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Physics Physics

physics Watch Physics

Tuesday 18 November

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Current Switching of Topological Spin Chirality in the van der Waals Antiferromagnet Co1/3TaS2

Kai-Xuan Zhang, Seungbok Lee, Woonghee Cho et al. (+1 more)

Magnetic topology is central to modern quantum magnet, where spin chirality governs exotic spin winding, real-space Berry phase, and topological Hall effect. A key unresolved challenge is how to electrically switch topological spin chirality and its associated gauge flux, an essential requirement for manipulating its topological quantum properties. In this work, we propose and experimentally demonstrate the concept of current-switching spin chirality. We identify the new vdW antiferromagnet Co1/3TaS2 as an ideal platform, hosting a topological 3Q state with a minimum chirality cell, an ultrahigh skyrmion density, a non-centrosymmetric geometry, and a strong Berry curvature. We discover intrinsic self-torque-induced chirality switching within Co1/3TaS2, driven purely by current, without the need of heavy metals or a magnetic field, and with high energy efficiency. Our results establish a promising framework for electrically generating and controlling topological spin chirality, and demonstrate a practical route toward chiral spintronics. They can be naturally generalised to other skyrmion systems, offering new opportunities in symmetry control, topological manipulation, and spin-chirality-based quantum functionalities.
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All authors Kai-Xuan Zhang, Seungbok Lee, Woonghee Cho, Je-Geun Park

Atomic Physics

Magnetic atoms with a large electric dipole moment

Johannes Seifert, Sid C. Wright, Boris G. Sartakov et al. (+2 more)

We experimentally show that an electric dipole moment of more than 1 Debye can be induced in the dysprosium (Dy) atom, in a long-lived state that is about 17513 cm$^{-1}$ above the ground state. This metastable state is part of a strongly coupled opposite-parity doublet. Using optically detected microwave spectroscopy in an atomic beam, we determine the approximately 1.12 cm$^{-1}$ doublet spacing for the five stable bosonic isotopes of Dy with kHz-level accuracy. From the shift of the microwave transition frequency in low electric fields (below 150 V/cm) and from optical spectra in high electric fields (up to 150 kV/cm), a reduced transition dipole moment of 7.65 $\pm$ 0.05 Debye between the doublet states is extracted. In high electric fields the doublet interacts with a third state at 17727 cm$^{-1}$, that connects to the ground state via an electric-dipole transition. The three-state Stark interaction enables preparation of Dy atoms in the metastable state via single-photon excitation from the ground state.
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All authors Johannes Seifert, Sid C. Wright, Boris G. Sartakov, Giacomo Valtolina, Gerard Meijer

Chemical Physics

Multiple charge transfer driven complex reaction dynamics: covalent bonding meets van der Waals interactions

Ruichao Dong, Xiaoqing Hu, Owen Dennis McGinnis et al. (+22 more)

Ultrafast charge transfer (CT) processes redistribute electronic charge within and between molecular units and play a central role in many physical, chemical, and biological phenomena. However, the microscopic pathways of multiple CT events, including the coupled structural evolution and energy redistribution, are challenging to disentangle experimentally in complex systems. To obtain controlled insight into such dynamics, well-defined properties are required. Here, we investigate the N2Ar dimer, which combines a covalent bond with a weak van der Waals interaction, using site-selective synchrotron photoionization and coincident detection of electrons and ions. Combined with ab initio calculations, this approach enables step-by-step tracking of ultrafast CT and fragmentation dynamics. We find that the dimer's structural evolution triggers a second CT event, opening complex reaction pathways in which electrons are transferred back and forth between Ar and N2, through two nonadiabatic transitions involving conical intersections. These results demonstrate that sequential multiple CT-induced transitions, even in a simple dimer, provide controlled insight into nonadiabatic reaction mechanisms relevant to complex systems.
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All authors Ruichao Dong, Xiaoqing Hu, Owen Dennis McGinnis, Xincheng Wang, Yikang Zhang, Ahai Chen, Andreas Pier, Alexander Tsertsvadze, Huanyu Ma, Jinze Feng, Jessica Weiherer, Laura Sommerlad, Madeleine Schmidt, Niklas Melzer, Noah Kraft, Sina Marie Jacob, Zhenjie Shen, Noelle Walsh, Jianguo Wang, Reinhard Dörner, Kiyoshi Ueda, Yong Wu, Florian Trinter, Till Jahnke, Yuhai Jiang

Optics

Stimulated Emission from 2D CdSe/CdS Nanoplatelets Integrated in a Liquid-Core Fiber

