Papers

Coherent transition radiation (CTR) spectroscopy is a critical diagnostic for characterizing the longitudinal structure of relativistic electron bunches in laser-plasma and conventional accelerators. In practice, recovering the bunch profile from a measured CTR spectrum is an ill-posed phase-retrieval problem. Traditionally, this is addressed using Gerchberg-Saxton (GS)-type iterative algorithms. However, these implementations often rely on explicit inverse propagators, making them difficult to adapt to sophisticated experimental forward models. In this work, we introduce a flexible gradient-based framework for CTR phase retrieval. By leveraging a differentiable forward model, we propose a phase-only gradient descent (GD-Phase) approach that enforces the measured spectral amplitude as a hard constraint while optimizing the Fourier phase under physical real-space priors. Using synthetic CTR spectra spanning multi-peaked and strongly modulated profiles, we benchmark GD-Phase against traditional GS and a real-space amplitude-parametrized gradient descent (GD-Amp) algorithm. Unlike traditional methods, this formulation allows for the seamless inclusion of arbitrary differentiable experimental effects into the reconstruction loop. We demonstrate that this physics-informed approach not only reproduces the fidelity of GS methods but also establishes a robust baseline for incorporating multi-diagnostic constraints and uncertainty quantification. This enables the systematic extension to higher-dimensional, multimodal, and uncertainty-aware diagnostics, facilitating fast and scalable phase retrieval in realistic experimental settings.

We demonstrate submicrometer focusing of isolated attosecond pulses (IAPs) in the extreme ultraviolet (XUV) region using a custom ellipsoidal mirror. The obtained focal spot sizes were verified using knife-edge measurements with a sharp silicon edge, confirming reproducible dimensions down to 0.46 $\mu$m $\times$ 0.36 $\mu$m (FWHM), approaching the diffraction limit. Focusing a 1.1-GW tabletop IAP source yields a peak intensity of 3 $\times$ 10$^{15}$ W/cm$^2$, and a realistic pathway toward 10$^{16}$ W/cm$^2$ is obtained by optimizing the beamline throughput. These results establish a practical route toward attosecond nonlinear optics in both gas and solid phases, driven by intense XUV fields.

High-harmonic generation is a sensitive all-optical probe of symmetry and electron dynamics in solids. Here, we use first-principles time-dependent density functional theory (TDDFT) to study high-harmonic generation in T$_d$-WTe$_2$, a two-dimensional semimetal with switchable out-of-plane ferroelectric polarization driven by interlayer sliding. We show that the mirror-symmetry breaking underlying the ferroelectric state produces robust signatures in polarization-resolved high-harmonic spectra, enabling optical identification of the polarization state. By incorporating interlayer shear motion in coupled electron-lattice TDDFT simulations, we further show that the 0.24 THz shear mode is slow enough to remain effectively decoupled from the ultrafast electronic response responsible for harmonic emission. Our results establish high-harmonic spectroscopy as a non-invasive probe of sliding ferroelectricity and lattice symmetry in two-dimensional quantum materials.

We introduce a Hopfield-type associative memory in which effective connectivity is multiplicatively modulated by astrocytic gains evolving under an entropy-regularized replicator equation. The coupled neuron-astrocyte dynamics admit a Lyapunov function, ensuring global convergence. At fixed points, astrocytic gains implement a softmax-normalized allocation over pattern similarity scores, yielding a mechanistic realization of self-attention as emergent routing on the gain simplex. In regimes of high memory load and interference, the model significantly improves retrieval accuracy relative to classical Hopfield dynamics and recent neuron-astrocyte baselines. These results establish a dynamical systems framework linking glial modulation, competitive resource allocation, and attention-like computation.

