Applied Physics
Dynamic Sensing via Photomodulated Gas Desorption in Plasmonic Nanoparticle Chemiresistors
Lukas Mielke, Dahee Heo, Gabriele Carelli et al. (+1 more)
Quasi-static sensing, i.e., measurement of a sensor signal change induced by analyte presence with respect to a baseline signal observed in a reference gas beforehand, is the state of the art for qualitative and quantitative analyte identification in chemiresistive sensing. However, this approach is prone to baseline drift and, especially for inexpensive miniaturized point-of-care sensors, repeated calibration with reference gas is not feasible. To access reliable baseline information, active switching between analyte and reference gas would be required, causing a limitation for miniaturized implementation. Dynamic excitation of sensors offers an alternative: Via external stimuli the sensor is reversibly driven out of
equilibrium in a controlled way, and the resulting transient sensor response, which is dependent on analytes present, is recorded and interpreted. Correlation of excitation and response signals can reduce effects of baseline drift and furthermore, dynamic features in sensor responses may contain valuable information. Especially light activation is a powerful and potentially miniaturizable approach to agitate sorption processes and therefore induce dynamics. In this work we report photothermal heating of hybrid, chemiresistive gold nanoparticle composites via LED excitation matching the plasmon resonance, to dynamically shift the analyte sorption
equilibrium and induce dynamic sensor responses in a highly controlled way. We demonstrate that these sensor responses enable the detection of volatile organic compounds (VOC) via interpretation of differential signal components and that this approach improves the chemiresistors' baseline stability.
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All authors Lukas Mielke, Dahee Heo, Gabriele Carelli, Hendrik Schlicke
Physics and Society · Cross-listed from nlin.AO
Double explosive transitions in adaptive multilayer networks with higher-order interactions
Anath Bandhu Das and Pinaki Pal
Can asymmetry between two interacting networks fundamentally change how they synchronize? We identify double explosive transitions in the forward direction, backward direction, or a combination thereof, with single or double hysteresis loops in an adaptive
bilayer multiplex network of Kuramoto oscillators with pairwise and three-body interactions and asymmetric phase lags. Using the Ott-Antonsen reduction, we derive a low-dimensional system and perform a stability analysis. The reduced model accurately captures the full microscopic dynamics and enables analytical expressions for the bifurcation points. Systematic mapping across multiple parameter planes reveals eight distinct synchronization regimes. The relative ordering of saddle-node and pitchfork bifurcation points—controlled by phase-lag asymmetry, cross-layer adaptation, and the higher-order interaction strength—creates two distinct coherent branches (weak and strong), giving rise to double explosive transitions. Crucially, phase-lag asymmetry acts as a robust control knob: while symmetric phase lags suppress explosive transitions, layer-specific differences promote multistability and double explosive transitions. The higher-order interaction strength $K_2$ and adaptation strengths $q$, $p$, and $h$ further modulate these transitions in a complex, parameter-dependent manner. Excellent agreement between analytical predictions and numerical simulations confirms the robustness of our reduced description.
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Chemical Physics
Orbital choice in constructing model Hamiltonians
David W. O. Sousa and Elvira R. Sayfutyarova
Model
Hamiltonians (e.g., the Hubbard or Heisenberg models) provide a simple yet physically meaningful description of complex electronic phenomena through a small number of parameters, such as electron hopping integrals or
magnetic exchange couplings. Their construction typically exploits the local nature of electron correlation effects and therefore relies on localized orbitals. Although many localization schemes are available, the resulting localized orbitals depend not only on the chosen localization functional but also on the orbital space to which the localization procedure is applied. These choices are often treated as technical details and are rarely discussed explicitly. Here, we demonstrate that different, chemically reasonable choices of localized orbitals can lead to substantially different model
Hamiltonian parameters, even when they produce nearly identical electronic energies. Using Density
Matrix Downfolding, we systematically investigate how the localization functional and, more importantly, the choice of model orbital space affect effective
Hamiltonians derived from ab initio calculations for representative $\pi$-conjugated systems and transition metal complexes.
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Atomic Physics
Hyperfine-driven polarization effects in elastic muon scattering by atomic nuclei
Ivan A. Moiseev, Daria M. Vasileva, Konstantin N. Lyashchenko et al. (+3 more)
We present a theoretical study of polarization dynamics in the elastic scattering of
muons and antimuons by high-
magnetic-moment atomic
nuclei, using ${}_{83}^{209}$Bi as a
benchmark. The analysis tracks the
evolution of (anti)
muon polarization and its transfer to the
nucleus, emphasizing
nuclear-structure corrections. These corrections significantly alter both the differential cross sections and the polarization observables. Our results demonstrate that measuring scattered
muon polarization serves as a sensitive probe for
nuclear charge radii and
magnetic dipole moments.
