It is critical to characterize the carrier and instantaneous frequency distribution variation in ultrafast processes, all of which are determined by the optical phase. Nevertheless, there is no method that can single-shot record the intro-pulse phase evolution of pico/femtosecond signals, to date. By analogying holographic principle in space to the time domain and using the time-stretch method, we propose the dispersive temporal holography to single-shot recover the phase and amplitude of ultrafast signals. It is a general and comprehensive technology and can be applied to analyze ultrafast signals with highly complex dynamics. The method provides a new powerful tool for exploring ultrafast science, which may benefit many fields, including laser dynamics, ultrafast diagnostics, nonlinear optics, and so on.

We present an energy scaling function to predict, in a specific range, the energy of bosonic trimers with large scattering lengths and finite range interactions, which is validated by quantum Monte Carlo calculations using microscopic Hamiltonians with two- and three-body potentials. The proposed scaling function depends on the scattering length, effective range, and a reference energy, which we chose as the trimer energy at unitarity. We obtained the scaling function as a limit cycle from the solution of the renormalized zero-range model with effective range corrections. We proposed a simple parameterization of the energy scaling function. Besides the intrinsic interest in theoretical and experimental investigations, this scaling function allows one to probe Efimov physics with only the trimer ground-states, which may open opportunities to identify Efimov trimers whenever access to excited states is limited.

In this work, we present an experimental study of nanosecond high-voltage discharges in a pin-to-pin electrode configuration at atmospheric conditions operating in single-pulse mode (no memory effects). Various discharge parameters, including voltage, current, gas density, rotational/vibrational/gas temperature, and electron number density, were measured. Several different measurement techniques were used, including microwave Rayleigh scattering, laser Rayleigh scattering, optical emission spectroscopy enhanced with a nanosecond probing pulse, fast photography, and electrical parameter measurements. Spark and corona discharge regimes were studied with discharge pulse duration of 90 ns and electrode gap sizes ranging from 2 to 10 mm. The spark regime was observed for gaps < 6 mm using discharge pulse energies of 0.6-1 mJ per mm of the gap length. Higher electron number densities, total electron number per gap length, discharge currents, and gas temperatures were observed for smaller electrode gaps and larger pulse energies, reaching maximal values of about 7.5x10^15 cm-3, 3.5x10^11 electrons per mm, 22 A, and 4,000 K (at 10 us after the discharge), respectively, for a 2 mm gap and 1 mJ/mm discharge pulse energy. Initial breakdown was followed by a secondary breakdown occurring about 30-70 ns later and was associated with ignition of a cathode spot and transition of the discharge to cathodic arc. A majority of the discharge pulse energy was deposited into the gas before the secondary breakdown (85-89%). The electron number density after the ns discharge pulse decayed with a characteristic time scale of 150 ns governed by dissociative recombination and electron attachment to oxygen mechanisms. For the corona regime, substantially lower pulse energies (~0.1 mJ/mm), peak conduction current (1-2 A), and electron numbers (3-5x10^10 electrons per mm), and gas temperatures (360 K) were observed.

A study of the dynamical formation of networks of friends and enemies in social media, in this case Twitter, is presented. We characterise the single node properties of such networks, as the clustering coefficient and the degree, to investigate the structure of links. The results indicate that the network is made from three kinds of nodes: one with high clustering coefficient but very small degree, a second group has zero clustering coefficient with variable degree, and finally, a third group in which the clustering coefficient as a function of the degree decays as a power law. This third group represents $\sim2\%$ of the nodes and is characteristic of dynamical networks with feedback. This part of the lattice seemingly represents strongly interacting friends in a real social network.

Heavy-ion therapy, particularly using scanned (active) beam delivery, provides a precise and highly conformal dose distribution, with maximum dose deposition for each pencil beam at its endpoint (Bragg peak), and low entrance and exit dose. To take full advantage of this precision, robust range verification methods are required; these methods ensure that the Bragg peak is positioned correctly in the patient and the dose is delivered as prescribed. Relative range verification allows intra-fraction monitoring of Bragg peak spacing to ensure full coverage with each fraction, as well as inter-fraction monitoring to ensure all fractions are delivered consistently. To validate the proposed filtered Interaction Vertex Imaging method for relative range verification, a ${}^{16}$O beam was used to deliver 12 Bragg peak positions in a 40 mm poly-(methyl methacrylate) phantom. Secondary particles produced in the phantom were monitored using position-sensitive silicon detectors. Events recorded on these detectors, along with a measurement of the treatment beam axis, were used to reconstruct the sites of origin of these secondary particles in the phantom. The distal edge of the depth distribution of these reconstructed points was determined with logistic fits, and the translation in depth required to minimize the $\chi^2$ statistic between these fits was used to compute the range shift between any two Bragg peak positions. In all cases, the range shift was determined with sub-millimeter precision, to a standard deviation of 200 $\mu$m. This result validates filtered Interaction Vertex Imaging as a reliable relative range verification method, which should be capable of monitoring each energy step in each fraction of a scanned heavy-ion treatment plan.

Abstract: Visual-angle has been used as the conventional unit to determine the field-of-view (FOV) in traditional fundus photography. Recently emerging usage of eye-angle as the unit in wide field fundus photography creates confusions about FOV interpretation in instrumentation design and clinical application. This study is to systematically derive the relationship between the visual-angle {\theta}v and eye-angle {\theta}e, and thus to enable reliable determination of the FOV in wide field fundus photography. FOV conversion ratio {\theta}e/{\theta}v, angular conversion ratio {\Delta}{\theta}e/{\Delta}{\theta}v, retinal conversion ratio {\Delta}d/{\Delta}{\theta}v, retinal distance and area are quantitatively evaluated. Systematical analysis indicates that reliable conversion between the {\theta}v and {\theta}e requires determined nodal point and spherical radius of the eye; and the conversion ratio is not linear from the central field to peripheral region. Based on the eye model with average parameters, both angular conversion ({\Delta}{\theta}e/{\Delta}{\theta}v) and retinal conversion ({\Delta}d/{\Delta}{\theta}v) ratios are observed to have a 1.51-fold difference at the central field and far peripheral region. A conversion table, including {\theta}e/{\theta}v, {\Delta}{\theta}e/{\Delta}{\theta}v, {\Delta}d/{\Delta}{\theta}v, retinal area and percentage ratio, is created for reliable assessment of imaging systems with variable FOV.

This paper developed a fatigue-driven residual strength model considering the effects of low-velocity impact (LVI) damage and stress ratio. New fatigue failure criteria based on fatigue-driven residual strength concept and fatigue progressive damage model were developed to simulate fatigue damage growth and predict fatigue life for plain-weave composite laminates with LVI damage. To validate the proposed model, LVI tests of plain-weave glass fibre reinforced polymer 3238A/EW250F laminates were conducted, followed by post-impact constant amplitude tension-tension, compression-compression fatigue tests and multi-step fatigue tests. Experimental results indicate that the LVI damage degrades fatigue strength of plain-weave glass fibre composite laminate drastically. The load history also plays an important role on the fatigue accumulation damage of post-impact laminates. The new fatigue progressive damage model achieves a good agreement with fatigue life of post-impact laminates and is able to capture the load sequence effect, opening a new avenue to predict fatigue failure of composite laminates.

The measured capacitance, modulus and strength of carbon nanotube-polyaniline (CNT-PANI) composite electrodes render them promising candidates for structural energy storage devices. Here, CNT-PANI composite electrodes are manufactured with electrodeposition of PANI onto the bundle network of CNT mats produced via a floating catalyst chemical vapour deposition process. PANI comprises 0% to 30% by volume of the electrode. The composition, modulus, strength and capacitance of the electrodes is measured in the initial state, after the first charge, and after 1000 charge/discharge cycles. Electrode modulus and strength increase with increasing CNT volume fraction; in contrast, the capacitance increases with increasing PANI mass. Charging or cycling reduce the electrode modulus and strength due to a decrease in CNT bundle volume fraction caused by swelling; the electrode capacitance also decreases due to a reduction in PANI mass. A micromechanical model is able to predict the stress-strain response of pre-charged and cycled electrodes, based upon their measured composition after pre-charging and cycling. The electrodes possess up to 63% of their theoretical capacitance, and their tensile strengths are comparable to those of engineering alloys. Their capacitance and strength decrease by less than 15% after the application of 1000 charge/discharge cycles. These properties illustrate their potential as structural energy storage devices.

