Papers

Electrochemical Impedance Spectroscopy (EIS) is a non-invasive technique widely used for understanding charge transfer and charge transport processes in electrochemical systems and devices. Standard approaches for the interpretation of EIS data involve starting with a hypothetical circuit model for the physical processes in the device based on experience/intuition, and then fitting the EIS data to this circuit model. This work explores a mathematical approach for extracting key characteristic features from EIS data by relying on fundamental principles of complex analysis. These characteristic features can ascertain the presence of inductors and constant phase elements (non-ideal capacitors) in circuit models and enable us to answer questions about the identifiability and uniqueness of equivalent circuit models. In certain scenarios such as models with only resistors and capacitors, we are able to enumerate all possible families of circuit models. Finally, we apply the mathematical framework presented here to real-world electrochemical systems and highlight results using impedance measurements from a lithium-ion battery coin cell.

In experimental nuclear physics (NP), high-precision electromagnetic calorimetry typically requires a good energy resolution and linear photosensor response on the level of (1-2)% over a full dynamic range of the detector. The beam of secondary leptons at the Jefferson Lab experimental complex, provided by the Hall D pair spectrometer (PS), is an optimal facility for studies aiming to understand the impact of light collection and signal processing on calorimetry energy resolution under real experimental conditions. The light emission and collection processes depend on radiator component quality and type, while signal processing depends on photosensor type and front-end electronics design. Various calorimeter tower components and detector assemblies for current and future NP experiments were tested within the lepton momentum range of (3-6) GeV/c using PS. The energy resolution of the PS itself is estimated to be better than approximately 0.6%.

Kinetic frictional forces resisting droplet motion often appear to be separate to surface wettability and adhesive forces. Here we show that such friction arises from a simple combination of the contact angle hysteresis and adhesive force. We show theoretically, and confirm using tilt angle experiments of droplets on liquid-like surfaces, the dependence of the coefficient of droplet-on-solid kinetic friction on system parameters. We also show that a molecular kinetic-type model can describe the observed non-linear velocity-force relationship. Our findings provide a fundamental understanding of the relationship between droplet-on-solid friction, and wettability and liquid adhesion.

This paper presents an application of geometrothermodynamics (GTD) to the economic analysis of Bogotá's sports sector through the Satellite Account of Sport (CSDB). By establishing an analogy between thermodynamic systems and economic structures, we develop a mathematical framework where monetary flows behave analogously to energy, while economic entropy, temperature, and heat capacity acquire well-defined economic interpretations. The study focuses on two contrasting sectors: gambling and betting $\mathbb{S}_{15}$, and recreational and sports activities $\mathbb{S}_{16}$, analyzing data from 2018-2023. Our results demonstrate that $\mathbb{S}_{15}$ exhibits lower economic entropy than $\mathbb{S}_{16}$ , indicating a higher degree of organization and regulatory structure in the gambling sector compared to the more heterogeneous recreational sports sector. The heat capacity function reveals critical points that may signal phase transitions in economic dynamics, while Ricci and Kretschmann curvature scalars identify potential crisis points in the sectoral organization. Furthermore, the cross-income elasticity analysis shows distinct resource flow patterns between sectors, suggesting that gambling activities may serve as an economic driver for recreational sports. This thermodynamic approach provides a quantitative tool for analyzing resource redistribution policies and anticipating critical transitions in sectoral economics. The findings suggest that econophysics and statistical thermodynamics constitute powerful frameworks for understanding the sectoral dynamics of Bogotá's sports economy, with significant potential for developing prospective analysis tools in public policy design.

