Papers

Broadband optical response governs light-matter interactions across photonics, plasmonics, thermal radiation, and quantum fluctuation electrodynamics, yet determining a continuous dielectric function over many decades in frequency typically requires combining multiple spectroscopies, extrapolations, and material models. Here we show that quantum-fluctuation forces provide a route to broadband optical characterization. Casimir interactions depend on the dielectric response of materials across the electromagnetic spectrum, but this information is encoded through Lifshitz theory in a spectrally weighted and nontrivial way. By training physics-constrained supervised learning models on synthetic dielectric spectra and their corresponding Casimir force curves, we invert this relationship and constrain the complex permittivity of materials over more than seven orders of magnitude in frequency and provide an estimate of their values from force-distance data. The reconstruction reveals a direct separation-frequency correspondence: large separations constrain the free-carrier response, whereas shorter separations encode higher-frequency resonant structure. Applying the method to measured force gradients identifies the current experimental limits imposed by measurement noise, restricted separation range, and model complexity. These results establish fluctuation-induced forces as a spectrally weighted route to broadband optical characterization and define the experimental and physical limits that govern what spectral information is accessible from near-field quantum electromagnetic measurements.

Modeling yield stress fluids in complex flow scenarios presents significant challenges, particularly because conventional rheological characterization methods often yield material parameters that are not fully representative of the intricate constitutive behavior observed in complex conditions. We propose a Bayesian uncertainty quantification framework for the calibration and selection of constitutive models for yield stress fluids, explicitly accounting for uncertainties in both modeling accuracy and experimental observations. The framework addresses the challenge of complex flow modeling by making discrepancies that emanate from rheological measurements explicit and quantifiable. We apply the Bayesian framework to rheological measurements and squeeze flow experiments on Carbopol 980. Our analysis demonstrates that Bayesian model selection yields robust probabilistic predictions and provides an objective assessment of model suitability through evaluated plausibilities. The framework naturally penalizes unnecessary complexity and shows that the optimal model choice depends on the incorporated physics, the prior information, and the availability of data. In rheological settings, the Herschel-Bulkley and biviscous power law models perform well. However, when these rheological outcomes are used as prior information for a rheo-informed squeeze flow analysis, a significant mismatch with the experimental data is observed. This is due to the yield stress inferred from rheological measurements not being representative of the complex squeeze flow case. In contrast, an expert-informed squeeze flow analysis, based on broader priors, yields accurate predictions. These findings highlight the limitations of translating rheological measurements to complex flows and underscore the value of Bayesian approaches in quantifying model bias and guiding model selection under uncertainty.

Mo-Si multilayer mirrors are central to extreme ultraviolet lithography, where nanoscale optical interference and heat accumulation together constrain reflectivity and operational stability. Here we develop an analytical electromagnetic-thermal coupling model that directly links transfer-matrix-based interference-controlled energy deposition with transient heat conduction in EUV-irradiated multilayers. The model reveals a fundamental trade-off whereby increasing the multilayer period number enhances reflectivity but simultaneously elevates temperature by impeding heat dissipation. Interference-driven volumetric absorption further gives rise to pronounced axial temperature gradients and a post-pulse downward migration of the heat-flux maximum, a delayed-heating effect inaccessible to conventional surface-flux-based models. Systematic analysis establishes scaling laws connecting interfacial thermal resistance, beam size, and incident energy density to thermal confinement and temperature rise. By incorporating interfacial compaction kinetics, the model enables a quantitative assessment of mirror lifetime. This work offers a theoretical tool for thermal-optical co-design of multilayer nanostructures including EUV mirrors under pulsed irradiation across a wide spectral range.

Static phase detuning fundamentally constrains coherent state transfer in asymmetric classical and quantum systems. We introduce a Bloch-sphere formulation for piecewise-coherent modulation that recasts coupled-mode dynamics as geometric trajectories, transforming algebraic control into path optimization. The approach reveals a cone of inaccessibility at the target pole and yields exact geodesic criteria for complete mode conversion in detuned systems. Leveraging this framework, we break time-reversal symmetry to realize a magnet-free optical isolator with near-unity contrast. Furthermore, for detuning larger than coupling between modes, we develop a recursive multi-step protocol enabling deterministic transfer for arbitrary detunings and derive a universal geometric lower bound on the required number of coupling-switching events.

