Accelerator Physics
Energy spectrums of slowed neutrons in heterogeneous uranium-carbon and thorium-carbon fission media
Vyacheslav Lavrukhin, Serhiy Chernezhenko, Mykhailo Shcherbyna et al. (+2 more)
Using the Geant4 and OpenMC Monte Carlo codes, the energy spectra of moderated
neutrons were studied in homogeneous uranium dicarbide and uranium dioxide media, as well as in heterogeneous uranium and carbon and thorium and carbon channel type fission structures with various compositions and
lattice parameters. In homogeneous uranium dicarbide the spectral maximum lies in the from 20 to 50 keV range, which is important for the design of a prototype fast single channel reactor operating in the traveling wave fission mode with a soft fast
neutron spectrum. A heterogeneous thorium and carbon medium that forms a thermal
neutron spectrum has been identified, enabling the realization of a traveling wave mode of
neutron nuclear fission on thermal
neutrons. By varying channel
lattice parameters and introducing burnable absorbers (Cd, In), the possibility of forming a super thermal
neutron spectrum (from 1 to 20 eV) in a heterogeneous uranium and carbon medium was demonstrated. The results are useful for the development of
nuclear transmutation reactors and next generation reactors operating in the traveling wave mode.
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All authors Vyacheslav Lavrukhin, Serhiy Chernezhenko, Mykhailo Shcherbyna, Viktor Tarasov, Edgar Zhelezko
Optics · Cross-listed from quant-ph
Atmospheric Turbulence-Aware Optimization of Generalized Kennedy Receivers for Coherent-State BPSK Quantum Communication
Md Ashraf Hossain Ifty and Rahul Bhadani
We investigate generalized Kennedy receivers for coherent-state BPSK communication over turbulent free-space optical channels. An ergodic mutual-information framework is developed to jointly optimize the receiver displacement and input prior probabilities under Gamma–Gamma fading.
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Instrumentation and Detectors
Demonstration of inkjet-printed targets for activation cross-section measurements: deuteron-induced reactions on strontium up to 24 MeV
Akihiro Nambu, Masayuki Aikawa, Yudai Shigekawa et al. (+4 more)
Excitation functions for the $^{nat}$Sr($d,x$) reactions producing $^{86m,g}$Y, $^{87m,g}$Y, and $^{88}$Y were measured up to 24-MeV deuteron energy using the stacked-foil technique and gamma-ray spectrometry. The $^{nat}$Sr targets were prepared using an inkjet printing method to ensure sufficient uniformity. To the best of our knowledge, this is the first experimental report of excitation functions measured using inkjet-printed targets, demonstrating the applicability of this technique to cross-section measurements. The measured cross sections were discussed in comparison with literature data and TENDL-2023 predictions. Our cross sections were generally consistent with those reported in the previous study, but were slightly higher in the threshold energy region. The TENDL-2023 library generally overestimates the experimental values. We report the experimental cross sections for the $^{nat}$Sr($d,x$)$^{86m}$Y reaction for the first time. These measured cross sections contribute to the refinement of
nuclear reaction databases for practical applications.
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All authors Akihiro Nambu, Masayuki Aikawa, Yudai Shigekawa, Yousuke Kanayama, Tomohiro Tomitsuka, Sayantani Mitra, Hiromitsu Haba
Plasma Physics
Gas release from metals under irradiation with elliptic Gaussian laser beam during LID-QMS analysis
A.A. Stepanenko and Yu.M. Gasparyan
Laser-induced-desorption quadrupole-mass-spectrometry (LID-QMS) diagnostics is considered as one of the candidate methods for the remote control of tritium inventory in the ITER first wall. Studies involving LID-QMS generally assume the circular shape of the
laser spot on the analyzed surface. At the same time, the diagnostics
laser source cannot be always positioned so as to irradiate tokamak tiles under normal angles, which results in the
laser spot shape differing from the circular one. In this contribution, we analyze the tritium removal process under sample irradiation by an
elliptic Gaussian
laser beam, extending the results of our previous analysis [A.A. Stepanenko, Yu.M. Gasparyan, Physica Scripta 99 (8), 085604 (2025)]. The thermal desorption model governing the heat transport and tritium removal from the solid is formulated. The new analytical expression describing the sample temperature dynamics is derived. The developed model is used to examine the impact of the
laser beam/spot ellipticity on the tritium desorption process from a tungsten sample. The conditions, under which the
elliptic beam can be approximated with the circular one for the rapid assessment of the amount of desorbed tritium, are assessed.
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General Physics
Coherent Oscillations of Protons in Hydrogen-loaded Metals
G. Modanese
We review recent calculations and numerical simulations showing the formation of coherent states of
protons in hydrogen-loaded metals with a cubic
crystal lattice. In these states
protons oscillate coherently at frequencies of the order of $10^{13}\,\mathrm{Hz}$ and in a fixed phase relation with a strong high-frequency electric field which is trapped in the material, especially if the material is made of micro-powders. The energy gap of the coherent ground state is estimated to be well above thermal energies, of the order of a fraction of an eV per particle, and therefore large enough to make the state robust against thermal fluctuations. The analytical calculations address the realistic case of a large number of
protons, in the rotating-wave approximation. The numerical calculations are presently limited to a small number of
protons but go beyond the rotating-wave approximation and allow one to take into account a dissipation term associated with the strong oscillating electric field. The next task of this theoretical model is to compute the excited states of the coherent system. There are strong indications that in those states
protons can be excited by an external pump to energies much larger than those achievable by single incoherent
protons in condensed matter. Such energies are large enough to make possible some electron-capture processes, with generation of slow
neutrons. This dynamical mechanism offers an alternative to the Widom–Larsen hypothesis of “heavy electrons”, and is closer to current models in mainstream physics. The consequences, in terms of
nuclear transmutations, of
neutron generation via electron capture would be similar to those predicted by Widom and Larsen, plus several other processes like those recently re-examined by Metzler et al.
