Papers

It is well known that electron-positron pairs can be created in the strong-field environments formed by (i) a high-intensity laser field and a high-energy $\gamma$-photon (nonlinear Breit-Wheeler process) or (ii) a high-intensity laser field and a nuclear Coulomb field (nonlinear Bethe-Heitler process). Both of these processes are particularly interesting in the interaction regime where the laser field enters nonperturbatively. Various experimental collaborations are currently aiming at detecting for the first time the nonperturbative Breit-Wheeler process, by exploiting high-intensity laser pulses and $\gamma$-ray sources based on bremsstrahlung. In contrast, an experimental observation of the nonlinear, nonperturbative Bethe-Heitler process still lies further ahead in the future because its technical realization appears at present more challenging. Our comparative study shows, however, that the physical properties of the total rates for the processes (i) and (ii) can become remarkably similar when the parameters for the bremsstrahlung-driven nonperturbative Breit-Wheeler process are properly chosen. In this sense, the upcoming experiments on the nonlinear Breit-Wheeler process could also be used to closely “simulate” the currently hard to observe nonlinear Bethe-Heitler process.

Crystal symmetry dictates whether a physical response tensor must vanish, establishing a direct test for machine learning predictions independent of property calculations. We derive the parity gap, a group-theoretic metric quantifying the piezoelectric tensor freedom permitted by a crystal's proper rotation subgroup $SO(3)$ but eliminated by inversion symmetry in $O(3)$. Across state-of-the-art equivariant neural network architectures, unconstrained $SO(3)$ models systematically predict forbidden non-zero responses matching the parity gap of each centrosymmetric crystal class, while polar distortion paths dynamically map output responses to the loss of inversion symmetry. Regression controls confirm that enforcing full $O(3)$ parity incurs no consistent accuracy cost across predictive tasks. Crucially, while training interventions using explicit zero labels reduce violation magnitudes, they leave residual forbidden outputs. Exact physical compliance instead requires structural enforcement through $O(3)$ representation design or explicit output antisymmetrization. The parity gap thus provides a unified framework to distinguish empirical error reduction from exact structural compliance with physical law.

Detection and attribution studies typically rely on free running climate models with modified anthropogenic forcings, yet they fail to reproduce key observed decadal trends. Despite reduced biases, higher predictive skill, large ensembles, and improved trends through frequent reinitialization, seasonal forecast models have not been used for this purpose. We introduce a new set of counterfactual seasonal hindcasts using the ECMWF coupled seasonal forecasting system based on alternative forcing scenarios by modifying atmospheric forcing and ocean and sea ice initial conditions. An observation based estimate of the forced ocean temperature signal is derived to amplify or remove this signal from the ocean initial conditions. Retrospective forecasts include a control configuration together with enhanced and reduced forcing experiments in which either CO2 increases together with doubled anthropogenic ocean warming or CO2 is fixed and the anthropogenic ocean-warming signal is removed. Additional experiments isolate aerosol forcing. The counterfactual hindcasts substantially alter long term temperature trends while largely preserving seasonal prediction skill, interannual variability, and model drift. Enhanced forcing strengthens several observed climate trends underestimated by the control, including top of atmosphere radiative fluxes and aspects of tropical Pacific atmospheric circulation. However, the coupled atmosphere ocean system fails to sustain the strengthened tropical Pacific temperature gradient through Bjerknes feedbacks, suggesting a fundamental model limitation. Aerosol forcing has little impact, likely because indirect aerosol effects are omitted. These results establish counterfactual seasonal hindcasts as a powerful tool for dynamic attribution and diagnosing model deficiencies in responses to anthropogenic climate forcing.