Image classification is a core task of intelligent sensing, conventionally follows a sequential imaging then processing pipeline. However, redundant high-dimensional image reconstruction is inherently inefficient, especially in photon limited scenarios. Here we report a photon level image classification method using quantum compressed sensing, which reformulates the classification task as a sparse signal measurement problem directly oriented toward class labels. By exploiting the parallelism of photonic quantum superposition states, a single photon can be encoded the complete spatial information of a high-dimensional image. Through a diffractive deep neural network, we physically construct a dedicated measurement basis aligned with the class space, enabling signal-dependent adaptive compressive measurement. Ideally, our method can extract class information via a single quantum projective measurement, reducing the required number of measurements from the logarithmic scaling O(Klog(N/K)) of classical compressed sensing to the constant-order information-theoretic limit M = K = 1. Experimental results show that a classification accuracy of 69.0% can be achieved by using a single-photon detection event as the decision criterion, while it increases to 95.0% with four-photon detection events. This work demonstrates image classification at the energy efficiency limit and introduces a measurement as decision framework. It provides a foundation for intelligent sensing systems that operate under extreme photon budgets and harsh environments.

A K-mirror rotates the wavefront of an incident optical field. However, the rotation always introduces polarization changes in the transmitted field. This is a serious concern for applications ranging from astronomical image derotation to orbital angular momentum spectrum characterization in photonic quantum technology. Recent efforts have shown that the polarization change can be minimized significantly, but these require either a very small base angle that limits the field of view, or mirrors with a customized refractive index. Making the transmitted polarization state completely independent of the rotation angle has remained an open problem. In this work, we show that placing half-wave plates before and after a K-mirror and rotating them synchronously at half the K-mirror rotation angle makes the polarization change in the transmitted field exactly independent of the rotation angle. This works for any wavefront rotator, any base angle, any mirror refractive index, and any input state of polarization. We experimentally demonstrate the approach using a K-mirror with a base angle of $30^{\circ}$, which gives the largest field of view among practical designs, and find a mean polarization error of ~1%, limited only by the retardance imperfection of commercially available half-wave plates. This has significant practical implications for applications that require precise wavefront rotation without polarization change.

This work addresses the challenge of learning reduced-order models (ROMs) capable of generalizing to unobserved dynamical regimes across unseen control parameters. We introduce the Control-oriented Cluster-based Network Model (CNMc), a framework for synthesizing reduced-order dynamics at held-out operating conditions without requiring simulation data at those conditions. While the traditional Cluster Network Model (CNM) is limited to observed regimes, CNMc enables generalization by fitting supervised regression models to the transition probabilities and transition times of the CNM as functions of the control parameter. A key enabler is a Procrustes transformation that maps each operating condition's state space to a common coordinate system in which trajectories across all conditions are standardised and shape-aligned, permitting a shared cluster partition to be learned. We evaluate CNMc on two fluid dynamics benchmarks, the Lorenz-63 system and a controlled turbulent boundary layer, demonstrating that the predicted statistics at the withheld condition closely match those of a CNM trained directly on test data. CNMc also outperforms the competing interpolation-based CNM approaches under identical conditions. These results represent a step toward parameter-aware ROMs suitable for real-time flow control and the acceleration of parametric design studies.

The rotation measure (RM) and dispersion measure (DM) of fast radio bursts (FRBs) serve as critical probes of the magneto-ionic environments along the line of sight. The significant temporal evolution of RM observed in some repeating FRBs is generally attributed to the local environment of the source, since the intergalactic medium is not expected to vary on such short timescales. Recent observations of repeating FRB 20201124A and FRB 20220529 exhibit complex RM phenomenology, including large-amplitude global fluctuations and short-term substructures. Here, we attribute these short-term RM variations to the ponderomotive force exerted by inertial \alfven~waves (IAWs). We propose that IAWs, generated via magnetic reconnection or turbulent cascades in a low-$\beta$ plasma, induce nonlinear density perturbations in the source environment. We demonstrate that the resulting plasma density redistribution can produce RM suppression consistent with observed substructures. This model presents a physically motivated mechanism for the short-term RM variability observed in active repeaters. It demonstrates that such fluctuations can arise from wave-driven density cavitation within a broad, coupled parameter space involving wave amplitude, plasma density, and temperature, thereby characterizing the localized plasma dynamics required to produce the observed RM jitters.