Early research in aerodynamics and biological propulsion was dramatically advanced by the analytical solutions of Theodorsen, von K\'{a}rm\'{a}n, Wu and others. While these classical solutions apply only to isolated swimmers, the flow interactions between multiple swimmers are relevant to many practical applications, including the schooling and flocking of animal collectives. In this work, we derive a class of solutions that describe the hydrodynamic interactions between an arbitrary number of swimmers in a two-dimensional inviscid fluid. Our approach is rooted in multiply-connected complex analysis and exploits several recent results. Specifically, the transcendental (Schottky-Klein) prime function serves as the basic building block to construct the appropriate conformal maps and leading-edge-suction functions, which allows us to solve the modified Schwarz problem that arises. As such, our solutions generalize classical thin aerofoil theory, specifically Wu's waving-plate analysis, to the case of multiple swimmers. For the case of a pair of interacting swimmers, we develop an efficient numerical implementation that allows rapid computations of the forces on each swimmer. We investigate flow-mediated equilibria and find excellent agreement between our new solutions and previously reported experimental results. Our solutions recover and unify disparate results in the literature, thereby opening the door for future studies into the interactions between multiple swimmers.

A non-equilibrium model for laser-induced plasmas is used to describe how nano-second temporal mode-beating affects plasma kernel formation and growth in quiescent air. The chemically reactive Navier-Stokes equations describe the hydrodynamics, and non-equilibrium effects are modeled based on a two-temperature model. Inverse Bremsstrahlung and multiphoton ionization are self-consistently taken into account via a coupled solution of the equations governing plasma dynamics and beam propagation and attenuation (i.e., Radiative Transfer Equation). This strategy, despite the additional challenges it may bring, allows to minimize empiricism and enables for more accurate simulations since it does not require an artificial plasma seed to trigger breakdown. The benefits of this methodology are demonstrated by the good agreement between the predicted and the experimental plasma boundary evolution and absorbed energy. The same goes for the periodic plasma kernel structures which, as suggested by experiments and confirmed by the simulations discussed here, are linked to the modulating frequency.

Estimation of the initial state of turbulent channel flow from spatially and temporally resolved wall data is performed using adjoint-variational data assimilation. The accuracy of the predicted flow deteriorates with distance from the wall, most precipitously across the buffer layer beyond which only large-scale structures are reconstructed. To quantify the difficulty of the state estimation, the Hessian of the associated cost function is evaluated at the true solution. The forward-adjoint duality is exploited to efficiently compute the Hessian matrix from the ensemble-averaged cross-correlation of the adjoint fields due to impulses at the sensing locations and times. Characteristics of the Hessian are examined when observations correspond to the streamwise or spanwise wall shear stress or wall pressure. Most of the eigenmodes decay beyond the buffer layer, thus demonstrating weak sensitivity of wall observations to the turbulence in the bulk. However, when the measurement time $t_m^+ \gtrsim 20$, some streamwise-elongated Hessian eigenfunctions remain finite in the outer flow, which corresponds to the sensitivity of wall observations to outer large-scale motions. Furthermore, we report statistics of the adjoint-field kinetic-energy budget at long times, which are distinctly different from those of the forward model. One notable difference is the high concentration of energy within the buffer layer and its narrower support. A large and exponentially amplifying adjoint field in that region leads to large gradients of the cost function, smaller step size in the gradient-based optimization, and difficulty to achieve convergence especially elsewhere in the domain where the gradients are comparatively small.

Within the incompressible three-dimensional Euler equations, we study the pancake-like high vorticity regions, which arise during the onset of developed hydrodynamic turbulence. We show that these regions have an internal fine structure consisting of three vortex layers. Such a layered structure, together with the power law of self-similar evolution of the pancake, prevents development of the Kelvin-Helmholtz instability.

Redox flow batteries (RFBs) offer the capability to store large amounts of energy cheaply and efficiently, however, there is a need for fast and accurate models of the charge-discharge curve of a RFB to potentially improve the battery capacity and performance. We develop a multifidelity model for predicting the charge-discharge curve of a RFB. In the multifidelity model, we use the Physics-informed CoKriging (CoPhIK) machine learning method that is trained on experimental data and constrained by the so-called "zero-dimensional" physics-based model. Here we demonstrate that the model shows good agreement with experimental results and significant improvements over existing zero-dimensional models. We show that the proposed model is robust as it is not sensitive to the input parameters in the zero-dimensional model. We also show that only a small amount of high-fidelity experimental datasets are needed for accurate predictions for the range of considered input parameters, which include current density, flow rate, and initial concentrations.

In this work, we have developed a method to generate ultra-short pulses below the Fourier limit, extending the concept previously worked in reference 1 for generating sub-diffractive Gaussian beams. Alternatively, we introduce new alternatives based on a temporally non-symmetrical interference to narrow ultrashort pulses allowing, sub-Fourier scales. The experimental setup scheme is simple and versatile being able to work with high-power laser sources and ultra-short pulses with a broad bandwidth at any central wavelength. The results presented, are promising and help to enlighten new routes and strategies in the design of coherent control systems. We glimpse they will become broadly useful in different fields from strong field domain to quantum information.

Particle accelerators are invaluable discovery engines in the chemical, biological and physical sciences. Characterization of the accelerated beam response to accelerator input parameters is of-ten the first step when conducting accelerator-based experiments. Currently used techniques for characterization, such as grid-like parameter sampling scans, become impractical when extended to higher dimensional input spaces, when complicated measurement constraints are present, or prior information is known about the beam response is scarce. In this work, we describe an adaptation of the popular Bayesian optimization algorithm, which enables a turn-key exploration algorithm that replaces parameter scans and minimizes prior information needed about the measurements' behavior and associated measurement constraints. We experimentally demonstrate that our algorithm autonomously conducts an adaptive, multi-parameter exploration of input parameter space,while navigating a highly constrained, single-shot beam phase-space measurement. In addition to applications in accelerator-based scientific experiments, this algorithm addresses challenges shared by many scientific disciplines and is thus applicable to autonomously conducting experiments over a broad range of research topics.

We propose a supervised-machine-learning-based wall model for coarse-grid wall-resolved large-eddy simulation (LES). Our consideration is made on LES of turbulent channel flows with a first grid point set relatively far from the wall ($\sim$ 10 wall units), while still resolving the near-wall region, to present a new path to save the computational cost. Convolutional neural network (CNN) is utilized to estimate a virtual wall-surface velocity from $x-z$ sectional fields near the wall, whose training data are generated by a direct numerical simulation (DNS) at ${\rm Re}_{\tau}=180$. The virtual wall-surface velocity is prepared with the extrapolation of the DNS data near the wall. This idea enables us to give a proper wall condition to correct a velocity gradient near the wall. The estimation ability of the model from near wall information is first investigated as a priori test. The estimated velocity fields by the present CNN model are in statistical agreement with the reference DNS data. The model trained in a priori test is then combined with the LES as a posteriori test. We find that the LES can successfully be augmented using the present model at both the friction Reynolds number ${\rm Re}_{\tau}=180$ used for training and the unseen Reynolds number ${\rm Re}_{\tau}=360$ even when the first grid point is located at 5 wall units off the wall. We also investigate the robustness of the present model for the choice of sub-grid scale model and the possibility of transfer learning in a local domain. The observations through the paper suggest that the present model is a promising tool for recovering the accuracy of LES with a coarse grid near the wall.

In a Drude-like model for the conduction electrons of Metal Nanoparticles (MNPs) in a periodic linear chain, considering dipole-dipole interactions of adjacent particles, an analytical expression is derived for each particle permittivity for two different polarizations of incident light: parallel with and perpendicular to the chain line. A numerical analysis is carried out for a chain including 10 identical gold Nanoparticles (NPs) for two different sizes of NPs and two different host media of air and glass. It is shown that in the parallel case of polarization, interaction of NPs leads to a substantial increase in the extinction cross section and the red-shift of the Surface Plasmon Resonance (SPR) wavelength. In comparison with the linear properties of a single NP, the second and penultimate particles have the most increase in the extinction cross section and SPR wavelength displacement while the first and last particles experience the least variations due to the mutual interactions. For the perpendicular polarization, inversely, the dipolar coupling causes the decrease in extinction cross section of all particles and the blue-shift of SPR wavelength. For the parallel polarization, the absolute values of the real and imaginary parts of complex permittivity of each MNP decrease in comparison with the single particle case while they increase for the perpendicular state of polarization.

We present an approach that extends the theory of targeted free energy perturbation (TFEP) to calculate free energy differences and free energy surfaces at an accurate quantum mechanical level of theory from a cheaper reference potential. The convergence is accelerated by a mapping function that increases the overlap between the target and the reference distributions. Building on recent work, we show that this map can be learned with a normalizing flow neural network, without requiring simulations with the expensive target potential but only a small number of single-point calculations, and, crucially, avoiding the systematic error that was found previously. We validate the method by numerically evaluating the free energy difference in a system with a double-well potential and by describing the free energy landscape of a simple chemical reaction in the gas phase.

