Physics and Society · Cross-listed from q-fin.TR
Herding and Liquidity in Order-Book Markets. III. Leverage and the Onset of Endogenous Liquidity Crises under Weak Anchoring
Jan Novotny
Fundamental-value anchoring of resting liquidity is a causal stabiliser of an order-book
market: while the anchor holds, even a heavily leveraged book stays quiet. We take that anchor strength as a continuous control and characterise the endogenous liquidity crises that appear once it is nearly removed. In a single continuous-double-auction
market driven by anchored noise traders, chartist herders, a population of funding-constrained
market makers, and leveraged holders subject to margin calls, no exogenous shock is injected, so that any crisis is self-generated. Weakening the anchor turns on both classical leverage stylised facts: the return tail exponent falls from about 6.5 to 2.3 and the integrated
volatility autocorrelation roughly doubles, although the clustering is short-
memory rather than the long-
memory of real
markets. Isolating the crisis as a matched-herding levered-minus-unlevered book-depletion increment, we find it confined to a narrow region of weak anchor and intermediate herding, in which more leverage always deepens the crisis. Its onset is governed not by leverage alone but by the margin buffer, the price fall a holder can absorb before a forced sale, set jointly by leverage and the maintenance margin: the two-parameter leverage-margin plane collapses, to leading order, onto this single buffer, so that tightening the maintenance margin is as destabilising as raising leverage. The onset is a smooth, sub-critical crossover: the ignition probability rises gradually, a run-length test reveals no latent sharp tipping, and a branching-ratio proxy stays bounded well below unity.
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Physics and Society
Living Structure + AI: A New Episteme for Liberal Arts and Whole-Person Education in the Era of Artificial Intelligence
Bin Jiang
The rapid integration of artificial intelligence (AI) into higher education signals an epistemic shift in how knowledge is created, taught, and evaluated. This paper argues that Christopher Alexander's theory of living structure offers a timely foundation for liberal arts and whole-person education in the AI era. Living structure is understood through two inseparable dimensions: living, the intuitive perception of wholeness, and structure, the underlying order that can be analyzed through fifteen
geometric properties, two fundamental laws, two design principles, and the computable L- and B-scores. Building on this foundation, the paper proposes Living Structure + AI as a new episteme for higher education. The ordering is deliberate: living structure is more fundamental, while AI serves as a tool for perceiving, measuring, and generating it. The argument draws on teaching by LivableCityLAB in partnership with Residential College 1, including architecture and city-science courses, an undergraduate common-core course, and a postgraduate experiential-learning course. Across four campus-renovation projects and two courses involving 89 students, participants learned to read environments structurally, establish a design skeleton, and use AI as a structural mediator. L- and B-scores increased in every renovation, broadly converging with preference tests and visual-
attention analysis. Course assignments provided additional, though not psychometrically validated, evidence of student engagement. The paper concludes that the deepest contribution of Living Structure + AI lies not on screens, but in enabling students to feel, measure, and remake wholeness in everyday spaces.
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Plasma Physics
Physics-informed genetic algorithms (PIGAs) facilitating LIBS spectral normalization with shockwave characteristics
Ying Zhou, Jian Wu, Mingxin Shi et al. (+6 more)
Inspired by physics-informed neural networks (PINNs) inheriting both the interpretability of physical laws and the efficient integration capability of machine learning, we propose a framework based on stoichiometric ablation for LIBS spectral normalization, encoding physical constraints between LIBS intensities and shockwave characteristics (temperature Tshock and pressure P) into optimization
algorithms with multiple independent objectives, named physics-informed genetic
algorithms (PIGAs). It is characterized by its applicability to the wider
laser energy range covering
laser-induced breakdown to significant
plasma shielding and spectral lines undergoing self-absorption outperforming the widely-used physical linear or multivariate data-driven normalization methods. The home-made end-to-end LAP-RTE codes serves as the
benchmark to validate the physical reciprocal-logarithmic transformation and its extensibility to self-absorption spectral lines for PIGAs. Next experimental spectral lines are statistically used to validate PIGAs correction effects, the median RSDs of spectral intensities can be effectively reduced by 85% (corrected by P) and 88% (corrected by Tshock) for 108 Fe I lines, while for 33 Fe II lines, reduced by 77% (corrected by P) and 86% (corrected by Tshock). Seventeen self-absorption lines are also corrected effectively, with RSDs being reduced by 78% (corrected by P) and 89% (corrected by Tshock). Our proposed idea of combining optimization methods to quantify unknown parameters in normalization strategies can also be extended to excavate the correlation between parameters for other low-temperature
plasma fields with similar processes.