In the theory of open quantum systems, spectral densities are key quantities for modeling the dynamics and spectroscopic properties of the system under investigation. In the case of light-harvesting complexes, they encode the frequency-dependent coupling of electronic excitations in pigment molecules to their environment, reflecting contributions from both intrinsic vibrational modes and the protein surrounding. In particular, the low-frequency components of the spectral densities are crucial for exciton transfer between pigment molecules. Apparently, slow internal modes of bacteriocholophyll molecules in the gas phase are less well represented by common force fields based on classical molecular dynamics (MD) simulations. Here, we demonstrate that Born-Oppenheimer molecular dynamics (BOMD) based on the numerically efficient density functional-based tight-binding approach can accurately recover these low-frequency features, whereas normal mode analysis captures them only partially. In contrasting approaches for determining spectral densities, the low-frequency region of the spectral densities obtained is only associated with protein fluctuations; the usage of BOMD, however, also captures the low-frequency contributions arising from slow intramolecular vibrations of the pigment molecules themselves. Notably, this behavior is consistently observed for both the flexible B800 and the more rigid B850 rings in light-harvesting 2 (LH2) complexes of purple bacteria, as well as in the Fenna-Matthews-Olson (FMO) complex of green sulfur bacteria. Interestingly, we also find that the spectral densities of the pigments in the B850 ring of LH2 are not influenced by the environment, i.e., the gaps between ground and first excited state are not changed significantly by the fluctuations of the protein environment.

Global storm-resolving models aspire to become digital twins of the Earth, delivering information at the local scale at which humans experience climate. We evaluated how well two such models, ICON and IFS-FESOM, reproduce the climate as classified by the Köppen-Geiger system, using 30-year (2020-2049) simulations from the nextGEMS project at 9~km global resolution under SSP3-7.0 scenario. Both models capture the global distribution of the five main climate categories, encouraging given the infancy of storm-resolving climate modelling. Substantial regional biases nonetheless remain. Both underestimate tropical rainforest (Af) extent due to insufficient dry-month precipitation in Amazonia and equatorial Africa. ICON almost eliminates hot arid desert (BWh) across Australia through excessive precipitation, while IFS-FESOM reproduces it well. The two models show opposing biases along the temperate–continental boundary: IFS-FESOM winters are too cold in western Europe, ICON winters too warm. Substituting observed temperature or precipitation into the model fields reveals that precipitation errors dominate misclassification, while temperature biases play a secondary role confined to mid-latitude climate zone boundaries. Under climate change, the two models and CMIP6 projections agree on the direction of climate zone shifts: expansion of tropical savanna and hot desert at the expense of subarctic, tundra, and ice cap zones. However, inter-model differences in present-day climate exceed the 30-year climate change signal for many zones, calling for caution in regional projections and adaptation planning. Our results expose where local-scale climate representation still falls short of the digital twin ambition, while confirming that storm-resolving models already perform well across many regions. We propose Köppen-Geiger classification as a standard diagnostic to help track further progress.

Interest in studying the interaction of small molecules with DNA is caused by the need to develop new, highly effective, and low-toxic drugs for cancer treatment. The strong and highly specific binding of thionine with DNA makes it a promising candidate for use in medicine and pharmacology. In this study, DNA-thionine complexes in aqueous solutions were investigated using UV-Vis absorption spectroscopy. The thermal stability of native DNA was studied in a broad range of thionine concentrations. The mechanisms of thionine binding to DNA, depending on the concentration of thionine, have been established. At low thionine concentrations $([c_{th}] \le 1.5 \text{ mg/L})$, thionine molecules intercalate between the base pairs of the DNA double helix. At a thionine concentration of 1.5-10 mg/L, the groove binding and external electrostatic interaction of positively charged thionine with negatively charged biopolymer phosphate groups of the DNA backbones is preferable. In all cases, the interaction of thionine with DNA leads to an increase in the thermal stability of the polynucleotide. These findings provide valuable insight into the concentration-dependent molecular mechanisms of DNA-small molecule interactions, supporting the rational design of anticancer and antimicrobial agents, as well as exploiting molecular probes for nucleic acid detection, imaging, and other biomedical applications.