Optically pumped room temperature masers are a promising platform for driven dissipative spin photon physics beyond steady state emission. Here we observe a sequence of dynamical thresholds in a room temperature nitrogen vacancy diamond maser as the optical pump is increased above the conventional masing threshold. The first threshold yields narrow-line continuous wave emission, while a second threshold produces a periodic train of microwave pulses whose repetition rate generates a frequency comb spectrum. At higher pump power, a third threshold gives rise to pulses with an oscillatory, frequency chirped decay. Time-resolved measurements link the comb directly to self-pulsing dynamics and Fourier analysis of individual bursts reveals a broad distribution of frequencies consistent with collective spin-resonator dynamics in an inhomogeneously broadened ensemble. These results establish the diamond maser as a room temperature platform for nonlinear nonequilibrium light matter dynamics and microwave comb generation.

A key aspect of structure formation in collisionless plasmas is particle trapping or, more precisely, the gap this process leaves in the theoretical description. While the dynamics prior to the onset of trapping are governed by Landau physics and phase mixing, the full effects of nonlinearity only emerge during the trapping phase, for which an explicit description is lacking. Consequently, this gap divides the temporal evolution into a linear Vlasov-Poisson phase preceding the transition and a post-transient Vlasov-Poisson phase characterized by a wide spectrum of particle trapping scenarios and associated Schamel equilibria. Metaphorically, this trapping process can thus be compared to a waterfall in fluid dynamics, where, similarly, no explicit dynamic link can be established between the regions above and below the cascade. To resolve this problem of the gap, an analysis using the method of matched asymptotic expansions is proposed. Applied to the singular boundary of the separatrix zone, this approach employs local smoothing techniques, such as those mediated by the two-particle correlation function. It offers a suitable mechanism for selecting hole equilibria in the post-transition phase. Furthermore, we report the existence of a spatially periodic Langmuir hole that vanishes if regularity requirements are too stringent, and we demonstrate that self-acceleration, accompanying the transition from a slow electron acoustic hole to a fast Langmuir hole, is driven by the release of particularly deeply trapped electrons.

It is sometimes said that a reason to prefer Everettian quantum mechanics is that it allows one to avoid the kind of spooky action at a distance that is a consequence of quantum entanglement according to other approaches. There is a straightforward argument to show EQM has this virtue, however some advocates argue that this requires we see branching as a local causal process. I explain this reasoning and then show why, given the way Everettians standardly conceive of worlds and branching as emergent phenomena, branching need not be viewed as a causal process for EQM to be relativistically local. Forthcoming in Local Quantum Mechanics, OUP 2026.

Granular flows are ubiquitous in natural and industrial systems, yet their complex dynamics remain difficult to characterize. For inverse problems involving unknown inlet, outlet, and wall boundary conditions, where CFD simulations are challenging, reconstructing complete flow fields from sparse observations constitutes a challenging inverse problem. In this study, a physics-informed neural network framework driven by both physical mechanisms and measurement data is developed to reconstruct the steady-state full-field distribution of granular flows in a pipe. The proposed approach integrates sparse measurement data with governing equations and constitutive relations and is trained using high-fidelity datasets generated by CFD solutions of a continuum model. The framework incorporates a dimensionless loss formulation, physics-informed initialization, dynamic global weighting, and a locally weighted granular temperature data-loss strategy. These treatments enable accurate reconstruction of the complete flow-field evolution. This work establishes a robust methodological framework for flow-field reconstruction in complex granular flow systems.

Calculating strong-field, broadband nonlinear phenomena in complex nanophotonic structures remains difficult because it requires simultaneous handling of non-perturbative dynamics, impulsive processes, and structural complexity. Here, we introduce a unified framework that combines the transfer matrix method with an iterative Green's function approach. The linear multilayer response is incorporated as boundary conditions into a nonlinear boundary value problem, which is then solved self-consistently, naturally accommodating broad spectra and arbitrary nonlinearity. The framework is validated with two examples in the transparent and resonant regimes, respectively. The first demonstrates an impulsive spectral modulation in second harmonic generation that is captured only by a full-structure broadband treatment. The second demonstrates the entire dynamical evolution of exciton-polaritons in a pump-probe experiment reproduced by a unified simulation. This framework directly links nanophotonic design with ultrafast nonlinear dynamics.