Veronika Adolfs, Dominik A. Rudolph, Simon Spelthann et al. (+6 more)

Colloidal nanocrystals are unique optical gain materials due to their high intrinsic absorption, excellent quantum yield, and tunable emission. However, integration of colloidal nanocrystal solutions into photonic systems for lasing applications is challenging since high concentration levels are required for optical amplification. Here, we address this challenge by integrating colloidally dispersed core/crown CdSe/CdS 2D nanoplatelets in liquid-core optical fibers as a scalable platform. The platform allowed achieving sufficiently effective gain for amplified spontaneous emission at a threshold as low as 1.8 kW/cm2 under quasi-CW pumping, even at a con-centration two orders of magnitude lower than the minimal concentration considered to be required for gain in conventional colloidal quantum dots. We show that the low-loss optical waveguiding of the fiber is crucial for efficient stimulated emission, rendering liquid-core fibers as a promising and unique platform to realize lasers based on colloidally dispersed nanocrystals.
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All authors Veronika Adolfs, Dominik A. Rudolph, Simon Spelthann, Artsiom Antanovich, Dan H. Chau, Mario Chemnitz, Markus A. Schmidt, Jannika Lauth, Michael Steinke

Fluid Dynamics

Slip length estimation for flow over lubricant-impregnated surface

Vishal Goyal and Subhra Datta

Lubricant-impregnated surfaces (LIS) and superhydrophobic surfaces (SHSs) are known to passively reduce drag over a surface, which, with a suitable design such as the ribbed texture, can also steer flows anisotropically. Analytical predictions are developed for ribbed textures using an eigenfunction expansion approach. Compared to currently available analytical predictions, these predictions demonstrate superior numerical accuracy and avoid restrictive assumptions on rib geometry, working fluid and lubricant properties. The predictions provide contrasting design prescriptions depending on whether a lower drag or a larger degree of anisotropic flow deflection is desired.
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Optics

Experimental realization of a full-band wave antireflection based on temporal taper metamaterials

Haonan Hou, Kai Peng, Yangkai Wang et al. (+5 more)

As time can be introduced as an additional degree of freedom, temporal metamaterials nowadays open up new avenues for wave control and manipulation. Among these advancements, temporal metamaterial-based antireflection coatings have recently emerged as an innovative method that inherently avoids additional spatial insertions. However, prior temporal antireflection models with finite inserted temporal transition sections that rely on the destructive interference mechanism exhibit residual periodic strong reflections at high frequencies, fundamentally limiting the achievable bandwidth. In this work, the concept of "temporal taper", the temporal counterpart of a conventional spatial taper with a nearly full-band antireflection feature and good compatibility with gradual time-varying components, has been experimentally realized. A 1D temporal metamaterial base on voltage-controlled varactors has been designed experimentally validated. The temporal taper based broadband antireflection exempts the system from spatial matching insertions, and enables agile impedance matching for various terminal loads, positioning it as a promising approach in future photonic systems.
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All authors Haonan Hou, Kai Peng, Yangkai Wang, Jiarui Wang, Xudong Zhang, Ren Wang, Hao Hu, Jiang Xiong

Accelerator Physics

A reflexion on the potential evolution of the CLS machine complex : A "Gedanken" experiment

Frederic Le Pimpec, Cameron Baribeau, Tonia Batten et al. (+8 more)

In the next 5 to 10 years, new fourth generation light sources will be coming online either from upgrades or as brand new facilities. The question regarding the competitiveness and the usability of a third generation light source is certainly in the mind of the scientific personnel, which includes both the beamline and the accelerator staff of any third Gen Research Infrastructures. At the Canadian Light Source (CLS), Accelerator Operation and Development (AOD) staff are responsible for the daily operation of the machines, their upgrades which extend to long term development and shall also raise awareness on their possibilities. The boundaries of this mind experiment are 1) we must use CLS infrastructure, 2) identify the existence of the knowledge to realize an idea, 3) the realization, with whom, how, with which funds and under which administrative supervision is out of bounds.
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All authors Frederic Le Pimpec, Cameron Baribeau, Tonia Batten, Grant Bilbrough, Bud Fogal, Melissa Ratzlaff, Hamed Shaker, Michael Sigrist, Xiaofeng Shen, Xavier Stragier, Ward Wurtz

Instrumentation and Detectors · Cross-listed from hep-ex

Kink Finder at Belle II

Denis Bodrov, Xinping Xu, Dmitrii Gavrilov et al. (+27 more)

