provide a probabilistic geomagnetic storm forecast. Specifically, we have used a two-layered architecture to separately predict storm ($\text{K}_\text{p}\geq 5^-$) and non-storm cases. As solar wind-driven models are limited in their ability to predict the onset of transient-driven activity we also introduce a model variant using solar X-ray flux to assess whether simple models including proxies for solar activity can improve the predictions of geomagnetic storm activity with lead times longer than the L1-to-Earth propagation time. By comparing the performance of these models we show that including operationally-available information about solar irradiance enhances the ability of predictive models to capture the onset of geomagnetic storms and that this can be achieved while also enabling probabilistic forecasts.

In material testing applications, Computed Tomography is a well established imaging technique that allows the recovery of the attenuation map of an object. Conventional modalities exploit only primary radiation and although in the energy ranges used in industrial applications Compton scatter radiation is significant, it is removed from the measured data. On the contrary, Compton Scattering Tomography not only accounts for the Compton effect but also uses it to image material electronic density. Despite its promising applications, some aspects of Compton scattering tomography have not been studied so far and, since they are necessary for the design of a operational system, they need to be addressed. In this paper we analyze the effect of some physical influences regarding real detectors for the Circular Compton Scattering tomography, a system recently introduced by the authors. This is accomplished through the formulation of a new weighted Radon transform. In addition, we propose to adapt the acquired data with pre-processing steps so that they are suitable for reconstruction with a filtered back-projection type reconstruction algorithm, and thus, properly deal with missing data of real measurements. Finally, we introduce a bi-imaging configuration that allows recovering simultaneously the electronic density map of the object as well as its attenuation map.

In this work, we theoretically and experimentally investigate the working principle and non-volatile memory (NVM) functionality of 2D {\alpha}-In2Se3 based ferroelectric-semiconductor-metal-junction (FeSMJ). First, we analyze the semiconducting and ferroelectric properties of {\alpha}-In2Se3 van-der-Waals (vdW) stack via experimental characterization and first-principle simulations. Then, we develop a FeSMJ device simulation framework by self-consistently solving Landau-Ginzburg-Devonshire (LGD) equation, Poisson's equation, and charge-transport equations. Based on the extracted FeS parameters, our simulation results show good agreement with the experimental characteristics of our fabricated {\alpha}-In2Se3 based FeSMJ. Our analysis suggests that the vdW gap between the metal and FeS plays a key role to provide FeS polarization-dependent modulation of Schottky barrier heights. Further, we show that the thickness scaling of FeS leads to a reduction in read/write voltage and an increase in distinguishability. Array-level analysis of FeSMJ NVM suggests a 5.47x increase in sense margin, 18.18x reduction in area and lower read-write power with respect to Fe insulator tunnel junction (FTJ).

Using the failure forecast method we describe a first assessment of failure time on present-day unrest signals at Campi Flegrei caldera (Italy) based on the horizontal deformation data collected in [2011, 2020] at eleven GPS stations.

We present a self-consistent approach for computing the correlated quasiparticle spectrum of charged excitations in iterative $\mathcal{O}[N^5]$ computational time. This is based on the auxiliary second-order Green's function approach [O. Backhouse \textit{et al.}, JCTC (2020)], in which a self-consistent effective Hamiltonian is constructed by systematically renormalizing the dynamical effects of the self-energy at second-order perturbation theory. From extensive benchmarking across the W4-11 molecular test set, we show that the iterative renormalization and truncation of the effective dynamical resolution arising from the $2h1p$ and $1h2p$ spaces can substantially improve the quality of the resulting ionization potential and electron affinity predictions compared to benchmark values. The resulting method is shown to be superior in accuracy to similarly scaling quantum chemical methods for charged excitations in EOM-CC2 and ADC(2), across this test set, while the self-consistency also removes the dependence on the underlying mean-field reference. The approach also allows for single-shot computation of the entire quasiparticle spectrum, which is applied to the benzoquinone molecule and demonstrates the reduction in the single-particle gap due to the correlated physics, and gives direct access to the localization of the Dyson orbitals.

We present a set of self-consistent cross sections for electron transport in gaseous tetrahydrofuran (THF), that refines the set published in our previous study [J. de Urquijo et al., J. Chem. Phys. 151, 054309 (2019)] by proposing modifications to the quasielastic momentum transfer, neutral dissociation, ionisation and electron attachment cross sections. These adjustments are made through the analysis of pulsed-Townsend swarm transport coefficients, for electron transport in pure THF and in mixtures of THF with argon. To automate this analysis, we employ a neural network model that is trained to solve this inverse swarm problem for realistic cross sections from the LXCat project. The accuracy, completeness and self-consistency of the proposed refined THF cross section set is assessed by comparing the analysed swarm transport coefficient measurements to those simulated via the numerical solution of Boltzmann's equation.

Diseases and other contagion phenomena in nature and society can interact asymmetrically, such that one can benefit from the other, which in turn impairs the first, in analogy with predator-prey systems. Here, we consider two models for interacting disease-like dynamics with asymmetric interactions and different associated time scales. Using rate equations for homogeneously mixed populations, we show that the stationary prevalences and phase diagrams of each model behave differently with respect to variations of the relative time scales. We also characterize in detail the regime where transient oscillations are observed, a pattern that is inherent to asymmetrical interactions but often ignored in the literature. Our results contribute to a better understanding of disease dynamics in particular, and interacting processes in general, and could provide interesting insights for real-world applications, most notably, the interplay between the dynamics of fact-checked and fake news.

Gaussian process regression (GPR) is a useful technique to predict composition--property relationships in glasses as the method inherently provides the standard deviation of the predictions. However, the technique remains restricted to small datasets due to the substantial computational cost associated with it. Here, using a scalable GPR algorithm, namely, kernel interpolation for scalable structured Gaussian processes (KISS-GP) along with massively scalable GP (MSGP), we develop composition--property models for inorganic glasses based on a large dataset with more than 100,000 glass compositions, 37 components, and nine important properties, namely, density, Young's, shear, and bulk moduli, thermal expansion coefficient, Vickers' hardness, refractive index, glass transition temperature, and liquidus temperature. Finally, to accelerate glass design, the models developed here are shared publicly as part of a package, namely, Python for Glass Genomics (PyGGi).

Achieving ultrafast all-optical switching in a silicon waveguide geometry is a key milestone on the way to an integrated platform capable of handling the increasing demands for higher speed and higher capacity for information transfer. Given the weak electro-optic and thermo-optic effects in silicon, there has been intense interest in hybrid structures in which that switching could be accomplished by integrating another material into the waveguide, including the phase-changing material, vanadium dioxide (VO2). It has long been known that the phase transition in VO2 can be triggered by ultrafast laser pulses, and that pump-laser fluence is a critical parameter governing the recovery time of thin films irradiated by femtosecond laser pulses near 800 nm. However, thin-film experiments are not a priori reliable guides to using VO2 for all-optical switching in on-chip silicon photonics because of the large changes in VO2 optical constants in the telecommunications band, the requirement of low insertion loss, and the limits on switching energy permissible in integrated photonic systems. Here we report the first measurements to show that the reversible, ultrafast photo-induced phase transition in VO2 can be harnessed to achieve sub-picosecond switching when small VO2 volumes are integrated in a silicon waveguide as a modulating element. Switching energies above threshold are of order 600 fJ/switch. These results suggest that VO2 can now be pursued as a strong candidate for all-optical switching with sub-picosecond on-off times.