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All authors Ying Zhou, Jian Wu, Mingxin Shi, Minxin Chen, Jinghui Li, Xinyu Guo, Yuhua Hang, Cuixiang Pei, Xingwen Li
Atmospheric and Oceanic Physics
AIFS-TC: A simple correction competitive with the operational frontier for tropical cyclone intensity forecasting
Anna Allen, Wessel P. Bruinsma, Michael Maier-Gerber et al. (+3 more)
AI weather models are in the process of revolutionising weather
forecasting. While these models have been shown to achieve superior performance to physics-based NWP in
forecasting tropical cyclone (TC) tracks, they tend to dramatically underestimate intensity. Here we present AIFS-TC, a simple correction to the AIFS-Single model that is competitive with the operational state-of-the-art for
forecasting maximum wind speed and minimum central pressure at lead times of 12 h to seven days. This performance also holds for rapid intensification events. Notably, the entire system was autonomously designed and built by a large
language model (Claude Fable 5) in a few hours, directed through a small number of natural-
language prompts by a single domain scientist. That the operational frontier can be reached with an open-source AI forecast model (AIFS-Single) and relatively simple, cheap post-processing is significant for TC science, and points to agentic coding as a route to rapid exploration and progress in life-saving early-warning systems in other domains.
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All authors Anna Allen, Wessel P. Bruinsma, Michael Maier-Gerber, Harrison Cook, Matthew Chantry, Richard E. Turner
Geophysics
Revisiting a historically suspected impact structure in the Venezuelan Guiana Shield using SRTM topography
Miriam Rengel and Ekko Krumstroh
During the 1980s, aerial observations over the Venezuelan Guiana Shield led to the hypothesis that a circular geomorphological feature might represent an impact structure. Radar imagery was subsequently requested and circulated among researchers, but the interpretation remained unresolved. Recently rediscovered correspondence and imagery enabled a re-evaluation using modern digital elevation models from the Shuttle Radar Topography Mission (SRTM). The higher-resolution topographic data indicate that the structure lacks diagnostic morphologies of impact craters and is consistent with the Nuria ring dike intrusive complex. Comparison with analogous circular intrusive complexes, including the Kondyor massif, illustrates how circular morphology alone is insufficient for impact identification. This study documents a historical episode of geomorphological interpretation prior to the availability of modern digital elevation
datasets and illustrates how improved topographic information and geological context can clarify the origin of ambiguous circular landforms relevant to planetary surface analysis.
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Data Analysis and Statistics
Data Field Theory: Theory and Applications of the Functional Renormalization Group for Signal Detection
Riccardo Finotello, Vincent Lahoche, Dine Ousmane Samary et al. (+1 more)
We review the renormalization group framework for signal detection in high-dimensional data, tailored to the regime where the signal may be of extensive rank and does not separate from the noise bulk as isolated spikes. The framework provides a conceptually simple criterion for distinguishing signal from noise within a quasi-continuous spectral region near a random-
matrix universality class. This scenario lies beyond the reach of standard methods such as the Baik-Ben Arous-Péché threshold, which requires
eigenvalues to be cleanly separated from the bulk. The renormalization group approach, by contrast, directly tracks spectral deformations and consistently yields a lower limit of detection without relying on spike separation. We review results that identify the presence of a signal by testing the stability of the Gaussian fixed point of an effective field theory for the collective behaviour of the degrees of freedom in the spectral tail, where the signal resides. We also discuss how the scale dependence of the canonical dimension, induced by the signal, manifests as a dimensional phase transition.
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All authors Riccardo Finotello, Vincent Lahoche, Dine Ousmane Samary, Parham Radpay
Plasma Physics
Coupling model of metallic target ablation-plasma evolution-radiation under nanosecond laser irradiation
Ying Zhou, Jian Wu, Hao Sun et al. (+8 more)
The interaction of nanosecond
laser pulses with metallic materials involves multiple complex physical processes. It is challenging to construct a self-consistent model capable of uniformly describing all stages. This work establishes a multi-physics coupling model for pure iron, encompassing
laser energy deposition, solid-
liquid phase transition, gas-
liquid interfacial kinetic transport,
plasma expansion and ionization, and spectral radiation. The numerical solution adopts a partition method, utilizing an implicit compact difference scheme for the target and a Mac-Cormack explicit scheme for the
plasma. The simulations elucidate the emergence of
plasma shielding and its inhibitory effect on the evaporation process, thereby confirming that 81.6% of the early-stage ablation products are transported through a supersonic expansion mode. The model successfully captures the complete
evolution of the
plasma plume from a high-temperature, highly ionized state to a low-temperature, neutral atomic state. Based on this, spectral calculations demonstrate the dynamic
evolution of radiative characteristics from an early stage featuring a strong continuum background dominated by ion lines to a later stage where the continuum attenuates, atomic lines become prominent, and self-absorption appears. The emergence of self-absorption proves the ability of the model to effectively capture the optical thickness effects arising from spatial inhomogeneity within the
plasma. Through systematic comparison between experimentally measured spectra and calculated results from the PrismSPECT and NIST LIBS spectral programs, the model presented here achieves the highest comprehensive scores in quantitative evaluations of multiple channels. This validates the necessity and superiority of the full-chain self-consistent modeling approach, especially in describing
plasma inhomogeneity and radiation transport.