Recently, physics-driven deep learning methods have shown particular promise for the prediction of physical fields, especially to reduce the dependency on large amounts of pre-computed training data. In this work, we target the physics-driven learning of complex flow fields with high resolutions. We propose the use of \emph{Convolutional neural networks} (CNN) based U-net architectures to efficiently represent and reconstruct the input and output fields, respectively. By introducing Navier-Stokes equations and boundary conditions into loss functions, the physics-driven CNN is designed to predict corresponding steady flow fields directly. In particular, this prevents many of the difficulties associated with approaches employing fully connected neural networks. Several numerical experiments are conducted to investigate the behavior of the CNN approach, and the results indicate that a first-order accuracy has been achieved. Specifically for the case of a flow around a cylinder, different flow regimes can be learned and the adhered "twin-vortices" are predicted correctly. The numerical results also show that the training for multiple cases is accelerated significantly, especially for the difficult cases at low Reynolds numbers, and when limited reference solutions are used as supplementary learning targets.

The concept of lumped optical nanoelements (or metactronics), wherein nanometer-scale structures act as nanoinductors, nanocapacitors and nanoresistors, has attracted a great deal of attention as a simple toolbox for engineering different nanophotonic devices in analogy with microelectronics. While recent studies of the topic have been predominantly focused on linear functionalities, nonlinear dynamics in microelectronic devices plays a crucial role and provides a majority of functions, employed in modern applications. Here, we extend the metactronics paradigm and add nonlinear dynamical modalities to those nanophotonic devices that have never been associated with optical nanoantennas. Specifically, we show that nonlinear dimer nanoantennae can operate in the regimes of tristable and astable multivibrators as well as chaos generators. The physical mechanism behind these modalities relies on the Kerr-type nonlinearity of nanoparticles in the dimer enhanced by a dipolar localized surface plasmon resonance. This allows one to provide a positive nonlinear feedback at moderate optical intensities, leading to the desired dynamical behavior via tuning the driving field parameters. Our findings shed light on a novel class of nonlinear nanophotonic devices with a tunable nonlinear dynamical response.

We report on the experimental observation of beaming elastic and surface enhanced Raman scattering (SERS) emission from a bent-nanowire on a mirror (B-NWoM) cavity. The system was probed with polarization resolved Fourier plane and energy-momentum imaging to study the spectral and angular signature of the emission wavevectors. The out-coupled elastically scattered light from the kink occupies a narrow angular spread. We used a self-assembled monolayer of molecules with a well-defined molecular orientation to utilize the out-of-plane electric field in the cavity for enhancing Raman emission from the molecules and in achieving beaming SERS emission. Calculated directionality for elastic scattering and SERS emission were found to be 16.2 and 12.5 dB respectively. The experimental data were corroborated with three-dimensional numerical finite element and finite difference time domain based numerical simulations. The results presented here may find relevance in understanding coupling of emitters with elongated plasmonic cavities and in designing on-chip optical antennas.

Multi-fluid models have recently been proposed as an approach to improving the representation of convection in weather and climate models. This is an attractive framework as it is fundamentally dynamical, removing some of the assumptions of mass-flux convection schemes which are invalid at current model resolutions. However, it is still not understood how best to close the multi-fluid equations for atmospheric convection. In this paper we develop a simple two-fluid, single-column model with one rising and one falling fluid. No further modelling of sub-filter variability is included. We then apply this model to Rayleigh-B\'{e}nard convection, showing that, with minimal closures, the correct scaling of the heat flux (Nu) is predicted over six orders of magnitude of buoyancy forcing (Ra). This suggests that even a very simple two-fluid model can accurately capture the dominant coherent overturning structures of convection.

Extending plasmonics into the ultraviolet range imposes the use of aluminum to achieve the best optical performance. However, water corrosion is a major limiting issue for UV aluminum plasmonics, as this phenomenon occurs significantly faster in presence of UV light, even at low laser powers of a few microwatts. Here we assess the performance of nanometer-thick layers of various metal oxides deposited by atomic layer deposition (ALD) and plasma-enhanced chemical vapor deposition (PECVD) on top of aluminum nanoapertures to protect the metal against UV photocorrosion. The combination of a 5 nm Al2O3 layer covered by a 5 nm TiO2 capping provides the best resistance performance, while a single 10 nm layer of SiO2 or HfO2 is a good alternative. We also report the influence of the laser wavelength, the laser operation mode and the pH of the solution. Properly choosing these conditions significantly extends the range of optical powers for which the aluminum nanostructures can be used. As application, we demonstrate the label-free detection of streptavidin proteins with improved signal to noise ratio. Our approach is also beneficial to promote the long-term stability of the aluminum nanostructures. Finding the appropriate nanoscale protection against aluminum corrosion is the key to enable the development of UV plasmonic applications in chemistry and biology.

During the last decades, scientific community has been investigating both biological and hydrographic processes that affect fisheries. Such an interdisciplinary and synergic approach is nowadays giving a fundamental contribution, in particular, in connecting the dots between hydrographic phenomena and biomass variability and distribution of small pelagic fish. Here we estimate impacts of hydrographic fluctuations on small pelagic fishery, focusing on the inter-annual variability that characterizes connectivity between spawning and recruiting areas for the European anchovy (Engraulis encrasicolus, Linnaues 1758), in the Northern side of the Sicily Channel (Mediterranean Sea). Results show that coastal transport dynamics of a specific year largely affect the biomass recorded the following year. Our work, moreover, quantifies the specific monetary impacts on landings of European anchovy fishery due to hydrodynamics variability, connecting biomass fluctuations with fishery economics in a highly dynamic and exploited marine environment as the Sicily Channel. In particular, we build a model that attributes a monetary value to the hydrographic phenomena (i.e., cross-shore vs. alongshore eggs and larvae transport), registered in the FAO Geographical Sub-Area (GSA) 16 (Southern Sicily). This allows us to provide a monetary estimation of catches, derived from different transport dynamics. Our results highlight the paramount importance that hydrographic phenomena can have over the socio-economic performance of a fishery.

The classical Doppler shift originates from the movement of a target's center of mass, but it does not hold information about the internal dynamics of the scattering object. In contrast, micro-Doppler signatures contain data about the micro-motions that arise from internal degrees of freedom within the target (such as rotation and vibration), which can be remotely detected by careful analysis of the scattered field. Here we investigate, both theoretically and experimentally, how coupling between a pair of closely situated targets affects the resulting micro-Doppler signatures. The presented model considers a pair of near-field coupled resonators with dynamically reconfigurable scattering properties. Voltage controlled varactor diodes enable modulating the scattering cross-section of each target independently, mimicking rotational degrees of freedom. As a result, coupled micro-Doppler combs are observed, containing new frequency components that arise from the near field coupling, making it possible to extract information about the internal geometry of the system from far-field measurements. From a practical point of view, micro-Doppler spectroscopy allows remote classification of distant objects, while deep understanding of the coupling effects on such signatures in the low frequency regime can provide valuable insight for radar and sonar systems, as well as optical and stellar radio-interferometry, among many others.

Terahertz (THz) technology is promising in several applications such as imaging, spectroscopy and communications. Among several methods in the generation and detection of THz waves, a THz time domain system (TDS) that is developed using photoconductive antennas (PCA) as emitter and detector presents several advantages such as simple alignment, low cost, high performance etc. In this work, we report the design, fabrication and characterization of a 2-D PCA array that is capable of detecting both the amplitude and phase of the THz pulse. The PCA array is fabricated using LT-GaAs and has 8 channels with 64 pixels (8x8). The infrared probe beam is steered and focused towards each pixel of the PCA array using a spatial light modulator (SLM). The measured photocurrent (amplitude and phase) from each channel is recorded separately and the frequencies up to 1.4 THz can be detected. Furthermore, the parameters such as directional time delay of the THz pulse, crosstalk between the channels etc., were characterized. Finally, we show that the proposed 2D PCA array design is flexible and can be used for accelerated THz spectral image acquisition.

Material susceptibilities govern interactions between electromagnetic waves and matter and are of a crucial importance for basic understanding of natural phenomena and for tailoring practical applications. Here we present a new calibration-free method for relative complex permittivity retrieval, which allows using accessible and cheap apparatus and simplifies the measurement process. The method combines advantages of resonant and non-resonant techniques, allowing to extract parameters of liquids and solids in a broad frequency range, where material's loss tangent is less than 0.5. The essence of the method is based on exciting magnetic dipole resonance in a spherical sample with variable dimensions. Size-dependent resonant frequencies and quality factors of magnetic dipolar modes are mapped on real and imaginary parts of permittivity by employing Mie theory. Samples are comprised of liquid solutions, enclosed in stretchable covers, which allows changing the dimensions continuously. This approach allows tuning magnetic dipolar resonance over a wide frequency range, effectively making resonance retrieval method broadband. The technique can be extended to powder and solid materials, depending on their physical parameters, such as granularity and processability.