Convolutional neural networks (CNN) are utilized to encode the relation between initial configurations of obstacles and three fundamental quantities in porous media: porosity ($\varphi$), permeability $k$, and tortuosity ($T$). The two-dimensional systems with obstacles are considered. The fluid flow through a porous medium is simulated with the lattice Boltzmann method. It is demonstrated that the CNNs are able to predict the porosity, permeability, and tortuosity with good accuracy. With the usage of the CNN models, the relation between $T$ and $\varphi$ has been reproduced and compared with the empirical estimate. The analysis has been performed for the systems with $\varphi \in (0.37,0.99)$ which covers five orders of magnitude span for permeability $k \in (0.78, 2.1\times 10^5)$ and tortuosity $T \in (1.03,2.74)$.

The ability to understand and engineer molecular structures relies on having accurate descriptions of the energy as a function of atomic coordinates. Here we outline a new paradigm for deriving energy functions of hyperdimensional molecular systems, which involves generating data for low-dimensional systems in virtual reality (VR) to then efficiently train atomic neural networks (ANNs). This generates high quality data for specific areas of interest within the hyperdimensional space that characterizes a molecule's potential energy surface (PES). We demonstrate the utility of this approach by gathering data within VR to train ANNs on chemical reactions involving fewer than 8 heavy atoms. This strategy enables us to predict the energies of much higher-dimensional systems, e.g. containing nearly 100 atoms. Training on datasets containing only 15K geometries, this approach generates mean absolute errors around 2 kcal/mol. This represents one of the first times that an ANN-PES for a large reactive radical has been generated using such a small dataset. Our results suggest VR enables the intelligent curation of high-quality data, which accelerates the learning process.

In turbulent wall sheared thermal convection, there are three different flow regimes, depending on the relative relevance of thermal forcing and wall shear. In this paper we report the results of direct numerical simulations of such sheared Rayleigh-B\'enard convection, at fixed Rayleigh number $Ra=10^6$, varying the wall Reynolds number in the range $0 \leq Re_w \leq 4000$ and Prandtl number $0.22 \leq Pr \leq 4.6$, extending our prior work by Blass et al. (2020), where $Pr$ was kept constant at unity and the thermal forcing ($Ra$) varied. We cover a wide span of bulk Richardson numbers $0.014 \leq Ri \leq 100$ and show that the Prandtl number strongly influences the morphology and dynamics of the flow structures. In particular, at fixed $Ra$ and $Re_w$, a high Prandtl number causes stronger momentum transport from the walls and therefore yields a greater impact of the wall shear on the flow structures, resulting in an increased effect of $Re_w$ on the Nusselt number. Furthermore, we analyse the thermal and kinetic boundary layer thicknesses and relate their behaviour to the resulting flow regimes. For the largest shear rates and $Pr$ numbers, we observe the emergence of a Prandtl-von Karman log-layer, signalling the onset of turbulent dynamics in the boundary layer. Finally, our results allow to extend the Grossmann-Lohse theory for heat transport in Rayleigh-B\'enard convection to the sheared case, universally describing $Nu(Ra,Pr,Re_w)$.

Ultrarelativistic electron beam-laser pulse scattering experiments are the workhorse for the investigation of QED and of possible signatures of new physics in the still largely unexplored strong-field regime. However, shot-to-shot fluctuations both of the electron beam and of the laser pulse parameters render it difficult to discern the dynamics of the interaction. Consequently, the possibility of benchmarking theoretical predictions against experimental results, which is essential for validating theoretical models, is severely limited. Here we show that the stochastic nature of quantum emission events provides a unique route to the on-shot diagnostic of the electron beam-laser pulse interaction, therefore paving the way for accurate measurements of strong-field QED effects.

Flow electrode CDI systems (FE-CDI) have recently garnered attention because of their ability to prevent cross contamination, and operate in uninterrupted cycles ad infinitum. Typically, FE-CDI electrodes suffer from low conductivity, which reduces deionization performance. Higher mass loading to combat low conductivity leads to poor rheological properties, which prevent the process from being continuous and scalable. Herein, Ti3C2Tx MXenes were introduced as 1 mg/mL slurry electrodes in an FE-CDI system for the removal and recovery of ammonia from stimulated wastewater. The electrode performance was evaluated by operating the FE-CDI system with a feed solution of 500 mg/L NH4Cl running in batch mode at a constant voltage of 1.2 and -1.2 V in charging and discharging modes respectively. Despite low loading compared to activated carbon solution, Ti3C2Tx flowing electrodes showed markedly improved performance by achieving 60% ion removal efficiency in a saturation time of 115 minutes, and an unprecedented adsorption capacity of 460 mg/g. The system proved to be a green technology by exhibiting satisfactory charge efficiency of 58-70% while operating at a relatively low energy consumption of 0.45 kWh/kg when compared to the current industry standard nitrification-denitrification ammonia stripping process. A 92% regeneration efficiency showed that the electrodes were stable and suitable for long term and scalable usage. The results demonstrate that MXenes hold great potential in improving the FE-CDI process for energy-efficient removal and recovery of ammonium ions from wastewater.

Geometrical Volume-of-Fluid (VoF) methods mainly support structured meshes, and only a small number of contributions in the scientific literature report results with unstructured meshes and three spatial dimensions. Unstructured meshes are traditionally used for handling geometrically complex solution domains that are prevalent when simulating problems of industrial relevance. However, three-dimensional geometrical operations are significantly more complex than their two-dimensional counterparts, which is confirmed by the ratio of publications with three-dimensional results on unstructured meshes to publications with two-dimensional results or support for structured meshes. Additionally, unstructured meshes present challenges in serial and parallel computational efficiency, accuracy, implementation complexity, and robustness. Ongoing research is still very active, focusing on different issues: interface positioning in general polyhedra, estimation of interface normal vectors, advection accuracy, and parallel and serial computational efficiency. This survey tries to give a complete and critical overview of classical, as well as contemporary geometrical VOF methods with concise explanations of the underlying ideas and sub-algorithms, focusing primarily on unstructured meshes and three dimensional calculations. Reviewed methods are listed in historical order and compared in terms of accuracy and computational efficiency.

Solutions to the Stokes equations written in terms of a small number of hydrodynamic image singularities have been a useful tool in theoretical and numerical computations for nearly fifty years. In this article, we extend the catalogue of known solutions by deriving the flow expressions due to a general point torque and point source in the presence of a stationary sphere with either a no-slip or a stress-free (no shear) boundary condition. For an axisymmetric point torque and a no-slip sphere the image system simplifies to a single image point torque, reminiscent of the solution for a point charge outside an equipotential sphere in electrostatics. By symmetry, this also gives a simple representation of the solution due to an axisymmetric point torque inside a rigid spherical shell. In all remaining cases, the solution can be described by a collection of physically intuitive point and line singularities. Our results will be useful for the theoretical modelling of the propulsion of microswimmers and efficient numerical implementation of far-field hydrodynamic interactions in this geometry.