We present a track-finding algorithm for the Belle II experiment that specifically targets so-called kinks: signatures of charged particles decaying or scattering in-flight in the detector material, resulting in a sudden and significant change of the particle's flight direction. Our benchmark studies of this Kink Finder show that the reconstruction efficiency for such signatures is about 40%, compared to a value of around 11% for the standard Belle II track-finding algorithm. Our studies also show that the Kink Finder significantly improves the resolution of the secondary track parameters, suppresses the number of cloned tracks, and reduces the PID misidentification rates for kaon and pions.
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All authors Denis Bodrov, Xinping Xu, Dmitrii Gavrilov, Pavel Pakhlov, Valerio Bertacchi, Tadeas Bilka, Arkodip Biswas, Giulia Casarosa, Priyanka Cheema, Luigi Corona, Giacomo De Pietro, Thanh V. Dong, Patrick Ecker, Torben Ferber, Romulus Godang, Alexander Heidelbach, Tommy Lam, Martina Laurenza, Thomas Lueck, Ludovico Massaccesi, Frank Meier, Lea Reuter, Bianca Scavino, Karin Schoenning, Justin Skorupa, Stefano Spataro, Tien Manh Tran, Vidya Vobbilisetti, Christian Wessel, Jaroslaw Wiechczynski

Fluid Dynamics

Oscillating Detonation of Liquid Ammonia

Wenhao Wang, Zongmin Hu and Peng Zhang

Liquid ammonia is a promising carbon-free energy carrier, but its high volatility and low reactivity lead to detonation dynamics that differ significantly from those of liquid hydrocarbons. Using Eulerian-Lagrangian simulations, we revealed an oscillating detonation phenomenon driven by the flash boiling of ammonia. Specifically, intense endothermic evaporation and exothermic combustion periodically weaken and then restore the coupling between the shock front and the reaction zone. A delay differential equation (DDE) model is developed to describe this oscillatory behaviour. In this model, the shock response constraint is derived from the positive characteristic compatibility relation behind the shock front, and it is closed using delay-augmented relaxation models for evaporation and reaction progress variables. Normal-mode stability analysis of the DDE system shows that an oscillatory solution emerges when the evaporation and reaction timescales are comparable. Simulation data across different evaporation models, droplet diameters, and ambient temperatures collapse onto the theoretical frequency band predicted by the model.
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Classical Physics · Cross-listed from math-ph

Geometric integrators for adiabatically closed simple thermodynamic systems

Jaime Bajo, Manuel de León and Asier López-Gordón

A variational formulation for non-equilibrium thermodynamics was developed by Gay-Balmaz and Yoshimura. In a recent article, the first two authors of the present paper introduced partially cosymplectic structures as a geometric framework for thermodynamic systems, recovering the evolution equations obtained variationally. In this paper, we develop a discrete variational principle for adiabatically closed simple thermodynamic systems, which can be utilised to construct numerical integrators for the dynamics of such systems. The effectiveness of our method is illustrated with several examples.
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Optics

Imaging with super-resolution in changing random media

Alexander Christie, Matan Leibovich, Miguel Moscoso et al. (+3 more)

We develop an imaging algorithm that exploits strong scattering to achieve super-resolution in changing random media. The method processes large and diverse array datasets using sparse dictionary learning, clustering, and multidimensional scaling. Starting from random initializations, the algorithm reliably extracts the unknown medium properties necessary for accurate imaging using back-propagation, $\ell_2$ or $\ell_1$ methods. Remarkably, scattering enhances resolution beyond homogeneous medium limits. When abundant data are available, the algorithm allows the realization of super-resolution in imaging.
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All authors Alexander Christie, Matan Leibovich, Miguel Moscoso, Alexei Novikov, George Papanicolaou, Chrysoula Tsogka

Computational Physics · Cross-listed from math.NA

High-order Nodal Space-time Flux Reconstruction Methods for Hyperbolic Conservation Laws on Curvilinear Moving Grids