We study the finite-genus algebro-geometric solutions of the Wadati-Konno-Ichikawa (WKI) equation with the saturable nonlinearity and long-time asymptotic behaviors of their short-range perturbations. First, for both the focusing and defocusing reductions, we formulate the finite-genus Baker-Akhiezer functions as explicitly solvable the matrix Riemann-Hilbert (RH) problems on the complex spectral plane and obtain theta-function representations together with the reconstruction formulae for the WKI field and the reciprocal coordinate. We then consider the Cauchy problem of the defocusing WKI equation on a finite-genus algebro-geometric background. We construct the scattering data and RH problem, and perform a Deift-Zhou nonlinear steepest descent analysis. The space-time plane is divided into two transition regions, a Zakharov-Manakov (ZM) region, and a fast-decay region. The leading term is a phase-shifted finite-genus WKI solution. The transition corrections are governed by a Painlevé-XXXIV model, while the ZM radiation is described by parabolic-cylinder functions. The reciprocal-coordinate asymptotics are obtained simultaneously.

Ion conduction, membrane permeation and metal recognition hinge on electronic structure, yet first-principles simulation reaches only hundreds of atoms. UBio-MolFM lifts that ceiling: a foundation model trained on 160 million quantum-chemical labels, its receptive field spanning non-covalent distances at near-linear cost. The barrier is cost, not principle. One untuned potential keeps force error near 20 meV/Å past a thousand atoms, reproduces water's X-ray structure and ion hydration, and holds an RNA Mg$^{2+}$ site without ion-specific parameters. Cyclosporine A pays 3.5 kcal/mol in water for its permeable conformer, gated by one kinetically asymmetric hydrogen bond that a fixed-charge model flattens. In a 108,964-atom KcsA channel on one GPU, the relaxed four-ion column is anhydrous in all five replicas, in direct contact in four—the knock-on geometry ten fixed-charge simulations never form. It remains orders of magnitude costlier. Where electronic structure decides the answer, first-principles simulation is in reach.

Calculating cross sections in the Color Glass Condensate effective theory requires Fourier transforms of multi-Wilson-line correlators from transverse coordinate space to transverse momentum space. Under the common assumption of impact-parameter independence, each transform reduces to a set of Hankel transforms whose Bessel-function kernels oscillate rapidly at phenomenologically relevant momenta, making direct quadrature prohibitively expensive. We present a Filon-type quadrature, applicable to any integrand, that integrates these oscillatory factors in closed form on the stored coordinate grid, reducing each Hankel transform to a precomputed weight vector and the full nested transform chain to a sequence of matrix products. We develop and validate the method on the deep inelastic scattering dijet cross section beyond the correlation-limit approximation, where an exprel-based reformulation of the quadrupole Wilson-line correlator removes a numerical $0/0$ instability inherent to its standard parametrization. Porting the calculation to the Graphics Processing Unit (GPU), with custom CUDA kernels that fuse the momentum-space contraction directly into the correlator evaluation, brings the runtime for one dipole input down to about two minutes on a single NVIDIA A800, from several hours on a multi-core Central Processing Unit (CPU). We further generalize the algorithm to three sequential Hankel transforms and validate the resulting six-dimensional transform against an analytic Gaussian integrand family with closed-form results at every stage. This general, process-independent algorithm is directly applicable to next-to-leading-order proton-nucleus and electron-ion scattering cross-section calculations performed without the correlation-limit approximation. The code is publicly available at https://github.com/CCNU-CGC-py/FFT_filon.