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Computational Physics · Cross-listed from cond-mat.stat-mech
Power Series for the Quantum Statistical Mechanics Probability with Results for the Second Virial Coefficient of Helium
Phil Attard
A power series for the Wigner-Kirkwood pair commutation function for
quantum statistical mechanics in classical phase space is given with terms automatically generated by recursion. The calculated second virial coefficient agrees with the measured values of helium for temperatures greater than 65 K. Prospects for a general
quantum Monte Carlo
algorithm are discussed.
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Optics
Sidewall-Poled Nanophotonic Lithium Niobate with Bidirectional Characterization
Aditya Tripathi, Michael S. Bullock, Parash Thapalia et al. (+10 more)
Accurate characterization of integrated nonlinear photonic devices is often limited by unknown facet-coupling losses and fabrication-induced non-uniformities, leading to systematic over- or underestimation of the intrinsic on-chip performance. Here, we present and demonstrate a unified bidirectional characterization framework that exploits nonlinear interactions under forward and backward propagation to independently extract facet-specific coupling efficiencies, intrinsic nonlinear conversion efficiency, and the longitudinal quasi-phase-matching profile using only classical power measurements. We experimentally validate the method using sidewall-poled thin-film lithium niobate waveguides, obtaining a normalized second-harmonic generation efficiency of $(1850 \pm 20)~\%\mathrm{W}^{-1}$ while simultaneously demonstrating broadband non-degenerate optical parametric amplification and parametric generation spanning more than $10~\mathrm{THz}$. Our framework is non-destructive, relies solely on classical power measurements, requires neither time-intensive microscopy nor calibrated internal references, and is compatible with wafer-scale testing, providing a general route to rigorous benchmarking and high-throughput characterization of photonic devices across material platforms.
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All authors Aditya Tripathi, Michael S. Bullock, Parash Thapalia, Pooja Kulkarni, Jaber Balalhabashi, Robert Kwolek, Shiva Behzadfar, Kazuki Hirota, Shion Eto, Rintaro Tsuchida, Liam Beaudoin, Sasan Fathpour, Rajveer Nehra
Computational Physics · Cross-listed from q-fin.CP
Calibrating Inelastic Markets to Options: The Lean Marketron and the Generalized Langevin Equation
Andrey Itkin
The Marketron model of \cite{HalperinItkin2025Mark} and its option pricing extension in \cite{HalperinItkinMarketron2} suffer from structural non-identifiability: an eighteen-parameter space traps solvers in suboptimal local minima and renders economic quantities unmeasurable. By removing exact scaling gauges and sign
symmetries, freezing non-financial parameters by explicit criteria, and adiabatically eliminating the fast hidden signal, we derive a robust nine-parameter reduced model. A Gauss-Newton Hessian with empty null space and a
manifold-boundary analysis confirm that the reduced core carries no exact
symmetry and admits no further reduction. A diffusive correlation between flow and return innovations captures the short-maturity skew. A staged calibration from the physical measure to the risk-neutral measure, illustrated on SPX options, fits the whole surface with a single parameter set. The same reduction turns the wedge between the physical and pricing values of the flow block into a well-defined
market price of flow risk rather than a ridge artifact, identifiable here for the first time, though a single surface constrains its level only weakly. Finally, our analysis reveals that in the Marketron model the log-price obeys a generalized Langevin equation with a closed-form, state-modulated
memory kernel, and that the
memory variable itself is the exact Markovian lift of this kernel. This mapping also yields a testable condition, the equality of the signal and
memory relaxation rates, which on the SPX surface come out well separated, though both weakly identified, placing the fitted
market tentatively in the driven, non-
equilibrium regime and turning the active-matter reading from an analogy into a falsifiable constraint.
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Fluid Dynamics
Wind farms as sensor arrays of turbulent boundary layer spatio-temporal flow structure
Manuel Ayala, Dennice Gayme and Charles Meneveau
Temporal fluctuations of wind farm-generated power arise from the interaction between atmospheric
turbulence, turbine properties, and wind-farm layout. However, accurately characterizing these fluctuations remains an open challenge. We here present and extend an analytical framework to predict the temporal spectrum of wind farm power-fluctuations, and compare its predictions with detailed large-eddy-simulations (LES) of a wind farm operating within a conventionally neutral boundary layer. The modeling framework assembles several established concepts from turbulent boundary layer physics: a spatio-temporal
turbulence spectral model accounting for mean advection and assuming random sweeping by large eddies, a top-down wind farm model of a fully developed wind turbine array boundary layer flow providing the required mean-flow and
turbulence scales, and a spatial sampling kernel representing turbine positions and finite rotor size. The latter is extended to three dimensions to represent filtering of spatial fluctuations of
turbulence along the vertical direction. Using only atmospheric, turbine, and layout parameters, the model predictions are evaluated against an extensive LES database of a large wind farm on flat terrain. The model accurately predicts the aggregate power frequency spectrum, including peaks associated with advection between turbine rows, the decay of inertial-range
turbulence fluctuations due to rotor averaging, and spectra of aggregate power signals from various arrangements of groups of turbines within the array (e.g. staggered or random subsets). The ability to predict wind power fluctuation spectra from fundamental fluid dynamics and existing boundary layer
turbulence models could help improve wind farm grid integration.