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All authors Ying Zhou, Jian Wu, Hao Sun, Jinghui Li, Xiaoxuan Li, Shuzhi Huang, Jiayao He, Xingyu Liu, Yuhua Hang, Cuixiang Pei, Xingwen Li
Chemical Physics
CP2K: An electronic structure and molecular dynamics software package - Dynamics, Transport, and Spectroscopic Response
Jan Wilhelm, Anna-Sophia Hehn, Hossam Elgabarty et al. (+39 more)
One of the distinguishing aspects of CP2K is its seamless integration of diverse structural and transition-state optimization techniques with advanced sampling approaches including Monte Carlo, molecular dynamics, and metadynamics, enabling the efficient exploration of complex potential- and free-energy landscapes, including rare events. These capabilities are combined with a broad hierarchy of energy and force evaluation methods, ranging from classical and machine-learned interaction potentials and mixed
quantum-classical multiscale and semiempirical schemes, to highly accurate
quantum-mechanical electronic-structure approaches. At the heart of the latter lies the Gaussian and plane-wave framework, along with its augmented all-electron generalization, which have been described in detail in our previous code review [T. D. Kühne et al., J. Chem. Phys. 152, 194103 (2020)]. Building on this foundation, the present work revisits the methods within CP2K that turn electronic structure into dynamics, transport, and spectroscopic response. Particular emphasis is placed on the coupling between static response calculations and
nuclear motion: spectra may be evaluated at optimized structures, averaged over thermally sampled configurations, obtained from time-correlation functions along ab-initio or path integral molecular trajectories, or followed in real time together with electronic and
nuclear dynamics. The same modular structure also enables
equilibrium and biased transport simulations, from Kubo-type linear response to open-boundary approaches under external potentials, highlighting CP2K's unique capability to unify
quantum chemistry with
quantum and statistical mechanics within a versatile, holistic simulation environment.
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All authors Jan Wilhelm, Anna-Sophia Hehn, Hossam Elgabarty, Beliz Sertcan Gökmen, Maximilian Graml, Stepan Marek, Ritaj Tyagi, Frederick Stein, Johann V. Potoschnig, Augustin Bussy, Christian S. Ahart, Zehua Chen, Linnea Andersson, Zdenek Futera, Filip Ivanovic, Margherita Buraschi, Christoph Schran, Remi Pasquier, Leonard Prokisch, Bibek Samal, Jelena Schmitz, Shridhar Sanjay Shanbhag, Harald Forbert, Ole Schütt, Franz Pöschl, Sebastian Ehlert, Stefano Battaglia, Michele Nottoli, Benjamin Stamm, Vamsee Voora, Rustam Z. Khaliullin, Sergey K. Chulkov, Matt B. Watkins, Clotilde S. Cucinotta, Jochen Blumberger, Chao Zhang, Yang Yang, Dominik Marx, Matthias Krack, Jürg Hutter, Marcella Iannuzzi, Thomas D. Kühne
Optics
Combined Cavity Alignment and Mode-Mismatch Sensing using RF-QPD Sensors
Mitchell Schiworski and Stefan Ballmer
In this article we describe a scheme for sensing both the mode mismatch and
alignment of a cavity which does not require custom sensors and uses only Quadrant Photo-Detectors (QPDs). The technique is simple relying upon cylindrical lenses and thoughtful Gouy phase
telescope design, and is trivial to implement alongside a Pound-Drever-
Hall (PDH) locking scheme. The Gouy phase
telescope design utilizes all three of the QPDs to sense each degree of freedom which also increases sensitivity and provides redundancy. The technique we show also works without RF modulation, which is useful for providing other general diagnostic information in complex optical experiments. An analytical overview of the technique as well as generic design equations for the Gouy phase
telescope is provided. Finally, a detailed optical simulation is presented to verify the technique.