Our original paper \cite{VanMieghem2025} described the stochastic approximation $\overline{rel}_G(p)=\bigl[1-\phi_D(1-p)\bigr]^{N}$ in \cite[eq. (2.2)]{VanMieghem2025} and the first-order approximation $(R_1)_G(p)=\prod_{i=1}^{N}\!\bigl[1-(1-p)^{d_i}\bigr]$ in \cite[eq. (4.1)]{VanMieghem2025} as upper bounds for the all-terminal reliability polynomial \(rel_G(p)\). The present corrigendum clarifies that the unique upper bound is \(\Pr[\hat D_{\min}\geq 1]\), which is difficult to compute exactly, because we must account for correlated node-isolation events. Both the stochastic approximation $\overline{rel}_G$ and the first-order approximation $(R_1)_G$ ignore those correlations, assume independence and, consequently, do not always upperbound \(rel_G(p)\) as stated previously. The complete graph \(K_{3}\) is a counterexample, where both approximations lie below the exact reliability polynomial $rel_{K_3}(p)$, illustrating that they are not upper bounds. Moreover, as claimed in \cite{VanMieghem2025}, the first-order approximation $(R_1)_G$ is not always more accurate than the stochastic approximation $\overline{rel}_G$. We show by an example that the relative accuracy of the stochastic approximation $\overline{rel}_G$ and the first-order approximation $(R_1)_G$ varies with the graph $G$ and the link operational probability $p$. }{network robustness, node failure, probabilistic graph, reliability polynomial

Combining complementary imaging modalities is critical to build reliable 3D coronary models: intravascular imaging gives sub-millimetre resolution but limited whole-vessel context, while CCTA supplies 3D geometry but suffers from limited spatial resolution and artefacts (e.g., blooming). Prior work demonstrated intravascular/CCTA fusion, yet no open, flexible toolkit is tailored for multi-state analysis (rest/stress, pre-/post-stenting) while offering deterministic behaviour, high performance, and easy pipeline integration. multimodars addresses this gap with deterministic alignment algorithms, a compact NumPy-centred data model, and an optimised Rust backend suitable for scalable, reproducible experiments. The package accepts CSV/NumPy inputs including data formats produced by the AIVUS-CAA software

Resolving the most fundamental questions in cosmology requires simulations that match the scale, fidelity, and physical complexity demanded by next-generation sky surveys. To achieve the realism needed for this critical scientific partnership, detailed gas dynamics, along with a host of astrophysical effects, must be treated self-consistently with gravity for end-to-end modeling of structure formation. As an important step on this roadmap, exascale computing enables simulations that span survey-scale volumes while incorporating key subgrid processes that shape complex cosmic structures. We present results from CRK-HACC, a cosmological hydrodynamics code built for the extreme scalability requirements set by modern cosmological surveys. Using separation-of-scale techniques, GPU-resident tree solvers, in situ analysis pipelines, and multi-tiered I/O, CRK-HACC executed Frontier-E: a four trillion particle full-sky simulation, over an order of magnitude larger than previous efforts. The run achieved 513.1 PFLOPs peak performance, processing 46.6 billion particles per second and writing more than 100 PB of data in just over one week of runtime.

The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment uses superconducting tunnel junction (STJ) sensors to search for physics beyond the standard model (BSM) with recoil spectroscopy of the $\mathbf{^7}$Be EC decay into $\mathbf{^7}$Li. A pulsed UV laser is used to calibrate the STJs throughout the experiment with $\sim$20 meV precision. Phase-III of the BeEST experiment revealed a systematic calibration discrepancy between STJs. We found these artifacts to be caused by resistive crosstalk and by intensity variations of the calibration laser. For phase-IV of the BeEST experiment, we have removed the crosstalk by designing the STJ array so that each pixel has its own ground wire. We now also use a more stable UV laser for calibration. The new STJ arrays were fabricated at STAR Cryoelectronics and tested at LLNL and FRIB. They have the same high energy resolution of $\sim$1-2~eV in the energy range of interest below 100~eV as before, and they no longer exhibit the earlier calibration artifacts. We discuss the design changes and the STJ array performance for the next phase of the BeEST experiment.