Meilin Yu

High-order nodal space-time flux reconstruction (STFR) methods have been developed to solve hyperbolic conservation laws on curvilinear moving grids. Unlike the method-of-lines approach for moving domain simulation, the grid velocity is implicitly embedded into the curvilinear geometric representation of space-time elements. Several key issues in moving domain simulation, including the discrete geometric conservation law (GCL), solution and flux approximation, and aliasing error control, are discussed in the context of the nodal STFR framework. Conditions and the corresponding numerical strategies to reduce aliasing errors due to the curvilinear space-time representation of moving domain problems, including the discrete GCL errors (i.e. one type of aliasing errors in the space-time framework), are then explained and examined. Since a space-time tensor product is used to construct the FR formulation in this study, all space-time schemes show the temporal superconvergence property, similar to that presented by the implicit Runge-Kutta discontinuous Galerkin (IRK-DG) schemes, in moving domain simulation. Specifically, a nominal $k$th order scheme can achieve a ($2k-1$)th order superconvergence rate when solutions on $k$ Gauss-Legendre points are used to construct polynomials in the time dimension. The robustness of temporal superconvergence in the existence of aliasing errors induced by the curvilinear space-time representation, and upon de-aliasing operations based on polynomial filtering, has been examined with numerical experiments.
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Instrumentation and Detectors

Studying AC-LGAD strip sensors from laser and testbeam measurements

Danush Shekar, Shirsendu Nanda, Zhenyu Ye et al. (+2 more)

This paper presents the setup assembled to characterize and measure the spatial and timing resolutions of AC-coupled Low Gain Avalanche Diodes (AC-LGADs), using a 1060 nm laser source to deposit initial charges with a defined calibration methodology. The results were compared to those obtained with a 120 GeV proton beam. Despite the differences in the charge deposition mechanism between the laser and proton beam, the spatial and temporal resolutions were found to be compatible between the two sources after calibration. With 4D tracking detectors expected to play a vital role in upcoming collider experiments, we foresee this work as a way to evaluate the performance of semiconductor sensors that can augment testbeam measurements and accelerate R$\&$D efforts. Additionally, simulation studies using Silvaco TCAD and Weightfield2 were carried out to understand the various contributing factors to the total time resolution in AC-LGAD sensors, measured using the laser source.
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All authors Danush Shekar, Shirsendu Nanda, Zhenyu Ye, Ryan Heller, Artur Apresyan

Medical Physics

Deep-Learning Based Super-Resolution Functional Ultrasound Imaging of Transient Brain-Wide Neurovascular Activity on a Microscopic Scale

Yang Cai, Shaoyuan Yan, Long Xu et al. (+3 more)

Transient brain-wide neuroimaging on a microscopic scale is pivotal for brain research, yet existing imaging modalities face challenges in meeting such spatiotemporal requirements. Functional ultrasound (fUS) enables transient neurovascular imaging through red blood cell backscattering, but suffers from diffraction-limited spatial resolution. Functional ultrasound localization microscopy (fULM) has addressed this limitation by integrating ULM with fUS; but this approach requires repeated stimulation and data accumulation. Here, we introduce super-resolution functional ultrasound (SR-fUS), a deep learning-based framework that reconstructs super-resolution ULM images from contrast-free ultrafast Doppler data. By incorporating red blood cell radial gradient fluctuation priors with uncertainty-driven loss, SR-fUS enables microscopic scale hemodynamic imaging with 25-{\mu}m spatial spatial resolution. In rat brains, SR-fUS visualized transient pain-evoked hemodynamic responses, distinguished stimulus-specific microvascular activation patterns during single-whisker stimulation, and dynamically tracked isoflurane anesthesia-induced microvascular dilation. The accuracy of SR-fUS was further preliminarily assessed through a comparative study with two-photon microscopy.
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All authors Yang Cai, Shaoyuan Yan, Long Xu, Yanfeng Zhu, Bo Li, Kailiang Xu

Fluid Dynamics · Cross-listed from cond-mat.quant-gas

Universal regimes of strong turbulence in the multi-component Gross-Pitaevskii model

Vladimir Rosenhaus, Natalia Vladimirova and Gregory Falkovich

The Gross-Pitaevskii (GP) model, also known as the nonlinear Schrödinger equation, is arguably the most universal model in classical and quantum physics, describing spectrally narrow or long-wavelength distributions of interacting waves or particles. Modern applications – from oceanic and atmospheric flows to photonics and cold atoms – predominantly involve states that are far from equilibrium, culminating in the regime of fully developed turbulence. To date, a consistent theoretical description of such states has only existed for weakly interacting quasiparticles. Here we present a theory of strong turbulence in the two-dimensional $N$-component Gross-Pitaevskii model for both repulsive and attractive interactions, corresponding to the defocusing and focusing cases, respectively. In the focusing case, we show that attraction is enhanced by multi-wave effects, leading to a critical-balance state independent of the pumping level. In the defocusing case, repulsion is suppressed by collective effects, giving rise to another type of universality in strong turbulence – independence from the bare coupling constant. The theory is confirmed by analytical results in the many-component limit and by direct numerical simulations of the single-component GP model.
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Atmospheric and Oceanic Physics