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All authors Ivan A. Moiseev, Daria M. Vasileva, Konstantin N. Lyashchenko, Igor A. Zhosan, Deyang Yu, Oleg Yu. Andreev
Physics Education
From Local Context to Climate Science: Low-Cost Experimentation in the Initial Training of Physics Teachers
André A. A. Marinho, Edson R. L. Lopes, Jhon KF V. Silva et al. (+2 more)
Climate change poses a major scientific, environmental, and educational challenge, requiring approaches that connect physical concepts, empirical evidence, and socially relevant environmental issues. This study presents and analyzes a low-cost experimental investigation developed within the "Physics and the Environment" course of a Physics teacher training program at the State University of the Tocantina Region of Maranhão (UEMASUL), Brazil. The experiment involved constructing a simplified thermal simulator using accessible materials and comparing a confined system with an open control system, both exposed simultaneously to
solar radiation. The results showed that the average temperature inside the simulator was $45.91^{\circ}\mathrm{C}$, compared to $38.58^{\circ}\mathrm{C}$ in the external control system, corresponding to a mean temperature difference of $7.33^{\circ}\mathrm{C}$ (among other analyses). These results demonstrate that the experimental setup was capable of producing and measuring a significant thermal difference between the two systems. However, the observed temperature rise should not be interpreted as a direct measure of the atmospheric greenhouse effect, given that the experimental apparatus involves both radiative and non-radiative heat transfer mechanisms. The study emphasizes the educational potential of low-cost experimentation as a strategy to integrate electromagnetic radiation, energy balance, temperature, heat transfer, and
climate science into the initial training of physics teachers. It also highlights the importance of explicitly discussing the limitations of experimental models and distinguishing local experimental evidence from conclusions regarding global
climate processes.
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All authors André A. A. Marinho, Edson R. L. Lopes, Jhon KF V. Silva, Mariana S. Costa, Maria A. Morais
Optics
Evaluating the predictive power of pump-probe imaging contrast of melanin for metastatic outcome: A 71-patient study
David Grass, Emma Bao, Martin C. Fischer et al. (+3 more)
Significance: Most melanoma deaths arise from metastatic spread, yet current staging imperfectly identifies which primary tumors will progress. Melanin structure is altered during malignant transformation, and pump-probe microscopy (PPM) measures melanin excited-state dynamics in standard biopsy sections, offering molecular contrast that is complementary to morphology-based assessment. Aim: To determine whether PPM-derived melanin excited-state dynamics in primary cutaneous melanoma can predict metastatic outcome. Approach: We imaged unstained sections from 71 primary cutaneous melanomas and 18 melanoma metastases. Transient absorption curves were fit to a biexponential excited-state model, and the fit parameters were used as features for learning classifiers to predict metastatic outcome. Results: Melanin dynamics separated primary from metastatic tissue: both excited-state lifetimes were shorter in primaries, with common-
language effect sizes up to 0.26. The same parameters did not separate primary tumors by outcome (effect sizes 0.41-0.61), and univariate logistic regression found no significant association for either the excited-state lifetimes or the ESA/GSB ratio. The best classifier reached 74% patient-level accuracy (AUC 0.73), a plateau reached by several unrelated architectures. Conclusions: PPM robustly distinguishes primary from metastatic melanoma tissue, consistent with progressive melanin disaggregation. While it is clear that pump-probe features of melanin thus correlate with tissue differences, melanin dynamics in single sections of the primary tumor, confounded by heterogeneity, do not give robust predictions of metastatic outcome.
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All authors David Grass, Emma Bao, Martin C. Fischer, M. Angelica Selim, Georgia M. Beasley, Warren S. Warren
Physics Education
From data to structure: Construction, breakdown, and reconstruction of an empirical representation in a black-box RC circuit
Kazumasa Kushida
In introductory physics laboratories, a central instructional goal is to help students construct, evaluate, and revise mathematical representations from experimental data rather than apply given formulas. We present a guided data-driven activity in which an RC
circuit is treated as a black box defined through observable input-output relations. Experimental and graphical procedures are provided, while standard RC
circuit theory is initially withheld. Students first examine discharging data obtained under different nominal values of R and C. They rescale time using T=t/RC and compare the normalized voltage v=V/E across
circuit conditions, bringing the discharging data closer to a common trajectory. Graphical linearization through a plot of lnv versus T provides a basis for proposing an empirical representation and allows RC to be interpreted as a time scale rather than being assigned that meaning a priori. When the representation proposed for discharging is tested with charging data, logarithmic linearity is lost despite the continued organization of the data by T. Replacing v with the distance from the steady state, 1-v, restores linearity, and the resulting linear relation provides a basis for proposing a revised representation for charging. The activity thus uses a familiar physical system to make representation construction, breakdown, and reconstruction experimentally explicit. It also emphasizes that an empirical representation must be accompanied by a specified domain of validity and that standard
circuit theory can be introduced a posteriori to interpret the physical meanings that emerge from representational constraints.
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Computational Physics
Structure-Informed Bayesian Inference of Anomalous Transport and Hidden Molecular Trapping in Amorphous Media
Andrey Ananev, Maria Potapova, Nikolay Kondratyuk et al. (+2 more)
Molecular
diffusion in fluctuating amorphous and macromolecular media governs key transport processes across soft-matter physics, energy storage, and biological membranes. Extracting localized trapping states from single-particle tracking trajectories remains a fundamental challenge; because thermal structural breathing continuously reconfigures pore boundaries, conventional
geometric algorithms suffer from severe systematic biases, erroneously merging distinct localized states during cyclic molecular returns. Here, we address this deadlock by shifting the paradigm from local
geometric recurrence to a structure-informed
Bayesian regularization. Leveraging discrete Morse theory, we extract the time-invariant topological skeleton of the fluctuating host
matrix to construct robust, gas-specific physical priors that account for individual molecular dimensions. Trajectory steps are sequentially partitioned via a two-stage probabilistic refinement that dynamically adapts to the transport landscape. Benchmarked against a rigorous environment where synthetic particles explore the actual interconnected
matrix graph, our approach eliminates systemic biases, restricting macroscopic trapping parameter deviations to just a few percent under optimal linear $O(N)$ computational scaling. Applied to hydrogen and methane transport within a type-I kerogen
matrix, serving as a prototype for highly tortuous, flexible macromolecular networks, the method successfully decodes the hidden microscopic mechanisms of confined
diffusion. To ensure immediate broad impact, the documented open-source code and data are made publicly available, offering an accessible strategy readily adaptable to a broad spectrum of tracking phenomena, from ion transport in battery
polymers to
protein trafficking within cellular environments.