We have previously described RapidBrachyMCTPS, a brachytherapy treatment planning toolkit consisting of a graphical user interface (GUI) and a Geant4-based Monte Carlo (MC) dose calculation engine. This work describes the tools that have recently been added to RapidBrachyMCTPS, such that it now serves as the first stand-alone application for MC-based brachytherapy treatment planning. Notable changes include updated applicator import and positioning, three-plane contouring tools, and updated dose optimization algorithms that, in addition to optimizing dwell position and dwell time, also optimize the rotating shield angles in intensity modulated brachytherapy. The main modules of RapidBrachyMCTPS were validated including DICOM import, applicator import and positioning, contouring, material assignment, source specification, catheter reconstruction, EGSphant generation, interface with the MC code, and dose optimization and analysis tools. Two patient cases were simulated to demonstrate these principles, illustrating the control and flexibility offered by RapidBrachyMCTPS for all steps of the treatment planning pathway. RapidBrachyMCTPS is now a stand-alone application for brachytherapy treatment planning, and offers a user-friendly interface to access powerful MC calculations. It can be used to validate dose distributions from clinical treatment planning systems or model-based dose calculation algorithms, and is also well suited to testing novel combinations of radiation sources and applicators, especially those shielded with high-Z materials.

We investigate laser-induced acoustic wave propagation through smooth and roughened titanium-coated glass substrates. Acoustic waves are generated in a controlled manner via the laser spallation technique. Surface displacements are measured during stress wave loading by alignment of a Michelson-type interferometer. A reflective coverslip panel facilitates capture of surface displacements during loading of as-received smooth and roughened specimens. Through interferometric experiments we extract the substrate stress profile at each laser fluence (energy per area). The shape and amplitude of the substrate stress profile is analyzed at each laser fluence. Peak substrate stress is averaged and compared between smooth specimens with reflective panel and rough specimens with reflective panel. The reflective panel is necessary because the surface roughness of the rough specimens precludes in situ interferometry. Through these experiments we determine that the surface roughness employed has no significant effect on substrate stress propagation and smooth substrates are an appropriate surrogate to determine stress wave loading amplitude of roughened surfaces less than 1.2 {\mu}m average roughness (Ra). No significant difference was observed when comparing the average peak amplitude and loading slope in the stress wave profile for the smooth and rough configurations at each fluence.

In this work we present an algorithm to perform algorithmic differentiation in the context of quantum computing. For the derivative of the arbitrary composite function $f\circ g\circ...\circ h,$ three $n$-qubit states are sufficient, where $n$ refers to the quantum computer precision. Namely, with these 3 $n$-qubit states we construct a set of operation which can be iteratively applied in such a way to calculate the derivative of any composite function. For the sum, $f(x)+g(x)+...+h(x)$ or the product $f(x)\cdot g(x)\cdot...\cdot h(x)$ one needs at least 6 $n$-qubit states, if a re-initialization is implemented. Since the implementation of elementary functions is already possible on quantum computers, the scheme that we propose can be easily applied. Moreover, since some steps (such as the CNOT operator) can (or will be) faster on a quantum computer than on a classical one, the applied procedure may lead in the (near or far) future to quantum algorithmic differentiation being more advantageous than its classical counterpart.

In this work, a classical/quantum correspondence for a pseudo-hermitian system with finite energy levels is proposed and analyzed. We show that the presence of a complex external field can be described by a pseudo-hermitian Hamiltonian if there is a suitable canonical transformation that links it to a real field. We construct a covariant quantization scheme which maps canonically related pseudoclassical theories to unitarily equivalent quantum realizations, such that there is a unique metric-inducing isometry between the distinct Hilbert spaces. In this setting, the pseudo-hermiticity condition for the operators induces an involution which guarantees the reality of the corresponding symbols, even for the complex field case. We assign a physical meaning for the dynamics in the presence of a complex field by constructing a classical correspondence. As an application of our theoretical framework, we propose a damped version of the Rabi problem and determine the configuration of the parameters of the setup for which damping is completely suppressed.

The Late Devonian was a protracted period of low speciation resulting in biodiversity decline, culminating in extinction events near the Devonian-Carboniferous boundary. Recent evidence indicates that the final extinction event may have coincided with a dramatic drop in stratospheric ozone, possibly due to a global temperature rise. Here we study an alternative possible cause for the postulated ozone drop: a nearby supernova explosion that could inflict damage by accelerating cosmic rays that can deliver ionizing radiation for up to $\sim 100$ kyr. We therefore propose that end-Devonian extinction was triggered by one or more supernova explosions at $\sim 20 \ \rm pc$, somewhat beyond the ``kill distance'' that would have precipitated a full mass extinction. Nearby supernovae are likely due to core-collapses of massive stars in clusters in the thin Galactic disk in which the Sun resides. Detecting any of the long-lived radioisotopes \sm146, \u235 or \pu244 in one or more end-Devonian extinction strata would confirm a supernova origin, point to the core-collapse explosion of a massive star, and probe supernova nucleosythesis. Other possible tests of the supernova hypothesis are discussed.

The prisoner's dilemma (PD) is a game-theoretic model studied in a wide array of fields to understand the emergence of cooperation between rational self-interested agents. In this work, we formulate a spatial iterated PD as a discrete-event dynamical system where agents play the game in each time-step and analyse it algebraically using Krohn-Rhodes algebraic automata theory using a computational implementation of the holonomy decomposition of transformation semigroups. In each iteration all players adopt the most profitable strategy in their immediate neighbourhood. Perturbations resetting the strategy of a given player provide additional generating events for the dynamics. Our initial study shows that the algebraic structure, including how natural subsystems comprising permutation groups acting on the spatial distributions of strategies, arise in certain parameter regimes for the pay-off matrix, and are absent for other parameter regimes. Differences in the number of group levels in the holonomy decomposition (an upper bound for Krohn-Rhodes complexity) are revealed as more pools of reversibility appear when the temptation to defect is at an intermediate level. Algebraic structure uncovered by this analysis can be interpreted to shed light on the dynamics of the spatial iterated PD.

Classical turning surfaces of Kohn-Sham potentials, separating classically-allowed regions (CARs) from classically-forbidden regions (CFRs), provide a useful and rigorous approach to understanding many chemical properties of molecules. Here we calculate such surfaces for several paradigmatic solids. Our study of perfect crystals at equilibrium geometries suggests that CFRs are absent in metals, rare in covalent semiconductors, but common in ionic and molecular crystals. A CFR can appear at a monovacancy in a metal. In all materials, CFRs appear or grow as the internuclear distances are uniformly expanded. Calculations with several approximate density functionals and codes confirm these behaviors. A classical picture of conduction suggests that CARs should be connected in metals, and disconnected in wide-gap insulators. This classical picture is confirmed in the limits of extreme uniform compression of the internuclear distances, where all materials become metals without CFRs, and extreme expansion, where all materials become insulators with disconnected and widely-separated CARs around the atoms.