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Optics
Impact of Plasmonic Modes and Thermophysical Properties on the Double-Pulse Structuring of Highly-Ordered LIPSS for Biosensing Applications
G.D. Tsibidis, F. Fraggelakis, P. Lingos et al. (+5 more)
The fabrication of highly ordered
laser-induced periodic surface structures (LIPSS) on thin metallic films is dictated, predomaninatly, by a synergy of periodic electromagnetic energy deposition and complex fluid dynamics. In this work, we present a combined experimental and theoretical study on the formation of ultra-regular LIPSS on 32-nm-thick Au films using a double-pulse femtosecond
laser scheme. We demonstrate that for thin films, the excitation of coupled Surface Plasmon Polaritons (SPPs) at both interfaces dictates the initial energy distribution. On the othe hand, the final morphology is greatly influenced by hydrodynamical processes. Interestingly, due to the low electron-
phonon coupling of Au and the high thermal confinement of the thin film, single-pulse irradiation leads to uncontrolled hydrodynamic instabilities a non uniform topographies. Thus, we demonstrate that a double-pulse approach with an optimized interpulse delay ({\Delta}{\tau}=1.2 ns) effectively controls the melt duration and viscosity, suppressing complex fluid motion and promoting the growth of highly ordered arrays. These structures support narrow surface
lattice resonances (SLRs) suitable for high-sensitivity plasmonic biosensing.
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All authors G.D. Tsibidis, F. Fraggelakis, P. Lingos, E. Cusworth, V.G. Kravets, A.N. Grigorenko, A.V. Kabashin, E. Stratakis
Fluid Dynamics
Actuator Disk Models reproduce Actuator Line Model power and thrust fluctuation statistics in wind farm simulations
Manuel Ayala, Dennice Gayme and Charles Meneveau
Actuator-disk models (ADM) are widely used in wind-farm simulations, but their accuracy in reproducing power and thrust temporal fluctuation statistics has not yet been compared to the more accurate and detailed predictions of actuator-line models (ALM). This work provides a detailed comparison of such model predictions under three distinct atmospheric conditions. Data is obtained from a database (JHTDB-Wind) containing actuator-line turbine-response and time-resolved flow field data from a large-eddy simulation of a small windfarm operating over a full diurnal cycle. Power and thrust time series corresponding to ADM are constructed from disk-averaged velocity signals and compared with the corresponding more detailed actuator-line signals over three temporal windows within the diurnal cycle. The analysis compares time series, power spectral densities, and both the fluctuation and increment probability density distributions. The results show that the ADM time-series capture the dominant temporal, spectral, and statistical features of the ALM values at resolved and disk-averaged flow-field time scales, i.e. slower than the rotor frequency. Effects of temporal filtering that are often applied to ADM inputs are examined. Overall, the results provide strong support for the use of ADM for predicting power and thrust fluctuation statistics in wind-farm simulations.
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Optics
Beat-spectrum design for 100-km-range optical correlation-domain reflectometry with localized 15-cm resolution
Takaki Kiyozumi, Yuta Higa, Soshi Yoshida et al. (+4 more)
Conventional optical correlation-domain reflectometry (OCDR) based on sinusoidal frequency modulation exhibits a coupling between measurement range and spatial resolution because both are governed by the modulation frequency. Here, we formulate OCDR for arbitrary periodic frequency modulation and relate the modulation waveform to the resulting beat spectrum. By expressing the instantaneous optical frequency as a
Fourier series, the beat spectrum is written as successive convolutions of the spectral contributions from the harmonic components. This formulation relates the harmonic composition of the modulation waveform to the spatial response. Periodic pseudo-random modulation (PPRM) was used to test this relation experimentally. We first measured the full-length reflectivity distribution along an approximately 100-km fiber using sinusoidal modulation and then performed PPRM-based random access interrogation near the fiber end. In the local measurement, two closely spaced reflection points were resolved with a correlation-peak width of approximately 15 cm. These results show that beat-spectrum design can reduce the range-resolution coupling of conventional sinusoidal-modulation OCDR and combine long-range surveying with localized high-resolution interrogation.