Electron dynamics in water are of fundamental importance for a broad range of phenomena, but their real-time study faces numerous conceptual and methodological challenges. Here, we introduce attosecond size-resolved cluster spectroscopy and build up a molecular-level understanding of the attosecond electron dynamics in water. We measure the effect that the addition of single water molecules has on the photoionization time delays of water clusters. We find a continuous increase of the delay for clusters containing up to 4-5 molecules and little change towards larger clusters. We show that these delays are proportional to the spatial extension of the created electron hole, which first increases with cluster size and then partially localizes through the onset of structural disorder that is characteristic of large clusters and bulk liquid water. These results establish a previously unknown sensitivity of photoionization delays to electron-hole delocalization and reveal a direct link between electronic structure and attosecond photoemission dynamics. Our results offer novel perspectives for studying electron/hole delocalization and its attosecond dynamics.

Atmospheric turbulences can generate scintillation or beam wandering phenomena that impairs free space optical (FSO) communication. In this paper, we propose and demonstrate a proof-of-concept FSO communication receiver based on a spatial demultiplexer and a photonic integrated circuit coherent combiner. The system collects the light from several Hermite Gauss spatial modes and coherently combine on chip the energy from the different modes into a single output. The FSO receiver is characterized with a wavefront emulator bench that generates arbitrary phase and intensity patterns. The multimode receiver presents a strong resilience to wavefront distortions, compared to a monomode FSO receiver. The system is then used to detect a modulation of the optical beam through a random wavefront profile.

It is well known that performance of a thermophotovoltaic (TPV) device can be enhanced if the vacuum gap between the thermal emitter and the TPV cell becomes nanoscale due to the photon tunneling of evanescent waves. Having multiple bandgaps, multi-junction TPV cells have received attention as an alternative way to improve its performance by selectively absorbing the spectral radiation in each subcell. In this work, we comprehensively analyze the optimized near-field tandem TPV system consisting of the thin-ITO-covered tungsten emitter (at 1500 K) and GaInAsSb/InAs monolithic interconnected tandem TPV cell (at 300 K). We develop a simulation model by coupling the near-field radiation solved by fluctuational electrodynamics and the diffusion-recombination-based charge transport equations. The optimal configuration of the near-field tandem TPV system obtained by the genetic algorithm achieves the electrical power output of 8.41 W/cm$^2$ and the conversion efficiency of 35.6\% at the vacuum gap of 100 nm. We show that two resonance modes (i.e., surface plasmon polaritons supported by the ITO-vacuum interface and the confined waveguide mode in the tandem TPV cell) greatly contribute to the enhanced performance of the optimized system. We also show that the near-field tandem TPV system is superior to the single-cell-based near-field TPV system in both power output and conversion efficiency through loss analysis. Interestingly, the optimization performed with the objective function of the conversion efficiency leads to the current matching condition for the tandem TPV system regardless of the vacuum gap distances.

If the originally flat bottom of a wide quantum well with multiple eigenstates is periodically modulated, its eigenvalues rearrange into denser groups separated by wider gaps. We show that this effect, if implemented in an elongated bottle microresonator (also called a SNAP microresonator) allows to design microwave photonic tunable filters with an outstanding performance.

We report world record high data transmission over standard optical fiber from a single optical source. We achieve a line rate of 44.2 Terabits per second (Tb/s) employing only the C-band at 1550nm, resulting in a spectral efficiency of 10.4 bits/s/Hz. We use a new and powerful class of micro-comb called soliton crystals that exhibit robust operation and stable generation as well as a high intrinsic efficiency that, together with an extremely low spacing of 48.9 GHz enables a very high coherent data modulation format of 64 QAM. We achieve error free transmission across 75 km of standard optical fiber in the lab and over a field trial with a metropolitan optical fiber network. This work demonstrates the ability of optical micro-combs to exceed other approaches in performance for the most demanding practical optical communications applications.

The design, fabrication, and characterization of low loss ultra-compact bends in high index (n = 3.1 at {\lambda} = 1550 nm) PECVD silicon rich silicon nitride (SRN) is demonstrated and utilized to realize efficient, small footprint thermo-optic phase shifter. Compact bends are structured into a folded waveguide geometry to form a rectangular spiral within an area of 65 x 65 \mum2 possessing a total active waveguide length of 1.2 mm. The device features a phase shifting efficiency of 8 mW/{\pi} and a 3 dB switching bandwidth of 15 KHz. We propose SRN as a promising thermo-optic platform combining the properties of silicon and silicon stoichiometric nitride

We present the physical concept and sample engineering design of a new miniature pressure sensor based on the whispering gallery modes (WGMs) optically excited in a dielectric microsphere placed near a flexible reflective membrane which acts as an ambient pressure sensing element. WGMs excitation is carried out by free-space coupling of optical radiation to a microsphere. The distinctive feature of proposed sensor design is double excitation of optical eigenmodes by forward and backward propagating radiation reflected from a membrane that causes WGMs interference in particle volume. The optical intensity of resulting resonant field established in the microsphere carries information about the exact position of the pressure-loaded reflecting membrane. The sensitivity of the proposed sensor strongly depends on the quality factor of the excited resonant mode, as well as geometrical and mechanical parameters of the flexible membrane. Important advantages of the proposed sensor are miniature design (linear sensor dimensions depends only on the membrane diameter) and the absence of a mechanical contact of pressure-sensitive element with WGM resonator.

Does a physical field exist independently of the interaction between the field source and the test body used to measure it at a given point? What does propagate between two physical bodies when they interact? These are the fundamental questions we answer in the present work for electromagnetic and gravitational interactions. We come to the conclusion that gravitational fields as well as spacetime curvature cannot depend on the passive-gravitational to inertial mass ratio of the test bodies, because this would lead to energy conservation and causality violation except when this ratio is universally exactly equal to one. For what concerns the hypothetical dependence of electromagnetic fields on the charge to inertial-mass ratio of test bodies, this would call for the propagation of an operationally ill defined quantity (Coulomb . Meter$^2$ / Second$^2$) that would replace energy (Joule = Kilogram . Meter$^2$ / Second$^2$) transfer in the interaction between two electrically charged bodies. Hence electromagnetic fields cannot depend on the charge to inertial-mass ratio of test bodies. A consequence of these results is also the disqualification of Murat Ozer's unification theory of gravitation and electromagnetism.

In this paper, I respond to a critique of one of my papers previously published in this journal, entitled `Dr. Bertlmann's socks in a quaternionic world of ambidextral reality.' The geometrical framework presented in my paper is based on a quaternionic 3-sphere, or S^3, taken as a model of the physical space in which we are inescapably confined to perform all our experiments. The framework intrinsically circumvents Bell's theorem by reproducing the singlet correlations local-realistically, without resorting to backward causation, superdeterminism, or any other conspiracy loophole. In this response, I demonstrate point by point that, contrary to its claims, the critique has not found any mistakes in my paper, either in the analytical model of the singlet correlations or in its event-by-event numerical simulation based on Geometric Algebra.

Almost 25 years ago, Jarzynski published a paper in which it was asserted: the work done, W, in driving a system from state A to state B, characterized by the Helmholtz free energies FA and FB, satisfies an equality in which an average over an ensemble of measurements for W determines the difference in Free energy. Several features of this result require more detailed description, to be given in the text. The equality is significant and unexpected. So is the statement that the equality is independent of the rate of change from state A to state B. A few years ago, I had presented three papers in which the contraction of the description from full phase space to coordinate space only was made. This was motivated by the large difference in time scales for momenta relaxation and coordinate relaxation. The Jarzynski equality (JE) will be shown here to be correct only in the limit of extremely slow processes. The proposed counterexample is for a macromolecular harmonic oscillator with a Hooke's spring constant, k, that during the time interval linearly changes from k1 to k2. When performed very slowly, we obtain JE in a form in which the free energy is related to the ratio of the k's. However, when the transition is performed more rapidly the equality is lost.

The solutions of a particle's Dirac equation contains a negative kinetic energy (NKE) branch. Such an energy spectrum has an upper limit but no lower limit, so that the system with this spectrum, called NKE system, is of negative temperature. Fundamental formulas of statistical mechanics and thermodynamics of NKE systems are presented. All the formulas have the same forms of those of positive kinetic energy (PKE) systems. Almost all thermodynamic quantities, except entropy and specific heat, have a contrary sign compared to those of PKE systems. Specially, pressure is negative and its microscopic mechanism is given. Entropy is always positive and Boltzmann entropy formula remains valid. The three laws of thermodynamics remain valid, as long as the thermodynamic quantities have a negative sign. Negative temperature Carnot engine can work between two negative temperatures. Since the NKE levels need not be fully filled, it is argued that the concept of Dirac's Fermion Sea can be totally abandoned.