Targeting a cone with the half-angle as 10-deg at M = 27 and H = 72 km, simulations were conducted comparatively to analyze the predictions by different equilibrium and non-equilibrium gas models. Following validation and grid studies, systematic comparisons on aerodynamic performance, flow structures, and characteristic distributions were performed. The key findings are: (1) While the overall flow structures are broadly similar, discrepancies exist in the features at the base locations, e.g., the diverse high-temperature distributions. Notably, the vibrational temperatures distribute differently under slip and non-slip boundary conditions near the wall; (2) The equilibrium gas model predicts higher drag coefficient, wall heat flux, and skin friction than those of non-equilibrium models. Predictions also vary among the non-equilibrium models themselves. Specifically, compared to the three-temperature model, the one- and two-temperature models predict larger drag coefficients with the relative difference exceeding 5%. Nevertheless, the results from the three-temperature model with and without slip conditions are largely consistent; (3) The disparities between equilibrium and non-equilibrium characteristics are primarily manifested in the shock layer and wake regions. Within these regions, the overall temperature for the equilibrium gas is lower than that for the non-equilibrium cases, while in the latter specific non-equilibrium features are distinctly exhibited, e.g., the translational-rotational temperature is generally higher than that from the one-temperature model, and the vibrational-electronic temperature shows the opposite trend. Notably, in the slip flow within the three-temperature model, the translational-rotational temperature is higher and, particularly, the vibrational temperature is even larger than counterparts of the non-slip flows near the wall and base center line.

We present a model of active particles interacting through a dynamic, heterogeneous environment, leading to emergent collective behaviors without direct agent-to-agent communication. Expanding the resource-dependent framework introduced in Briozzo et al., 2025, arXiv:2512.08762, agents perform a persistent random walk combined with chemotaxis, directing toward nutrient-rich patches, whose resources are generated by logistic regrowth. We identify distinct phases of collective organization, ranging from disordered gas-like states to polar traveling waves and nematic independent clusters, depending on the interplay between chemotactic sensitivity and angular noise. The system exhibits spontaneous symmetry breaking and density waves driven purely by the coupling between population dynamics (birth-death processes) and environmental feedback. Our results bridge active matter physics and movement ecology, demonstrating that complex spatiotemporal patterns can arise without direct interaction between agents, but solely from the maximization of resource intake in a reactive environment.

Sheath formation near biased electrodes in magnetic fields parallel to the wall is an understudied topic, especially within the context of Z-pinch fusion experiments. We perform 1X-2V Boltzmann-Poisson simulations of an axial cut at the pinch radius of a Z-pinch plasma between two biased electrodes with a magnetic field parallel to the wall. The collision frequencies are artificially increased to enhance thermalization of the plasma in the smaller simulation domain versus the actual experiment size; this increases the perpendicular mobility and partially de-magnetizes the ions resulting in non-monotonic sheath profiles with the potential increasing away from the wall to a peak before decaying. A classical sheath forms within an electron gyroradius from the wall not due to the natural thermal motion of the electrons, but due to the magnetized electrons gyrating into the wall; therefore, the sheath structure does not significantly change with bias potential or between electrodes. With increasing bias potential, a current is induced perpendicular to the wall due to changes in ion flow, differing from unmagnetized cases where current is induced by changes in electron flow. The magnetic field acts as a high resistivity with the perpendicular current density being three orders of magnitude lower than unmagnetized theoretical predictions. There is, however, significant flow parallel to the wall from the force balance between the pressure tensor and Lorentz force. These parallel flows induce a parallel current density three orders of magnitude larger than the perpendicular current density.