Rasnik is a three-point optical displacement sensor originally developed for particle detector alignment in high-energy physics experiments, including the muon chambers of L3 at LEP and ATLAS at the LHC. The system has evolved from four-quadrant photodiodes to CMOS pixel sensors with custom ChessField coded masks, enabling absolute position measurement with no cumulative drift due to absolute value coded. Key advantages include electromagnetic immunity through purely optical measurement principles, working distances from 50 mm to 15 m, and multi-degree-of-freedom sensitivity perpendicular to the optical axis. RasCal, a comprehensive control and analysis software, is presented in this paper and its real-time image processing shows 5 pm/$\sqrt{\text{Hz}}$ spatial resolution. With GPU acceleration, 274.5 Hz is achieved during live camera acquisition and 109 Hz on CPU. In maximum-throughput configurations, the processing rates exceed 300 Hz on simple consumer hardware. System performance is demonstrated across diverse applications: 5 pm/$\sqrt{\text{Hz}}$ displacement sensitivity is achieved in the VATIGrav setup, dynamic behavior is characterized with a Watt's linkage. In addition, the lack of cumulative drift due to absolute coding with minimal thermal sensitivity under controlled conditions is used for vibration and thermal characterization of photodiode mounts for the LISA space mission. Millisecond-level command latency and thread-safe multi-camera support are provided by the RasCal software, establishing it as a robust and cost-effective precision measurement solution for demanding alignment applications in gravitational-wave detectors and space instrumentation.

Mode-locked lasers (MLLs) are essential for a wide range of photonic applications, such as frequency metrology, biological imaging, and high-bandwidth coherent communications. The growing demand for compact and scalable photonic systems is driving the development of MLLs on various integrated photonics material platforms. Along these lines, developing MLLs on the emerging thin-film lithium niobate (TFLN) platform holds the promise to greatly broaden the application space of MLLs by harnessing TFLN 's unique electro-optic (E-O) response and quadratic optical nonlinearity. Here, we demonstrate the first electrically pumped, self-starting passive MLL in lithium niobate integrated photonics based on its hybrid integration with a GaAs quantum-well gain medium and saturable absorber. Our demonstrated MLL generates 4.3-ps optical pulses centered around 1060 nm with on-chip peak power exceeding 44 mW. The pulse duration can be further compressed to 1.75 ps via linear dispersion compensation. Remarkably, passive mode-locking occurs exclusively at the second harmonic of the cavity free spectral range, exhibiting a high pulse repetition rate $\sim$20 GHz. We elucidate the temporal dynamics underlying this self-starting passive harmonic mode-locking behavior using a traveling-wave model. Our work offers new insights into the realization of compact, high-repetition-rate MLLs in the TFLN platform, with promising applications for monolithic ultrafast microwave waveform sampling and analog-to-digital conversion.

The Electromagnetic Calorimeter (ECAL), consisting of 1,596 lead tungstate scintillating crystals, has been recently constructed and installed in Experimental Hall D at Jefferson Lab (JLab). The calorimeter is a key component of the JLab Eta Factory Experiment, whose main goal is to measure the decays of eta and eta prime mesons into multi-photon final states. The ECAL replaces the inner part of the former forward lead-glass calorimeter. Scintillation light from each crystal is detected using Hamamatsu R4125 photomultiplier tubes. Calorimeter modules were fabricated and tested in the lab using light from light-emitting diodes before being installed in the detector frame. The detector is currently undergoing commissioning using the light monitoring system and cosmic rays. We will present an overview of the fabrication and testing of the calorimete modules, along with the first detector commissioning results. The ECAL was ready for data-taking in spring 2025.

Writing is a critical skill for modern science, enabling collaboration, scientific discourse, public outreach, and more. Accordingly, it is important to consider how physicists and astronomers are trained to write. This study aims to understand the landscape of science writing education, specifically in physics and astronomy, in higher education in the United States. An online survey probing various aspects of their writing training in both undergraduate and graduate school was administered to 515 participants who have obtained training in physics and/or astronomy, or related fields, at the level equal to or beyond upper-division undergraduate study. Humanities and writing requirement courses appear to have a key role in general writing education, while laboratory courses and feedback from mentors are the dominant modes of science writing education in undergraduate and graduate school respectively. There is substantial variation in the quality of writing education in physics and astronomy, often dependent on the student's institution and/or mentor. Some participants also report that their success in disciplinary writing was a result of a solid foundation from K-12 education and/or self-direction towards resources; such reliance on past experiences and student background may contribute to inequality in the field. Many participants also stated a clear desire for more structured writing training to be available in the field. We provide suggestions for how to implement such training to meet the needs of the community identified in the survey.