The quantitative analysis of viral transmission risk in public places such as schools, offices, university lecture halls, hospitals, museums, theaters or shopping malls makes it possible to identify the effective levers for a proactive policy of health security and to evaluate the reduction in transmission thus obtained. The contribution to the epidemic propagation of SARS-CoV-2 in such public spaces can be reduced in the short term to a level compatible with an epidemic decline, i.e. with an overall epidemic reproduction rate below one. Here, we revisit the quantitative assessment of indoor and outdoor transmission risk. We show that the long range aerosol transmission is controlled by the flow rate of fresh air and by the mask filtering quality, and is quantitatively related to the CO2 concentration, regardless the room volume and the number of people. The short range airborne transmission is investigated experimentally using dedicated dispersion experiments performed in two French shopping malls. Exhaled aerosols are dispersed by turbulent draughts in a cone, leading to a concentration inversely proportional to the squared distance and to the flow velocity. We show that the average infection dose, called the viral quantum, can be consistently determined from epidemiological and biological experimental data. Practical implications. The results provide a rational design of sanitary policies to prevent the dominant routes of viral transmission by reinforced ventilation, air purification, mechanical dispersion by fans and incentives for correct wearing of quality masks (surgical mask, possibly covered by a fabric mask, or non-medical FFP2 masks). Combined, such measures significantly reduce the airborne transmission risk of SARS-CoV-2, with a quantitative assessment.

Overlay measurements are a critical part of modern semiconductor fabrication, but overlay targets have not scaled down in the way devices have. In this work, we produce overlay targets with very small footprint, consisting of just a few scattering nanoparticles in two separate device layers. Using moir\'e patterns to deterministically generate many overlay errors on a single chip, we demonstrate successful readout of the relative displacement between the two layers and show that calibration on one realization of the targets can be used for overlay measurements on subsequent instances. Our results suggest using greater quantities of smaller overlay targets may benefit performance both directly and through finer sampling of deformation.

Turbidity is a physical property related to the scattering of light by particles that are suspended in a liquid. Commercial turbidimeters are priced at the range of hundreds to thousands of dollars. Considering this scenario, it is proposed in this work the development of a low-cost portable turbidimeter for monitoring of turbidity in processes. An infrared LED was used as light emitter, and an infrared phototransistor as light receiver. The signal processing control unit was developed with the Arduino Uno platform. The calibration of the turbidimeter was done by means of a comparative test in triplicate, using as reference the commercial turbidimeter 2100P, HACH. The turbidimeter was able to perform analysis in the range of 100 to 1000 NTU, presenting an innovation character given its portability and computer communication via USB, and in a good price range for the prototype, costing US$ 46.30.

In this paper we develop an asymptotic theory for steadily travelling gravity-capillary waves under the small-surface tension limit. In an accompanying work [Shelton et al. (2021), J. Fluid Mech., accepted/in press] it was demonstrated that solutions associated with a perturbation about a leading-order gravity wave (a Stokes wave) contain surface-tension-driven parasitic ripples with an exponentially-small amplitude. Thus a naive Poincar\'e expansion is insufficient for their description. Here, we shall develop specialised methodologies in exponential asymptotics for derivation of the parasitic ripples on periodic domains. The ripples are shown to arise in conjunction with Stokes lines and the Stokes phenomenon. The analysis relies crucially upon the derivation and analysis of singularities in the analytic continuation of the classic Stokes wave. A solvability condition is derived, showing that solutions of this type do not exist at certain values of the Bond number. The asymptotic results are compared to full numerical solutions and show excellent agreement. The work provides corrections and insight of a seminal theory on parasitic capillary waves first proposed by Longuet-Higgins [J. Fluid Mech., vol. 16 (1), 1963, pp. 138-159].

In this article, formulas for the calculation of force and torque between two circular filaments arbitrarily oriented in space were derived by using Kalantarov-Zeitlin's method. Formulas are presented in an analytical form through integral expressions, whose kernel function is expressed in terms of the elliptic integrals of the first and second kinds, and provide an alternative formulation to Babic's expressions. The derived new formulas were validated via comparison with a series of reference examples. Also, we obtained additional expressions for the calculation of force and torque between two circular filaments by means of differentiation of Grover's formula for the mutual inductance between two circular filaments with respect to appropriate coordinates. These additional expressions allow to verifying comprehensively and independently derived new formulas.

Near-field radiative heat transfer (NFHT) research currently suffers from an imbalance between numerous theoretical studies, as opposed to experimental reports that remain, in proportion, relatively scarce. Existing experimental platforms all rely on unique custom-built devices on which it is difficult to integrate new materials and structures for studying the breadth of theoretically proposed phenomena. Here we show high-resolution NFHT measurements using, as our sensing element, silicon nitride (SiN) freestanding nanomembranes$-$a widely available platform routinely used in materials and cavity optomechanics research. We measure NFHT by tracking the high mechanical quality (Q) factor ($>2\times10^6$) resonance of a membrane placed in the near-field of a hemispherical hot object. We find that high Q-factor enables a temperature resolution ($1.2\times10^{-6} \ \mathrm{K}$) that is unparalleled in previous NFHT experiments. Results are in good agreement with a custom-built model combining heat transport in nanomembranes and the effect of non-uniform stress/temperature on the resonator eigenmodes.

With the development of laser technologies, nuclear reactions can happen in high-temperature plasma environments induced by lasers and have attracted a lot of attention from different physical disciplines. However, studies on nuclear reactions in plasma are still limited by detecting technologies. This is mainly due to the fact that extremely high electromagnetic pulses (EMPs) can also be induced when high-intensity lasers hit targets to induce plasma, and then cause dysfunction of many types of traditional detectors. Therefore, new particle detecting technologies are highly needed. In this paper, we report a recently developed gated fiber detector which can be used in harsh EMP environments. In this prototype detector, scintillating photons are coupled by fiber and then transferred to a gated photomultiplier tube which is located far away from the EMP source and shielded well. With those measures, the EMPs can be avoided, and this device has the capability to identify a single event of nuclear reaction products generated in laser-induced plasma from noise EMP backgrounds. This new type of detector can be widely used as a Time-of-Flight (TOF) detector in high-intensity laser nuclear physics experiments for detecting neutron, photons, and other charged particles.

We have experimentally characterized the light-output response of a deuterated trans-stilbene (stilbene-d12) crystal to quasi-monoenergetic neutrons in the 0.8 to 4.4 MeV energy range. These data allowed us to perform neutron spectroscopy measurements of a DT 14.1 MeV source and a PuBe-239 source by unfolding the impinging neutron spectrum from the measured light-output response. The stilbene-d12 outperforms a H1-stilbene of similar size when comparing the shape of the unfolded spectra and the reference ones. These results confirm the viability of non-hygroscopic stilbene-d12 crystal for direct neutron spectroscopy without need for time-of-flight measurements. This capability makes stilbene-d12 a well suited detector for fast-neutron spectroscopy in many applications including nuclear reaction studies, radiation protection, nuclear non-proliferation, and space travel.

The simultaneity framework describes the relativistic interaction of time with space. The two major proposed simultaneity frameworks are differential simultaneity, in which time is offset with distance in "moving" or rotating frames for each "stationary" observer, and absolute simultaneity, in which time is not offset with distance. We use the Mansouri and Sexl test theory to analyze the simultaneity framework in rotating frames in the absence of spacetime curvature. The Mansouri and Sexl test theory has four parameters. Three parameters describe relativistic effects. The fourth parameter, $\epsilon (v)$, was described as a convention on clock synchronization. We show that $\epsilon (v)$ is not a convention, but is instead a descriptor of the simultaneity framework whose value can be determined from the extent of anisotropy in the unidirectional one-way speed of light. In rotating frames, one-way light speed anisotropy is described by the Sagnac effect equation. We show that four published Sagnac equations form a relativistic series based on relativistic kinematics and simultaneity framework. Only the conventional Sagnac effect equation, and its associated isotropic two-way speed of light, is found to match high-resolution optical data. Using the conventional Sagnac effect equation, we show that $\epsilon (v)$ has a null value in rotating frames, which implies absolute simultaneity. Introducing the empirical Mansouri and Sexl parameter values into the test theory equations generates the rotational form of the absolute Lorentz transformation, implying that this transformation accurately describes rotational relativistic effects.