Memory effects are essential for dynamics of condensed materials and are responsible for non-exponential relaxation of correlation functions of dynamic variables through the memory function. Memory functions of dipole rotations for polar liquids have never been calculated. We present here calculations of memory functions for single-dipole rotations and for the overall dipole moment of the sample for SPC/E water. The memory functions for single-particle and collective dipole dynamics turn out to be nearly identical. This result validates theories of dielectric spectroscopy in terms of single-particle time correlation functions and the connection between the collective and single-particle relaxation times through the Kirkwood factor. The dielectric function in this formalism contains no new dynamic information that does not exist in the single-dipole correlation function. A short memory time, $\lesssim 1$ fs, justifies the use of rotational diffusion model to describe dynamics of a single molecular dipole moment in bulk water.

Superconductivity in sulfur superhydride H$_{3}$S under extreme pressures has been explained theoretically, but it requires a peaked concentration of the electronic density of states (DOS), which has been found in first-principles calculations. The mechanism of this peak formation, though vital for its high transition temperature, has however remained obscure. We address this problem through detailed analysis of the first-principles electronic wave functions. The valence wave functions are shown to be significantly plane-wave-like. From the Fourier-mode analysis of the self-consistent potential and atomic pseudopotentials, we extract the nearly uniform models that accurately reproduce the first-principles band structure with very few parameters. The DOS peak is shown to be the consequence of the hybridization of specific plane waves. Adjacency of Jones' large zone to the plane-wave spherical Fermi surface is posited to be the root cause of the multiple plane-wave hybridization, the DOS peak formation and its proximity to the Fermi level. The present theory resolves the minimal modeling problem of electronic states in H$_{3}$S, as well as establishes a mechanism that may help to boost the transition temperatures in pressure induced superconductors.

Integrating computation into physics teaching is a curricular move that, at present, has been predominately studied for its cognitive impacts. However, if this modality of instruction shifts how students engage with physics, we argue there is room for students to redefine what it means to do physics and how they perceive themselves relative to the field. To investigate this, we situate a comparative case study in the context of a computationally integrated physics course. We study two students' experiences with a multi-day activity to understand how and why they came to affectively divergent self-perceptions. We propose a modified use of conjecture mapping to visualize the production of affective outcomes and connect narrative analysis to activity design. Our analysis highlights how different interpretations of and engagement with activity design reflect students' epistemic framing of code, which, in turn, drives engagement with scaffolding in manners that shape self-perception.

Accurately capturing electron correlation in large-scale molecular systems remains one of the foremost challenges in quantum chemistry and a primary driver for the development of quantum algorithms. Classical configuration-interaction methods, while rigorous, suffer from exponential scaling, rendering them impractical for large or strongly correlated systems. Overcoming this limitation is central to realizing the promise of quantum computing in chemistry. Here, we investigate the pyridine-Li ion complex using three quantum algorithms: the variational quantum eigensolver (VQE), the subspace quantum diagonalization (SQD) method, and the recently introduced handover iterative VQE (HI-VQE). Our results demonstrate how new generations of hybrid quantum-classical frameworks overcome the scalability and noise sensitivity that constrain conventional VQE approaches. SQD and HI-VQE achieve ground-state energy calculations for problem sizes inaccessible to classical computation, marking a clear advance toward quantum advantage. In particular, HI-VQE enables calculations within active spaces as large as (24e,22o), requiring 44 qubits-well beyond the reach of classical CASCI and VQE. This capability provides a systematic pathway for incorporating increasing numbers of electrons into quantum treatment, thereby approaching exact molecular energies. Importantly, both SQD and HI-VQE exhibit robustness against hardware noise, a critical improvement over earlier approaches. By enabling quantum simulations of molecular systems previously deemed intractable, SQD and HI-VQE offer a realistic route toward practical quantum advantage in computational chemistry. The comparison between HI-VQE and SQD shows that optimizing circuit parameters is crucial for accurate simulation.