Precise measurement of radiation has long played a vital role in a wide range of research and industrial fields, from fundamental physics beyond the Standard Model to medical imaging such as time-of-flight positron emission tomography. Developing radiation detectors that achieve high timing precision-on the order of a few tens of picoseconds-and energy measurement capabilities remains indispensable yet challenging. In this study, we developed two types of scintillator-integrated microchannel plate photomultiplier tubes (SCI-IMPs), one incorporating barium fluoride, and the other bismuth germanate, to enable simultaneous high-precision timing and energy measurements. To evaluate their performance over a wide energy range from keV- to GeV-scale, electron-positron annihilation gamma rays and cosmic ray muons were used. For energy measurements, both detectors achieved an energy resolution of approximately 35% at 511 keV. For timing measurements using 511 keV, coincidence time resolutions (CTRs) of approximately 50 ps full width at half maximum (FWHM) were obtained for both detectors. In contrast, for cosmic ray muon experiments where cosmic ray muon energy is typically on the order of GeV, CTRs were measured to be 25.1 and 16.8 ps FWHM for barium fluoride- and bismuth germanate-based detectors, respectively. The versatile scintillator-integration technique established in this study can broaden the applicability of the newly developed SCI-IMPs. In particular, these results demonstrate that the developed detectors push the boundaries of timing performance while retaining energy measurement and hold promise for future applications in fundamental physics experiments and medical imaging.

Machine learning interatomic potentials (MLIPs) combine near-ab initio accuracy with the computational efficiency of classical force fields, making them promising tools for modeling molecular liquids and electrolytes. Their predictive accuracy depends strongly on the diversity of the training set, while the explicit treatment of electrostatics is increasingly recognized as an important factor in improving their performance. In this work, we assess the impact of incorporating explicit electrostatics and environment-dependence of atomic charges by comparing short-ranged Moment Tensor Potentials (MTPs) with electrostatics-augmented MTPs, including fixed-charge and environment-dependent charge models. To this end, we employ D-optimality-based active learning (AL) to train short-ranged MTPs and extend the AL procedure, previously unavailable for long-range electrostatics-augmented MTPs, to these models, enabling largely automated generation of diverse training sets for pure ethylene carbonate (EC) and ethyl methyl carbonate (EMC), their mixtures, and LiPF6 solutions. For EC, EMC, and their mixtures, electrostatics-augmented MTPs achieve accuracy comparable to or better than that of their short-ranged counterparts while requiring fewer machine-learned parameters. For LiPF6 solutions, however, a notable improvement in accuracy is achieved only with environment-dependent charges, which also enhance stability in large-scale molecular dynamics simulations, unlike the fixed-charge model. The resulting short-ranged MTPs and environment-dependent-charge models reproduce experimental densities with mean absolute deviations of 0.2-6% and ionic conductivities with deviations of 11-15%, while capturing the experimentally observed temperature dependence of conductivity.

Long-axial field-of-view (LAFOV) PET/CT has the potential to redefine the role of molecular imaging in theranostics by making multiparametric whole-body (MPWB) imaging and predictive dosimetry more clinically feasible. Compared to conventional PET systems, LAFOV scanners provide dramatic gains in sensitivity and coverage, allowing dynamic acquisitions, delayed imaging, and dual-tracer protocols within clinically feasible workflows. These advances supply the quantitative data required for physiologically based pharmacokinetic (PBPK) modeling and the creation of theranostic digital twins, supporting true personalization of radiopharmaceutical therapy.

Elongate animals and robots use undulatory body waves to locomote through diverse environments. Geometric mechanics provides a framework to model and optimize such systems in highly damped environments, connecting a prescribed shape change pattern (gait) with locomotion displacement. However, the practical applicability of controlling compliant physical robots remains to be demonstrated. In this work, we develop a framework based on geometric mechanics to predict locomotor performance and search for optimal swimming strategies of compliant swimmers. We introduce a compliant extension of Purcell's three-link swimmer by incorporating series-connected springs at the joints. Body dynamics are derived using resistive force theory. Geometric mechanics is incorporated into movement prediction and into an optimization framework that identifies strategies for controlling compliant swimmers to achieve maximal displacement. We validate our framework on a physical cable-driven three-link limbless robot and demonstrate accurate prediction and optimization of locomotor performance under varied programmed, state-dependent compliance in a granular medium. Our results establish a systematic, physics-based approach for modeling and controlling compliant swimming locomotion, highlighting compliance as a design feature that can be exploited for robust movement in both homogeneous and heterogeneous environments.