Self assembly is a ubiquitous process in synthetic and biological systems, broadly defined as the spontaneous self-organization of multiple subunits (e.g. macromolecules, particles) into ordered multi-unit structures. The vast majority of equilibrium assembly processes give rise to two ``states'': one consisting of dispersed disassociated subunits, and the other, a bulk-condensed state of unlimited size. This review focuses on the more specialized class of {\it self-limiting assembly}, which describes equilibrium assembly processes resulting in finite-size structures. These systems pose a generic and basic question, how do thermodynamic processes involving non-covalent interactions between identical subunits ``measure'' and select the size of assembled structures? In this review, we begin with an introduction to the basic statistical mechanical framework for assembly thermodynamics, and use this to highlight the key physical ingredients that ensure equilibrium assembly will terminate at finite dimensions. Then, examples of self-limiting assembly systems will be introduced and classified within this framework based on two broad categories: {\it self-closing assemblies} and {\it open-boundary assemblies}. These will include well-known cases -- micellization of amphiphiles and shell/tubule formation of tapered subunits -- as well as less widely known classes of assemblies, such as short-range attractive/long-range repulsive systems and geometrically-frustrated assemblies. For each of these self-limiting mechanisms, we describe the physical mechanisms that select equilibrium assembly size, as well as potential limitations of finite-size selection. Finally, we discuss alternative mechanisms for finite-size assemblies and draw contrasts with the size-control that these can achieve relative to self-limitation in equilibrium, single-species assemblies.

Soliton and breather solutions of the nonlinear Schr\"odinger equation (NLSE) are known to model localized structures in nonlinear dispersive media such as on the water surface. One of the conditions for an accurate propagation of such exact solutions is the proper generation of the exact initial phase-shift profile in the carrier wave, as defined by the NLSE envelope at a specific time or location. Here, we show experimentally the significance of such initial exact phase excitation during the hydrodynamic propagation of localized envelope solitons and breathers, which modulate a plane wave of constant amplitude (finite background). Using the example of stationary black solitons in intermediate water depth and pulsating Peregrine breathers in deep-water, we show how these localized envelopes disintegrate while they evolve over a long propagation distance when the initial phase shift is zero. By setting the envelope phases to zero, the dark solitons will disintegrate into two gray-type solitons and dispersive elements. In the case of the doubly-localized Peregrine breather the maximal amplification is considerably retarded; however locally, the shape of the maximal focused wave measured together with the respective signature phase-shift are almost identical to the exact analytical Peregrine characterization at its maximal compression location. The experiments, conducted in two large-scale shallow-water as well as deep-water wave facilities, are in very good agreement with NLSE simulations for all cases.

A universal characterization of non-Markovianity for any open hybrid quantum systems is presented. This formulation is based on the negativity volume of the generalized Wigner function, which serves as an indicator of the quantum correlations in any composite quantum systems. It is shown, that such defined measure can be utilized for any single or multi-partite quantum system, containing any discrete or continuous variables. To demonstrate its power in revealing non-Markovianity in such quantum systems, we additionally consider a few illustrative examples.

Unconventional Weyl points (WPs), carrying topological charge 2 or higher, possess interesting properties different from ordinary charge-1 WPs, including multiple Fermi arcs that stretch over a large portion of the Brillouin zone. Thus far, such WPs have been observed in chiral materials and acoustic metamaterials, but there has been no clean demonstration in photonics in which the unconventional photonic WPs are separated from trivial bands. We experimentally realize an ideal symmetry-protected photonic charge-2 WP in a three-dimensional topological chiral microwave metamaterial. We use field mapping to directly observe the projected bulk dispersion, as well as the two long surface arcs that form a noncontractible loop wrapping around the surface Brillouin zone. The surface states span a record-wide frequency window of around 22.7% relative bandwidth. We demonstrate that the surface states exhibit a novel topological self-collimation property and are robust against disorder. This work provides an ideal photonic platform for exploring fundamental physics and applications of unconventional WPs.

Curie's principle states that "when effects show certain asymmetry, this asymmetry must be found in the causes that gave rise to them". We demonstrate that symmetry equivariant neural networks uphold Curie's principle and this property can be used to uncover symmetry breaking order parameters necessary to make input and output data symmetrically compatible. We prove these properties mathematically and demonstrate them numerically by training a Euclidean symmetry equivariant neural network to learn symmetry breaking input to deform a square into a rectangle.

The worldwide outbreak of COVID-19 has posed a dire threat to the public. Human mobility has changed in various ways over the course of the pandemic. Despite current studies on common mobility metrics, research specifically on state-to-state mobility is very limited. By leveraging the mobile phone location data from over 100 million anonymous devices, we estimate the population flow between all states in the United States. We first analyze the temporal pattern and spatial differences of between-state flow from January 1, 2020 to May 15, 2020. Then, with repeated measures ANOVA and post-hoc analysis, we discern different time-course patterns of between-state population flow by pandemic severity groups. A further analysis shows moderate to high correlation between the flow reduction and the pandemic severity, the strength of which varies with different policies. This paper is promising in predicting imported cases.

In-situ small- and wide-angle scattering experiments at synchrotrons often result in massive amounts of data within seconds only. Especially during such beamtimes, processing of the acquired data online, so without mentionable delay, is key to obtain feedback on failure or success of the experiment. We thus developed SAXSDOG, a python based environment for real-time azimuthal integration of large-area scattering-images. The software is primarily designed for dedicated data-pipelines: once a scattering image is transferred from the detector onto the storage-unit, it is automatically integrated and pre-evaluated using integral parameters within milliseconds. The control and configuration of the underlying server-based processes is done via a graphical user interface SAXSLEASH, which visualizes the resulting 1D data together with integral classifiers in real time. SAXSDOG further includes a portable 'take-home' version for users that runs on standalone computers, enabling its use in labs or at the preferred workspace.

Quantitative measure of disorder or randomness based on the entropy production characterizes thermodynamical irreversibility, which is relevant to the conventional second law of thermodynamics. Here we report, in a quantum mechanical fashion, the first theoretical prediction and experimental exploration of an information-theoretical bound on the entropy production. Our theoretical model consists of a simplest two-level dissipative system driven by a purely classical field, and under the Markovian dissipation, we find that such an information-theoretical bound, not fully validating quantum relaxation processes, strongly depends on the drive-to-decay ratio and the initial state. Furthermore, we carry out experimental verification of this information-theoretical bound by means of a single spin embedded in an ultracold trapped $^{40}$Ca$^{+}$ ion. Our finding, based on a two-level model, is fundamental to any quantum thermodynamical process and indicates much difference and complexity in quantum thermodynamics with respect to the conventionally classical counterpart.

Recovering a signal from auto-correlations or, equivalently, retrieving the phase linked to a given Fourier modulus, is a wide-spread problem in imaging. This problem has been tackled in a number of experimental situations, from optical microscopy to adaptive astronomy, making use of assumptions based on constraints and prior information about the recovered object. In a similar fashion, deconvolution is another common problem in imaging, in particular within the optical community, allowing high-resolution reconstruction of blurred images. Here we address the mixed problem of performing the auto-correlation inversion while, at the same time, deconvolving its current estimation. To this end, we propose an I-divergence optimization, driving our formalism into a widely used iterative scheme, inspired by Bayesian-based approaches. We demonstrate the method recovering the signal from blurred auto-correlations, further analysing the cases of blurred objects and band-limited Fourier measurements.