Lattice Boltzmann (LB) on quantum devices must reconcile unitary gate evolution with the dissipative collision step. In the multiple-relaxation-time (MRT) class, we work in the common setting of modewise diagonal moment relaxation, $\delta m_r'=\lambda_r\,\delta m_r$ with $\lambda_r\in[-1,1]$ (overrelaxation if $\lambda_r<0$). Embedding that contraction in a unitary by block encoding or a linear combination of unitaries (LCU) typically yields subunitary success probability that decays multiplicatively across modes, sites, and time, a key bottleneck for quantum LB. For the dissipative MRT block alone we give a block-encoding-free construction: a signed two-rail population encoding, then a completely positive trace-preserving (CPTP) map (per-rail amplitude damping with survival $|\lambda_r|$ and, if $\lambda_r<0$, a rail SWAP) so that, after the decode, the map agrees with classical MRT relaxation exactly (expectations of the rail number operators, common encoding–decode scale). Trace preservation gives success probability $1$ for that substage. The main result is the dissipative MRT block; construction of the equilibrium moment vector~$m^{\mathrm{eq}}=Mf^{\mathrm{eq}}$ (prescribed~$f^{\mathrm{eq}}$, host moment matrix~$M$; notation as in Section~\ref{subsec:generic-mrt}), moment transforms, streaming, and boundaries are composed with it as in a standard host pipeline and lie outside the scope of the formal theorem. Hybrid and fully coherent encodings, adaptive scales, Carleman-based context, and a one-rail no-go in the same nonnegative population framework are in the main text. Audits of the open-channel map on a long LBM collide-stream simulation and on stencil-free inputs both match the target to machine precision.

A cost-effective augmented reality (AR) system is presented for visualising three-dimensional magnetic field structures and charged-particle trajectories in magnetically confined fusion plasmas. The system presented in this study integrates an orbit-following simulation code with a marker-based AR framework using a web camera and the OpenCV library. By synchronizing the time step of the simulation with the frame rate of the camera, the trajectories are continuously updated and superimposed in real time onto the camera image. Through the interactive operation of manipulating the web camera, users can observe three-dimensional structures, such as magnetic islands, from various positions and viewing angles. Such an AR environment supports an interactive means of exploring three-dimensional spatial structures that can be difficult to interpret from two-dimensional representations alone. It also provides a common visual representation that can be shared through a display by researchers and students with diverse backgrounds in physics, engineering, and related fields. The developed system has been used in practical exercises at the JT-60SA International Fusion School, with exploratory feedback from students.

We clarified the physical mechanism of superconducting strip single photon detectors (SSPDs) with optical cavities by using transmission line and impedance models. By introducing the transmission line model, we derived the analytical formulae for the absorptance of SSPDs with optical cavities. We compared the absorptance obtained from the analytical formulae for SSPDs with single-side, double-side, and dielectric multi-layer optical cavities against the results of numerical simulations. The comparison showed that the results were nearly identical. By introducing the impedance model, it was clearly shown that the SSPDs with optical cavities achieved the maximum absorptance when their input impedance of the SSPDs with optical cavities matched the impedance of the input medium. The design concepts proposed in this study are applicable to other superconducting detectors, such as microwave kinetic inductance detectors and transition-edge sensors.

Synthetic materials are obtained by assembling atoms or artificial atoms into regular arrays, thereby forming artificial crystals that offer powerful platforms to emulate and explore condensed-matter phenomena in highly controlled settings. They enable probing outstanding questions in many-body physics and designing new phases of matter with no direct analogue in nature. Beyond their fundamental interest, these materials hold potential for future technological applications through the emergence of novel concepts and functionalities. Synthetic materials have been engineered using a wide range of physical platforms, including both natural atoms and fabricated artificial atoms in the solid-state. A particularly intriguing approach relies on photons. When confined in optical cavities and strongly coupled to matter excitations, photons acquire an effective mass and can experience interactions, giving rise to hybrid light-matter quasiparticles known as polaritons. By arranging polaritons in periodic structures, one can engineer synthetic photonic materials with tailored band structures and controllable interactions, offering a promising route toward exploring strongly correlated photonic phases. This chapter focuses on a solid-state realization of such systems: exciton polaritons confined in semiconductor microcavities. Following a general introduction, we describe how photon mass and photonic band structures emerge from cavity confinement, and how interactions arise via strong coupling to excitons in quantum wells. We finally review how these ingredients can be used to explore rich physics from the mean-field to the quantum regime.