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All authors Andrey Ananev, Maria Potapova, Nikolay Kondratyuk, Timur Vostroknutov, Aleksey Khlyupin
Chemical Physics
Examination of Cluster Based Methods to Fermionic Systems
Jeffrey Keyes and Carlos Jimenez-Hoyos
We present the cluster mean field(cMF) and its extensions into perturbation theory(cPT) and coupled cluster(cCC) methods for fermionic systems. We discuss how the commutation rules for fermionic systems modifies the method as well as other computational details. We then perform calculations on the Hubbard model and a few select conjugated molecules to demonstrate the efficacy of the method. We will also use these examples to compare cluster methods to CAS-SCF.
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Instrumentation and Detectors
Non-destructive 3D doping imaging of silicon sensors
Xiangyu Xie, Anna Bergamaschi, Maria Carulla et al. (+9 more)
Silicon sensors are the foundational detection medium for X-rays and charged particles. While their bulk dopant distribution determines device performance, it is conventionally assumed homogeneous because traditional profiling is destructive, spatially restricted, and insensitive at the relevant concentrations. Here we introduce a non-destructive 3D doping imaging technique that turns the readout electronics of a charge-integrating hybrid pixel detector into a massively parallelized capacitance-voltage profiler. With a few tens of micrometres of 3D resolution over wafer-scale areas at concentrations on the order of $10^{11}$ cm$^{-3}$, we image the bulk doping concentration of operational sensors. Macroscopically, we resolve depth-evolving concentric doping rings; microscopically, we uncover scattered doping anomalies that distort local electric fields. The rings modulate the depletion voltage, while the anomalies disrupt local charge collection, a previously overlooked cause of pixel yield and performance degradation. By bridging manufacturing signatures with microscopic defects, this approach provides a non-destructive framework for sensor characterization and yield optimization.
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All authors Xiangyu Xie, Anna Bergamaschi, Maria Carulla, Roberto Dinapoli, Erik Fröjdh, Viktoria Hinger, Davide Mezza, Aldo Mozzanica, Jonathan Mulvey, Bernd Schmitt, Saverio Silletta, Jiaguo Zhang
Chemical Physics · Cross-listed from cond-mat.str-el
Examining Convergence of Cluster Perturbation Theory and Cluster Coupled Cluster for J1-J2 Heisenberg Spin Lattices
Jeffrey Keyes and Carlos Jimenez-Hoyos
In previous work, it was shown that using the cluster mean field(cMF) wavefunction as the zeroth order wavefunction for perturbation theory and coupled cluster produces a reasonable approximation for the J 1-J 2 Heisenberg model in the thermodynamic limit(TDL). However, this work was limited to cPT4 and cCCSD. The central claim of cMF is that it takes strongly correlated systems and makes them weakly correlated so that PT weakly correlated methods can be used. To confirm that this claim is true, it is important to show that the PT and CC series converge. In this paper, we extend the previous calculations to cPT7 and cCCSDTQ5 where we show that the energy is converging. We also discuss how to perform cluster based calculations efficiently in the thermodynamic limit, which is crucial for these more expensive calculations.
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Data Analysis and Statistics
Quantity, quality, and timing: Guiding glacier data assimilation strategies in the high Arctic
Wenxue Cao, Kristoffer Aalstad, Louise S. Schmidt et al. (+1 more)
Accurate simulation of glacier surface mass balance is essential for predicting sea level rise and freshwater resources, but it is constrained by uncertainties in meteorological forcing and model parameters. Here, we deploy glacier data assimilation strategies to assess the value of observations for improving surface mass balance simulation, focusing on observation quantity, quality, and timing. We perform synthetic twin experiments on Kongsvegen glacier, Svalbard, using a Particle Batch Smoother with 1000 ensemble members. Synthetic observations of albedo, snow depth, and surface temperature are assimilated at two quality levels, under two climatic scenarios, and over 12 years. Assimilation benefit is measured as the percentage improvement in the continuous ranked probability score of the posterior glacier surface mass balance relative to the prior. A single optimally timed high quality observation yields mean improvements of up to 80%. Larger numbers of low quality observations partially compensate for lower improvement. In the accumulation zone, however, additional snow depth observations degrade performance through particle degeneracy. Optimal timing is governed by the seasonal transitions of the truth trajectory rather than by prior ensemble spread alone. The optimal windows shift by up to six weeks between early and late melting years. Joint assimilation adds value through temporal diversity rather than observational diversity, while independently timed observations outperform same day combinations. The asynchronously optimally timed combined assimilation of three variables sustains improvements of 85 to 97% across all years in the ablation zone. These findings provide guidelines for adaptive observation scheduling in glacier monitoring and reanalysis.