In this paper, a susceptible-infected-removed (SIR) model has been used to track the evolution of the spread of the COVID-19 virus in four countries of interest. In particular, the epidemic model, that depends on some basic characteristics, has been applied to model the time evolution of the disease in Italy, India, South Korea and Iran. The economic, social and health consequences of the spread of the virus have been cataclysmic. Hence, it is essential that available mathematical models can be developed and used for the comparison to be made between published data sets and model predictions. The predictions estimated from the SIR model here, can be used in both the qualitative and quantitative analysis of the spread. It gives an insight into the spread of the virus that the published data alone cannot do by updating them and the model on a daily basis. For example, it is possible to detect the early onset of a spike in infections or the development of a second wave using our modeling approach. We considered data from March to June, 2020, when different communities are severely affected. We demonstrate predictions depending on the model's parameters related to the spread of COVID-19 until September 2020. By comparing the published data and model results, we conclude that in this way, it may be possible to better reflect the success or failure of the adequate measures implemented by governments and individuals to mitigate and control the current pandemic.

Light pollution is one of the most rapidly increasing types of environmental degradation. To limit this pollution several effective practices have been defined: shields on lighting fixtures to prevent direct upward light; no over lighting, i.e. avoid using higher lighting levels than strictly needed for the task, constraining illumination to the area where and when it is needed. Nevertheless, even after the best control of the light distribution is reached and when the proper quantity of light is used, upward light emission remains, due to reflections from the lit surfaces and atmospheric scatter. The environmental impact of this "residual light pollution" cannot be neglected and should be limited too. We propose a new way to limit the effects of this residual light pollution on wildlife, human health and stellar visibility. We performed analysis of the spectra of common types of lamps for external use, including the new LEDs. We evaluated their emissions relative to the spectral response functions of human eye photoreceptors, in the photopic, scotopic and melatonin suppressing bands finding that the amount of pollution is strongly dependent on the spectral characteristics of the lamps, with the more environmentally friendly lamps being low pressure sodium, followed by high pressure sodium. Most polluting are the lamps with a strong blue emission, like white LEDs. Migration from the now widely used sodium lamps to white lamps (Metal Halide and LEDs) would produce an increase of pollution in the scotopic and melatonin suppression bands of more than five times the present levels, supposing the same photopic installed flux. This increase will exacerbate known and possible unknown effects of light pollution on human health, environment and on starry sky visibility. We present quantitative criteria to evaluate the lamps based on their spectral emissions and we suggest regulatory limits.

We develop a rigorous theoretical framework for interaction-induced phenomena in the waveguide quantum electrodynamics (QED) driven by mechanical oscillations of the qubits. Specifically, we predict that the simplest set-up of two qubits, harmonically trapped over an optical waveguide, enables the ultrastrong coupling regime of the quantum optomechanical interaction. Moreover, the combination of the inherent open nature of the system and the strong optomechanical coupling leads to emerging parity-time (\PT) symmetry, quite unexpected for a purely quantum system without artificially engineered gain and loss. The $\mathcal{PT}$ phase transition drives long-living subradiant states, observable in the state-of-the-art waveguide QED setups.

We present an efficient and accurate immersed boundary (IB) finite element (FE) solver for numerically solving incompressible Navier--Stokes equations. Particular emphasis is given to internal flows with complex geometries (blood flow in the vasculature system). IB methods are computationally costly for internal flows, mainly due to the large percentage of grid points that lie outside the flow domain. In this study, we apply a local refinement strategy, along with a domain reduction approach in order to reduce the grid that covers the flow domain and increase the percentage of the grid nodes that fall inside the flow domain. The proposed method utilizes an efficient and accurate FE solver with the incremental pressure correction scheme (IPCS), along with the boundary condition enforced IB method to numerically solve the transient, incompressible Navier--Stokes flow equations. We verify the accuracy of the numerical method using the analytical solution for Poiseuille flow in a cylinder. We further examine the accuracy and applicability of the proposed method by considering flow within complex geometries, such as blood flow in aneurysmal vessels and the aorta, flow configurations which would otherwise be extremely difficult to solve by most IB methods. Our method offers high accuracy, as demonstrated by the verification examples, and high efficiency, as demonstrated through the solution of blood flow within complex geometry on an off-the-shelf laptop computer.

Much of the science underpinning the global response to the COVID-19 pandemic lies in the soft matter domain. Coronaviruses are composite particles with a core of nucleic acids complexed to proteins surrounded by a protein-studded lipid bilayer shell. A dominant route for transmission is via air-borne aerosols and droplets. Viral interaction with polymeric body fluids, particularly mucus, and cell membranes control their infectivity, while their interaction with skin and artificial surfaces underpins cleaning and disinfection and the efficacy of masks and other personal protective equipment. The global response to COVID-19 has highlighted gaps in the soft matter knowledge base. We survey these gaps and suggest questions that can (and need to) be tackled, both in response to COVID-19 and to better prepare for future viral pandemics.

In recent years, arrays of atomic ions in a linear RF trap have proven to be a particularly successful platform for quantum simulation. However, a wide range of quantum models and phenomena have, so far, remained beyond the reach of such simulators. In this work we introduce a technique that can substantially extend this reach using an external field gradient along the ion chain and a global, uniform driving field. The technique can be used to generate both static and time-varying synthetic gauge fields in a linear chain of trapped ions, and enables continuous simulation of a variety of coupling geometries and topologies, including periodic boundary conditions and high dimensional Hamiltonians. We describe the technique, derive the corresponding effective Hamiltonian, propose a number of variations, and discuss the possibility of scaling to quantum-advantage sized simulators. Additionally, we suggest several possible implementations and briefly examine two: the Aharonov-Bohm ring and the frustrated triangular ladder.

We unravel the ground state properties and the non-equilibrium quantum dynamics of two bosonic impurities immersed in an one-dimensional fermionic environment by applying a quench of the impurity-medium interaction strength. In the ground state, the impurities and the Fermi sea are phase-separated for strong impurity-medium repulsions while they experience a localization tendency around the trap center for large attractions. We demonstrate the presence of attractive induced interactions mediated by the host for impurity-medium couplings of either sign and analyze the competition between induced and direct interactions. Following a quench to repulsive interactions triggers a breathing motion in both components, with an interaction dependent frequency and amplitude for the impurities, and a dynamical phase-separation between the impurities and their surrounding for strong repulsions. For attractive post-quench couplings a beating pattern owing its existence to the dominant role of induced interactions takes place with both components showing a localization trend around the trap center. In both quench scenarios, attractive induced correlations are manifested between non-interacting impurities and are found to dominate the direct ones only for quenches to attractive couplings.