In this work, we show that injecting a single space-time-coupled light pulse-beam into a multimode graded-index fiber generates a train of multimode solitons. Space-time couplings excite the spatial modes with distinct temporal profiles. Due to nonlinear interactions, with a properly chosen input power these profiles split into several unique multimode solitons. In the case of a spatially chirped input pulse, two solitons composed of modes $LP_{01}$ and $LP_{11}$ are formed. In the case of the injection of a space-time optical vortex, characterized by its topological charge $\ell$, a train composed of $|\ell| + 1$ multimode solitons is generated. Their energy and modal composition are directly determined by the absolute value of the topological charge.

We study statistical properties of atmospheric particulate matter fluctuations using six years of daily PM2.5 concentration data from fifty-four Indian cities. Despite diverse urban settings and heterogeneous climatic conditions, we find that the fluctuations show strikingly universal behaviour in both the distributional properties and temporal dynamics. After removing slow trends and seasonal components, the rescaled probability density functions of the residual fluctuations collapse onto a single curve and are well described by an exponentially modified Gaussian distribution. The rescaled residual time-series for all the cities further exhibit certain robust dynamical features, with similar decay of auto-correlation functions, and power spectral densities displaying a similar 1/f decay at the tails. Finally, we propose a minimal stochastic model for the residual dynamics, which explains the observed universal features – the stationary distribution, temporal correlation, and spectral scaling.

This paper investigates resonance transmission in two unidirectionally coupled Duffing oscillators with fractional damping, where the driver is harmonically forced and the receiver is connected through a linear coupling spring. Particular attention is paid to how fractional damping in the receiver modifies amplitude amplification, energy redistribution, and the structure of the coupled response. The numerical results reveal a clear distinction between transmitted resonance, associated with a coupling-power balance consistent with direct energy transfer through the coupling spring, and storage-dominated resonance, in which the receiver still exhibits a pronounced oscillatory response while the time-averaged coupling power becomes negative under the adopted convention. In this latter regime, fractional memory promotes temporary energy accumulation within the receiver–coupling subsystem, followed by partial release through the coupling spring without any feedback on the driver dynamics. We further show that detuning the receiver natural frequency enhances the interaction between the lower-frequency transmitted response and the higher-frequency coupled response, leading to a superposed resonance regime with increased receiver amplitude, stronger localization, and sharper response. The roles of the fractional order, coupling strength, and receiver natural frequency are systematically analyzed through frequency-response curves and parametric maps. Overall, the results show how fractional memory can be used to tune resonance transmission, energy localization, and amplified response in coupled nonlinear oscillators.

Objective: This study aims to investigate the influence of organ architecture (specifically the distinction between serial and parallel tissue) on the protective FLASH effect when organs are irradiated with inhomogeneous dose distributions. Approach: An in silico modeling framework was developed using two distinct methods to calculate the effective FLASH dose: the first method utilized a biophysical model of radiolytic oxygen depletion (ROD); the second employed a phenomenological logistic function where the effective FLASH dose is a function of local dose and dose rate. Both models assume that the underlying mechanism behind the FLASH effect is local. Normal Tissue Complication Probability (NTCP) for heterogeneous dose distributions was calculated using the Lyman-Kutcher-Burman (LKB) model and the generalized equivalent uniform dose, varying the volume effect parameter n from 1.0 (parallel) to below 0.01 (serial) to explore different architectures. Results: Both the ROD and phenomenological models showed FLASH sparing compared to conventional radiotherapy. Also, the sparing increased with decreasing $n$ (the sparing is more important for serial organs). For example, for a specific calculation, when the NTCP for conventional radiotherapy was 0.2 (set value) the corresponding NTCP for FLASH delivery ranged from 0.14 for n=1 to 0.11 for n=0.1. Significance: Our results indicate that if the underlying mechanism/s behind the FLASH effect is/are local, the toxicity sparing associated to FLASH-RT can be dependent on the architecture of the irradiated organ/tissue, being more important for serial organs, which are more sensitive to large local doses than to average doses.