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All authors Wenxue Cao, Kristoffer Aalstad, Louise S. Schmidt, Thomas V. Schuler
Atomic Physics · Cross-listed from hep-ph
Backward Compton scattering with three vortex particles
Yi Liao, Zhaolong Teng and Hao-Lin Wang
We investigate backward Compton scattering in which an incident
vortex (vx)
photon collides head-on with a plane-wave (pw) electron and both final-state particles are projected onto
vortex states, $\gamma_{\rm vx}+e^-_{\rm pw}\to\gamma_{\rm vx}+e^-_{\rm vx}$. We derive analytically the scattering amplitude and differential cross sections in the energy and cone angle of either final particle. Rotational
symmetry implies a selection rule associated with the conservation of the total angular momentum along the collision axis. A Bessel-Gaussian wave packet is adopted for the incident
photon to provide a physical normalization and regularize the boundary singularities of ideal Bessel states. We present numerical results for a $10~{\rm MeV}$ electron colliding with a
vortex photon of central energy $1~{\rm MeV}$ or $10~{\rm keV}$. The final-
photon distributions exhibit strong energy–angle correlations, topological-charge-dependent interference fringes, and systematic shifts of their dominant peaks, allowing different topological charge sectors to be enhanced through angular or energy post-selection. For a longitudinally polarized incident electron, the dominant channels favor final
photons of matching helicity. For the $1~{\rm MeV}$
photon benchmark, the final electron can likewise be produced as a MeV-scale
vortex state with a sizable cone angle and a large angular-momentum projection. These results demonstrate that triple-
vortex backward Compton scattering offers a potential means of generating and controlling high-energy
vortex photons and electrons.
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Optics
Dynamic Chirality in Photonic Time Crystals
Jianming Mai, Chenwen Yang and Shubo Wang
Temporal modulation offers a fundamentally distinct degree of freedom for active wave control beyond static spatial structuring. Photonic time
crystals (PTCs), based on periodic modulation of electromagnetic parameters in time, have expanded photonic band engineering from space to time by enabling controlled energy exchange between light and the modulation. Yet, the use of PTCs to synthesize rotational dynamics and thereby control chirality and circular dichroism (CD) remains largely unexplored. Here, we propose a spatiotemporal PTC whose central cylindrical element is driven by an azimuthally traveling-wave permittivity modulation. Although the structure is geometrically static, its dielectric profile evolves as an effectively rotating pattern in time. This synthetic rotation lifts a static modal degeneracy and produces two nondegenerate counter-rotating states with opposite orbital angular momenta. These
chiral modes selectively couple to left- and right-circularly polarized light, giving rise to tunable CD. In addition, the spatiotemporal modulation induces orbital angular-momentum conversion between the Floquet replica bands. Our work reveals the microscopic origin of dynamic
chiral response and establishes a strategy for reconfigurable
chiral photonics without mechanical motion.
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Chemical Physics
Competing Ring-Opening and Hofmann Elimination Pathways in Aqueous TEMPO Catholytes: A First-Principles Study
Line Mouaffac, Maiwenn Souetre, Guillaume Jeanmairet et al. (+1 more)
Aqueous redox-flow batteries based on TEMPO derivatives are promising for large-scale energy storage, but their practical use is limited by the chemical instability of the oxidized N -oxoammonium state. In this work, we investigate the degradation of five TEMPO derivatives using ab initio molecular dynamics combined with enhanced sampling. Two proposed degradation mechanisms, ring opening and Hofmann elimination, are examined and their corresponding activation free energies are compared. For all derivatives considered, ring opening exhibits a lower activation free energy than Hofmann elimination, identifying it as the kinetically preferred degradation pathway. The magnitude of the ring-opening barrier, however, varies significantly between molecules, showing that different functionalizations strongly influence its stability toward degradation. The predicted preference for ring opening is consistent with available experimental studies, which have identified or inferred ring-opening degradation for several TEMPO-based catholytes. These results provide an atomistic picture of degradation pathways that are difficult to resolve experimentally and highlight the importance of molecular structure in controlling the kinetic stability of TEMPO derivatives in aqueous electrolytes.
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All authors Line Mouaffac, Maiwenn Souetre, Guillaume Jeanmairet, Mathieu Salanne
Computational Physics · Cross-listed from astro-ph.IM
Full Characterisation of the Polarisation Primary Beam of the GRAO 32-m Telescope
Theophilus Ansah-Narh, Nia Imara, Benedicta Woode et al. (+4 more)
Direction-dependent instrumental polarisation is a major systematic limitation in high-fidelity single-dish
radio polarimetry, yet a unified characterisation of beam leakage and the conditioning of polarisation recovery is lacking for the Ghana
Radio Astronomy Observatory (GRAO) 32-m
telescope. We aim to establish a quantitative, direction-dependent polarimetric beam model at 5.0 and 6.7 GHz. High-resolution GRASP electromagnetic simulations of the nominal
telescope configuration are used to derive the full complex Jones response and corresponding Mueller
matrices, from which beam shape, beam squint, instrumental Stokes leakage, and intrinsic cross-polarisation ratio (IXR) are evaluated across the primary beam. The Stokes $I$ beams have half-power beam widths of $396.4$ and $295.3$ arcsec at 5.0 and 6.7 GHz, respectively, with main-beam efficiencies of $56.4$ and $55.6$ per cent. At 5.0 GHz, the circular-polarisation beam squint is $9.96$ arcsec ($2.5$ per cent of the HPBW), whereas no statistically significant squint is detected at 6.7 GHz. Leakage from Stokes $I$ into linear polarisation remains below $0.1$ per cent within the half-power beam but increases substantially towards the sidelobes. IXR reaches approximately $80$ dB on axis and decreases with angular offset. These results establish the intrinsic electromagnetic polarimetric response of the GRAO 32-m
telescope and provide a quantitative baseline for direction-dependent calibration and subsequent observational validation.