One of the most public episodes of gatekeeping in modern science was the case of so-called 'cold fusion'. At a news conference in 1989 the electrochemists Martin Fleischmann and Stanley Pons announced that they had found evidence of nuclear fusion in palladium electrodes loaded with deuterium. There was worldwide interest. Many groups sought to reproduce the results, most unsuccessfully. Within months, the prevailing view became strongly negative. The claims of Fleischmann and Pons came to be regarded as disreputable, as well as false. As the Caltech physicist David Goldstein put it, cold fusion became 'a pariah field, cast out by the scientific establishment' (Goldstein 1994). The case would already be interesting for students of gatekeeping if the story had ended at that point. Even more interestingly, however, the field survived and persisted. It has been enjoying a modest renaissance, with recent government funding both in the US and the EU. This piece offers an opinionated introduction to cold fusion as a case study of scientific gatekeeping, discussing both its early and recent history

Photon statistics plays a governing role in multi-photon interference. While interference visibility in the standard two-photon case, known as Hong-Ou-Mandel interference, monotonically degrades with higher intensity correlation functions, we show that this monotonicity does not hold for three-photon interference in symmetric circuits. We reveal that, in the discrete Fourier transform circuit, engineered super-Poissonian photon-number fluctuations, realized using a modulated laser, maximize the visibility, surpassing the magnitude of the single-photon signature. In addition, by tuning the symmetric circuit parameters, we demonstrate that the visibility hierarchy inverts relative to the benchmark of Poissonian statistics. This trade-off implies that quantum and classical advantages are mutually exclusive resources for interference, indicating a form of statistical complementarity.

Interface circuits are the key components that enable the hybrid integration of superconductor and semiconductor digital electronics. The design requirements of superconductor-semiconductor interface circuits vary depending on the application, such as high-performance classical computing, superconducting quantum computing, and digital signal processing. In this survey, various interface circuits are categorized based on the working principle and structure. The superconducting output drivers are explored, which are capable of converting and amplifying, e.g., single flux quantum (SFQ) voltage pulses, to voltage levels that semiconductor circuits can process. Several trade-offs between circuit- and system-level design parameters are examined. Accordingly, parameters such as the data rate, output voltage, power dissipation, layout area, thermal/heat load of cryogenic cables, and bit-error rate are considered.

This exploratory study examines the classroom deployment of aiPlato, an AI-enabled homework platform, in a large introductory physics course at the University of Texas at Arlington. Designed to support open-ended problem solving, aiPlato provides step-wise feedback and iterative guidance through tools such as "Evaluate My Work" and "AI Tutor Chat", while preserving opportunities for productive struggle. Over four optional extra-credit assignments, the platform captured detailed student interaction data, which were analyzed alongside course performance and end-of-semester survey responses. We examine how students engaged with different feedback tools, whether engagement patterns were associated with performance on the cumulative final exam, and how students perceived the platform's usability and learning value. Students who engaged more frequently with aiPlato tended to achieve higher final exam scores, with a mean difference corresponding to a standardized effect size of approximately 0.81 between high and low engagement groups after controlling for prior academic performance. Usage patterns and survey responses indicate that students primarily relied on iterative, formative feedback rather than solution-revealing assistance. As a quasi-experimental pilot study, these findings do not establish causality and may reflect self-selection effects. Nonetheless, the results demonstrate the feasibility of integrating AI-mediated, step-wise feedback into authentic physics homework and motivate future controlled studies of AI-assisted tutoring systems.

Interfering deep ultraviolet (DUV) lasers can induce substantial density modulations in an ozone-doped gas flow via photochemical reactions, creating volume diffraction gratings. These transient optics are immune to target debris and shrapnel and feature orders-of-magnitude higher damage thresholds than conventional solid optics, providing a promising method for efficiently manipulating high-energy lasers. In this work, we describe gas gratings that can efficiently diffract probe beams across a variety of wavelengths and pulse durations, ranging from deep ultraviolet to near-infrared and from nanosecond to femtosecond, achieving a full beam diffraction efficiency up to 99% while preserving the focusability and wavefront quality. In addition, we present a comprehensive characterization of the performance of the gas gratings under various experimental conditions, including imprint fluence, gas composition, and grating geometries, showing significant enhancement of this process with the addition of carbon dioxide. We also demonstrate stable performance over hours of operation. Our results validate a previously developed theoretical model and suggest optimal parameters to efficiently scale gas gratings to high-energy applications.