Quantitative photoacoustic computed tomography (qPACT) is a promising imaging modality for estimating physiological parameters such as blood oxygen saturation. However, developing robust qPACT reconstruction methods remains challenging due to computational demands, modeling difficulties, and experimental uncertainties. Learning-based methods have been proposed to address these issues but remain largely unvalidated. Virtual imaging (VI) studies are essential for validating such methods early in development, before proceeding to less-controlled phantom or in vivo studies. Effective VI studies must employ ensembles of stochastically generated numerical phantoms that accurately reflect relevant anatomy and physiology. Yet, most prior VI studies for qPACT relied on overly simplified phantoms. In this work, a realistic VI testbed is employed for the first time to assess a representative 3D learning-based qPACT reconstruction method for breast imaging. The method is evaluated across subject variability and physical factors such as measurement noise and acoustic aberrations, offering insights into its strengths and limitations.

The ionizations per photon, or S/XB, method uses spectroscopic measurements of radiating impurity ions to determine the influx from a solid surface. It is highly useful as a non-perturbing, in-situ measure of the gross erosion flux of plasma-facing components (PFCs). In sheared-flow-stabilized (SFS) Z-pinch devices, the electrode supplies the plasma current and directly contacts the core Z-pinch plasma. Electrode erosion due to the large particle and heat fluxes affects electrode durability, which is an important factor in existing and future devices. An improved understanding of these plasma-electrode interactions is required, in particular as energy density increases. Experiments on the ZaP-HD device investigate erosion of the graphite electrode by applying the S/XB method for C-III emission at 229.7 nm. The S/XB coefficients are determined from electron density and temperature profiles obtained from Digital Holographic Interferometry (DHI) measurements. An approach for expanding these profiles to represent plasma contacting the electrode is described. In both cases, the measured erosion fluxes are on the order of 10$^{30}$-10$^{31}$ atoms m$^{-2}$s$^{-1}$. These values are significantly larger than the expected erosion flux due to physical sputtering of H$^+$ ions on carbon, but are comparable to theoretical sublimation fluxes. This suggests that the source of carbon erosion flux is primarily from sublimation as opposed to sputtering. The dominance of sublimation over sputtering processes implies a difference in energy of the eroded neutrals which may provide insight on redeposition and net erosion behavior.

Although transient convection is ubiquitous in natural and manmade phenomena, few research works attempted to make a compact model for it, altogether, others attempted a compact model that contradicts problem physics. The correct modelling pattern is deduced here analytically for a simple geometry, but it can readily be used for many common applications such as the transient heating of an evacuated solar tube due to temporary cloud shading or for a more precise model of transient building wall heating in a zero-energy building approach. As opposed to detailed model, which is based on the governing PDE with a fixed and rigid boundary and initial conditions, usually solved numerically, aiming at obtaining temperatures everywhere and at any time for a prescribed boundary and initial conditions, the compact model on the contrary is based on a few simple equations, and aims at giving directly the relation between heat flux and the temperature difference producing it, for any boundary and initial conditions. For transient convection prevails as of today an unphysical approach consisting of modeling it by using a time variant thermal resistance. In this work, starting from the energy PDE, applied to a simple but typical transient forced convection problem, we will get analytically the correct modelling pattern. This has two main advantages: It replaces the classical unphysical approach, with a pair of time constants, one for each important temperature (the fluid bulk and that near the wall), which has an evident physical meaning and can be readily extended to more complex geometries. In contrast with the time varying resistance model, one and the same model as deduced here can be reused for any arbitrary time varying function of the input heat flux. Model validation was made by comparing with a fully blown CFD simulation.