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All authors Theophilus Ansah-Narh, Nia Imara, Benedicta Woode, Joseph Bremang Tandoh, Emmanuel Proven Adzri, Diana Klutse, Evaristus Uzochukwu Iyida
Optics
Quantized transport of two-dimensional multifrequency solitons
Fangwei Ye, Yaroslav V. Kartashov and Vladimir V. Konotop
We consider Thouless pumping of two-dimensional quadratic
solitons composed from coherently interacting fundamental frequency (FF) and second harmonic (SH) components propagating in a periodic $\chi^{(2)}$ material. The pumping is induced by two mutually sliding two-dimensional
lattices defined by shallow transverse and longitudinal periodic refractive index modulation. Focusing on
solitons in the semi-infinite gap, we find three distinct pumping scenarios: the absence of transport for small-amplitude
solitons, non-quantized transport in a transient regime at intermediate amplitudes, and stable quantized transport for
solitons with relatively large amplitudes. Different directions of the sliding velocity were investigated resulting in different trajectories of
soliton center. The transition to the regime of quantized transport is found to depend strongly on phase mismatch between FF and SH waves that also influences stability properties of two-dimensional $\chi^{(2)}$
lattice solitons. We also show that pumping with longitudinal periods in the x and y directions, whose ratio approximates an irrational number, induces quantized transport whose direction rapidly converges, with increase of the accuracy of the approximation, to a limiting pumping direction determined by this irrational number and corresponding to truly incommensurate longitudinal periods.
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Physics and Society
HierX: Fast Multi-Scale Distance-Decay Interaction on Million-Node Networks
Alexander Hellervik, Joakim Bohlin and Claes Andersson
Many models across the sciences require global distance-decay interactions on large sparse networks.
Gravity models, accessibility measures, spatial economic models, and network influence processes all evaluate distance-weighted potential fields: each location accumulates contributions from every other location, weighted by a decaying function of the shortest-path travel cost between them. Computed directly, such aggregate fields require the dense
matrix of all pairwise network costs, which scales quadratically in time and
memory. Common approximations either discard long-range contributions or fail when interaction is governed by network distances rather than
geometric proximity. We introduce HierX, a hierarchical sparse-plus-correction operator for distance-decay potential fields on networks. HierX constructs multi-scale representative layers with explicit correction terms ensuring each location pair contributes exactly once at the finest available resolution. Under bounded-growth assumptions common in spatially embedded networks, applying HierX scales as O(n log n). Systematic
benchmarks confirm quasi-linear scaling to 100,000 nodes. In head-to-head comparison with distance cutoff truncation and Nystrom low-rank approximation on 25,000-zone networks, HierX achieves 5-9% RMSE at a fraction of the computational work; Nystrom degrades severely on steep decay kernels. Case studies compute population-weighted accessibility on the 2.58-million-node Great Britain driving network and the 1.77-million-node London pedestrian network: a one-time hierarchy construction (~1 hour) yields a compact reusable operator that then evaluates each national-scale accessibility field in under one second (~700 ms for Great Britain, ~150 ms for London). Open-source code and worked examples are provided.
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Instrumentation and Detectors
Event-by-Event Space-Charge Gain Suppression in LGADs and Its Impact on Time Resolution
Djunes Janssens, Michael Moll and Heinrich Schindler
Low Gain Avalanche Detectors (LGADs) achieve time resolutions below 50 ps through internal charge multiplication, yet the gain is not a fixed device property as the space-charge of the multiplied electron-hole density screens the gain layer field, which suppresses further impact ionization. While TCAD simulations reproduce the average gain suppression, their deterministic treatment of a continuous charge density cannot capture the event-by-event fluctuations that determine the timing performance. We present a Monte Carlo study of space-charge-induced gain suppression in LGADs using the Garfield++ framework, in which the dynamic field of the drifting carriers, computed from a coarse-grained system of charged rings, is superimposed on TCAD-computed static field maps of Centro Nacional de Microelectrónica (CNM) and Hamamatsu Photonics (HPK) produced sensors while preserving single carrier avalanche statistics. The simulated gain reproduces published two-
photon absorption-transient current technique measurements across two orders of magnitude in injected charge, including the dependence on the injection depth. For minimum ionizing particles, the event-by-event coupling between deposited charge and gain compresses the Landau tail of the multiplied charge, narrowing the signal arrival time distribution and improving the intrinsic time resolution of the HPK-S1 sensor investigated in this work from 53.9 $\pm$ 1.0 ps to 44.5 $\pm$ 0.9 ps. Treating the primary ionization as a
stochastic sequence of charge clusters, it is further shown analytically that any gain suppression that decreases with the cluster size narrows the centroid time distribution.
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Fluid Dynamics
Closed-Form Solution for Oscillatory Flow and Wall Shear Stress in Axisymmetric Corrugated Tubes
Frederik Keil, Paolo Malgaretti, Othmane Aouane et al. (+1 more)
Pulsatile flow in corrugated tubes arises in hemodynamics and microfluidics, where oscillatory forcing and
geometric constrictions jointly determine transport and wall loading. We extend Womersley's classical solution for oscillatory flow in a rigid circular tube to rigid axisymmetric tubes of slowly varying radius. Within the lubrication approximation, we derive closed-form expressions for the axial velocity profile, volumetric flow rate, phase lag, and wall shear stress at an arbitrary Womersley number. Three-dimensional
lattice Boltzmann simulations are used to assess the regime of validity of the theory. The analysis shows that the local velocity profile varies strongly along the tube, ranging from plug-like in wide sections to more
parabolic near bottlenecks. The cycle-maximum flow rate decreases with increasing corrugation, but this reduction weakens as pulsatility increases, reflecting a crossover from the quasi-steady scaling $\langle R^{-4}\rangle^{-1}$ to the high-frequency scaling $\langle R^{-2}\rangle^{-1}$. The wall shear stress is maximal at the bottleneck and decreases with Womersley number. For sinusoidal corrugations, the bottleneck wall shear stress depends non-monotonically on the corrugation because of the competition between local shear amplification and global hydraulic resistance. Closed-form expressions for the time-averaged wall shear stress and oscillatory shear index further connect the theory to standard hemodynamic metrics.