The prediction of equilibrium beach profiles under tidal influence is of fundamental importance for sustainable coastal development, informing shoreline protection strategies and managing coastal ecosystems under changing environmental conditions. However, it remains challenging due to the highly nonlinear interactions among wave, tide, and sedimentary processes. Traditional empirical and numerical models often exhibit limited adaptability across diverse coastal environments, with especially pronounced limitations in beach systems where tidal processes are important . To improve data-driven prediction under these conditions, this study proposes MorphoGP, a unified category-specific Gaussian process framework for predicting equilibrium beach profiles (EBPs) under tidal influence. The framework first introduces a ContourCluster model based on contrastive learning to classify tide-influenced beach morphologies automatically. Within each morphological category, a specialized Gaussian process expert learns statistical associations between environmental descriptors including waves, tides, and sediments and the beach profile's shape. A Gating Net then integrates the outputs of all experts through a probabilistic weighting mechanism to produce the final prediction. Evaluated on data from over 180 beach profiles from tide-influenced coasts along the Chinese coast, MorphoGP achieves improved predictive performance compared with conventional and deep learning models, reducing the test RMSE by about 59.3% compared with the best baseline and achieving a final RMSE of 0.297 m. The proposed framework provides a physically informed, data-driven tool for equilibrium beach-profile prediction under tidal influence and coastal management, while stronger process-level physical coupling remains an important direction for future development.

We present a simple geometric proof of Kepler's first law. The core of the argument rests on a kinematic invariant that we call the velocity projection ratio - the ratio between the radial projection of the velocity and its projection onto a fixed direction parallel to the periapsis line. We show that the constancy of this ratio is an immediate consequence of Newton's laws, and that it leads directly to the focus-directrix property of the orbit. By establishing a direct link between planetary dynamics and the classical geometric definition of conics, our proof reveals the conic nature of the orbit as an inevitable consequence of the inverse-square law.

We are witnessing an explosion of agentic systems for computational chemistry: from four in 2024 to seventeen in 2025 and over sixty now, surveyed here. What is delegated to these systems is shifting from single calculations to whole in silico experiments and even manuscript writing. The ultimate destination is a fully autonomous AI scientist, where the entirety of computational chemistry is performed on a machine by a machine, without human supervision. Our survey shows that these systems are turning into vetted chemistry skills on general-purpose coding agents, and that they must be evaluated not only on their final answers but also on whether their calculations actually support these answers. The role of the human computational chemist is shifting from performing calculations to directing and supervising them, and the field should invest in the judgement that makes the supervision reliable: we propose a reporting standard, an evaluation reproducing published studies, a controlled comparison with general-purpose coding agents, and how to teach.

We investigate the propagation of structured scalar optical beams in an effective anisotropic background inspired by the scalar sector of the Standard-Model Extension and controlled by a single dimensionless parameter $\lambda$. The physically relevant configuration is a transverse radial director field that modifies the radial part of the Helmholtz operator while preserving axial symmetry. Starting from the Green-function representation, we cast the propagation problem as an initial-value spectral reconstruction of a prescribed finite-aperture entrance profile at $z=0$ and verify that this profile is recovered at the launch plane across the values of $\lambda$ used in the analysis, within small numerical error. We use the Laguerre–Gaussian mode $L_3$ as the representative vortex-free Laguerre case, retain $L_4$ only as a quantitative benchmark for radial-order dependence, and compare both with a Bessel–Gaussian beam of input order $m=0$. The effective anisotropy produces a systematic redistribution of radial intensity, determines whether the central peak remains dominant or is overtaken by off-axis maxima as propagation advances, and controls the radial displacement of the dominant side lobes. For the finite-aperture Bessel–Gaussian beam, the same parameter quantifies how the approximately diffraction-resistant ring structure broadens for negative $\lambda$ and compresses for positive $\lambda$ during propagation.

We present TDSE-Z, a high-performance open-source framework for strong-field quantum dynamics in atomic, molecular, and semiconductor effective-mass systems. The core engine implements a weak-form Galerkin discretisation of the Hermitian BenDaniel-Duke operator, $\hat{T}_{\mathrm{BDD}} = -\frac{1}{2}\nabla\cdot(m^{-1}(\mathbf{r})\nabla)$, on geometry-adapted B-spline meshes, supporting arbitrary potentials and customisable laser configurations in one to three dimensions. We validate the static position-dependent-mass (PDM) eigensolver through two stringent benchmarks: a comparison to the analytical Quesne PDM model and a $\text{GaAs/Al}_{0.3}\text{Ga}_{0.7}\text{As}$ double quantum well, where the exponential decay of computed tunnel splittings follows Wentzel-Kramers-Brillouin (WKB) theory at the sub-percent level. We further demonstrate the time-propagation engine on constant-mass systems, accurately reproducing high-harmonic generation (HHG) spectra in atomic benchmarks and confirming the importance of dimensionality in fully capturing the strong light-matter interaction. Our implementation demonstrates robust strong-scaling efficiency, maintaining performance across hundreds of CPU cores. While the static eigensolver currently supports optional GPU offloading, the time-propagation engine is CPU-optimised, providing a modular architecture for future expansion toward exascale quantum dynamics.