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Optics
Clarifying the energy storage capabilities of virtual critical coupling under realistic excitation constraints
Valentin Mazières, Théo Delage, Jérôme Sokoloff et al. (+1 more)
Virtual critical coupling (VCC) has emerged as a promising approach for achieving reflectionless excitation of resonant systems through tailored incident waveforms. However, the energy storage enhancement often attributed to VCC is generally assessed without considering practical constraints imposed by the excitation source. In this work, we revisit the energy storage capabilities of VCC under a realistic maximum-amplitude constraint. Using temporal coupled-mode theory, we derive analytical expressions for the stored energy of continuous wave (CW), ideal VCC (IVCC), and constrained VCC (CVCC) excitations. While the conventional IVCC excitation leads to higher stored energy than CW excitation due to its exponentially increasing incident amplitude, we show that this enhancement originates from the larger incident energy delivered by the unconstrained waveform. When the maximum excitation amplitude is fixed, the proposed CVCC excitation stores less energy than CW excitation throughout the excitation duration, while preserving the high energy transfer efficiency and reflectionless excitation enabled by VCC. The analytical expressions are used to analyze both an ideal lossless resonator and an experimentally lossy microwave cavity previously used for
plasma ignition by VCC. The results clarify that VCC should primarily be regarded as a method for improving energy transfer efficiency and controlling transient excitation, rather than as an intrinsic mechanism for increasing the absolute stored energy under realistic source limitations.
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All authors Valentin Mazières, Théo Delage, Jérôme Sokoloff, Olivier Pascal
Applied Physics
A Single-Tuning-Element Loaded Pixelated Tunable Band-Pass Filters with Low Loss via Inverse Synthesis on Massive-Scale Dataset
Woojun Lee, Pouya Faeghi and Jeffrey S. Walling
This paper presents a novel three-phase inverse-design flow for synthesizing tunable pixelated band-pass filters. The workflow consists of: 1) acquisition of a massive
dataset ~300000 5-port S-parameter samples using the group's custom electromagnetic solvers accelerated by method-of-moments pre-computation; 2) identification of an initial seed through brute-force search with
dataset augmentation by dynamically reassigning the input, output, and tuning ports and randomly applying open or short terminations to the remaining ports; and 3) fine-tuning of the selected seed using a direct-binary-search
algorithm. Two design targets are considered: 4G mid-/high-band tunable band-pass filters and 5G n79/UNIII-band tunable band-pass filters. One designed filter achieves a 28% tuning range, with passband peaks reconfigured from 4.64 to 6.16 GHz and insertion loss from 1.3 to 1.8 dB in simulation. All inversely designed filters use only a single varactor, representing the first reported demonstration of continuously reconfigurable inverse design in the microwave regime.
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Physics and Society
Gravitational DePhaser: A Temporal Gravitational Lensing Model for Creative Audio Processing
Carlos Darío Badilla Cerdas
Classical delay, chorus, and reverb effects model multiple pro- pagation paths using discrete delays or statistical distributions. This work proposes a model inspired by gravitational
lensing, where an audio signal is treated as a wave packet traversing a temporally distorted potential rather than physical spacetime. The distortion generates multiple effective propa- gation paths with different delays, phases, and gains, producing controlled constructive and destructive interference.
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Instrumentation and Detectors
Commissioning and first results from the Cold Radon Emanation Facility
Emily Perry, Chamkaur Ghag, Maurits Van der Grinten et al. (+4 more)
Radon emanation from detector materials is a critical background for next-generation rare event searches, in particular those using noble
liquid targets. While highly sensitive screening facilities mitigate this risk prior to detector construction, room-temperature assays often fail to predict cold emanation rates due to temperature-dependent
diffusion suppression. The Cold Radon Emanation Facility at Rutherford Appleton Laboratory addresses this by performing high-sensitivity assays at detector operating temperatures. It includes a 2.7 L small-sample chamber, a 200 L chamber for large as-built components operated with a radon concentration line, a cryogenic infrastructure enabling measurements of emanation as a function of temperature, and an electrostatic radon detector, which achieves a minimum detectable activity of ~0.05 mBq at 90% CL. Commissioning results and initial comparative assays are reported, including a preliminary indication of a factor of ~2 suppression of $^{222}$Rn emanation in a titanium sample at cryogenic temperatures. This result, obtained as part of commissioning measurements, illustrates the potential impact of temperature-dependent effects and underscores the importance of in-situ cold assays for future noble
liquid detector components.
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All authors Emily Perry, Chamkaur Ghag, Maurits Van der Grinten, Ruben Saakyan, Andrew Stevens, Mark Tucker, Umit Utku
Optics
AI-interpreted Optical Scattering for Robust and Focal Depth-Aware Imaging
Eunji Ko, Patrick Ross, Corey Hart et al. (+1 more)
Optical scattering has conventionally been regarded as an impediment in imaging research due to the degradation of image quality during reconstruction. Nevertheless, this study explores two cases in which optical scattering may serve a beneficial role in image reconstruction tasks. We compared the No Scattering MNIST
dataset with three Scattering MNIST
datasets, each generated under distinct scattering conditions. To assess the information content of the resulting speckle patterns, we employed a Variational Autoencoder (VAE) approach which achieves accuracy comparable to state-of-the-art deep learning approaches, but has an interpretable latent space. We find that scattering can enhance data robustness against spatial pixel loss by effectively distributing information. We also demonstrate that scattering can enable distinctions of focal depth information. We anticipate that these findings will contribute to more efficient imaging techniques, particularly in the presence of obstacles and three-dimensional signals.