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All authors Frederik Keil, Paolo Malgaretti, Othmane Aouane, Jens Harting
Accelerator Physics
Flexible Spectral-Normalized Neural Gaussian Process for Dynamic Aperture Prediction
Yousra El-Bachir, Frederik Van der Veken, Davide di Croce et al. (+4 more)
We address the challenge of scalable uncertainty quantification in large-scale scientific applications, where complex state-of-the-art machine learning methods are often computationally infeasible. Our primary contribution is a simple yet effective empirical Bayes method for automatically tuning the hyperparameters of a flexible, heteroscedastic Spectral-normalized Neural Gaussian Process. This approach retains the expressiveness and uncertainty-awareness of semi-
Bayesian neural models while significantly reducing the computational burden by integrating hyperparameter learning directly into the training loop. We demonstrate the practical impact of our method on the task of estimating the dynamic aperture in circular particle accelerators, a fundamental problem in high-energy physics
colliders and storage rings, using simulation data from the case of the Large
Hadron Collider at CERN. Traditional approaches to DA estimation require extensive particle-tracking simulations, which are prohibitively time-consuming and resource-intensive. Our results show that the proposed method achieves competitive predictive performance and well-calibrated uncertainty estimates at much lower computational cost than state-of-the-art approaches. We stress that, beyond this application, the proposed empirical Bayes framework offers a general solution for training heteroscedastic neural models in situations where manual hyperparameter tuning is impractical. Accordingly, we anticipate that this framework can be applied to other domains that encounter comparable computational limitations.
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All authors Yousra El-Bachir, Frederik Van der Veken, Davide di Croce, Carlo Emilio Montanari, Massimo Giovannozzi, Ekaterina Krymova, Tatiana Pieloni
Atmospheric and Oceanic Physics
Neptune: An AI model for Global Ocean Subseasonal Prediction
Davide Donno, Italo Epicoco, Massimo Cafaro et al. (+8 more)
Subseasonal-to-seasonal (S2S)
forecasting is societally critical, supporting decision-making in sectors ranging from water and agricultural management to disaster risk reduction, energy planning, and insurance. Achieving reliable predictions at these timescales requires representing the ocean and its dynamics, but traditional physics-based Ocean General Circulation Models (OGCMs), are computationally expensive and difficult to develop and improve because of the code complexity. In this work, we propose Neptune, an end-to-end data-driven framework for global ocean and sea-ice components emulation tailored for S2S timescales, up to 60 days. Neptune combines Convolutional Neural Networks (CNNs) and Spherical
Fourier Neural Operators (SFNOs) to effectively capture local features and global cross-scale interactions, thereby obtaining a coherent representation of the ocean state. Forced by prescribed daily atmospheric fields, Neptune emulates ocean state variables, from temperature and salinity, to zonal and meridional currents, from sea surface height to sea ice thickness and concentration, with daily outputs at the ocean surface and through the water column. Specifically, we propose two variants of Neptune, Neptune-1 and Neptune-025, capable of emulating the ocean state at 1{\deg} and 0.25{\deg} resolution, respectively. Evaluated against a suite of metrics, including statistics (RMSE, CRPS and ACC), physical coherency (Ocean Heat Content, Eddy Kinetic Energy and Ice Brier Score) and
climate indices (ENSO and Z20 metric, IOD), Neptune successfully reproduces the spatio-temporal
evolution of the oceanic fields up to 60 days, and is stable over long timescales. Neptune provides compelling evidence that end-to-end data-driven ocean emulators can become a powerful component of next-generation S2S
forecasting systems, emulating ocean state at high spatio-temporal resolution.
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All authors Davide Donno, Italo Epicoco, Massimo Cafaro, Gabriele Accarino, Mohammad M. Amirian, Viviana Acquaviva, Paola Nassisi, Doroteaciro Iovino, Annalisa Bracco, Simona Masina, Pierre Gentine
Computational Physics · Cross-listed from cs.LG
Structured Multi-Level-Set Inversion for 3-D Electromagnetic Inverse Scattering
Yutong Du, Zicheng Liu, Bo Qi et al. (+3 more)
Many dielectric targets encountered in 3-D electromagnetic inverse scattering exhibit piecewise-homogeneous material distributions, which provide useful structural information for inversion. To exploit this property, this paper proposes a structured multi-level-set inversion (SMLSI) method within a physics-driven neural network (PDNN) framework. Instead of directly parameterizing the contrast distribution, SMLSI represents it in terms of object support and material distribution. Multiple level-sets are mapped to soft-support functions and combined through a soft-union operation to construct the object support. The normalized contributions of these soft-support functions, together with trainable complex relative permittivities, determine the material distribution within the support. The level-set residuals are parameterized by a coordinate-based neural network, and the trainable parameters are optimized from scattered field data. Structure-aware regularization terms are introduced to promote binary object support and spatially coherent material regions while reducing material mixing and redundant activation of level-set supports. Adaptive regularization weighting is further employed to reduce the dependence on manual parameter tuning. Numerical experiments demonstrate that SMLSI improves reconstruction accuracy over direct contrast parameterization and enables the recovery of irregular 3-D geometries, closely spaced objects, and multiple material regions. Compared with CSI and $L_{2/3}$-FBE-WCIE, SMLSI achieves more accurate reconstructions on representative synthetic targets. Experimental validation using 3-D Fresnel data further demonstrates its applicability to measured scattering data.