A three-channel X-/Ku-band Doppler backscattering (DBS) system has been developed and installed on QUEST for turbulence and electric-field measurements. In spherical tokamaks, the large magnetic-field pitch angle increases the geometric mismatch between the probing beam wave vector and the local magnetic-field vector, reducing the effective perpendicular projection and resulting in a systematic underestimation of the measured scattering intensity. In addition, in QUEST, where low plasma density requires a low-frequency probe beam, beam propagation effects become increasingly significant, further complicating the interpretation of the measured DBS power in terms of local density fluctuation amplitude. To address these issues, a quantitative correction methodology based on the synthetic DBS code SCOTTY was established. All relevant diagnostic response effects were evaluated using SCOTTY along ray trajectories, yielding a correction factor for reconstructing the local turbulence amplitude from the measured scattering signal. The correction factor exhibits strong spatial and frequency dependence, varying by up to an order of magnitude between the plasma core and edge regions, highlighting the necessity of frequency-dependent corrections. By applying the derived correction factor to experimental measurements, quantitative density fluctuation amplitudes were reconstructed from the detected scattering signals. Evaluation of the fluctuation amplitude indicates enhanced turbulence activity in the plasma edge region, where a finite negative radial electric field is inferred. This work demonstrates the first quantitative turbulence evaluation using low-frequency X-/Ku-band DBS measurements in QUEST and establishes a framework for quantitative DBS analysis in spherical tokamaks.

Climate model simulations indicate that surface ultraviolet (UV) radiation would change after soot injection into the stratosphere during a nuclear war, due to the competing effects of ozone depletion and aerosol attenuation. Using climate model simulations, we evaluate UV impacts under two scenarios: a regional India-Pakistan conflict producing 5 Tg of soot and a global U.S.-Russia war producing 150 Tg. UV enhancements due to ozone depletion substantially shorten safe outdoor exposure time, particularly for individuals with lighter skin types. Applying UV dose-response relationships to the year 2000 population data, without accounting for direct conflict mortality or famine-related population loss, the 5 Tg scenarios result in approximately 5,300-9,800 additional skin cancer deaths within 10-15 years and up to 75,000 cumulative excess deaths over the following century. In contrast, strong aerosol attenuation under the 150 Tg scenario initially suppresses surface UV, resulting in about 8,500 fewer skin cancer deaths within 15 years and a maximum cumulative reduction of approximately 17,000 deaths over the following century. These findings demonstrate that nuclear war-induced changes in surface UV radiation represent a persistent but previously understudied health impact of nuclear war. While skin cancer would not dominate overall mortality following a nuclear war, enhanced cumulative surface UV radiation represents an additional, long-lasting threat to human health that compounds other global impacts such as climate disruption and food insecurity. The excess UV may also pose negative impacts on animals and plants, including those used for agriculture, which remain to be quantified.

This article investigates the role of polyaniline as a conductive polymer in the active layer of perovskite solar cells. Samples were created by incorporating polyaniline into the transport layers to assess its impact on enhancing efficiency and conductivity. The application of this polymer across various layers of the cell structure led to improved stability and performance. Given its high doping capability, polyaniline was examined in detail, particularly focusing on two types of oxidation doping and its integration into the hole transport layer. Graphene oxide and reduced graphene oxide were chosen as comparative models, and their performance was evaluated against the standard polyaniline configuration. Laboratory results revealed that power conversion efficiency increased by 17.5% with graphene oxide and by 36.8% with reduced graphene oxide. Furthermore, short-circuit current density improved by 9.8% and 23.1%, respectively. These findings are consistent with existing studies in the field and support the validity of the approach.