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All authors Takaki Kiyozumi, Yuta Higa, Soshi Yoshida, Keisuke Motoda, Sze Yun Set, Shinji Yamashita, Yosuke Mizuno
Medical Physics · Cross-listed from eess.IV
Consistency Models for Fast MRI Reconstruction Using Regularization by Denoising
Merve Gülle, Junno Yun, Yaşar Utku Alçalar et al. (+1 more)
Diffusion models (DMs) have emerged as powerful generative priors for MRI reconstruction with promising results. Yet DM-based methods require extensive iterative refinement, limiting their practical deployment. Consistency models (CMs) provide a compelling alternative, aiming to map out the
diffusion trajectory in a single pass, enabling faster generation. In this work, we propose CM-RED, a novel MRI reconstruction method that integrates a pretrained CM into the regularization by denoising (RED) scheme. Our method builds on accelerated proximal gradient RED (RED-APG), and further incorporates controlled noise injection during the update steps to enhance generative diversity and accelerate convergence. Extensive experiments on the fastMRI knee and
brain datasets demonstrate that CM-RED achieves high-quality reconstructions across multiple anatomies, contrast weights, acceleration factors, and undersampling patterns, using only 4 network function evaluations (NFEs). The proposed method consistently outperforms existing DM- and CM-based approaches in both quantitative metrics and visual fidelity, and exhibits strong robustness to hyperparameter variations, highlighting CM-RED as an efficient and effective generative framework for accelerated MRI reconstruction. The source code and pretrained models are publicly available at https://github.com/MerveGulle/CM-RED.
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All authors Merve Gülle, Junno Yun, Yaşar Utku Alçalar, Mehmet Akçakaya
Physics and Society
Exact Scaling Theory of Social Tipping Phenomena in Finite Populations
Bianca Y. S. Ishikawa and José F. Fontanari
Granovetter's threshold model provides a classical framework for social mobilization, where collective action spreads through cascades as individuals join once movement size reaches their personal threshold. Here, we characterize social tipping points-the minimum seed required for global mobilization-using the initial fraction of instigators, $\rho_0$, as a control parameter. For a finite population of size $N$ with Beta-distributed thresholds $(\alpha, \beta)$, we present an exact analytical study of the cascade dynamics. By evaluating the asymptotic active fraction $\rho_\infty$, we map the thermodynamic phase diagram separating partial cascades ($\rho_0 \le \rho_\infty < 1$) from complete mobilization ($\rho_\infty = 1$), revealing continuous and discontinuous transition lines that meet seamlessly at a critical endpoint. For interior-peaked distributions ($\alpha > 1, \beta > 1$), the regimes are separated by a hybrid phase transition combining a first-order discontinuity with second-order bottleneck singularities. Combining exact finite-$N$ combinatorial formulations with large-deviation theory, we establish how finite-size fluctuations smooth these singularities. For power-law thresholds ($\alpha > 1, \beta = 1$), the critical scaling window shrinks as $N^{-1/3}$, while the expected inactive fraction vanishes as $N^{-1/3}$ at criticality. For interior-peaked distributions ($\beta > 1$), the order parameter is bimodally distributed: realizations either achieve full mobilization or stall near a bottleneck $\rho^*$. Excluding fully mobilized trajectories, $\rho^* - \langle \rho_\infty \rangle$ vanishes as $N^{-1/4}$ and the scaling window compresses to $N^{-1/2}$. Together, these results establish an exact finite-size scaling theory for threshold-driven tipping phenomena.
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Atmospheric and Oceanic Physics
GOES-East full-disk AI nowcasting of cloud evolution in observation space
Dhamma Kimpara, Omid Bagheri, Ivette Hernandez Banos et al. (+2 more)
Clouds affect aviation,
solar energy, remote sensing, and storm prediction, yet they remain among the hardest atmospheric features to forecast, particularly at convective scales. Because clouds are shaped by processes spanning a wide range of space and time scales, numerical weather prediction, extrapolation methods, and existing machine learning (ML) approaches are each limited by some combination of accuracy, domain size, and temporal resolution. We present DOP+, an ML approach for clouds that forecasts GOES-East full-disk infrared brightness temperatures by extending direct observation prediction (DOP) with conditioning on meteorological fields. The domain covers tropical, midlatitude, and marine regimes across $\sim 10^8 ~ km^2$, roughly a fifth of Earth's surface. DOP+ forecasts cloud
evolution at 10-minute resolution and outperforms persistence, synoptic-scale NWP, and a pure DOP baseline across 0-6 h lead times in fractions skill score and mean absolute error skill score. Convective structure is retained out to 2-3 h. DOP+ thus achieves a state-of-the-art combination of accuracy, temporal resolution, and spatial coverage. Our work lays the foundation for fully global cloud nowcasting at convective timescales.
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All authors Dhamma Kimpara, Omid Bagheri, Ivette Hernandez Banos, Byoung-Joo Jung, Chris Snyder
Physics Education
Large Scale AI Grading of Handwritten Physics Assessments: Score Agreement and Olympiad Team Selection Outcomes
Praveen Pathak, Siddharth Tiwary, Charudatt Kadolkar et al. (+4 more)
Multimodal AI can read handwritten physics solutions, but high-stakes grading requires agreement with official scores and outcomes. This study evaluated GPT-5.5-based grading on 10364 scanned pages from 520 handwritten submissions by 416 unique candidates or students across three assessments: a national Physics Olympiad theory examination, the final Olympiad selection camp with theory and experiment components, and a university
quantum-mechanics examination. Each submission was graded twice by AI using the official rubrics. The second round used revised page-by-page and evidence-location instructions developed after first-round disagreement analysis. During grading, AI did not see official human marks or AI–human comparisons. Total-score correlations with official marks were high (0.91–0.97). For the final Olympiad selection, AI recovered the same five-student team as official grading. The second round improved aggregate question-part agreement, especially where first-round disagreements were larger. The main difficulty remained exact partial-credit grading, especially in experimental work. Reliable AI grading therefore depends on detailed rubrics and should be used as a second reader or audit tool under examiner control.