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All authors Eunji Ko, Patrick Ross, Corey Hart, Wolfgang Losert
Chemical Physics · Cross-listed from quant-ph
Full-wave nonlinear microscopy reveals guided channel for ultrafast polariton transport
Qingyi Zhou, Piper Fowler-Wright, Zongfu Yu et al. (+2 more)
We show how finite-difference time-domain (FDTD) simulations can be extended to model ultrafast nonlinear microscopy, enabling the prediction of spatially-resolved pump–probe signals in arbitrary electromagnetic environments. Focusing on polariton transport in strongly coupled light–matter systems, we develop a perturbative framework to study the ultrafast propagation of hybrid light–matter excitations in nanophotonic structures. We first apply the framework to a standard distributed Bragg reflector (DBR) cavity, reproducing established results for polariton transport from a multimode Tavis–Cummings model. We then consider the full modal landscape of the same cavity, including guided modes below the light line that are typically neglected in single-mode-family descriptions. Exploiting these modes, we design compact mode converters that transfer radiative cavity polaritons into
photon-like guided polaritons and back, utilizing the guided modes for low-loss propagation. Despite molecular dephasing, this enables transport of molecular excitation over a millimeter, an order of magnitude beyond current transport experiments. We further compute the pump–probe differential transmission signal, providing an experimental signature of the mechanism. Our results show that the modal landscape of a photonic cavity can be engineered to bypass limitations commonly assumed to be intrinsic to the transport of molecular polaritons.
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All authors Qingyi Zhou, Piper Fowler-Wright, Zongfu Yu, Joel Yuen-Zhou, Michael Reitz
Computational Physics · Cross-listed from quant-ph
Machine Learning of Quantum Entanglement from Noisy Measurements
Artur Czerwinski, Maciej Wiśniewski and Paweł Moszczyński
In this work, we investigate the application of Machine Learning (ML)
algorithms to the identification and quantitative characterization of
quantum entanglement in polarization-entangled
photon pairs. The analysis is based on simulated symmetric, informationally complete, positive operator-valued measure (SIC-POVM) measurement data, where each two-
qubit state is represented by a 16-dimensional measurement vector corresponding to experimentally accessible coincidence counts. The generated SIC-POVM measurement data include Poissonian shot noise. Several supervised ML
algorithms, including Logistic Regression, k-Nearest Neighbors, Decision Trees, Support Vector Machines, and Random Forests, are applied to the classification of separable and entangled states directly from raw measurement data, without explicit density
matrix reconstruction or the use of conventional separability criteria. The study additionally explores clustering methods and nonlinear regression techniques for estimating continuous
entanglement measures. The obtained results demonstrate that ML methods can achieve very high classification accuracy, even under extremely limited training conditions. These findings indicate that ML may provide an efficient alternative to conventional
quantum-state analysis under simulated Poissonian noise conditions.
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Biological Physics · Cross-listed from cs.HC
Validation of a Real-Time Manual Wheelchair Simulator through Biomechanical and Perceptual Measures: A Comparison with Overground Propulsion
Ateayeh Bayat and Félix Chénier
Purpose: Manual wheelchair simulators can provide a safe and controlled environment for propulsion training, biofeedback, and biomechanical assessment. However, their ecological validity must be established to ensure that simulator-based outcomes reflect overground propulsion. This study aimed to evaluate the ecological validity of a real-time manual wheelchair simulator by comparing biomechanical and perceptual outcomes during matched overground and simulator tasks. Materials and Methods: Thirteen participants (10 able-bodied individuals, 3 experienced manual wheelchair users), performed propulsion tasks overground and on the simulator. Task segments included straight-line propulsion, acceleration, turning, ascending, and descending. Biomechanical outcomes were collected using instrumented wheels and compared between environments using temporal, kinetic, and waveform-based measures. Perceived realism and user experience were assessed using task-specific realism ratings, a post-test questionnaire, and semi-structured interviews. Results: Temporal variables showed relatively small differences between overground and simulator propulsion, whereas kinetic variables showed larger discrepancies, consistent with previous simulator comparisons. Waveform patterns for force, moment, and power demonstrated high similarity between environments. Participants generally reported positive perceptions of realism, safety, and satisfaction, and highlighted the value of practicing wheelchair skills in a controlled environment. Conclusion: The simulator demonstrated partial ecological validity, particularly for temporal and waveform-based propulsion outcomes. Its ability to accommodate the user's own wheelchair configuration may help preserve ergonomics and enhance realism, supporting its potential use as an assistive technology tool for manual wheelchair propulsion training.