Physics-based models of lithium-ion batteries require the open-circuit potential (OCP) of each electrode as a function of its lithiation. The multi-species multi-reaction (MSMR) model provides a compact, thermodynamically grounded description of this relationship, representing each insertion reaction by a standard potential, a site fraction and a disorder parameter. Here, we parametrize the MSMR model for nickel-cobalt-aluminum oxide (NCA), a cathode chemistry widespread in automotive cells, using the positive electrode of a commercial silicon-graphite/NCA cell. Cathode material was harvested from a pristine cell and from cells cycle-aged to the end of life under two state-of-charge windows, and its half-cell OCP was measured by slow galvanostatic cycling. Smooth differential-capacity curves were obtained by histogram counting, and the charge and discharge branches were fitted with a constrained, scale-invariant optimization that keeps every reaction anchored to a visible peak. We report the first MSMR parameter set for an NCA cathode and show, through a differential-capacity peak analysis across aging states, that its thermodynamic signature is essentially unchanged by aging. This finding supports the common modeling practice of holding the electrode's intrinsic parameters fixed and ascribing aging to electrode-level capacity and alignment changes.

In this study, we use the harmonic oscillator s energy spectrum to connect its dynamical behavior to the formalism of statistical mechanics through entropy. We perform a thermal analysis of the entropy generated by this spectrum in both commutative and noncommutative two-dimensional configuration spaces, employing the Tsallis and Renyi entropy measures. The primary objective is to examine the possibility of an intrinsic link and mutual influence between the noncommutative parameter({\theta}) and the parameters arising from generalized entropies. By analyzing both Tsallis and Renyi frameworks, we investigate whether a fundamental relationship exists between {\theta} and the entropy index q. Establishing such a connection could provide new insights into the interplay between spacetime geometry and generalized statistical mechanics.

In the framework of $f(Q)$ gravity, we investigate whether spatial curvature can be made dynamically invisible in the cosmological background equations. We consider open spatial sections, $k<0$, on an explicitly specified homogeneous and isotropic symmetric-teleparallel connection branch. For $k\neq0$, the coincident gauge cannot be imposed simultaneously with the standard curved-FLRW coordinate form. Re-deriving the background equations from the minisuperspace action, we show that curvature enters through $x=H+\delta\sqrt{-k}/a$ and appears with inequivalent weights in the energy and pressure equations. For $f\in C^3((0,\infty))$, we prove a branch-specific no-go theorem: strict curvature independence for every scale factor and every $k<0$ requires $f=\mathrm{const}$, which contains no metric kinetic term. STEGR is not curvature-neutral, since its Friedmann equation retains the usual $3k/a^2$ contribution. A weaker cancellation, imposed only on backgrounds satisfying $\delta\sqrt{-k}/a=cH$, necessarily produces a coasting expansion and yields $f(Q)=A Q^{(c+2)/2}+B$, or $f(Q)=A\ln Q+B$ when $c=-2$. For the illustrative choice $c=-3$, the solution becomes $f=\alpha_1/\sqrt Q+\beta_1$. Under the conventional positive-coupling assumption $f_Q>0$, the required source violates the null energy condition. Moreover, adding positive radiation or pressureless matter forces a compensating negative-energy component at sufficiently early times. The weak branch is therefore neither curvature-neutral in an invariant sense nor a viable cosmological model. The principal result is the background-level obstruction itself. Perturbative stability and gravitational-wave propagation require a separate analysis including perturbations of the nontrivial affine connection and are not established in this work.

Saturated absorption spectroscopy is a powerful technique that provides valuable information about gas-phase atomic targets, including not only the precise positions of transitions but also the effects of velocity-changing collisions, which manifest as changes in the shape of the peaks. However, using a lock-in amplifier inappropriately can generate artifact side peaks, potentially leading to a misinterpretation of results. To investigate the emergence of these artifacts, we conducted numerical calculations based on the basic Lambert-Beer's law. Our model reproduced the artifact side peaks and revealed that these artifacts become more significant as the transmittance of the probe laser decreases.