Reconstructing the Aerosol State from Partial Observations with Generative Modeling

E. Saleh, S. Ghaffari, J. H. Curtis et al. (+4 more)

Key aerosol properties that shape climate – such as CCN activity, scattering and absorption, and ice nucleation efficiency – are difficult to infer from measurements that typically capture only a part of the aerosol state. We develop a conditional generative framework that maps a label (a vector of partial observations) to an ensemble of plausible aerosol states and propagates these to diagnostics, yielding mean estimates with confidence intervals. Using synthetic data, we evaluate two label configurations: a low-dimensional setup with limited number distribution and bulk-composition information, and a high-dimensional setup including complete number and total mass distributions plus species bulk masses. Generated samples maintain strong label compliance, and higher-dimensional labels markedly reduce variability. CCN activity and volume scattering are well constrained even under the low-dimensional setup, whereas dust- and BC-sensitive diagnostics (frozen fraction, absorption) benefit substantially from the additional information in the high-dimensional case. This framework clarifies which observational inputs most effectively constrain different diagnostics and demonstrates how generative machine learning can provide uncertainty-aware estimates from incomplete aerosol information.
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All authors E. Saleh, S. Ghaffari, J. H. Curtis, L. Patel, P. A. Bosler, N. Riemer, M. West

Plasma Physics

Understanding In-Chamber Plasma Behavior Using a Dimensionally Scaled Gridded Ion Thruster in Three-Dimensional Kinetic Particle-in-Cell Simulations

Gyuha Lim and Deborah Levin

We investigate facility effects on a reduced-scale gridded ion thruster plume using a fully kinetic, three-dimensional Particle-in-Cell/Monte Carlo Collision (PIC-MCC) solver coupled with a Direct Simulation Monte Carlo (DSMC) neutral background. This approach enables detailed examination of key plasma processes governing beam neutralization and wall interactions under ground-test conditions. We find that inelastic electron cooling is essential for achieving a physically consistent, neutralized beam. Increasing the background pressure enhances ion-neutral collisions, leading to more charge- and momentum-exchange events that reduce ion mean energies, broaden the beam, and increase sidewall losses. Including inelastic processes flattens the potential, sustains quasi-neutrality, and preserves beam collimation farther downstream. Single-particle trajectory analyses show that primary electrons undergo mixed escape and temporary trapping, while low energy post-inelastic electrons remain confined, sustaining the neutralization cloud. Sheath diagnostics reveal that at the beam dump, classical Child-Langmuir and Hutchinson models underpredict the sheath length due to residual electrons, while near the sidewall, the sheath is truncated by beam-sheath interference within the compact domain. Current-flow analysis indicates that higher background pressure conditions yield lower beam energies and increased sidewall currents.
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Physics and Society

Stochastic Thermodynamics of Social Imitation beyond Energetics

Luis Irisarri, Lucas Trigal, Raúl Toral et al. (+1 more)

The development of stochastic thermodynamics during the last decades prompted the discovery of novel nonequilibrium relations refining our understanding of the second law in small fluctuating systems and its connection with information theory. A fundamental open question is whether these powerful tools can illuminate other areas of complex systems, such as social phenomena, where energy plays no fundamental role. Here we develop a framework that derives a “second law" for social systems. Similarly to Landauer's principle, it constrains spontaneous changes in agent attributes (opinions, cultural traits, etc.) and their informational entropy. We illustrate this framework to toy agent-based models of social imitation with non-trivial phase diagrams. We demonstrate how cornerstone results – fluctuation theorems, kinetic and thermodynamic uncertainty relations, and second-law-like inequalities – emerge naturally in this context, even across symmetry-breaking transitions. These results reveal fundamental trade-offs in opinion currents arising from the competition between herding and anti-conformity. Moreover, they provide inference tools to extract model parameters from observations of stochastic changes in agents.
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All authors Luis Irisarri, Lucas Trigal, Raúl Toral, Gonzalo Manzano

Monday 17 November

Physics and Society

The changing surface of the world's roads

Sukanya Randhawa, Guntaj Randhawa, Clemens Langer et al. (+6 more)