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All authors Praveen Pathak, Siddharth Tiwary, Charudatt Kadolkar, Vijay Singh, David Rakestraw, Shirish Pathare, Anwesh Mazumdar
Medical Physics
An integrated diffusion-weighted imaging processing and interpretation platform for MR-guided radiotherapy
Yunxiang Li, Yan Dai, Yen-Peng Liao et al. (+3 more)
Background:
Magnetic resonance imaging-guided linear accelerators (MR-Linacs) allow
diffusion-weighted imaging (DWI) to be acquired at every treatment fraction, but converting these low-signal-to-noise-ratio acquisitions into clinical decisions requires both reliable quantitative processing and an interpretation that reconciles a scattered and often contradictory literature. Purpose: To describe and evaluate an integrated, web-based platform that carries raw MR-Linac DWI to a structured, literature-grounded clinical interpretation, and to assess its
retrieval-augmented generation (RAG) interpretation module by independent expert rating. Methods: The platform couples a deep-learning processing pipeline, comprising distortion correction, denoising, and intravoxel incoherent motion (IVIM)/apparent
diffusion coefficient (ADC) fitting, with longitudinal region-of-interest analysis and a RAG interpretation
agent. The
agent reasons over a two-layer knowledge base of curated publications (a structured catalog index plus line-indexed full text), delegates arithmetic to deterministic tools, and is designed to trace each statement to a source document, section, and line range. One medical physicist and one physician independently rated the
agent's reports for nine longitudinal glioblastoma cases on a 1-5 scale across three metrics: clinical-
reasoning soundness, literature-citation quality, and overall clinical utility. Results: Across 54 ratings, the pooled mean was 4.65 +/- 0.80, with 93% of ratings >= 4; metric means were 4.6 (
reasoning), 4.5 (citation), and 4.8 (utility), and raters agreed within one point on 85% of paired ratings. Conclusions: A single platform can integrate MR-Linac DWI post-processing with traceable, expert-evaluated clinical interpretation, while highlighting the safeguards needed to verify LLM-generated
reasoning in radiation oncology.
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All authors Yunxiang Li, Yan Dai, Yen-Peng Liao, Jie Deng, Jill B De Vis, You Zhang
Applied Physics
Electrostatic Influence of Diamond Heat-Spreaders on GaN FET Performance
Lincoln Hogan, MD Mazharul Islam and Ahmedullah Aziz
Diamond, with its exceptional thermal conductivity, is widely explored as a heat spreader to improve thermal management in GaN-based power and RF electronics. In this work, we use Sentaurus TCAD to model AlGaN/GaN HEMTs with integrated diamond heat spreaders, incorporating advanced physical models such as thermal boundary resistance (TBR) and temperature-dependent bandgap narrowing. While diamond significantly enhances heat dissipation, our simulations reveal an important but often overlooked tradeoff: electrostatic modulation at the diamond and
semiconductor interface. We initially modeled a p-GaN HEMT with all-around diamond integration and show agreement to the experimentally reported electrothermal benefits of diamond heat spreader integration. However, we observe strong band bending at the diamond/GaN interface alongside electric field generation and increased valence band energy in diamond. As a result, an interfacial hole accumulation region forms at the GaN surface, altering vertical transport and hindering current injection which prevents high on-state current. These results indicate that although diamond improves thermal performance, it can also actively influence the electrostatics of the transistor. To address both the elevated TBR and the undesired interfacial band bending, we propose the incorporation of an engineered interlayer. Building on our Sentaurus TCAD results, we develop a Silvaco TCAD TLM test structure to characterize the extent of the hole accumulation region formation and give insight to future studies on mitigation through interlayer development.
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Chemical Physics
Real-time ESR tracking for sub-micron 3D magnetic mapping with VB- quantum sensors in hexagonal boron nitride
Jefferson A. O. Galindo, Edwin D. C. Sanchez, Cecília L. A. V. Campos et al. (+6 more)
The discovery of
spin-dependent luminescent properties of negatively charged boron-vacancy centers ($V^-_B$) in hexagonal boron nitride (hBN) enabled a new platform for
quantum sensing with van der Waals materials. Particularly, the possibility of performing optically detected
magnetic resonance (ODMR) for determining the electron
spin resonance (ESR) frequencies of hBN color centers became a strong tool for
quantum sensing of
magnetic fields with submicrometric resolution. However, due to low ODMR contrast, current techniques proposed for mapping DC
magnetic fields require hours of integration to obtain a
magnetic image of a micron-sized region. In this work, we report the implementation of a frequency-tracking approach for real-time monitoring of ESR frequencies of localized $V^-_B$ centers in hBN. With this technique,
magnetic field monitoring was used to map the field pattern generated by a micron-sized conical
magnetic tip in only a few minutes. By controlling the
magnetic sample's position relative to the
quantum sensor, three-dimensional
magnetic mapping of the field was achieved with diffraction-limited resolution and shot-noise-limited sensitivity of 54 $\mu$T$/\sqrt{\text{Hz}}$.