The Nearest Neighbors estimation of likelihood is implemented for the multivariate amplitude analysis of the cascades of particle decays. In this approach Monte Carlo simulated events that are used to describe data are assigned weights dependent on the parameters of the theoretical fitting model. Each of such weighted events is considered as contributing to N-dimensional probability density function in it's neighborhood in the parameter space. No analytic p.d.f. or cpu-intensive re-generation of N-dimensional p.d.f. at each fit step are required. The method allows accurate accounting for reconstruction effects, demands modest cpu resources and can be effectively multi-threaded. General setup of the fit as well as toy example of the amplitude analysis of B-meson decays are demonstrated.

We investigate intramolecular hydrogen migration in acetonitrile dication in phase-controlled $\omega$-$2\omega$ intense laser fields (800 and 400 nm, 3.3$\times$10$^{14}$ W/cm$^2$) using three-dimensional coincidence ion momentum imaging. The two-body Coulomb explosion pathway, CH$_3$CN$^{2+}$ $\rightarrow$ CH$_3^+$ + CN$^+$, exhibits a clear phase-dependent fragment asymmetry along the laser polarization direction, showing that the tunnel ionization preferentially prepares the acetonitrile dication with the methyl group pointing toward the smaller amplitude side of the laser electric fields. The Coulomb explosion pathway occurring after the migration of a single hydrogen atom, CH$_3$CN$^{2+}$ $\rightarrow$ CH$_2^+$ + HCN$^+$, shows a pronounced reduction in the fragment asymmetry. A clear deuteration effect observed for the asymmetry of the hydrogen-migration pathway suggests that the two-color asymmetric laser field has a significant impact on directionality of intramolecular hydrogen migration in acetonitrile dication.

We study the evolution of electric potentials in the lunar wake. The wake potential exhibits two distinct spatial scales. The macroscopic scale arises from solar wind expansion into the vacuum, with a potential length-scale growing with distance from the Moon; the microscopic scales arises from ion acoustic shocks near the wake center, with transition layers spanning tens of local Debye lengths. This two-scale potential mediates energy conversion between ions and electrons during wake refilling. The macroscale potential retards electrons and accelerates ions to supersonic velocities, converting electron thermal energy to ion kinetic energy. The microscale potential then decelerates ions to subsonic velocities and heats both species, converting ion kinetic energy back to thermal energy. Together, the two-scale potential imprints distinct signatures on velocity distributions, including ion beams and electron flat-top distributions, consistent with ARTEMIS observations.

High contact resistances in atomically thin semiconductors often mask intrinsic electrical transport properties, particularly at low carrier densities where exotic correlated states emerge. We introduce optical voltage profiling, a noninvasive wide-field technique that replaces local voltage probes with a proximal monolayer MoSe$_2$ exciton sensor. Isolated by thin hexagonal boron nitride, this sensor converts the target's local electrostatic potential into spatially resolved modulations of exciton reflectance. Through pixel-wise in situ calibration, these signals yield quantitative two-dimensional voltage maps of an actively biased semiconductor device. Using this method, we demonstrate the carrier-density-driven metal-insulator transition in bilayer MoSe$_2$ and obtain channel resistances below 1 k$\Omega$ despite M$\Omega$-scale two-terminal resistances in the metallic region. The optically derived resistance exhibits a metal-insulator crossover near the resistance quantum $h/e^2$, and the voltage maps and reconstructed local conductivity reveal pronounced spatial heterogeneity in both insulating and metallic regimes. Beyond resolving channel resistance under high contact-resistance conditions, the technique provides spatially resolved access to microscopic transport heterogeneity in functional van der Waals devices.