According to the latest provisional statistics released by the UK Department for Transport, Great Britain recorded 1,633 road deaths in 2024, representing a slight increase from 2023 and raising concerns about safety progress, which indicates that preventable fatalities remain a challenge. The deployment of advanced mobility systems, even certified and safety-assessed, is not sufficient to deliver improved safety outcomes, and existing road infrastructure is not sufficiently equipped to prevent severe collisions. Successful application of the “Safe System” approach demands systems thinking in an integrated and holistic manner, encompassing all aspects of road safety. This paper argues that road safety must be managed as a complex socio-technical system where risk evolves dynamically and must be continuously monitored. To address these safety gaps, we propose a systems thinking approach that identifies factors contributing to fatal outcomes and mitigates them. The framework consists of four steps: 1) List stakeholders who influence road safety, 2) Model the interactions between these stakeholders, 3) List assumptions that might be identified as factors for fatalities, and 4) Monitor these assumptions throughout the system lifecycle. The approach is applied to the United Kingdom (UK) road network to demonstrate feasibility. The study provides actionable guidance and new KPIs categories for stakeholders to implement road safety monitoring and eliminate any unreasonable road safety risks.

The application of nonthermal plasma in agriculture has emerged as a sustainable and eco-friendly method to enhance seed vigor, germination, and crop productivity. This study investigates the effects of atmospheric pressure plasma treatment on five popular bread wheat varieties of North India, WH 1142, HI 1544, GW 366, GW 322, and GW 273. Direct dielectric barrier discharge (DBD) plasma exposure and plasma activated water irrigation were tested. Results indicated significant improvements in seed wettability, germination index, root and shoot growth, spike length, and grain yield compared to controls. Among treatments, 3 min DBD exposure and 15 min PAW irrigation consistently produced the best results, with variety specific differences in vigor and yield. These findings demonstrate the potential of plasma seed treatment as a chemical free technology to enhance productivity in wheat, contributing to sustainable agriculture in India.

Machine learning interatomic potentials (MLIPs) enable efficient modeling of molecular interactions with quantum mechanical (QM) accuracy. However, constructing robust and representative training datasets that capture subtle, system-specific interaction motifs remains challenging. We introduce PANIP (PAirwise Non-covalent Interaction Potential), an ensemble MLIP model built upon the NequIP framework and trained on non-covalent interactions (NCIs) between protein-derived fragments. PANIP is trained using an automated multi-fidelity active learning (MFAL) workflow, in which a representative training subset, termed PDB-FRAGID (PDB Fragment Interaction Dataset), was distilled from an otherwise prohibitively large pool of fragment dimers extracted from the Protein Data Bank (PDB). PANIP retains $\omega$B97X-D3BJ/def2-TZVPP-level accuracy and achieves mean absolute errors below 0.2 kcal/mol on out-of-distribution systems, demonstrating excellent transferability across diverse NCI motifs. Compared to the widely used ANI-2x potential, PANIP delivers substantially lower errors, particularly for charged and strongly interacting dimers. Coupled with a fragmentation-based energy decomposition scheme, PANIP estimates protein-ligand binding energies at near force-field computational cost yet QM-level accuracy, enabling its use as a fragment-based scoring function that rivals specialized docking scoring functions.

Accurate interface tracking is central to numerical simulations involving moving boundaries, including multiphase flows, free-surface dynamics, phase-change problems, and other interface-driven processes in computational mechanics. Although level set methods provide a flexible implicit representation of evolving interfaces, their grid-based advection and reinitialization procedures often introduce numerical diffusion, volume loss, and degradation of thin or highly curved structures. This paper introduces a Particle Flow Map Level Set (PFM-LS) method that addresses these limitations by transporting interface geometry through particle-carried bidirectional flow maps. In contrast to particle level set methods that use particles mainly as corrective markers, PFM-LS uses particles as primary carriers of level-set values, gradients, and Hessians within a narrow band around the interface. The method combines long-range flow-map transport, high-order particle-grid reconstruction, adaptive particle control, and a hybrid particle-grid redistancing scheme to preserve both signed-distance consistency and sub-grid geometric features. Numerical benchmarks in two and three dimensions, including topology-change tests, chamfer and Hausdorff shape-error metrics, and coupling to an incompressible free-surface flow solver, show that PFM-LS achieves strong volume preservation, high shape fidelity, and near fourth-order convergence, outperforming a broad range of existing level set and reference-map-based methods.