The problem of data-driven identification of coherent observables of measure-preserving, ergodic dynamical systems is studied using kernel integral operator techniques. An approach is proposed whereby complex-valued observables with approximately cyclical behavior are constructed from a pair eigenfunctions of integral operators built from delay-coordinate mapped data. It is shown that these observables are $\epsilon$-approximate eigenfunctions of the Koopman evolution operator of the system, with a bound $\epsilon$ controlled by the length of the delay-embedding window, the evolution time, and appropriate spectral gap parameters. In particular, $ \epsilon$ can be made arbitrarily small as the embedding window increases so long as the corresponding eigenvalues remain sufficiently isolated in the spectrum of the integral operator. It is also shown that the time-autocorrelation functions of such observables are $\epsilon$-approximate Koopman eigenvalue, exhibiting a well-defined characteristic oscillatory frequency (estimated using the Koopman generator) and a slowly-decaying modulating envelope. The results hold for measure-preserving, ergodic dynamical systems of arbitrary spectral character, including mixing systems with continuous spectrum and no non-constant Koopman eigenfunctions in $L^2$. Numerical examples reveal a coherent observable of the Lorenz 63 system whose autocorrelation function remains above 0.5 in modulus over approximately 10 Lyapunov timescales.

All clocks, classical or quantum, are open non equilibrium irreversible systems subject to the constraints of thermodynamics. Using examples I show that these constraints necessarily limit the performance of clocks and that good clocks require large energy dissipation. For periodic clocks, operating on a limit cycle, this is a consequence of phase diffusion. It is also true for non periodic clocks (for example, radio carbon dating) but due to telegraph noise not to phase diffusion. In this case a key role is played by accurate measurements that decrease entropy, thereby raising the free energy of the clock, and requires access to a low entropy reservoir. In the quantum case, for which thermal noise is replaced by quantum noise (spontaneous emission or tunnelling), measurement plays an essential role for both periodic and non periodic clocks. The paper concludes with a discussion of the Tolman relations and Rovelli's thermal time hypothesis in terms of clock thermodynamics.

The magnetic behavior of bcc iron nanoclusters, with diameters between 2 and 8 nm, is investigated via spin dynamics (SD) simulations coupled to molecular dynamics (MD), using a distance-dependent exchange interaction. Finite-size effects in the total magnetization as well as the influence of the free surface and the surface/core proportion of the nanoclusters are analyzed in detail for a wide temperature range, reaching the Curie temperature. Comparisons with experimental data and theoretical models based on the mean-field Ising model are also presented, including one adapted to small clusters, and another developed to take into account the influence of low coordinated spins at free surfaces. Magnetization results show excellent agreement with experimental measurements for small Fe nanoclusters. Large differences are found with frozen-atom simulations. Finite-size effects on the thermal behavior of the magnetization increase as the size of the clusters is reduced, especially near the Curie temperature, Tc. Analytical approximations to the magnetization as a function of temperature and size are proposed.

Knots and links are fundamental topological objects play a key role in both classical and quantum fluids. In this research, we propose a novel scheme to generate torus vortex knots and links through the reconnections of vortex rings perturbed by Kelvin waves in trapped Bose-Einstein condensates. We observe a new phenomenon in a confined superfluid system in which the transfer of helicity between knots/links and coils can occur in both directions with different pathways. The pathways of topology transition can be controlled through designing specific initial states. The generation of a knot or link can be achieved by setting the parity of the Kelvin wave number. The stability of knots/links can be improved greatly with tunable parameters, including the ideal relative angle and the minimal distance between the initial vortex rings.

We consider the operator $${\cal H} = {\cal H}' -\frac{\partial^2\ }{\partial x_d^2} \quad\text{on}\quad\omega\times\mathbb{R}$$ subject to the Dirichlet or Robin condition, where a domain $\omega\subseteq\mathbb{R}^{d-1}$ is bounded or unbounded. The symbol ${\cal H}'$ stands for a second order self-adjoint differential operator on $\omega$ such that the spectrum of the operator ${\cal H}'$ contains several discrete eigenvalues $\Lambda_{j}$, $j=1,\ldots, m$. These eigenvalues are thresholds in the essential spectrum of the operator ${\cal H}$. We study how these thresholds bifurcate once we add a small localized perturbation $\epsilon{\cal L}(\epsilon)$ to the operator ${\cal H}$, where $\epsilon$ is a small positive parameter and ${\cal L}(\epsilon)$ is an abstract, not necessarily symmetric operator. We show that these thresholds bifurcate into eigenvalues and resonances of the operator ${\cal H}$ in the vicinity of $\Lambda_j$ for sufficiently small $\epsilon$. We prove effective simple conditions determining the existence of these resonances and eigenvalues and find the leading terms of their asymptotic expansions. Our analysis applies to generic non-self-adjoint perturbations and, in particular, to perturbations characterized by the parity-time ($PT$) symmetry. Potential applications of our result embrace a broad class of physical systems governed by dispersive or diffractive effects. We use our findings to develop a scheme for a controllable generation of non-Hermitian optical states with normalizable power and real part of the complex-valued propagation constant lying in the continuum. The corresponding eigenfunctions can be interpreted as an optical generalization of bound states in the continuum. For a particular example, the persistence of asymptotic expansions is confirmed with direct numerical evaluation of the perturbed spectrum.

Dissipating of disorder quantum vortices in an annular two-dimensional Bose-Einstein condensate can form a macroscopic persistent flow of atoms. We propose a protocol to create persistent flow with high winding number based on a double concentric ring-shaped configuration. We find that a sudden geometric quench of the trap from single ring-shape into double concentric ring-shape will enhance the circulation flow in the outer ring-shaped region of the trap when the initial state of the condensate is with randomly distributed vortices of the same charge. The circulation flows that we created are with high stability and good uniformity free from topological excitations. Our study is promising for new atomtronic designing, and is also helpful for quantitatively understanding quantum tunneling and interacting quantum systems driven far from equilibrium.

An eight element, compact Ultra Wideband-Multiple Input Multiple Output (UWB-MIMO) antenna capable of providing high data rates for future Fifth Generation (5G) terminal equipments along with the provision of necessary bandwidth for Third Generation (3G) and Fourth Generation (4G) communications that accomplishes band rejection from 4.85 to 6.35 GHz by deploying a Inductor Capacitor (LC) stub on the ground plane is presented. The incorporated stub also provides flexibility to reject any selected band as well as bandwidth control. The orthogonal placement of the printed monopoles permits polarization diversity and provides high isolation. In the proposed eight element UWB-MIMO/diversity antenna, monopole pair 3-4 are 180o mirrored transform of monopole pair 1-2 which lie on the opposite corners of a planar 50 x 50 mm2 substrate. Four additional monopoles are then placed perpendicularly to the same board leading to a total size of 50 x 50 x 25 mm3 only. The simulated results are validated by comparing the measurements of a fabricated prototype. It was concluded that the design meets the target specifications over the entire bandwidth of 2 to 12 GHz with a reflection coefficient better than -10 dB (except the rejected band), isolation more than 17 dB, low envelope correlation, low gain variation, stable radiation pattern, and strong rejection of the signals in the Wireless Local Area Network (WLAN) band. Overall, compact and reduced complexity of the proposed eight element architecture, strengthens its practical viability for the diversity applications in future 5G terminal equipments amongst other MIMO antennas designs present in the literature.