The two-wire model (TWM) is a magnetic configuration generated by two parallel current-carrying wires, and it contains an X-point at its center and a separatrix. Since the TWM magnetic field is described by a closed-form analytic expression and contains no guide field, it offers a tractable setting for studying how a true magnetic null shapes plasma dynamics. This work investigates two complementary regimes: collisionless charged particle dynamics and collisional low temperature plasma transport. In the collisionless regime, a Lagrangian analysis identifies two particle motion invariants: the total kinetic energy and the base field line value, which is derived from the conserved axial canonical momentum. Collisionless test particle simulations show that the magnetic moment undergoes shifts when the particle traverses the large gradient region near the null. These shifts enable particles to migrate, the phenomenon in which a particle gyrating about one branch of a base field line jumps to the corresponding branch on the other side of the X-point. A threshold energy for migration is derived, and an empirical expression for the migration confinement time is formulated. In the collisional regime, reduced drift-diffusion models for low temperature plasmas are developed in a conformal field-aligned coordinate system, and they predict density plateau formation near the separatrix in the strongly magnetized regime. Self-consistent particle-in-cell simulations are performed to verify the predicted density plateau. The two complementary studies establish a fundamental understanding of plasma dynamics near a true magnetic null for both the collisionless and collisional regimes.

Coupled-cluster theory defines the accuracy standard for molecular electronic-structure properties but scales too steeply for routine application, whereas density-functional theory is affordable yet systematically biased. We resolve this trade-off with a single equivariant network, HARP (Hamiltonian Read-out for Properties), that predicts an effective one-electron Hamiltonian from one inexpensive B3LYP/def2-SVP calculation and derives a broad suite of properties from it (energy, optical gap, dipole, quadrupole, polarizability, Mulliken atomic charges, and Mayer bond orders) at coupled-cluster accuracy across nine main-group elements, including the under-served phosphorus, sulfur, and chlorine chemistries. The model is trained on a new in-house dataset of multi-property labels computed at the CCSD(T) level for all nine elements. On a held-out test set, it reduces the error of every property by a factor of 3.8 to 270 relative to semi-local, hybrid, and double-hybrid DFT (referenced to composite CCSD(T)/cc-pVTZ), while adding only ~0.1 s wall time per molecule, delivering coupled-cluster-quality predictions at the cost of a single DFT calculation. Critically, deriving every property from a predicted Hamiltonian rather than pooling per-atom features builds the correct size-scaling into the model architecture: on pi-conjugated oligothiophenes it matches finite-field CCSD polarizability to ~1% and the EOM-CCSD optical gap to ~3% at the largest sizes where those references remain affordable (44 and 37 atoms, where a single CCSD field point already costs ~500x the model's entire inference) and extrapolates the corrected trends to 58-atom chains, a regime where pooling-based architectures fail by construction. Accurate extrapolation is therefore set by the model's inductive bias rather than by the training data.

Hydrogen detection is becoming increasingly important as its use grows across energy and industrial systems. Optical sensing platforms based on palladium (Pd) nanoparticles are attractive for this task because hydrogen uptake directly alters their plasmonic response. Organizing such nanoparticles into periodic two-dimensional arrays, known as metasurfaces, further enhances their optical response through collective resonances. However, the large design space presented by chemical composition, nanoparticle geometry, and array structure calls for systematic approaches for optimizing complex nanoalloy metasurface geometries. Here, we develop an inverse-design framework based on Bayesian optimization that couples first-principles dielectric functions with electromagnetic simulations to identify high-performance PdAu nanodisk arrays for hydrogen sensing in the 1 to 100 mbar range where the flammability of H2 becomes a concern. We use our approach to search a five-dimensional design space, comprising nanodisk height and radius, array pitch, polymer coating thickness, and Au fraction in order to maximize the H-induced change in extinction at a single wavelength of choice. The results show that integrating first-principles optical models with data-efficient optimization yields experimentally feasible nanoparticle metasurfaces tailored for targeted hydrogen pressures, while providing a pathway to future multiobjective sensor design. They also reveal remaining gaps in the modeling methodologies that still limit the quantitative reliability of the approach.