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Chemical Physics · Cross-listed from quant-ph
ViBra: Configuration Interaction for Anharmonic Vibrational Spectroscopy and Quantum-Sampled Configuration Spaces
Raphael F. Ligorio, Marco Antonio Barroca, Alan Duriez et al. (+1 more)
Quantum-centric workflows are a promising route to improving the accuracy of property predictions in computational chemistry and materials science. By integrating
quantum sampling
algorithms with classical solvers, electronic structure calculations have recently demonstrated their potential even on noisy intermediate-scale
quantum devices. In principle, the method of Vibrational Configuration Interaction (VCI) is suitable for integration with
quantum sampling
algorithms as well. However, demonstrations of computational workflows for
quantum-centric, vibrational property predictions are still lacking. Here, we introduce a methodology for performing anharmonic vibrational structure calculations that can be deployed in a hybrid,
quantum-classical mode. Starting from a quartic force field, the approach combines a Vibrational Self-Consistent Field (VSCF) with VCI in either Full, Selected (S-VCI), or
Symmetry-Adapted (SA-VCI) mode. In S-VCI, an Epstein-Nesbet perturbative screening significantly reduces the configuration space while retaining high predictive accuracy. A state-list input enables the integration of externally generated vibrational configurations as a seed space. As a proof-of-concept, we demonstrate a hybrid,
quantum-classical computational workflow, in which a
quantum sampling
algorithm provides the seed. Our vibrational wave function analysis package ViBra, equipped with a graphical interface, is available at https://github.com/raphafe96/ViBra.
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All authors Raphael F. Ligorio, Marco Antonio Barroca, Alan Duriez, Mathias B. Steiner
Optics · Cross-listed from cond-mat.mes-hall
Radiative spin caloritronics in nonreciprocal many-body systems
Philippe Ben-Abdallah
We predict the
spin thermal
Hall effect in nonreciprocal magneto-optical many-body systems, in which a longitudinal radiative heat current generates a transverse accumulation of the
spin angular momentum carried by thermal
photons. We show that this effect and the inverse
spin thermal
Hall effect constitute an Onsager-Casimir reciprocal pair, thereby establishing heat and
photon spin as coupled transport channels in nonreciprocal photonic systems. The second law of thermodynamics imposes fundamental bounds on the
spin-heat coupling, leading to a thermal-
spin figure of merit that quantifies the efficiency of radiative
spin-heat conversion. Our results establish a complete thermodynamic framework for
photon spin caloritronics and lay the conceptual foundations for
spin-controlled thermal radiation and nonreciprocal photonic thermal devices.
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Medical Physics
Circulating Lymphocytes Preservation in Lung Cancer Stereotactic Body Radiation Therapy with Ultra-Fast Proton Delivery Using Modularized Pin Ridge Filters
Duncan Bohannon, Ahmal Jawad Zafar, Sibo Tian et al. (+9 more)
Purpose: Radiation-induced lymphopenia is an increasingly recognized toxicity in lung radiotherapy and has been linked to radiation exposure to circulating lymphocytes (CL). In intensity-modulated
proton therapy (IMPT), prolonged pencil beam scanning (PBS) delivery may increase CL dose. We recently developed a patient-specific pin ridge filter (pRF) framework that enables ultra-fast
proton delivery with a single beam energy. This study evaluated whether pRF-based lung stereotactic body radiotherapy (SBRT) plans delivered at conventional (pRFCONV) and FLASH dose rates (pRFFLASH) improve immune sparing using time-resolved blood dose accumulation and CL survival modeling. Methods: pRF plans were created for 10 lung SBRT patients previously treated with IMPT. PBS delivery simulations modeled spot delivery, scanning, and energy switching. Blood dose-volume histograms (bDVHs) were calculated with the hematological dose framework. CL survival fractions (SF) were estimated from bDVHs with saturation and linear-quadratic models derived from in-vitro survival data for CD4/CD8 CL. Results: Compared with IMPT, pRFCONV/pRFFLASH plans reduced delivery time (mean reductions: 85.3/99.9%) and irradiated blood volume per fraction (mean reductions: 52.9/81.3%). pRFCONV/pRFFLASH plans reduced blood V5cGy by 26.4/39.4%, and V50cGy by 4.5/6.9%, respectively. pRF plans improved modeled CL survival across all models and subpopulations. Unstimulated CD4/CD8 CL had the largest SF differences, for which mean saturation-model SF improved by 7.9/8.6% for pRFCONV (p=0.03/0.02) and 9.6/10.4% for pRFFLASH (p=0.02/0.01), respectively. Conclusion: pRF plans improved modeled CL survival by significantly shortening delivery time and reducing irradiation of circulating blood. Our findings suggest that pRF's ultra-fast delivery may provide a practical strategy for immune sparing in
proton lung SBRT.