We propose an effective approach for creating robust nonreciprocity of high-order sidebands, including the first-, second- and third-order sidebands, at microwave frequencies. This approach relies on magnon Kerr nonlinearity in a cavity magnonics system composed of two microwave cavities and one yttrium iron garnet (YIG) sphere. By manipulating the driving power applied on YIG and the frequency detuning between the magnon mode in YIG and the driving field, the effective Kerr nonlinearity can be strengthened, thereby inducing strong transmission non-reciprocity. More interestingly, we find the higher the sideband order, the stronger the transmission nonreciprocity marked by the higher isolation ratio in the optimal detuning regime. Such a series of equally-spaced high-order sidebands have potential applications in frequency comb-like precision measurement, besides structuring high-performance on-chip nonreciprocal devices.

State-of-the-art fiber Bragg grating interrogators utilize mature concepts and technologies like tunable lasers, optical spectrum analyzers and a combination of time, wavelength, or spatial division demultiplexing approaches. Here, we propose the use of computational compressed sensing (CS) techniques for interrogation of fiber Bragg gratings, reducing interrogator complexity by using a broadband ASE light source and single-pixel detection. We demonstrate temperature sensing using a pre-calibration approach to achieve reconstruction accuracy comparable to uncompressed measurements. We extend these principles for the interrogation of sensor networks, presenting strategies for tackling sparsity considerations. Our proof-of-principle demonstrations show how the presented computational compressed sensing techniques can provide an alternative for realizing low-complexity, small footprint interrogator configurations.

MOLLER is a future experiment designed to measure parity violation in Moller scattering to extremely high precision. MOLLER will measure the right-left scattering differential cross-section parity-violating asymmetry APV , in the elastic scattering of polarized electrons off an unpolarized LH2 target to extreme ppb precision. To make this measurement, the polarized electron source, generated with a circularly polarized laser beam, must have the ability to switch quickly between right and left helicity polarization states. The polarized source must also maintain minimal right-left helicity correlated beam asymmetries, including energy changes, position changes, intensity changes, or spot-size changes. These requirements can be met with appropriate choice and design of the Pockels cell used to generate the circularly polarized light. Rubidium Titanyl Phosphate (RTP) has been used in recent years for ultra-fast Pockels cell switches due to its lack of piezo-electric resonances at frequencies up to several hundred MHz. However, crystal non-uniformity in this material leads to poorer extinction ratios than in commonly used KD*P Pockels cells when used in hald-wave configuration. It leads to voltage dependent beam steering when used in quarter-wave configuration. Here we present an innovative RTP Pockels cell design which uses electric field gradients to counteract crystal non-uniformities and control beam steering down to the nm-level. We demonstrate this RTP Pockels cell design is capable of producing precisely controlled polarized electron beam at Jefferson Laboratory, a national accelerator facility, for current experiments, including the recent PREX II measurement, as well as the future MOLLER experiment.

The macroscopic dynamics of a droplet impacting a solid is crucially determined by the intricate air dynamics occurring at the vanishingly small length scale between droplet and substrate prior to direct contact. Here we investigate the inverse problem, namely the role of air for the impact of a horizontal flat disk onto a liquid surface, and find an equally significant effect. Using an in-house experimental technique, we measure the free surface deflections just before impact, with a precision of a few micrometers. Whereas stagnation pressure pushes down the surface in the center, we observe a lift-up under the edge of the disk, which sets in at a later stage, and which we show to be consistent with a Kelvin-Helmholtz instability of the water-air interface.

We investigate theoretically coherent detection implemented simultaneously on a set of mutually orthogonal spatial modes in the image plane as a method to characterize properties of a composite thermal source below the Rayleigh limit. A general relation between the intensity distribution in the source plane and the covariance matrix for the complex field amplitudes measured in the image plane is derived. An algorithm to estimate parameters of a two-dimensional symmetric binary source is devised and verified using Monte Carlo simulations to provide super-resolving capability for high ratio of signal to detection noise (SNR). Specifically, the separation between two point sources can be meaningfully determined down to $\textrm{SNR}^{-1/2}$ in the units determined by the spatial spread of the transfer function of the imaging system. The presented algorithm is shown to make a nearly optimal use of the measured data in the sub-Rayleigh region.

We describe the design of a soldered sapphire optical viewport, useful for spectroscopic applications of samples at high temperatures and high pressures. The sapphire window is bonded via active soldering to a metal flange with a structure of two c-shaped rings made of different metallic materials in between, as to mitigate thermally induced stress. A spectroscopic cell equipped with two of the optical viewports has been successfully operated with alkali metals in a noble gas environment at temperatures in the range $20\,${\deg}C to $450\,${\deg}C at noble gas pressures from $10^{-6}\,$mbar to $330\,$bar. At the upper pressure range, we observe a leakage rate smaller than our readout accuracy of $30\,$mbar per day.

Parameter values for seismic processing steps are often chosen on a regular grid of samples and interpolated. Active learning instead attempts to optimally select the samples on which parameter values are chosen. For parameters that do not vary smoothly, this often reduces the number of samples that need to be labelled in order to achieve a desired accuracy on the whole dataset. In regression tasks this is typically achieved using a query by committee strategy that selects the samples on which a committee of models is most uncertain. I implement such a strategy for the first break picking task, where the parameters to be chosen are the centre and width of the picking window for each trace. For the committee members I use the centre of the picking window and three popular picking algorithms. Applying this to a real dataset, and with samples corresponding to shot gathers, the active learning approach primarily selects gathers near a jump in the first breaks, and achieves similar levels of accuracy on the whole dataset with about half the number samples picked as when the samples are randomly selected.

Gallium oxide films were grown by HVPE on (0001) sapphire substrates with and without ${\alpha}-Cr_{2}O_{3}$ buffer produced by RF magnetron sputtering. Deposition on bare sapphire substrates resulted in a mixture of ${\alpha}-Ga_{2}O_{3}$ and ${\epsilon}-Ga_{2}O_{3}$ phases with a dislocation density of about $2{\cdot}10^{10} cm^{-2}$. The insertion of ${\alpha}-Cr_{2}O_{3}$ buffer layers resulted in phase-pure ${\alpha}-Ga_{2}O_{3}$ films and a fourfold reduction of the dislocation density to $5{\cdot}10^{9} cm^{-2}$.

We present here a theoretical analysis of the interaction between an ideal two-level quantum system and a super-oscillatory pulse, like the one proposed and successfully synthesized in Ref. this http URL As a prominent feature, these pulses present a high efficiency of the central super-oscillatory region in relation to the unavoidable side-lobes. Besides, our study shows an increase of the global bandwidth of the pulse, in the super-oscillatory region, and not only the appearance of a frequency higher than its highest Fourier-frequency component, as in the usual description of the phenomenon of super-oscillations. Beyond introducing the concept of super-bandwidth, the presented results could be relevant for experimental applications and opening new perspectives for laser-matter interaction.

Ionic clocks exhibit as one of the most promising candidates for the frequency standards. Recent investigations show profound advantages of interrogating two laser lights with different frequencies in the development of the frequency standards. Here, we present a scheme of a two-photon process to precisely calculate the dynamic polarizabilities of a few low-lying states of $^{137}$Ba$^+$ by employing highly correlated relativistic coupled-cluster theory. We demonstrate the Stark shift cancellation method for the clock states of $^{137}$Ba$^+$ at the two-photon magic wavelengths which would be an essential input to achieve better accuracy for the experiment dealing with the clock transitions of the ion. To serve as a reference and also for a comparative study, we calculate the magic wavelengths under the single-photon process as well. The calculated single and two-photon magic wavelengths, found for the clock transitions of the ion, lie in the optical regime and are thus significant for state-of-the-art experimental purposes. Further, as an application, we investigate the impact of the two-photon polarizability on the spin-mixing process of an ultra-cold spin-1 mixture $^{137}$Ba$^+$-$^{87}$Rb. We demonstrate the robustness of the spin-mixing mechanism in the mixture due to the two-photon process in the presence of a tunable magnetic field.

This paper presents studies on application of convolutional neural network (CNN) to simulation data generated with a scintillator detector subdivided into 1 cubic cm, which is designed for the long-baseline neutrino experiment. Classification of interaction, regression of momentum, and segmentation of hits are demonstrated for single particle and neutrino-nucleon interactions with well established CNN architectures by feeding reconstructed 2D projection images. In the study it is shown that the application of CNN to the 1 cm subdivided scintillator detector can provide a factor about 2 better momentum resolution compared to a standard method, as well as a classification capability of about 94% for the single particle and 70% for the neutrino-nucleon interactions.