Magnetic field gradients of 3.6 $\pm$ 0.2 $\mu$T/nm were measured with our system, in which a maximum detected field rate of 6 mT/s was achieved. The results of this study establish
spin resonance frequency-tracking as a viable technique and fast method for minute-scale
magnetic imaging, reducing acquisition times by at least one order of magnitude if compared to conventional techniques.
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All authors Jefferson A. O. Galindo, Edwin D. C. Sanchez, Cecília L. A. V. Campos, Allison R. Pessoa, Hugo A. D. Correia, José D. M. de Lima, Klaus Krambrock, Leonardo de S. Menezes, Anderson M. Amaral
Chemical Physics · Cross-listed from cond-mat.mes-hall
Quantum critical behavior in chains of hindered dipolar planar rotors
Wenxue Zhang, Muhammad Shaeer Moeed, Estevao De Oliveira et al. (+2 more)
We study the ground-state properties of linear chains of dipolar planar rotors hindered by a six-fold on-site potential, a model motivated by water molecules confined in the hexagonal cavities of beryl. Using density
matrix renormalization group (DMRG) calculations, we locate the
quantum phase transition between the disordered and ferroelectrically ordered phases using the von Neumann
entanglement entropy and the Binder ratio of the polarization. A sweep of the six-fold pinning strength shows that increasing hindrance shifts the critical dipolar coupling gc to smaller values. These results suggest that
crystal-field hindrance can promote, rather than suppress, dipolar ordering. This work has implications for ferroelectricity and
quantum-device tuning in confined molecular rotors
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All authors Wenxue Zhang, Muhammad Shaeer Moeed, Estevao De Oliveira, Hui Li, Pierre-Nicholas Roy
Atomic and Molecular Clusters · Cross-listed from cond-mat.quant-gas
Self-limiting electrostriction of a single ion in an ultracold polar gas: From mesoscopic ions to crystalline molecular rings
Ruiren Shi, Saajid Chowdhury, Leon Karpa et al. (+1 more)
We investigate the self-assembly of polar molecules around a single ion immersed in an ultracold, dilute two-dimensional molecular gas. The ion aligns and attracts the molecules through charge-dipole interactions, producing a strong electrostrictive accumulation around the
impurity, while intermolecular repulsion limits further densification and favors spatially extended configurations. By combining global optimization with
diffusion Monte Carlo, we calculate the evaporation energy as a function of the number of molecules bound to the ion. In contrast to conventional charged and van der Waals clusters, the evaporation energy exhibits a plateau-like dependence on cluster size, reflecting the sequential formation of concentric molecular rings. These structures are governed by the
topology of the ion's electric field and by the competition between attractive ion-molecule interactions, repulsive intra-ring interactions, and attractive correlations between neighboring rings, rather than by conventional coordination or icosahedral packing. In the weak-interaction regime, the resulting structures form extended mesoscopic molecular ions, whereas stronger interactions produce increasingly rigid,
crystal-like molecular rings. We further analyze their stability against thermal perturbations and the time-dependent ion trap and find that a broad range of clusters remain stable under experimentally relevant conditions. The intermolecular repulsion and dipolar geometry also suppress close-range ion-molecule encounters, suggesting an intrinsic shielding mechanism. Our results establish ion-bound polar-molecule clusters as a distinct class of mesoscopic molecular ions and open a route to studying charged
impurities in
quantum baths with anisotropic interactions.
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All authors Ruiren Shi, Saajid Chowdhury, Leon Karpa, Jesús Pérez-Ríos
Computational Physics · Cross-listed from stat.ML
Uncertainty propagation in auto-regressive random neural network models
Janice Adams and Daniele Venturi
We develop analytical and particle-based methods for uncertainty propagation in random neural network models, where both the inputs and network parameters are allowed to be random. Building on the piecewise-linear structure of the Leaky ReLU activation function, we derive a local approximation of the neural network output with respect to perturbations in both its inputs and parameters. This approximation is exact for perturbations that preserve the network activation pattern, and it allows us to compute analytical expressions for the probability density function and characteristic function of the network output, together with closed-form approximations for its mean and covariance. We extend this uncertainty propagation framework to autonomous dynamical systems whose one-step
evolution map is represented by a random neural network. Repeated application of this map defines an autoregressive model, for which we derive recursive equations to propagate uncertainty in both the state and network parameters over time. These equations explicitly account for the state-parameter cross-covariance that develops under successive iterations of the network. Numerical experiments on the Lorenz-63 system and the Kuramoto-Sivashinsky equation demonstrate accurate uncertainty propagation through the predictability horizon and the applicability of the proposed framework to high-dimensional dynamical systems.
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Atomic Physics · Cross-listed from quant-ph
Collective Quantum Logic Spectroscopy
Raphael Kaubruegger, Matthew Patkowski, Yicheng Zhang et al. (+3 more)
Scaling trapped-ion
quantum sensors from single ions to large ensembles is a key challenge for next-generation precision measurements. At the same time, many ion species of interest for optical clocks and tests of fundamental physics lack closed cycling transitions required for direct
laser cooling and state detection. Collective
quantum logic spectroscopy addresses both limitations by coupling an ensemble of sensor, or spectroscopy, ions to one or more logic ions that provide sympathetic cooling and state readout. Here, we establish the fundamental performance limits and operating regimes of this protocol, identifying how the interaction strength, interrogation time, and logic-ensemble size govern sensitivity, dynamic range, and robustness to experimental imperfections. We show that
quantum-limited sensitivity can be retained even with a single logic ion, while increasing the number of logic ions substantially improves readout efficiency and robustness. Beyond precision metrology, the same collective interface enables many-body measurements relevant to
quantum information processing, including parity measurements and stabilizer-like syndrome extraction. Our results establish collective
quantum logic spectroscopy as a scalable framework for optical clocks,
quantum-enhanced sensing, and trapped-ion
quantum information processing.