Recently, we have theoretically proposed and experimentally demonstrated an exact and efficient quantum simulation of photosynthetic light harvesting in nuclear magnetic resonance (NMR), cf. B. X. Wang, \textit{et al.} npj Quantum Inf.~\textbf{4}, 52 (2018). In this paper, we apply this approach to simulate the open quantum dynamics in various photosynthetic systems with different Hamiltonians. By numerical simulations, we show that for Drude-Lorentz spectral density the dimerized geometries with strong couplings within the donor and acceptor clusters respectively exhibit significantly-improved efficiency. Based on the optimal geometry, we also demonstrate that the overall energy transfer can be further optimized when the energy gap between the donor and acceptor clusters matches the peak of the spectral density. Moreover, by exploring the quantum dynamics for different types of spectral densities, e.g. Ohmic, sub-Ohmic, and super-Ohmic spectral densities, we show that our approach can be generalized to effectively simulate open quantum dynamics for various Hamiltonians and spectral densities. Because $\log_{2}N$ qubits are required for quantum simulation of an $N$-dimensional quantum system, this quantum simulation approach can greatly reduce the computational complexity compared with popular numerically-exact methods.

This article provides a focused review of recent findings which demonstrate, in some cases quite counter-intuitively, the existence of bound states with a singularity of the density pattern at the center, while the states are physically meaningful because their total norm converges. One model of this type is based on the 2D Gross-Pitaevskii equation (GPE) which combines the attractive potential ~ 1/r^2 and the quartic self-repulsive nonlinearity, induced by the Lee-Huang-Yang effect (quantum fluctuations around the mean-field state). The GPE demonstrates suppression of the 2D quantum collapse, driven by the attractive potential, and emergence of a stable ground state (GS), whose density features an integrable singularity ~1/r^{4/3} at r --> 0. Modes with embedded angular momentum exist too, and they have their stability regions. A counter-intuitive peculiarity of the model is that the GS exists even if the sign of the potential is reversed from attraction to repulsion, provided that its strength is small enough. This peculiarity finds a relevant explanation. The other model outlined in the review includes 1D, 2D, and 3D GPEs, with the septimal (seventh-order), quintic, and cubic self-repulsive terms, respectively. These equations give rise to stable singular solitons, which represent the GS for each dimension D, with the density singularity ~1/r^{2/(4-D). Such states may be considered as a result of screening of a "bare" delta-functional attractive potential by the respective nonlinearity.

In this paper we derive a sufficient condition for the existence of a unique solution of a Cauchy type q-fractional problem (involving the fractional q-derivative of Riemann-Liouville type) for some nonlinear differential equations. The key technique is to first prove that this Cauchy type q-fractional problem is equivalent to a corresponding Volterra q-integral equation. Moreover, we define the $q$-analogue of the Hilfer fractional derivative or composite fractional derivative operator and prove some similar new equivalence, existence and uniqueness results as above. Finally, some examples are presented to illustrate our main results in cases where we can even give concrete formulas for these unique solutions.

The anatomical axis of long bones is an important reference line for guiding fracture reduction and assisting in the correct placement of guide pins, screws, and implants in orthopedics and trauma surgery. This study investigates an automatic approach for detection of such axes on X-ray images based on the segmentation contour of the bone. For this purpose, we use the medically established two-line method and translate it into a learning-based approach. The proposed method is evaluated on 38 clinical test images of the femoral and tibial bone and achieves a median angulation error of 0.19{\deg} and 0.33{\deg} respectively. An inter-rater study with three trauma surgery experts confirms reliability of the method and recommends further clinical application.

We apply persistent homology, the dominant tool from the field of topological data analysis, to study electoral redistricting. Our method combines the geographic information from a political districting plan with election data to produce a persistence diagram. We are then able to visualize and analyze large ensembles of computer-generated districting plans of the type commonly used in modern redistricting research (and court challenges). We set out three applications: zoning a state at each scale of districting, comparing elections, and seeking signals of gerrymandering. Our case studies focus on redistricting in Pennsylvania and North Carolina, two states whose legal challenges to enacted plans have raised considerable public interest in the last few years. To address the question of robustness of the persistence diagrams to perturbations in vote data and in district boundaries, we translate the classical stability theorem of Cohen--Steiner et al. into our setting and find that it can be phrased in a manner that is easy to interpret. We accompany the theoretical bound with an empirical demonstration to illustrate diagram stability in practice.

During the past decade, semi-conductor photo sensors have replaced photo multiplier tubes in numerous applications featuring single-photon resolution, insensitivity to magnetic fields, higher robustness and enhanced photo detection efficiency at lower operation voltage and lower costs. This paper presents a measurement of gain, optical crosstalk and dark count rate of 127 Silicon Photo Multipliers (SiPMs) of type SensL MicroFJ-60035-TSV at nominal bias voltage. In SiPMs, optical crosstalk can fake higher multiplicities for single-photon hits. This paper demonstrates that optically coupled light guides reduce this probability significantly. The measured sensors offer a comparably small variation of their breakdown voltage with temperature of only $21.5\,\mathrm{mV/K}$. The manufacturer specifies a limited range of only $\pm 250\,\mathrm{mV/K}$ for their nominal breakdown voltage. This should allow for operation with small systematic errors without major efforts on temperature-based bias voltage compensation and without calibration of their individual breakdown voltages. This paper proves that the gain distribution of the measured sensors is consistent with the data sheet values.

Quantum geometric tensor (QGT), including a symmetric real part defined as quantum metric and an antisymmetric part defined as Berry curvature, is essential for understanding many phenomena. We studied the photogalvanic effect of a multiple-band system with time-reversal-invariant symmetry by theoretical analysis in this work. We concluded that the integral of gradient of the symmetric part of QGT in momentum space is related to the linearly photogalvanic effect, while the integral of gradient of Berry curvature is related to the circularly photogalvanic effect. Our work afforded an alternative interpretation for the photogalvanic effect in the view of QGT, and a simple approach to detect the QGT by nonlinear optical response.

An unsteady one-dimensional model of solid propellant combustion, based on a low-Mach assumption, is presented and semi-discretised in space via a finite volume scheme. The mathematical nature of this system is shown to be differential-algebraic of index one. A high-fidelity numerical strategy with stiffly accurate singly diagonally implicit Runge-Kutta methods is proposed, and time adaptation is made possible using embedded schemes. High-order is shown to be reached, while handling the constraints properly, both at the interface and for the mass conservation in the gaseous flow field. Three challenging test-cases are thoroughly investigated: ignition transients, growth of combustion instabilities through a Hopf bifurcation leading to a limit cycle periodic solution and the unsteady response of the system when detailed gas-phase kinetics are included in the model. The method exhibits high efficiency for all cases in terms of both computational time and accuracy compared to first and second-order schemes traditionally used in the combustion literature, where the time step adaptation is CFL-or variation-based.