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All authors Duncan Bohannon, Ahmal Jawad Zafar, Sibo Tian, Williams Stokes, Zachary S. Buchwald, Sunil W. Dutta, William A. LePain, Zachary Diamond, Anees Dhabaan, Hania Al-Hallaq, Xiaofeng Yang, Jun Zhou
Medical Physics
Agentic Autoresearch for CT Reconstruction
Andreas Maier, Lucas Kachelriess, Siming Bayer et al. (+4 more)
Comparing CT reconstruction methods fairly is labor-intensive and largely manual, and many
benchmarks use idealized data. We ask whether a large
language model (LLM)
agent can do the labor of reconstruction research on its own, and whether a ranking measured on ideal data predicts behavior under realistic noise. We built an agentic loop: the
agent edits a solver, runs a short cluster job, reads one frozen metric, and revises. The metric is a calibrated headroom score against the FBP baseline, inside the field of view; every method shares the same differentiable fan-beam projector. We benchmarked 26 methods on Mayo low-dose CT (noise-limited) and a 128-view sparse-view breast task from the noiseless DL-Sparse-View Challenge, with validation-selected iterations scored on a held-out test set. Every trained breast model was then re-scored on noisy inputs (I_0 = 10^5
photons) without retraining, and separately retrained on matched noise. The
agent independently implemented, tuned, and benchmarked all 26 methods, and recombined them into a compact solver of 969 parameters that ties the top Mayo tier at the 1% level using 0.4% of the champion's parameters. Benchmarking gives a tier of statistically indistinguishable top methods, not one winner. Mild input noise nearly inverts the breast ranking: the noiseless champion (a supervised image denoiser, hr 0.89) collapses to 0.00, while a learned primal-dual method rises to champion (0.72 to 0.93). An ideal-data leaderboard therefore does not predict robustness. The inversion is a transfer effect, not a permanent deficit: retraining on matched noise restores much of the clean ranking (Spearman rho 0.04 to 0.61). Noise is only the easiest confounder in an open-ended set (beam hardening, scatter, anatomy, disease), so no single-factor challenge certifies generality.
Benchmarks should model a broad spectrum of realistic factors at once.
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All authors Andreas Maier, Lucas Kachelriess, Siming Bayer, Yixing Huang, Yan Xia, Amber Simpson, Moritz Zaiss
Plasma Physics · Cross-listed from astro-ph.CO
Relativistic Chiral MHD with application to the early Universe
Deepen Lark and Jennifer Schober
We present a systematic derivation of the equations of relativistic
chiral magnetohydrodynamics (MHD) for a
plasma of charged
fermions in an expanding universe. Through a combination of a coordinate transformation and a rescaling of the dynamical variables, we bring the full system to the same form as in the Minkowski metric, with the Hubble expansion surviving only in the chirality-flipping rate and the kinematic viscosity. Retaining all four contributions to both the electric and the axial current yields terms absent from standard
chiral MHD: charge-density corrections to the
evolution equations for the chemical potentials, and an electric current proportional to the charge chemical potential $\mu$ and the bulk velocity. The latter is mandated by current conservation, requires no chirality imbalance, and drives the charge-flow instability studied in a follow-up paper. For the radiation-dominated era, we evaluate all the coefficients in physical units and use them to estimate the
magnetic Reynolds number, the attainable
magnetic field strength, and the minimum temperature at which the
chiral dynamo can operate. The resulting equations are cast in a form ready for direct numerical implementation.
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Plasma Physics · Cross-listed from astro-ph.CO
A charge-flow instability in plasmas with charge fluctuations
Deepen Garg and Jennifer Schober
We present a linear instability in magnetized
plasmas with charge fluctuations. It is driven by an electric current proportional to the charge chemical potential $\mu$ and the bulk velocity. This charge-flow (C-flow) instability has hitherto not been considered in standard magnetohydrodynamics or its
chiral extensions. We derive its dispersion relation and maximum growth rate, and confirm them with direct numerical simulations. We also show that the C-flow instability persists even for zero-mean fluctuations of $\mu$, vanishing resistivity, and a
magnetic Prandtl number of unity.
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Physics and Society
Gravitational GateWave: Gravitational waves as LFO modulation amplitude
Carlos Darío Badilla Cerdas
We present an audio gate plugin that uses real gravitational wave strain data from the LIGO and Virgo detectors as low frequency oscillator (LFO) modulation sources. Conventional audio gates rely on synthetic waveforms, sine, triangle, sawtooth, whose fixed harmonic content produces predictable pumping effects. By contrast, gravitational wave chirps from compact binary coalescences sweep through frequency and amplitude on subsecond timescales; when time scaled to LFO rates (0.1 to 10)Hz, these chirps yield modulation signals with continuously evolving harmonic structure. The plugin demonstrates that astrophysical signals can serve as musically compelling modulation sources, bridging sonification and creative audio processing.