Pairing the accuracy of Kohn-Sham density-functional framework with the efficiency of a stochastic algorithmic approach, mixed stochastic-deterministic Density Functional Theory (mDFT) achieves a favorable computational scaling with system sizes and electronic temperatures. We employ the recently developed mDFT formalism to investigate the dynamic charge-transport properties of systems in the warm dense matter regime. The optical conductivity spectra are computed for single- and multi- component mixtures of carbon, hydrogen, and beryllium using two complementary approaches: Kubo-Greenwood in the mDFT picture and real-time Time-Dependent mDFT. We further devise a decomposition of the Onsager coefficients leading up to the Kubo-Greenwood spectra to exhibit contributions from the deterministic, stochastic, and mixed electronic state transitions at different incident photon energies.

Submarine hydrodynamics presents unique challenges in accurately predicting flow separation, wake structure, and resistance due to complex geometry and turbulent behaviour at high Reynolds (Re) numbers. Traditional Reynolds-Averaged Navier-Stokes (RANS) approaches are often limited in resolving unsteady flow structures and turbulence in the near and far regions. To address these limitations, hybrid RANS-LES models such as Detached Eddy Simulation (DES) and Large Eddy Simulation (LES) offer improved performance in capturing near-wall vortical structures. The capturing of turbulent vortices and wake structures significantly contributes to conduct hydrodynamic noise analysis. Detailed resolution and understanding of these coherent structures help minimize hydroacoustic signatures, essential for submarines' stealth characteristics. Based on prior studies, Breuer et al. (2003) reported that RANS failed to capture unsteady vortex shedding, producing only steady results even in 3D simulations. In contrast, DES and LES successfully resolved asymmetric shedding across different grid resolutions. Spalart (2009) reported that DES is more effective than RANS or LES for high Re flows, although it suffers from challenges related to ambiguous grids and nonmonotonic grid refinement behaviour. Whereas Liang & Xue (2014) found that DES predicts tip vortex flow characteristics more accurately than RANS-SA and can capture complex 3D vortex structures. In addition, Guilmineau et al. (2018) demonstrated that the IDDES model accurately predicts recirculation bubbles and aligns more closely with experimental data for flow prediction. Long et al. (2021) confirmed the capability of DDES in simulating cavitating flows around hydrofoils and marine propellers. Lungu (2022) highlighted the efficiency and accuracy of the hybrid IDDES-SST model in DARPA submarine simulations. Zhang et al. (2023) also noted that URANS struggles with resolving small-scale turbulence structures, whereas IDDES is better suited for predicting complex phenomena such as ship air wake asymmetry. Nevertheless, capturing the unsteadiness and turbulence fluctuations scales is extremely challenging because the cell size requirements should suit each turbulence model employed. Thus, as a continuation of the prior work of Abidin et al. (2024), the unsteady simulation with high mesh resolution at $U_m=1.8235$ m/s and Re of $3.6\times 10^6$ to generate the asymmetrical wake dynamic and vortical structure. The current research expands the methodology by parameterizing the meshes and numerical scheme based on Taylor microscale refinement with respect to the characteristic length of (L, B and D) of submarine, particularly focusing on hybrid turbulence model and WALE to observe the ability to resolve turbulence in the wake region. The transient simulations were performed initially using wall-resolved mesh (76x10^6 cells) at y^+ < 5 and then wall-modelled mesh (56x10^6 to 74x10^6 cells) at y^+ > 30, which produced notably different and more detailed results (vortices and turbulence fluctuation) than previous steady-state RANS simulations without risking the accuracy of quantity of interest (global resistance).

This short review is devoted to celebration of two major events in quantum physics. The first one is the birth of the concept of Bose-Einstein condensation (1925) and the second is the experimental proof that it does exist and appears in the liquid 4He simultaneously with superfluidity below the $\lambda$-point (1975). The both of these events are tightly related to the Bogoliubov theory of superfluidity (1947). The existence of condensate in the system of interacting bosons is the key ansatz of this theory. Therefore, the experiments started in JINR in 1975 confirmed this prediction of the Bogoliubov theory that superfluidity of the liquid 4He (He II) should emerge at the same time as the Bose-Einstein condensation.