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All authors Yutong Du, Zicheng Liu, Bo Qi, Yali Zong, Xin Li, Peixian Han
Optics
Encoding Propagation Invariance into Light
Wenxiang Yan, Tianyue Li, Zhuolin Wu et al. (+6 more)
Diffraction governs the axial
evolution of optical fields, whereas conventional
holographic synthesis primarily controls their transverse structure. Here we add axial diffraction management as an additional design freedom to the transverse_field programmability of holography, enabling the transverse optical function and its diffraction-driven axial
evolution to be co_designed. By incorporating established propagation_invariant dynamics into computer_generated hologram and meta_hologram synthesis, we realize task_selectable axial responses in user_defined monochromatic, full-colour and vectorial fields. On a spatial light modulator, the same scalar user_defined field is configured either for a rapidly evolving 1.2_cm depth of field or for an approximately 75_cm propagation_invariant range. Millimetre_scale metasurfaces further enable metre_scale refocusing_free full_colour projection and vectorial colour fields with polarization textures preserved over more than 30 cm. This transverse_axial co_design framework extends
holographic field synthesis beyond transverse programmability, providing a broadly compatible route towards task_configurable optical systems and compact multidimensional photonics.
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All authors Wenxiang Yan, Tianyue Li, Zhuolin Wu, Yiyu Zhao, Zhi-Cheng Ren, Xi-Lin Wang, Hui-Tian Wang, Shuming Wang, Jianping Ding
Optics
Universal Broadband Linear Optical Transformations by an Interlaced Structured Integrated Photonic Processor
Ilya V. Kondratyev, Kseniia N. Urusova, Artem S. Argenchiev et al. (+8 more)
Reconfigurable photonic integrated
circuits enable applications in a wide range of fields. They represent a powerful platform for signal processing due to the ability to perform parallel computations. In this work, we demonstrate a photonic processor based on a six-channel universal chip fabricated by femtosecond
laser writing with an interlaced architecture comprising multiport beam splitters. We exploit and enhance a previously demonstrated calibration procedure for a single building block, and extend it to a complete six-channel interferometer, reconstructing the corresponding interferometer models over a broad spectral range. We validate them by measuring a set of 100 Haar-random
unitary matrices, achieving mean amplitude fidelities of 95.9 %, 98.0 %, and 96.0 % for radiation wavelengths 910, 945, and 980 nm, respectively, without on-device optimization. Furthermore, we experimentally realize spectral demultiplexing and multiplexing at these wavelengths, yielding routing fidelities ranging from 90.1 % to 96.5 % and total crosstalk values ranging from -9.6 to -14.4 dB, confirming the applicability of the fabricated photonic processor to practical wavelength-routing tasks.
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All authors Ilya V. Kondratyev, Kseniia N. Urusova, Artem S. Argenchiev, Sergei A. Zhuravitskii, Nikolay N. Skryabin, Alexander D. Golikov, Vadim V. Kovalyuk, Gregory N. Goltsman, Ivan V. Dyakonov, Stanislav S. Straupe, Sergei P. Kulik
Plasma Physics
Demonstration of a 10-metre-long discharge plasma source for plasma wakefield acceleration
C. Amoedo, N. Lopes, N. E. Torrado et al. (+13 more)
The AWAKE experiment at CERN uses high-energy
proton bunches to drive
plasma wakefields capable of accelerating electron bunches up to hundreds of GeV in a single
plasma. Realising this potential requires a
plasma source that can extend to tens of metres while maintaining high longitudinal uniformity and reproducibility. Towards this goal, we report on the first experimental characterisation and beam-based validation of a 10-metre-long pulsed-DC discharge
plasma source (DPS) used as an alternative to the
laser-ionised rubidium vapour
plasma source (VPS). The DPS reliably delivered
plasma densities in three noble gases (He, Ar, Xe) at electron densities between 10$^{14}$ and 10$^{15}$ cm$^{-3}$.
Proton bunch self-modulation was observed with all three gases, and the resulting modulation frequency was used as a beam-based diagnostic of the
plasma density, showing good agreement with laboratory interferometry measurements. The event-to-event modulation frequency was demonstrated to be reproducible to within 0.63%, comparable to that of the VPS. These results establish the DPS as a valid alternative
plasma source for beam-driven wakefield experiments, and support its further development towards longer
plasma lengths. The present design is tailored to AWAKE requirements, but the underlying discharge concept provides a route to long, reproducible
plasma sources with straightforward density control through discharge-beam timing for other beam-
plasma experiments.