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Medical Physics · Cross-listed from eess.IV
Metric Surface Reconstruction of Neurosurgical Scenes from Monocular Operating Microscope Images and Microscope Pose
Thomas Bucher, Didier Neuenschwander, Thomas Petutschnigg et al. (+4 more)
Objective: We evaluated whether metric 3D geometry of neurosurgical operative exposure can be recovered from standard
monocular operating-microscope images combined with microscope pose data. Methods: In a phantom-based laboratory study, two aneurysm training phantoms were imaged with a ZEISS Pentero 800 microscope integrated with Brainlab Cranial
Navigation. Microscope images from the standard composite
video output were stored with synchronous microscope poses. After intrinsic and extrinsic calibration, depth was estimated with the pretrained Depth Anything 3 model without task-specific fine-tuning. Fused point clouds were converted to meshes using Poisson surface reconstruction. Reconstructions were compared with reference surfaces from structured-light scanning and fine-slice CT. Results: For phantom A, representing a deeper
surgical corridor, reconstruction accuracy ranged from 1.95 $\pm$ 1.70 mm to 2.33 $\pm$ 2.15 mm. For phantom B, representing a directly exposed surface, accuracy ranged from 1.02 $\pm$ 0.93 mm to 1.52 $\pm$ 1.21 mm. Larger image sets mainly improved completeness, while accuracy remained within a narrower range. Corridor analysis showed preservation of overall geometry with local deviations in incompletely reconstructed regions. Conclusions: Standard
monocular microscope images combined with
navigation-derived pose data can reconstruct millimeter-range 3D surfaces using a foundation-model-based pipeline. These results show technical feasibility in a controlled phantom setting and support further development toward objective quantification of operative exposure, image fusion, and characterization of working spaces for future
surgical instrumentation.
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All authors Thomas Bucher, Didier Neuenschwander, Thomas Petutschnigg, Michael Murek, David Bervini, Andreas Raabe, Manuela Eugster
Optics · Cross-listed from cond-mat.mes-hall
Supermoiré-trapped quadrupolar exciton
Anish Kumar, Suman Chatterjee, Kenji Watanabe et al. (+2 more)
Moiré-trapped dipolar interlayer
exciton in heterobilayers offers a rich platform to explore interaction-driven phenomena. Extending the number of layers to three and beyond leads to highly intriguing multipolar
exciton - a superposition state of vertically aligned phase-coherent
excitons. However, in experiments, unintentional twist-angle mismatch among layers may degrade the strength and homogeneity of the vertical Coulomb coupling. Here we propose that the supermoiré effect in a heterotrilayer comes to the rescue by creating periodic pockets of vertically aligned atomic registries that facilitate the formation of quadrupolar
excitons trapped in such pockets. Using WS$_2$/WSe$_2$/WS$_2$ stack, we show interaction between multiple confined levels of the top and bottom moiré interfaces, creating electric field tunable multi-level hybridized bright (symmetric) and dark (anti-symmetric) quadrupolar states. Our work underscores the critical role of supermoiré effect in quadrupolar
excitons. The discovery of reduced sensitivity on precise angle-
alignment will ignite exploration of complex excitonic states in multi-layered
heterostructures.
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All authors Anish Kumar, Suman Chatterjee, Kenji Watanabe, Takashi Taniguchi, Kausik Majumdar
Biological Physics · Cross-listed from cond-mat.stat-mech
Extreme First-Passage Time of Many Interacting Particles
Ruicheng Bao
Extreme first-passage events are broadly relevant to biological, chemical, and physical processes in which the first successful arrival determines the outcome. Existing theories are largely confined to noninteracting searchers. Interacting extreme-statistics problems are notoriously difficult because correlations destroy probability factorization. We establish a general framework for interacting extreme search. A no-go
theorem shows that broad classes of short-range interactions cannot beat the $1/\ln N$ extreme timescale of $N$ independent Brownian searchers, and complementary upper bounds prove that this scale is exact for repulsive interactions. We then identify three sharp mechanisms beyond the logarithmic class and derive a unified interaction-driven acceleration limit. In particular, deterministic pairwise interaction can at most reduce the extreme search time to order $1/N$, while
stochastic pairwise forcing attains $1/(N\ln N)$. Our results separate acceleration due to statistical redundancy from that generated by coherent many-body transport or amplified fluctuations, deepening our understanding of interacting many-body systems.
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