Assessing turbulence control effects for wall friction numerically is a significant challenge since it requires expensive simulations of turbulent fluid dynamics. We instead propose an efficient deep reinforcement learning (RL) framework for modeling and control of turbulent flows. It is model-based RL for predictive control (PC), where both the policy and the observer models for turbulence control are learned jointly using Physics Informed Neural Operators (PINO), which are discretization invariant and can capture fine scales in turbulent flows accurately. Our PINO-PC outperforms prior model-free reinforcement learning methods in various challenging scenarios where the flows are of high Reynolds numbers and unseen, i.e., not provided during model training. We find that PINO-PC achieves a drag reduction of 39.0% under a bulk-velocity Reynolds number of 15,000, outperforming previous fluid control methods by more than 32%.

Polarization maintaining (PM), all-fiber amplifiers offer the benefits of alignment free and environmentally stable operation. To achieve high output powers, particularly in pulsed operation, it is necessary to balance the need to reduce deleterious nonlinear effects, often through the use of large mode area (LMA) fibers, with the onset of transverse mode instability whereby higher order modes (HOMs) mix with the desired fundamental mode output. Over the last few years, advances in high HOM loss, ytterbium-doped LMA fibers have enabled continuous wave (CW) output powers up to 5 kW and pulse energies up to 2 mJ in non-PM fibers. In CW operation, LMA PM fibers have shown up to 2 kW of average power. In this contribution, we present all-fiber nanosecond pulsed amplification in a high HOM loss, Yb-doped LMA fiber with a 26 micrometer mode field diameter and 2.4 dB/m of pump absorption at 976 nm, achieving 1 mJ of pulse energy at 1 kW of average power, and 1.5 mJ of pulse energy at 750 W of average power. The polarization extinction ratios were 20 dB or higher and the M2 was near the diffraction limit. We measured the in-pulse to out-of-pulse energy and found 99.9% or more of the measured power remained in-pulse.

Stokes polarimetry has been considered as an alluring platform that enables a plethora of applications ranging from single-molecule orientation to deep-space sensing. Existing polarimetry avenues, however, rely primarily on the transversely polarized field reconstruction, thus suffering from several challenges such as multiple time sequenced detections, complex demodulation algorithms, and intricate engineering procedures. To circumvent these challenges, here we first demonstrate a longitudinally polarized field mediated recipe for the realization of efficacious and refined Stokes polarimetry in situ. This is achieved by unraveling the spin-to-orbit momentum conversion under non-paraxial focusing conditions enabling the direct mapping of the polarization ellipse. Leveraging this mechanism, we reveal an analytical solution of polarization ellipse via the local sampling of longitudinal field, in which the robustness can be fairly reinforced by relevant global retrieval based on convolutional neural network. The resultant Stokes polarimetry is shown to simultaneously exhibit in-situ signal acquisition (direct discernment), unparalleled demodulation time (up tomicrosecond level), superior detection efficiency (no need of troublesome design), and ultra-high retrieved accuracy (less than 1%), which is fundamentally inaccessible with traditional polarimetry methods. Our work holds great promise for empowering an allin-one versatile vector polarimeter, which opens up a host of applications relevant to polarization control.

The influence of low-spatial frequency errors of an optical component of an imaging system on the point spread function can be quantified using Zernike polynomials. High-spatial frequency errors cause strong scattering due to which the focused energy is reduced but the shape of the point spread function is mainly preserved. In contrast, the influence of mid-spatial frequency errors is more difficult to quantify. Using a scalar diffraction model we evaluate the point-spread function in the presence of such errors and compare the results with experiments.

In astrophysical shear flows, the Kelvin-Helmholtz (KH) instability is generally suppressed by magnetic tension provided a sufficiently strong streamwise magnetic field. This is often used to infer upper (or lower) bounds on field strengths in systems where shear-driven fluctuations are (or are not) observed, on the basis that perturbations cannot grow in the absence of linear instability. On the contrary, by calculating the maximum growth that small-amplitude perturbations can achieve in finite time for such a system, we show that perturbations can grow in energy by orders of magnitude even when the flow is sub-Alfvénic, raising the possibility that shear-driven turbulence may be found even in the presence of strong magnetic fields, and challenging inferences from the observed presence or absence of shear-driven fluctuations. We further show that magnetic fields introduce additional nonmodal growth mechanisms relative to the hydrodynamic case, and that 2D simulations miss key aspects of these growth mechanisms.