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All authors C. Amoedo, N. Lopes, N. E. Torrado, F. Silva, P. Muggli, L. Verra, M. Turner, G. Zevi Della Porta, M. Bergamaschi, A. Clairembaud, J. Mezger, F. Pannell, N. Z. van Gils, E. Gschwendtner, A. Sublet, the AWAKE Collaboration
Computational Physics · Cross-listed from cs.SC
Physical Law Ecology: mapping multi-mechanism ecologies as the zeroth step of data-driven scientific discovery
Xiongheng Bian, Xiangyu Cui, Ma Feng et al. (+1 more)
Every data-driven equation discovery method assumes (implicitly and without verification) that the target system obeys a single governing law ($K{=}1$). Here we show that this assumption is the primary bottleneck limiting scientific discovery in multi-mechanism systems, and introduce Physical Law Ecology, a framework that makes $K^*$ (the number of coexisting independent mechanisms) itself the first quantity to be determined from data. The framework automatically mines a pool of topologically distinct candidate equations, constructs a continuous dominance weight field across parameter space, and discovers analytic
evolution laws governing mechanism succession—with optional monotonicity constraints encoding irreversible physics. Across four unrelated systems (elastomer mechanics, pool boiling,
galactic dynamics, and droplet evaporation), BIC consistently identifies $K^*{=}3$ independent governing
topologies. Applied to 163 SPARC
galaxies (3,269 spatially resolved measurements), the framework autonomously recovers three gravitational laws whose coexistence provides evidence against the single-universal-acceleration hypothesis of MOND ($p<10^{-34}$). In engineering applications, multi-law weighted prediction reduces error by 67-72% over single-equation baselines while retaining full interpretability. By establishing the determination of $K^*$ as the zeroth step of scientific discovery-prior to and independent of equation search—this work opens a direction orthogonal to existing symbolic regression: not finding better equations, but mapping the ecology of mechanisms that govern complex systems.
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All authors Xiongheng Bian, Xiangyu Cui, Ma Feng, Xiaoyan Shen
Optics
Harmonics of femtosecond and continuous-wave radiation for precision spectroscopy: generation efficiency and spectral line shape
Nikita Zhadnov, Olga Khronusova, Alexey Russkikh et al. (+2 more)
Precision spectroscopy in the UV and VUV ranges, including spectroscopy of the thorium-229
nuclear transition (148.4 nm), requires narrow-band sources obtained by frequency multiplication of stabilized
lasers. Upon harmonic generation, the radiation intensity drops and the phase noise grows. In this work, both factors are analyzed for two types of primary sources: a continuous-wave single-frequency
laser and a femtosecond optical frequency comb. It is shown that in the weak-conversion regime for equal average input powers, the power of the central mode in the spectrum of the Kth harmonic of femtosecond radiation matches the harmonic power of continuous-wave radiation for K=2 and noticeably exceeds it for K>2. Within the first-order dispersion approximation, group-velocity mismatch reduces the total conversion efficiency without affecting the power of the exactly phase-matched central mode. The transformation of the phase noise of an ultrastable
laser upon harmonic generation leads to two effects that depend on K: the harmonic linewidth grows linearly, whereas the power fraction in the carrier decreases as a Gaussian function and is determined by the high-frequency noise of the stabilization loop (the servo bumps). Measurements of the phase-noise spectra of a
laser stabilized to a Fabry-Perot cavity show that for a typical rms phase excursion of ~100 mrad the carrier loses about half of its power already at the eighth harmonic, while for a non-optimal stabilization-loop gain carrier collapse occurs at the second-third harmonic.
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All authors Nikita Zhadnov, Olga Khronusova, Alexey Russkikh, Nikolay Kolachevsky, Anatoly Masalov
Atmospheric and Oceanic Physics
On the role of moderator and mediator variables in conditional event attribution of heatwaves over Europe
Sebastian Buschow, Petra Friederichs and Andreas Hense
This study examines how a risk-based attribution analysis of European heat wave events under
climate change varies when explanatory variables are included in the analysis. Instead of relying solely on temperature statistics, the analysis is conducted while conditioning on large-scale circulation or pre-existing
climate anomalies. Using the hot European summers of 2006 and 2007 as examples, we observe several systematic effects. Controlling for the presence of atmospheric blocking explains much of the natural temperature variability and greatly improves the separation of present and pre-industrial distributions in both years. In 2006, the predominant strong blocking raised the expected temperatures, so that, by comparison, the observed anomaly no longer appeared unusually hot, even in a pre-industrial
climate. More complex effects occur when the conditions are part of the causal chain of
climate change, for example, acting as moderators or mediators. By conditioning on such variables, we may remove part of the
climate change signal and thus fundamentally alter the outcome of the attribution study. Using a simplified model we demonstrate why attribution studies with different kinds of conditions can reach different, seemingly contradictory conclusions.
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Chemical Physics
TSBench: A physics-grounded benchmark for evaluating LLM understanding of chemical reaction mechanisms
Xiaohu Xu and Tong Zhu
Understanding a chemical reaction requires mapping a symbolic reactant-product description onto the three-dimensional pathway through which atoms rearrange, yet chemistry
benchmarks for large
language models (LLMs) largely probe factual knowledge and text-based
reasoning. Here we introduce TSBench, a
benchmark in which an LLM
agent uses structure-editing tools to construct three-dimensional transition-state (TS) guesses verified by an automated
quantum-chemical pipeline, yielding a physics-grounded pass/fail verdict. Across 546 evaluations of seven frontier LLMs on 78 elementary reactions, the aggregate success rate rose from 50.4% to 66.8% under diagnosis-driven revision; the best models approached 90% on the simplest reactions, yet performance dropped sharply with mechanistic complexity. Most failed attempts produced locally plausible saddle points whose reaction paths led to the wrong reactant-product pair, revealing local
geometric intuition without a robust grasp of the global reaction coordinate. TSBench establishes a mechanism-level yardstick for LLM
agents in mechanism-sensitive tasks such as synthesis planning and autonomous experimentation.
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