Seasonality of acute viral respiratory diseases is a well-known and yet not fully understood phenomenon. Here we show that such seasonality, as well as the distribution of viral disease's epidemics with latitude on Earth, can be fully explained by the virucidal properties of UV-B and A Solar photons through a daily, minute-scale, resonant forcing mechanism. Such an induced periodicity can last, virtually unperturbed, from tens to hundreds of cycles, and even in presence of internal dynamics (host's loss of immunity) much slower than seasonal will, on a long period, generate seasonal oscillations.

The alkali-silica reaction (ASR) in concrete is a chemical reaction, which produces an expansive product, generally called ''ASR gel'', and causes cracking and damage in concrete over time. Affecting numerous infrastructures all around the world, ASR has been the topic of much research over the past decades. In spite of that, many aspects of this reaction are still unknown. In this numerical-investigation paper, a three-dimensional concrete meso-structure model is simulated using the finite-element method. Coarse aggregates, cement paste, and ASR gel are explicitly represented. A temperature dependent eigen-strain is applied on the simulated ASR gel pockets to capture their expansive behavior. This applies pressure on the surrounding aggregates and the cement paste, leading to cracks initiation and propagation. Free expansion of concrete specimens due to ASR is modeled and validated using experimental data. Influence of different key factors on damage generation in aggregates and paste and macroscopic expansion are discussed.

We propose a new method, called MonteCarlo Posterior Fit, to boost the MonteCarlo sampling of likelihood (posterior) functions. The idea is to approximate the posterior function by an analytical multidimensional non-Gaussian fit. The many free parameters of this fit can be obtained by a smaller sampling than is needed to derive the full numerical posterior. In the examples that we consider, based on supernovae and cosmic microwave background data, we find that one needs an order of magnitude smaller sampling than in the standard algorithms to achieve comparable precision. This method can be applied to a variety of situations and is expected to significantly improve the performance of the MonteCarlo routines in all the cases in which sampling is very time-consuming. Finally, it can also be applied to Fisher matrix forecasts, and can help solve various limitations of the standard approach.

In a retroreflective scheme atomic Raman diffraction adopts some of the properties of Bragg diffraction due to additional couplings to off-resonant momenta. As a consequence, double Raman diffraction has to be performed in a Bragg-type regime. Taking advantage of this regime, double Raman allows for resonant higher-order diffraction. We study theoretically the case of third-order diffraction and compare it to first order as well as a sequence of first-order pulses giving rise to the same momentum transfer as the third-order pulse. In fact, third-order diffraction constitutes a competitive tool for the diffraction of ultracold atoms and interferometry based on large momentum transfer since it allows to reduce the complexity of the experiment as well as the total duration of the diffraction process compared to a sequence.

Photon-induced nuclear excitation (i.e. photo-excitation) can be used for production of nuclear isomers, which have potential applications in astrophysics, energy storing, and medical diagnosis and treatment. This paper presents a feasibility study on production of four nuclear isomers ({99m}^Tc, {103m}^Rh and {113m, 115m}^In) using high-intensity {\gamma}-ray source based on laser-electron Compton scattering (LCS), for use in the medical diagnosis and treatment. The decay properties and the medical applications of these nuclear isomers were reviewed. The cross-section curves, simulated yields and activity of product of each photo-excitation process were calculated. The cutoff energy of LCS {\gamma}-ray beam is optimized by adjusting the electron energy in order to maximize the yields as well as the activities of photo-excitation products. It is found that the achievable activity of above-mentioned isomers can exceed 10 mCi for 6-hour target irradiation at an intensity of the order of 10^{13} {\gamma}/s. Such magnitude of activity satisfies the dose requirement of medical diagnosis. Our simulation results suggest the prospect of producing medically interesting isomers with photo-excitation using the state-of-art LCS {\gamma}-ray beam facility.

Progressive addition lenses contain a surface of spatially-varying curvature, which provides variable optical power for different viewing areas over the lens. We derive complete compatibility equations that provide the exact magnitude of cylinder along lines of curvatures on any arbitrary PAL smooth surface. These equations reveal that, contrary to current knowledge, cylinder, and its derivative, does not only depend on principal curvature and its derivatives along the principal line but also on the geodesic curvature and its derivatives along the line orthogonal to the principal line. We quantify the relevance of the geodesic curvature through numerical computations. We also derive an extended and exact Minkwitz theorem only restricted to be applied along lines of curvatures, but excluding umbilical points.

We introduce Spline Moment Equations (SME) for kinetic equations using a new weighted spline ansatz of the distribution function and investigate the ansatz, the model, and its performance by simulating the one-dimensional Boltzmann-BGK equation. The new basis is composed of weighted constrained splines for the approximation of distribution functions that preserves mass, momentum, and energy. This basis is then used to derive moment equations using a Galerkin approach for a shifted and scaled Boltzmann-BGK equation, to allow for an accurate and efficient discretization in velocity space with an adaptive grid. The equations are given in compact analytical form and we show that the hyperbolicity properties are similar to the well-known Grad moment model. The model is investigated numerically using the shock tube, the symmetric two-beam test and a stationary shock structure test case. All tests reveal the good approximation properties of the new SME model when the parameters of the spline basis functions are chosen properly. The new SME model outperforms existing moment models and results in a smaller error while using a small number of variables for efficient computations.

On surfaces with many motile cilia, beats of the individual cilia coordinate to form metachronal waves. We present a theoretical framework that connects the dynamics of individual cilia to the collective dynamics of a ciliary carpet via systematic coarse-graining. We uncover the criteria that control the selection of frequency and wavevector of stable metchacronal waves and examine how they depend on the geometric and dynamical characteristics of single cilia, as well as the geometric properties of the array. Our results can contribute to understanding how the collective properties of ciliary arrays can be controlled, which can have significant biological, medical, and engineering implications.

The severe acute respiratory syndrome COVID-19 has been in the center of the ongoing global health crisis in 2020. The high prevalence of mild cases facilitates sub-notification outside hospital environments and the number of those who are or have been infected remains largely unknown, leading to poor estimates of the crude mortality rate of the disease. Here we use a simple model to describe the number of accumulated deaths caused by COVID-19. The close connection between the proposed model and an approximate solution of the SIR model provides a system of equations whose solutions are robust estimates of epidemiological parameters. We find that the crude mortality varies between $10^{-4}$ and $10^{-3}$ depending on the severity of the outbreak which is lower than previous estimates obtained from laboratory confirmed patients. We also estimate quantities of practical interest such as the basic reproduction number and the expected number of deaths in the asymptotic limit with and without social distancing measures and lockdowns, which allow us to measure the efficiency of these interventions.

Model complexity plays an essential role in its selection, namely, by choosing a model that fits the data and is also succinct. Two-part codes and the minimum description length have been successful in delivering procedures to single out the best models, avoiding overfitting. In this work, we pursue this approach and complement it by performing further assumptions in the parameter space. Concretely, we assume that the parameter space is a smooth manifold, and by using tools of Riemannian geometry, we derive a sharper expression than the standard one given by the stochastic complexity, where the scalar curvature of the Fisher information metric plays a dominant role. Furthermore, we derive the minmax regret for general statistical manifolds and apply our results to derive optimal dimensional reduction in the context of principal component analysis.