Periodically time-varying media, known as photonic time crystals (PTCs), provide a promising platform for observing unconventional wave phenomena. We analyze the scattering of electromagnetic waves from spatially finite PTCs using the multispectral Floquet scattering matrix, which naturally incorporates the frequency-mixing processes intrinsic to such systems. For dispersionless, real, and time-periodic permittivities, this matrix is pseudounitary. Here we demonstrate that this property leads to multiple symmetry-breaking transitions: for increasing driving strength, scattering matrix eigenvalues lying on the unit circle (unbroken symmetry regime) meet at exceptional points (EPs), where they break up into inverse complex conjugate pairs (broken symmetry regime). We identify the symmetry operator associated with these transitions and show that, in time-symmetric systems, it corresponds to the time-reversal operator. Remarkably, at the parametric resonance condition, one eigenvalue vanishes while its partner diverges, signifying simultaneous coherent perfect absorption (CPA) and lasing. Since our approach relies solely on the Floquet scattering matrix, it is not restricted to a specific geometry but instead applies to any periodically time-varying scattering system. To illustrate this universality, we apply our method to a variety of periodically time-modulated structures, including slabs, spheres, and metasurfaces. In particular, we show that using quasi-bound states in the continuum resonances sustained by a metasurface, the CPA and lasing conditions can be attained for a minimal modulation strength of the permittivity. Our results pave the way for engineering time-modulated photonic systems with tailored scattering properties, opening new avenues for dynamic control of light in next-generation optical devices.

Herein, a self-assembled hierarchical structure of hematite ($\alpha$-$Fe_2O_3$) was synthesized via a one-pot hydrothermal method. Subsequently, the nanomaterial was doped to get $M_{x}Fe_{2-x}O_3$ (M = Mn-Co; x = 0.01, 0.05, 0.1) at precise concentrations. The electrode was fabricated by coating the resulting nanocomposite onto a Nickel Foam (NF) substrate. The electrochemical characterization demonstrated the excellent performance of cobalt-doped $\alpha$-$Fe_2O_3$, among which, $Co_0.05Fe_0.95O_3$ (CF5) exhibited superior performance, showing a two-fold increase in sensitivity of 1364.2 $\mu$A.m$M^{-1}$.$cm^{-2}$ $(\pm 0.03, n = 3)$ in 0.5 M KOH, a Limit of Detection (LOD) of $\sim 0.17 mM$, and a Limit of Quantification (LOQ) of {\sim}0.58 mM. Density Functional Theory (DFT) was performed to understand the doping prompting in the reduced bandgap. The fabricated electrode displayed a rapid response time of 2 s and demonstrated 95% stability, excellent reproducibility, and selectivity, as confirmed by tests with several interfering species. A comprehensive evaluation of the electrode's performance using human blood serum highlighted its robustness and reliability for cholesterol detection in clinical settings, making it a promising tool for clinical and pharmaceutical applications.

Enabling coherent light-matter interactions is a critical step toward next-generation quantum technologies. However, achieving this under ambient temperature conditions remains challenging due to rapid dephasing in optically excited systems. Optical metasurfaces based on quasi-bound states in the continuum have recently emerged as a powerful platform for reaching the strong light-matter coupling regime in flat, subwavelength thickness devices. Here, we investigate ultrafast exciton-polariton dynamics in self-hybridized WS$_2$ thin-film metasurfaces. Using hyperspectral momentum-resolved imaging, we reconstruct the highly anisotropic exciton-polariton dispersion, with a transition from positive to negative effective mass along orthogonal symmetry axes. Femtosecond pump-probe and multidimensional spectroscopy reveal detuning-dependent polariton dynamics with a coherence time up to ~110 fs, and allow direct observation of the coherent dynamics through ultrafast Rabi oscillations with ~45 fs period. We describe this behaviour with a three-eigenstate model that couples the photonic resonance with both bright and dark excitons, extending the conventional two-state picture of strong coupling. Our results establish van der Waals metasurfaces as a promising platform for next-generation polaritonic devices, enabling coherent quantum transfer of matter excitations at room temperature.