Effective water management is essential for the optimal performance of PEM fuel cells. We have developed an impedance model for liquid water transport through the membrane and coupled it with the two-phase model for cathode side impedance. The complete model was fitted to experimental spectra measured at anode/cathode relative humidities (RH) of 32/32%, 50/50% and 100/100% within a current density range of 100 to 1000 mA cm$^{-2}$ and an air flow stoichiometry of 2. Cathode catalyst layer (CCL) saturation decreases with current density due to a growing liquid pressure gradient. For all RH values, the CCL oxygen diffusivity increases dramatically with cell current due to progressive involvement of larger pores into the proton current conversion. Higher RH leads to higher double layer capacitance, which indicates that liquid water increases the electrochemically active surface area.

In this work we present a study on the viability and practicality of installing a Doppler reflectometer (DR) system in the JT-60SA advanced tokamak. First, we discuss its scientific scope in the context of the JT-60SA research plan. We identify a number of fields in which a DR would be very relevant for the accomplishment of said plan and outline a scientific program for the diagnostic. Then, starting from a number of design hypothesis, we use a ray tracing code to carry out a feasibility study for a number of relevant scenarios and identify a geometric solution for the installation of a DR such that both core and edge can be probed in the prescribed wave number range, thus achieving the proposed scientific objectives. Finally, we perform a preliminary discussion on the different possibilities for a conceptual design (including a minimum viable system and a baseline system) and their requirements in terms of components and space. We conclude that a viable conceptual design could be carried out using a small fraction of a horizontal port, leaving room for additional diagnostic systems.

Mathematical and astronomical achievements of the Islamic World during its golden era are briefly exposed. Thie article is based on the invited talk delivered remotely at the ICRANet-Isfahan Astronomical meeting, November 2-5, 2021, which, in turn, reproduces major parts of one of the chapters of my book “Our Celestial Clockwork”, published recently (2021) by the World Scientific.

We introduce the variable coherence model (VCM) for simulating free-electron laser (FEL) pulses generated through self-amplified spontaneous emission. Building on the established partial coherence model of [T. Pfeifer et. al, Opt. Lett. 35, 3441 (2010)], we demonstrate that the implementation of a variable coherence width allows for continuous control over the pulses' characteristic noise, while keeping the average pulse parameters such as the bandwidth fixed. We demonstrate this through systematic statistical analyses of the intensity and number of sub-pulses in VCM pulses, in both time and frequency. In particular, we analyze how the sub-pulse statistics are affected by the coherence width parameter. We perform our analyses across three distinct regimes of FEL parameters and demonstrate how the VCM can generate pulses that range from maximally random to fully coherent. Finally, we illustrate the effect of the VCM variable coherence width on an absorption simulation.

Physics education researchers have argued that authentic physics education includes computation as part of a physics student's training, and many parties have made efforts towards this goal. However, most research on this teaching modality has centered cognitive impacts rather than affective impacts, so little is known about the affective outcomes of holistically integrating computation into physics courses. To address that need, we present a case study of a multi-day activity within a computationally integrated modern physics laboratory course. With data from ethnographic course observations and semi-structured interviews, we introduce a novel modification of conjecture mapping to distinguish between the professor's intent behind the activity design and the impact on a student's physics computational literacy and physics identity. In doing so, we highlight the methodological suitability of conjecture mapping for comparing the intent and impact of curricular design and explicate the specific misalignments that led to different affective outcomes than intended.