We study the linear and nonlinear response of a unidirectional reflector where a nonlinear breaking of the Lorentz reciprocity is observed. The device under test consists of a racetrack microresonator, with an embedded S-shaped waveguide, coupled to an external bus waveguide (BW). This geometry of the microresonator, known as "taiji" microresonator (TJMR), allows to selectively couple counter-propagating modes depending on the propagation direction of the incident light and, at the nonlinear level, leads to an effective breaking of Lorentz reciprocity. Here, we show that a full description of the device needs to consider also the role of the BW, which introduces (i) Fabry-Perot oscillations (FPOs) due to reflections at its facets, and (ii) asymmetric losses, which depend on the actual position of the TJMR. At sufficiently low powers the asymmetric loss does not affect the unidirectional behavior, but the FP interference fringes can cancel the effect of the S-shaped waveguide. However, at high input power, both the asymmetric loss and the FPOs contribute to the redistribution of the energy between the clockwise and counterclockwise modes within the TJMR. This strongly modifies the nonlinear response, giving rise to counter-intuitive features where, due to the FP effect and the asymmetric losses, the BW properties can determine the violation of the Lorentz reciprocity and, in particular, the difference between the transmittance in the two directions of excitation. The experimental results are explained by using an analytical model based on the transfer matrix approach, a numerical finite-element model and exploiting intuitive interference diagrams.

The practical application of sodium-ion hybrid capacitors is limited by their low energy densities resulted from the kinetics mismatch between cathodes and anodes, and the fire safety related to the flammable electrolyte-separator system. Hence, we report a rational design of metal-organic frameworks (MOFs, UiO-66) modified PVDF-HFP separator. High tensile strength and dimensional thermal stability of the separator reduce the risk of electrode short circuit caused by the separator deformation. MCC test demonstrates a reduction of 75% in peak heat release rate (pHRR), indicating an enhanced fire-resistant property of the separator. This is due to the transformation of UiO-66 into ZrO2 accompanied by the consumption of oxygen and the formation of the barrier char that suppresses further heat release. Quasi-solid-state electrolyte prepared based on this separator presents an enhanced ionic conductivity of 2.44 mS*cm-1 and Na-ion transference number of 0.55, which are related to the high porosity ( >70%) and electrolyte uptake (~ 320%) of the separator. Moreover, the open metal sites of UiO-66 can capture PF6- and consequently liberate the Na+ for faster migration, thus reducing the kinetics mismatch between cathodes and anodes. Such multifunctional separator enables the quasi-solid-state Na-ion hybrid capacitor to achieve high energy density (182 Wh*kg-1 @31 W*kg-1) and power density (5280 W*kg-1 @22 Wh*kg-1), as well as excellent cyclic stability (10000 cycles @1000 mA*g-1). Keywords: Quasi-solid-state; PVDF-HFP; Metal-organic frameworks; Dimensional thermal stability; Fire safety; Selective charge transfer

The beam aperture of a particle accelerator defines the clearance available for the circulating beams and is a parameter of paramount importance for the accelerator performance. At the CERN Large Hadron Collider (LHC), the knowledge and control of the available aperture is crucial because the nominal proton beams carry an energy of 362 MJ stored in a superconducting environment. Even a tiny fraction of beam losses could quench the superconducting magnets or cause severe material damage. Furthermore, in a circular collider, the performance in terms of peak luminosity depends to a large extent on the aperture of the inner triplet quadrupoles, which are used to focus the beams at the interaction points. In the LHC, this aperture represents the smallest aperture at top-energy with squeezed beams and determines the maximum potential reach of the peak luminosity. Beam-based aperture measurements in these conditions are difficult and challenging. In this paper, we present different methods that have been developed over the years for precise beam-based aperture measurements in the LHC, highlighting applications and results that contributed to boost the operational LHC performance in Run 1 (2010-2013) and Run 2 (2015-2018).

We study a model of two-dimensional classical dimers on the square lattice with strong geometric constraints (there is exactly one bond with the nearest point for every point in the lattice). This model corresponds to the quantum dimer model suggested by D.S. Rokhsar and S.A. Kivelson (1988). We use the directed-loop algorithm to show the system undergoes a Berezinskii-Kostelitz Thousless transition (BKT transition) in finite temperatures. After that, if we destroy the geometric constraint of dimers, the topological transition will transfer to a quasi one-order transition. For the dimer updates, we also introduce a new cluster updating algorithm called the edged cluster algorithm. By this method, we succeed in rapidly traversing the winding (topological) sections uniformly and widening the effective matrical ensemble to include more topological sections.

Forthcoming radio surveys will include full polarisation information, which can be potentially useful for weak lensing observations. We propose a new method to measure the (integrated) gravitational field between a source and the observer, by looking at the angle between the morphology of a radio galaxy and the orientation of the polarisation. For this we use the fact that, while the polarisation of a photon is parallel transported along the photon geodesic, the infinitesimal shape of the source, e.g. its principal axis in the case of an ellipse, is Lie transported. As an example, we calculate the rotation of the shape vector with respect to the polarisation direction which is generated by lensing by a distribution of foreground Schwarzschild lenses. For radio galaxies, the intrinsic morphological orientation of a source and its polarised emission are correlated. It follows that observing both the polarisation and the morphological orientation provides information on both the unlensed source orientation and on the gravitational potential along the line of sight.

Vesicles are soft elastic bodies with distinctive mechanical properties such as bending resistance, membrane fluidity, and their strong ability to deform, mimicking some properties of biological cells. While previous three-dimensional (3D) studies have identified stationary shapes such as slipper and axisymmetric ones, we report a complete phase diagram of 3D vesicle dynamics in a bounded Poiseuille flow with two more oscillatory dynamics, 3D snaking and swirling. 3D snaking is characterized by planar oscillatory motion of the mass center and shape deformations, which is unstable and leads to swirling or slipper. Swirling emerges from supercritical pitchfork bifurcation. The mass center moves along a helix, the preserved shape rolls on itself and spins around the flow direction. Swirling can coexist with slipper.

In the pursuit of directly imaging exoplanets, the high-contrast imaging community has developed a multitude of tools to simulate the performance of coronagraphs on segmented-aperture telescopes. As the scale of the telescope increases and science cases move toward shorter wavelengths, the required physical optics propagation to optimize high-contrast imaging instruments becomes computationally prohibitive. Gaussian Beamlet Decomposition (GBD) is an alternative method of physical optics propagation that decomposes an arbitrary wavefront into paraxial rays. These rays can be propagated expeditiously using ABCD matrices, and converted into their corresponding Gaussian beamlets to accurately model physical optics phenomena without the need of diffraction integrals. The GBD technique has seen recent development and implementation in commercial software (e.g. FRED, CODE V, ASAP) but appears to lack an open-source platform. We present a new GBD tool developed in Python to model physical optics phenomena, with the goal of alleviating the computational burden for modeling complex apertures, many-element systems, and introducing the capacity to model misalignment errors. This study demonstrates the synergy of the geometrical and physical regimes of optics utilized by the GBD technique, and is motivated by the need for advancing open-source physical optics propagators for segmented-aperture telescope coronagraph design and analysis. This work illustrates GBD with Poisson's spot calculations and show significant runtime advantage of GBD over Fresnel propagators for many-element systems.

We consider a multiphysics model for the flow of Newtonian fluid coupled with Biot consolidation equations through an interface, and incorporating total pressure as an unknown in the poroelastic region. A new mixed-primal finite element scheme is proposed solving for the pairs fluid velocity - pressure and displacement - total poroelastic pressure using Stokes-stable elements, and where the formulation does not require Lagrange multipliers to set up the usual transmission conditions on the interface. The stability and well-posedness of the continuous and semi-discrete problems are analysed in detail. Our numerical study {is framed in} the context of different interfacial flow regimes in Cartesian and axisymmetric coordinates that could eventually help describe early morphologic changes associated with glaucoma development in canine species.

We discuss the use of comagnetometry in studying new physics that couples to fermionic spin. Modern comagnetometry is -- in absolute energy units -- the most sensitive experimental technique for measuring the energy difference between quantum states, reaching sensitivities in the $10^{-26}\,$eV range. The technique suppresses the magnetic interactions of the spins, making searches for non-standard-model interactions possible. Many implementations have been developed and optimized for various uses. New physics scenarios which can be probed with comagnetometers include: EDMs, violations of Lorentz invariance, Goldstone bosons of new high-energy symmetries, CP-violating long-range forces, and axionic dark matter. We consider the prospects for improvements in the technique, and show -- based purely on signal-to-noise ratio with existing technology -- that there is room for several orders of magnitude in further improvement. We also evaluate several sources of systematic error and instability that may limit improvements.