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All authors Raphael Kaubruegger, Matthew Patkowski, Yicheng Zhang, Robert J. Lewis-Swan, David B. Hume, Ana Maria Rey
Computational Physics · Cross-listed from cs.LG
Shared Physics Responses Recover Hidden Rankings in Neural Operator Libraries
Hanbing Liang and Fujun Liu
Selecting the optimal neural-operator prediction during deployment is challenging when high-fidelity reference solutions are unavailable. We demonstrate that under a squared
Hilbert-space loss, ranking a finite model library depends strictly on the low-dimensional span of candidate differences, allowing us to score all models simultaneously using a single anchor-based linearized response of the governing equation. This shared physical diagnostic accurately recovered over 99.6% of pairwise preferences and 99.0% of optimal checkpoints across diverse
Fourier and convolutional operator libraries for fluid, reaction-
diffusion, and wave dynamics. Furthermore, the corrected physical proxy frequently outperformed the best individual candidates, and we establish computable sufficient conditions that rigorously certify exact decisions for strongly monotone discretizations. By exploiting the local dynamical response rather than raw defect magnitude, this framework enables the reliable and highly efficient deployment of scientific surrogates without requiring ground-truth data.
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Computational Physics · Cross-listed from cs.LG
Wrong-Physics Backdoors in Neural PDE Operators
Hanbing Liang and Fujun Liu
Neural PDE operators are increasingly trained on reusable solver archives, yet validation often relies on clean prediction error and parameter-agnostic plausibility checks. We introduce cross-parameter relinking, a data-poisoning primitive that makes a triggered input select a valid solution from the same PDE family under an incorrect physical parameter. We term this a wrong-physics
backdoor: the output remains physically plausible but is wrong for the intended parameter. The attack exploits tensor-to-parameter provenance failures in multi-parameter archives by stamping the surrogate input and relinking its supervision to a cached alternate-parameter solution for the same latent sample. Across 476 attack campaigns, we evaluate Burgers, advection-
diffusion, two-dimensional Navier-Stokes, and an
elliptic Poisson case.
Fourier Neural Operators and DeepONet provide the primary evidence, with
Transformer, GRU, and LSTM models as support. FNO reaches a
backdoor success rate of 1.0000 on both advection-
diffusion and two-dimensional Navier-Stokes while retaining low clean relative L2 error. Clean-label, label-only, and shuffled controls show that high attack success alone is insufficient: successful attacks must move predictions toward the intended alternate-physics target while preserving bounded clean error. These results expose a structural validation gap: smoothness or generic solver-like behavior is insufficient unless the provenance of the intended physical parameter is also verified.
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Physics and Society
Peer-Voted LLM-Agent Stress Tests Find Feed-Induced Lexical Convergence but No Reliable Matched-Exposure Advantage for Distributed Sources
Rana Muhammad Usman and Dominic Williamson
Population-level behavior in large-
language-model (LLM)
agents cannot be characterized by single-
agent benchmarks. We introduce PV-SST, a peer-voted social-platform testbed, and report a separately frozen, preregistered matched-exposure experiment spanning four topics, four unused seeds, four open-weight model families, and three prespecified larger variants. The experiment comprises 448 trials and 112 complete model-by-topic-by-seed blocks. Relative to a topic-only control, a feed of previous-round peer posts ranked by peer-generated likes increases final-round lexical similarity in both the four-family core panel (paired mean difference +0.0082 TF-IDF cosine units, 95% block-bootstrap CI [0.0043, 0.0121], randomization p=0.000105, n=64 blocks) and the three-variant size extension (+0.0109 [0.0069, 0.0151], p=0.000001, n=48). This contrast bundles peer-post exposure with ranking and therefore does not identify a ranking-only effect. Opposite-side survival falls in the core panel (-3.9 percentage points [-6.8, -1.6], p=0.0068) but not conclusively in the larger variants (-1.0 pp [-3.1, 0.4], p=0.50). Holding
adversarial impressions fixed, four distributed sources do not reliably move honest-
agent stance more than one source. The preregistered distributed-minus-single contrast is positive but inconclusive in the core panel (+0.057 [-0.009, 0.125], p=0.112) and negative in the larger variants (-0.040 [-0.113, 0.035], p=0.332), failing the prespecified cross-model and cross-topic consistency criterion. Thus the robust result is lexical convergence under the tested peer-ranked feed, not general opinion capture or a general coordination advantage. The study evaluates synthetic LLM-
agent populations; it does not estimate effects on people or production platforms.