The threshold conditions to convective instability in a semi-infinite porous layer saturated by a fluid are determined. The classical setup for this problem in geothermal fluid dynamics was originally modelled by Wooding in 1960. Its formulation is here reconsidered to allow for an imperfect heat transfer across the boundary, parametrised through the Biot number. The temperature boundary condition considered by Wooding is here recovered as the limit of an infinite Biot number. The linear stability analysis of the stationary boundary layer which establishes in the porous medium when a boundary steady suction occurs is carried out. Two different versions of the Rayleigh number are considered, namely, a temperature-difference-based version and a heat-flux-based version. While the former is the classical Rayleigh number for flow in porous media, the latter is a variant definition which displays a finite limit at neutral stability in both the opposite limiting cases of an infinite or of a zero Biot number.

Dual-energy computed tomography (DECT) enables material-specific imaging through acquisitions at two different X-ray energy spectra. Material decomposition from DECT data is an ill-posed inverse problem that is highly sensitive to noise amplification. Conventional methods face challenges regarding accuracy and computational efficiency. We present a novel physics-informed deep learning (DL) framework for DECT material decomposition that eliminates the requirement for ground-truth material images during training. Our approach incorporates a polychromatic forward model into the training pipeline, enabling the network to learn the decomposition mapping by minimizing discrepancies in the projection domain. We validate our method on the AAPM DL-Spectral CT Challenge dataset, comparing performance against three state-of-the-art methods. In the projection domain, our method achieves the lowest root mean squared error (RMSE) across test datasets. For virtual monoenergetic images (VMIs) at 30 keV, 50 keV, and 70 keV, the approach consistently outperforms all conventional methods in both RMSE and structural similarity index (SSIM). These results demonstrate the potential of DL for accurate material decomposition in DECT without requiring labeled training data.

This study investigates the lift force acting on a finite-size, neutrally buoyant spherical particle suspended in a liquid while flowing through a shallow channel at low Reynolds numbers. Using an immersed boundary method, we calculate the lift force for particle radius-to-channel height ratios spanning \(0.03 \leq a/H \leq 0.35\) in 2D planar Poiseuille flows. We propose an explicit formula that accurately predicts the lift force for particles as large as \(a/H = 0.35\) and remains valid for particle Reynolds number \(Re_p \leq 1\), despite a reduction in near-wall lift force at higher \(Re_p\). The influence of slip boundary conditions is also explored, demonstrating that increased slip length reduces near-wall lift force and shifts the particle equilibrium position closer to the wall. Predictions of the particle trajectory from the derived model are in good agreement to the published experimental data. These findings offer a practical framework for estimating the migration of large particles in microfluidic devices.(This article has been accepted for publication in Physics of Fluids. After publication, it will be available via the AIP Publishing website.)

The free motion of charged colloids within ionic solutions and in the vicinity of charged boundaries, is a phenomenon that occurs in various natural, biological and industrial settings. Here, we develop an electrohydrodynamic lubrication theoretical framework, in order to characterize such a motion in the case of an infinite rigid cylinder near a rigid wall. Combining hydrodynamic lubrication theory, Debye-H\”uckel electrostatics, and Nernst-Planck electrokinetics, we derive the three coupled equations of motion for the normal, longitudinal and rotational degrees of freedom of the cylinder, which are then investigated numerically and through asymptotic analysis. Our results reveal complex behaviours, beyond existing asymptotic electroviscous-lift expressions, and extend the classical Faxen-Brenner-like mobility matrix when surface charges and dissolved ions are incorporated.