The ability to directly measure radiative-association rate coefficients for reactions between ions and neutral molecules has long challenged chemical physics laboratories, yet radiative association is one of the most important processes occurring in cold, diffuse regions of space. A reaction kinetics instrument has been developed for the investigation of ion–molecule radiative-association reactions, aimed at measuring slow, effective reaction rate coefficients for species relevant to astrophysical objects. The instrument consists of a glow-discharge ion source for production of bright and stable ion currents, a quadrupole mass filter for mass selection and detection, and a quadrupole ion trap capable of trapping reactants and products for the long times needed to measure slow kinetics. The performance and adaptability of the glow-discharge ion source has been evaluated using several configurations. To assess the feasibility of measuring reaction rate coefficients, the reaction of Ag$^{+}$ and O$_{2}$ was studied under pseudo-first-order conditions in the ion trap at room temperature. We present the first pressure-dependent study of this reaction and extract a lower limit of $1 \times 10^{-15}$ cm$^3$ molecule$^{-1}$ s$^{-1}$ for the Ag$^{+}$ + O$_{2}$ effective radiative-association rate coefficient. Measurements of effective radiative-association rate coefficients are possible for diverse atomic and molecular ions that react with neutral molecules over a range of rates in this versatile new instrument.

We theoretically investigate the optical dipole interaction between a multi-level quantum system and a single-mode optical waveguide of any local polarisation. We investigate several paradoxical seeming situations, for example we find a situation in which there exist two non-orthogonal quantum states, each of which results in a photon flux in the opposite direction to the other. We show how, despite appearances, this does not break the unitary requirements of quantum mechanics. We also find that an isotropic quantum emitter can be either reflective or transmissive to light depending on the waveguide polarisation at the emitter location, indeed in the zero loss limit such a system changes from 100% transmission to 100% reflection due to an infinitesimal polarisation rotation. An example case for a four level system is also considered, which is found to operate as a non-destructive parity measurement of the photon number.

Biomolecular thermodynamics and spectroscopy depend on relative conformer energies, local curvatures, and collective dipole fluctuations on the potential-energy surface. Conventional molecular mechanics force fields enable large-scale simulations, but their fixed functional forms can misrepresent infrared intensities, mode character, and environment-dependent vibrational response. Here we assess general-purpose machine-learned force fields across small molecules, finite-temperature infrared spectra, gas-phase peptides, and monomeric, oligomeric, and solvated protein assemblies. To enable this analysis, we introduce QVib, a dataset of 293 molecules and 1365 conformers, together with peptide amide-band benchmarks and p53 oligomerization-domain models, to evaluate vibrational transferability from DFT references to experimental spectra. Across these systems, machine-learned force fields substantially improve over molecular mechanics in reproducing DFT-level forces, vibrational frequencies, densities of states, mode eigenvectors, conformational energetics, and experimental infrared spectra. Among models with explicit long-range electrostatics, SO3LR provides the most favourable accuracy-cost balance for the biomolecular systems considered. These results show that machine-learned force-field dynamics can recover collective, environment-dependent vibrational landscapes at near-DFT fidelity, enabling spectroscopically validated biomolecular simulations at force-field-like cost.

Recent research in nanophotonics for scintillation-based imaging has demonstrated promising improvements in scintillator performance. In parallel, advances in nanophotonics have enabled wavefront control through metasurfaces, a capability that has transformed fields such as microscopy by allowing tailored control of optical propagation. This naturally raises the following question, which we address in this perspective: can wavefront-control strategies be leveraged to improve scintillation-based imaging? To answer this question, we explore nanophotonic- and metasurface-enabled wavefront control in scintillators to mitigate image blurring arising from their intrinsically diffuse light emission. While depth-of-field extension in scintillation faces fundamental limitations absent in microscopy, this approach reveals promising avenues, including stacked scintillators, selective spatial-frequency enhancement, and X-ray energy-dependent imaging. These results clarify the key distinctions in adapting wavefront engineering to scintillation and its potential to enable tailored detection strategies.

This tutorial paper shows how to compute the DC (or low-frequency) resistance, inductance and capacitance of a pair of parallel wires using the finite element method. A three-dimensional infinite domain (open boundary) modeling of electrostatic and magnetostatic fields is presented, along with the electrokinetic formulation for the current flow inside the wires. The effects of the insulation and of a proposed physical defect in the wires are also considered. The open-source ONELAB software is used to perform the simulations and the code listing is provided. Comparisons using analytical models (when applicable) and the Altair Flux software are performed to help validate the simulations.