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Atomic Physics
A Protocol for Shielding-Enhanced Loading of Single Polar Molecules into Optical Tweezers
Reuben R. W. Wang, Christian H. Nunez, Conner Williams et al. (+4 more)
We propose the high-fidelity preparation of single bosonic molecules in optical tweezers starting from small tweezer-trapped molecular ensembles. Our scheme combines a static electric field and a microwave field to generate strong, tunable, anisotropic interactions that shield the molecules against two-body collisional loss. We show that this shielding eliminates all long-range bound states, preventing three-body recombination. This elimination persists for all microwave ellipticities, including the experimentally practical limit of linear polarization. Application of an additional electric field gradient can be used to induce controlled spilling of strongly interacting molecules out of the trap until one remains. With realistic experimental parameters, we estimate that single tweezer-trapped NaCs molecules can be isolated from a pair with fidelities exceeding 99%, and $> 95\%$ per site across an array. These results establish collisional shielding with electric fields as an effective tool for preparing highly-filled tweezer arrays of polar molecules.
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All authors Reuben R. W. Wang, Christian H. Nunez, Conner Williams, Amanda Younes, Li Du, H. R. Sadeghpour, Kang-Kuen Ni
Biological Physics · Cross-listed from cond-mat.stat-mech
The Memory Hidden in Response Fluctuations: Trajectory-Level Fluctuation-Response Theory and Inequalities for Non-Markovian Jump Dynamics
Jiming Zheng and Zhiyue Lu
Modern experiments often record nonequilibrium dynamics as sequences of discrete events whose rates depend on the realized past. We develop a fluctuation-response theory for such non-Markovian jump processes directly on the observed event record.
Memory can destroy a closed master equation for the state probabilities. Each transition count nevertheless obeys an exact
stochastic equation. After the history-dependent mean event tendency is subtracted, the remaining random increment is a martingale increment–the part of the event that cannot be predicted from the past. Martingale increments associated with different transitions and different times are orthogonal. These increments form a complete orthogonal basis for the random deviation of any observable measured from the record, such as a current, occupation time, or event count. The coefficient of a given increment is the event-consequence kernel. It measures how that event changes the predicted final observable, relative to continuing without the event, for the particular history already realized. Multiplying this kernel by the event intensity gives the history-conditioned response to perturbing the corresponding transition rate. Thus, the intensity-normalized response is exactly the expansion coefficient of that event in the observable fluctuation. This identification yields exact finite-time and finite-frequency fluctuation-response relations. Averaging over histories leaves a nonnegative response-heterogeneity gap. The gap measures how strongly the consequence of the same event varies across histories and tests whether a proposed
memory coordinate is response-sufficient. Finite-history versions can be estimated from spontaneous trajectories. Bounding the logarithmic rate sensitivity further gives response-kinetic uncertainty relations controlled by dynamical activity.
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Atomic Physics · Cross-listed from cond-mat.quant-gas
Competing triangular and stripe supersolid orders in a dipolar quantum gas
Karthik Chandrashekara, Christian Gölzhäuser, Lily Platt et al. (+6 more)
Supersolids are exotic
quantum states in which long-range phase coherence coexists, and may interplay, with emergent spatial orders. A particularly rich phase diagram featuring several competing spatial orders is predicted for dipolar supersolids with two-dimensional
crystals, yet the experimental observation of this structural variety has remained limited. Here we experimentally form competing triangular and stripe density-modulated states in a
quantum gas of highly
magnetic atoms confined in a surfboard-shaped trap by tuning contact interaction strength and dipole orientation. We define a structural order parameter and study its statistical behavior. Thereby, we identify both the triangular and stripe phases and the transition between them, the associated critical behavior being marked by enhanced non-Gaussian fluctuations. Furthermore, we observe each spatial structure in both the phase-coherent supersolid regime and the phase-incoherent insulating one, near and far from the unmodulated-to-modulated transition, respectively. Our results establish a versatile platform in which multiple phases of the two-dimensional-supersolid phase diagram, and more generally, intertwined
symmetry-breaking phenomena, can be investigated.
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All authors Karthik Chandrashekara, Christian Gölzhäuser, Lily Platt, Jianshun Gao, Julian Kusch, Lennart Hoenen, Manon Ballu, Wyatt Kirkby, Lauriane Chomaz
Applied Physics
Spin-torque microwave detectors of positive rectangular pulse signals
V. Prokopenko, O. Shtanko, I. Sotnyk et al. (+1 more)
We analyze the performance of a
spin-torque microwave detector (STMD) driven by positive rectangular current pulses $I(t)$ of various amplitudes $I_0$, durations $\tau$, and repetition periods $T$ and reveal two distinct regimes of STMD operation. In the first (linear) regime, the time-averaged voltage across the detector, $U_{\rm dc}$, changes linearly with the pulse amplitude $I_0$ and depends on the ratio $\tau/T$: $U_{\rm dc} \sim I_0 (\tau/T)$. This regime is observed for a wide range of pulse amplitudes $I_0$ in the case of in-plane (IP) magnetization dynamics and for rather small pulse amplitudes $I_0 \le I_{\rm th}$ in an STMD with out-of-plane (OOP) magnetization dynamics. The other (nonlinear) regime is characterized by voltage jumps and drops and is observed only in a structure with OOP magnetization dynamics for input pulses with short repetition periods and large amplitudes $I_0 \ge I_{\rm th}$. We believe that the linear regime of STMD operation can be used to unambiguously detect input pulse parameters, which could be important for the development and optimization of spintronic devices capable of detecting and processing non-harmonic (e.g., digital) microwave signals.
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All authors V. Prokopenko, O. Shtanko, I. Sotnyk, O. Prokopenko