This study presents theoretical and numerical investigation of the coupled longitudinal and radial wakefields excited by ultrarelativistic electron beams propagating through a cold plasma channel subjected to an external axial magnetic field. A fully causal three dimensional Green function formalism is developed directly from the linearized Maxwell fluid equations in the presence of the magnetized plasma dielectric tensor. This unified framework captures the complete electromagnetic response, including the induction of a transverse plasma current and the resulting hybridization of longitudinal charge separation dynamics with cyclotron driven transverse motion. The analytical treatment reveals how magnetization modifies the effective restoring forces, enhances wake amplitudes, and reshapes the radial focusing defocusing structure of the wake. To validate the theoretical predictions and explore realistic parameter regimes, extensive three dimensional particle in cell simulations are performed using the EPOCH code across wide ranges of plasma density, magnetic field strength, beam Lorentz factor, transverse beam radius, and longitudinal current profiles. The simulations demonstrate excellent quantitative agreement with the analytical Green function solutions, confirming that increasing plasma density substantially amplifies the initial wake amplitude while accelerating the damping of higher order oscillations. Application of an external magnetic field induces coherent high frequency radial oscillations, strengthens focusing forces, and produces a hybrid eigenmode whose properties are absent in the unmagnetized limit. Variations in the driver Lorentz factor lead to rapid convergence toward a universal ultrarelativistic wake structure, while the transverse beam profile controls the radial extent and balance between longitudinal acceleration and transverse focusing.

A fluid-based theoretical framework is developed to describe the nonlinear cascade linking primary BRS-driven plasma wave amplification, oscillating two-stream instability (OTSI), nonlinear current generation within a self-formed ponderomotive channel, and radiation of the secondary electromagnetic mode. Systematic parameter studies reveal a strong sensitivity of the entire cascade to the relative handedness of laser polarization and axial magnetic field direction, as well as to cyclotron resonance strength. Resonant right-handed circular polarization significantly enhances ponderomotive expulsion, channel depth, BRS and OTSI growth rates, nonlinear current density, and the amplitude of the secondary harmonic, whereas non-resonant left-handed polarization effectively suppresses these processes. Fully kinetic particle in cell simulations using EPOCH, together with macroscopic finite-element modelling in COMSOL Multiphysics, corroborate the polarization- and magnetization dependent wake modulation and channelling efficiency across a wide range of laser wavelengths, pulse durations, and plasma densities. The temporal evolution and saturation of OTSI, resilience to density inhomogeneities, and wavenumber-resolved resonance tuning illustrate axial magnetization as a flexible control mechanism for adjusting the intensity, spectral position, bandwidth, and stability of multi peak Raman spectra. These findings demonstrate that cyclotron resonance and polarization control are effective methods for manipulating nonlinear Raman emission in high-intensity laser magnetized plasma interactions, offering predictive insights for forthcoming kinetic simulations and experimental implementations.

Spatially resolved characterization of the critical current density Jc in superconductors under high magnetic fields is crucial for both fundamental understanding and practical applications. However, conventional techniques primarily provide bulk-averaged values, making it difficult to resolve local variations of Jc, especially in high magnetic fields. In this work, we develop a magneto-optical imaging (MOI) technique that enables visualization of superconducting critical states in steady magnetic fields up to 13 T. This is achieved by employing a paramagnetic Nd-garnet indicator combined with a polarizing microscope system. Using this method, we directly image the magnetic flux distribution in a bulk single crystal of an iron-based superconductor Ba(Fe1-xCox)2As2 (x = 0.075) at 12 K and 20 K across the entire sample area (approximately 1 mm). From the measured magnetic field distributions, we quantitatively reconstruct the spatial distribution of the critical current density. The extracted field dependence of Jc is in good agreement with that obtained from conventional magnetization measurements. Furthermore, we demonstrate vector mapping of current flow within the sample by converting the magnetic field distribution into local current-density distributions. Our results establish high-field MOI as a powerful approach for spatially resolved evaluation of superconducting critical states and provide a new pathway for investigating inhomogeneous current transport in superconductors under high magnetic fields.