Galactic and extra-galactic sources produce X-rays that are often absorbed by molecules and atoms in giant molecular clouds (GMCs), which provides valuable information about their composition and physical state. We mimic this phenomenon with a laboratory Z-pinch X-ray source, which is impinged on neutral molecular gas. The novel technique produces a soft X-ray pseudo continuum using a pulsed-current generator. The absorbing gas is injected from a 1 cm long planar gas-puff without any window or vessel along the line of sight. An X-ray spectrometer with a resolving power of $\lambda/\Delta\lambda\sim$420, comparable to that of astrophysical space instruments, records the absorbed spectra. This resolution clearly resolves the molecular lines from the atomic lines; therefore, motivating the search of molecular signature in astrophysical X-ray spectra. The experimental setup enables different gas compositions and column densities. K-shell spectra of CO$_2$, N$_2$ and O$_2$ reveal a plethora of absorption lines and photo-electric edges measured at molecular column densities between $\sim$10$^{16}$ cm$^{-2}$ -- 10$^{18}$ cm$^{-2}$ typical of GMCs. We find that the population of excited-states, contributing to the edge, increases with gas density.

The increased phase sensitivity of N00N states has been used in many experiments, often involving photon paths or polarization. Here we experimentally combine the phase sensitivity of N00N states with the orbital angular momentum (OAM) of photons up to 100$\,\hslash$, to resolve rotations of a light field around its optical axis. The results show that both a higher photon number and larger OAM increase the resolution and achievable sensitivity. The presented method opens a viable path to unconditional angular super-sensitivity and accessible generation of N00N states between any transverse light fields.

The resonance frequency of membranes depends on the gas pressure due to the squeeze-film effect, induced by the compression of a thin gas film that is trapped underneath the resonator by the high frequency motion. This effect is particularly large in low-mass graphene membranes, which makes them promising candidates for pressure sensing applications. Here, we study the squeeze-film effect in single layer graphene resonators and find that their resonance frequency is lower than expected from models assuming ideal compression. To understand this deviation, we perform Boltzmann and continuum finite-element simulations, and propose an improved model that includes the effects of gas leakage and can account for the observed pressure dependence of the resonance frequency. Thus, this work provides further understanding of the squeeze-film effect and provides further directions into optimizing the design of squeeze-film pressure sensors from 2D materials.

We study theoretically subradiant states in the array of atoms coupled to photons propagating in a one-dimensional waveguide focusing on the strongly interacting many-body regime with large excitation fill factor $f$. We introduce a generalized many-body entropy of entanglement based on exact numerical diagonalization followed by a high-order singular value decomposition. This approach has allowed us to visualize and understand the structure of a many-body quantum state. We reveal the breakdown of fermionized subradiant states with increase of $f$ with emergence of short-ranged dimerized antiferromagnetic correlations at the critical point $f=1/2$ and the complete disappearance of subradiant states at $f>1/2$.

The Maximum Entropy Spectral Analysis (MESA) method, developed by Burg, provides a powerful tool to perform spectral estimation of a time-series. The method relies on a Jaynes' maximum entropy principle and provides the means of inferring the spectrum of a stochastic process in terms of the coefficients of some autoregressive process AR($p$) of order $p$. A closed form recursive solution provides an estimate of the autoregressive coefficients as well as of the order $p$ of the process. We provide a ready-to-use implementation of the algorithm in the form of a python package \texttt{memspectrum}. We characterize our implementation by performing a power spectral density analysis on synthetic data (with known power spectral density) and we compare different criteria for stopping the recursion. Furthermore, we compare the performance of our code with the ubiquitous Welch algorithm, using synthetic data generated from the released spectrum by the LIGO-Virgo collaboration. We find that, when compared to Welch's method, Burg's method provides a power spectral density (PSD) estimation with a systematically lower variance and bias. This is particularly manifest in the case of a little number of data points, making Burg's method most suitable to work in this regime.

Postprocessing ensemble weather predictions to correct systematic errors has become a standard practice in research and operations. However, only few recent studies have focused on ensemble postprocessing of wind gust forecasts, despite its importance for severe weather warnings. Here, we provide a comprehensive review and systematic comparison of eight statistical and machine learning methods for probabilistic wind gust forecasting via ensemble postprocessing, that can be divided in three groups: State of the art postprocessing techniques from statistics (ensemble model output statistics (EMOS), member-by-member postprocessing, isotonic distributional regression), established machine learning methods (gradient-boosting extended EMOS, quantile regression forests) and neural network-based approaches (distributional regression network, Bernstein quantile network, histogram estimation network). The methods are systematically compared using six years of data from a high-resolution, convection-permitting ensemble prediction system that was run operationally at the German weather service, and hourly observations at 175 surface weather stations in Germany. While all postprocessing methods yield calibrated forecasts and are able to correct the systematic errors of the raw ensemble predictions, incorporating information from additional meteorological predictor variables beyond wind gusts leads to significant improvements in forecast skill. In particular, we propose a flexible framework of locally adaptive neural networks with different probabilistic forecast types as output, which not only significantly outperform all benchmark postprocessing methods but also learn physically consistent relations associated with the diurnal cycle, especially the evening transition of the planetary boundary layer.

Deterministic frequency deviations (DFDs) critically affect power grid frequency quality and power system stability. A better understanding of these events is urgently needed as frequency deviations have been growing in the European grid in recent years. DFDs are partially explained by the rapid adjustment of power generation following the intervals of electricity trading, but this intuitive picture fails especially before and around noonday. In this article, we provide a detailed analysis of DFDs and their relation to external features using methods from explainable Artificial Intelligence. We establish a machine learning model that well describes the daily cycle of DFDs and elucidate key interdependencies using SHapley Additive exPlanations (SHAP). Thereby, we identify solar ramps as critical to explain patterns in the Rate of Change of Frequency (RoCoF).

Inferring parameter distributions of complex industrial systems from noisy time series data requires methods to deal with the uncertainty of the underlying data and the used simulation model. Bayesian inference is well suited for these uncertain inverse problems. Standard methods used to identify uncertain parameters are Markov Chain Monte Carlo (MCMC) methods with explicit evaluation of a likelihood function. However, if the likelihood is very complex, such that its evaluation is computationally expensive, or even unknown in its explicit form, Approximate Bayesian Computation (ABC) methods provide a promising alternative. In this work both methods are first applied to artificially generated data and second on a real world problem, by using data of an electric motor test bench. We show that both methods are able to infer the distribution of varying parameters with a Bayesian hierarchical approach. But the proposed ABC method is computationally much more efficient in order to achieve results with similar accuracy. We suggest to use summary statistics in order to reduce the dimension of the data which significantly increases the efficiency of the algorithm. Further the simulation model is replaced by a Polynomial Chaos Expansion (PCE) surrogate to speed up model evaluations. We proof consistency for the proposed surrogate-based ABC method with summary statistics under mild conditions on the (approximated) forward model.

Although projection-based reduced-order models (ROMs) for parameterized nonlinear dynamical systems have demonstrated exciting results across a range of applications, their broad adoption has been limited by their intrusivity: implementing such a reduced-order model typically requires significant modifications to the underlying simulation code. To address this, we propose a method that enables traditionally intrusive reduced-order models to be accurately approximated in a non-intrusive manner. Specifically, the approach approximates the low-dimensional operators associated with projection-based reduced-order models (ROMs) using modern machine-learning regression techniques. The only requirement of the simulation code is the ability to export the velocity given the state and parameters as this functionality is used to train the approximated low-dimensional operators. In addition to enabling nonintrusivity, we demonstrate that the approach also leads to very low computational complexity, achieving up to $1000\times$ reduction in run time. We demonstrate the effectiveness of the proposed technique on two types of PDEs.

In his 1935 Gedankenexperiment, Erwin Schr\"{o}dinger imagined a poisonous substance which has a 50% probability of being released, based on the decay of a radioactive atom. As such, the life of the cat and the state of the poison become entangled, and the fate of the cat is determined upon opening the box. We present an experimental technique that keeps the cat alive on any account. This method relies on the time-resolved Hong-Ou-Mandel effect: two long, identical photons impinging on a beam splitter always bunch in either of the outputs. Interpreting the first photon detection as the state of the poison, the second photon is identified as the state of the cat. Even after the collapse of the first photon's state, we show their fates are intertwined through quantum interference. We demonstrate this by a sudden phase change between the inputs, administered conditionally on the outcome of the first detection, which steers the second photon to a pre-defined output and ensures that the cat is always observed alive.

Advances in light shaping for optical trapping of neutral particles have led to the development of box traps for ultracold atoms and molecules. These traps have allowed the creation of homogeneous quantum gases and opened new possibilities for studies of many-body physics. They simplify the interpretation of experimental results, provide more direct connections with theory, and in some cases allow qualitatively new, hitherto impossible experiments. Here we review progress in this emerging field.