Universal machine-learned interatomic potentials (uMLIPs) offer a promising approach to performing atomistic simulations at near-DFT accuracy with greatly reduced computational cost. Here, we present a new high-temperature benchmarking dataset of 40~ps ab~initio molecular dynamics (AIMD) trajectories simulated at 300, 1000, and 2000 K for nine zinc- and zirconium-based metal-organic frameworks (MOFs): ZIF-8, CALF-20, MOF-10, MOF-5, MIP-206, UiO-66, UiO-67, UiO-66-NH2, and NU-1000. These trajectories capture equilibrium dynamics, thermally induced distortions, and early-stage decomposition events, including linker degradation and metal node aggregation. Subsequently, we use this dataset to benchmark five leading uMLIPs: ORB-v3, MACE-MP-0a, MACE-MPA-0, fairchem ODAC23, and fairchem OMAT. Our results reveal that ORB-v3 and fairchem OMAT achieve the lowest energy, force, and stress errors across all temperatures. However, all models exhibit significant error under high-temperature conditions. Long-timescale molecular dynamics simulations produced with ORB-v3 demonstrate that the generative error of uMLIPs far exceeds model losses captured during static validation, highlighting the limitations of current universal models for simulating high-temperature MOF dynamics. This work provides a benchmark for assessing the robustness of uMLIPs in extreme regimes and guides future development of potentials capable of accurately modeling the chemistry of high-temperature MOF dynamics.

Measuring energy consumption of marine organisms often requires enclosing the animal in a small, sealed chamber to quantify changes in oxygen concentration of the surrounding water. This can limit measurements of free-swimming organisms by introducing recirculation effects and movement restrictions. We experimentally investigate free-swimming jellyfish energy consumption at two scales: individual pulses and multi-day swimming. Prescribing pulse frequency using onboard microelectronic swim controllers enables comparison of wake energetics across stroke frequencies while allowing continuous swimming. On the microscale, we quantified pulse wake hydrodynamics using three-dimensional Particle Image Velocimetry. Electrical stimulation increased posterior wake energy loss 2.9 times compared to unstimulated jellyfish due to higher pulse rates and altered kinematics. On the macroscale, we used a 6-meter, 13,600-liter tank and tracking-based feedback control to enable continuous swimming against flow over 2.55 km without encountering tank limits. A non-invasive technique quantified changes in 3D morphology without feeding, and volume changes were converted to energy consumption using elemental analysis. Free-swimming, electrically stimulated animals consumed 2.5 times more energy than similarly stimulated animals in a constrained environment, consistent with hydrodynamic and behavioral differences including increased speed and reduced boundary effects. These results suggest hydrodynamic drag may be underrepresented in confined experimental studies.

We present the first quantum-hardware implementation of a Hamiltonian simulation algorithm that produces signed vector-field solutions to the time-domain Maxwells equations using a Schrodingerisation-based approach. The electromagnetic fields are discretized using finite-difference operators, and the resulting non-unitary matrices are mapped to Bell-basis Trotter blocks, enabling efficient circuit construction. We introduce a measurement procedure that retrieves not only field amplitudes, but also physical directions of the electric and magnetic field values at select spatial points. Implementing this logic on quantum hardware relies on relative-phase-based sign reconstruction. Numerical results obtained using IonQ QPU, show good agreement with analytical solutions of benchmark problems in two dimensions and on simulators; in three dimensions. We further extend our approach to compute fields scattered from simple bodies, by enforcing appropriate boundary conditions. Our work lays the foundational steps towards realizing quantum-hardware solutions for computational electromagnetics.

The vectorial structure of light, amplitude, phase, and polarization, encodes essential information for applications ranging from super-resolution microscopy to high-capacity communications and quantum information processing. However, existing characterization methods either rely on multiple sequential measurements or require bulky polarization splitting optics in the signal path. Here we propose and experimentally demonstrate a single shot holographic multiplexed detector that retrieves the full vectorial information from a single intensity recording. Two orthogonally polarized reference beams with distinct off axis carriers interfere with the unknown vectorial light field, encoding both polarization channels into one off axis hologram. Digital holographic reconstruction combined with a self calibrated global phase retrieval recovers the complex wavefronts in the two channels without any additional measurements. We validate our approach by characterizing the polarization structures and concurrence of various vectorial structured light beams on a higher order Poincare sphere (l=2). This compact, efficient detector may open new routes for real time vectorial metrology in light matter interaction, chiral sensing, vectorial adaptive optics, and dynamic structured light applications.