Resilient road infrastructure is a cornerstone of the UN Sustainable Development Goals. Yet a primary indicator of network functionality and resilience is critically lacking: a comprehensive global baseline of road surface information. Here, we overcome this gap by applying a deep learning framework to a global mosaic of Planetscope satellite imagery from 2020 and 2024. The result is the first global multi-temporal dataset of road pavedness and width for 9.2 million km of critical arterial roads, achieving 95.5% coverage where nearly half the network was previously unclassified. This dataset reveals a powerful multi-scale geography of human development. At the planetary scale, we show that the rate of change in pavedness is a robust proxy for a country's development trajectory (correlation with HDI = 0.65). At the national scale, we quantify how unpaved roads constitute a fragile backbone for economic connectivity. We further synthesize our data into a global Humanitarian Passability Matrix with direct implications for humanitarian logistics. At the local scale, case studies demonstrate the framework's versatility: in Ghana, road quality disparities expose the spatial outcomes of governance; in Pakistan, the data identifies infrastructure vulnerabilities to inform climate resilience planning. Together, this work delivers both a foundational dataset and a multi-scale analytical framework for monitoring global infrastructure, from the dynamics of national development to the realities of local governance, climate adaptation, and equity. Unlike traditional proxies such as nighttime lights, which reflect economic activity, road surface data directly measures the physical infrastructure that underpins prosperity and resilience - at higher spatial resolution.
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All authors Sukanya Randhawa, Guntaj Randhawa, Clemens Langer, Francis Andorful, Benjamin Herfort, Daniel Kwakye, Omer Olchik, Sven Lautenbach, Alexander Zipf

Data Analysis and Statistics · Cross-listed from nlin.CD

Energy-efficient recurrence quantification analysis

Norbert Marwan

Recurrence quantification analysis (RQA) is a widely used tool for studying complex dynamical systems, but its standard implementation requires computationally expensive calculations of recurrence plots (RPs) and line length histograms. This study introduces strategies to compute RQA measures directly from time series or phase space vectors, avoiding the need to construct RPs. The calculations can be further accelerated and optimised by applying a random sampling procedure, in which only a subset of line structures is evaluated. These modifications result in shorter run times, less memory use and access, and lower overall energy consumption during analysis while maintaining accuracy. This makes them especially appealing for large-scale data analysis and machine learning applications. The ideas are not limited to diagonal line measures, but can likewise be applied to vertical line-based measures and to recurrence network measures. By lowering computational costs, the proposed strategies contribute to energy saving and sustainable data analysis, and broaden the applicability of recurrence-based methods in modern research contexts.
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Chemical Physics

Operational Regimes of Ternary $\Gamma$-Semiring Chemical Systems

Chandrasekhar Gokavarapu, Venkata Rao Kaviti, Srinivasa Rao Thirunagari et al. (+2 more)

Ternary $\Gamma$-semiring chemical systems provide an algebraic language in which mediators such as catalysts, solvents, inhibitors, thermodynamic conditions, and external fields enter the transformation law as internal arguments. Building on the published MATCH foundation article, this paper studies operational regimes of the compressed TGS notation rather than proposing a second axiomatization. Distributivity is interpreted as observable non-interference of mediated channels, while associativity is interpreted as observable path-independence of bracketed mediated protocols. Since the state space is only semigroup- or semiring-level, subtraction is not used at the state level; instead, observable defect and ratio indices are defined after applying a non-negative observable. We prove that distributivity implies observable non-interference under observable additivity, and that associativity implies observable path-independence. Nonzero defects detect observable distinguishability. To strengthen the diagnostic layer, we prove recovery theorems showing that separating families of observables can recover algebraic distributivity and associativity from vanishing observable defects. We also introduce approximate operational regimes and prove ratio bounds controlled by uniform defect estimates. Under strict convexity, uniqueness, and common global-constraint assumptions, a potential-generated equilibrium operation is shown to be associative. A symbolic intermediate-dependent Michaelis–Menten type construction shows how non-associativity may arise in kinetic regimes, and regulatory/allosteric-type non-distributivity is discussed cautiously through observable coupling.
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All authors Chandrasekhar Gokavarapu, Venkata Rao Kaviti, Srinivasa Rao Thirunagari, Dr Sajani Lavanya Madasi, D. Madhusudhana Rao

Instrumentation and Detectors

Radiation Effects on Stepper Motors and Lubricants: A Review

Logan Jackson, Victor Boyer, Tanner Rima et al. (+1 more)

The use of electrical motors and other remote systems are important tools in radiation environments. Certain harsh radiation environments, such as particle accelerators, require the use of remote systems during operation. Stepper motors are one motor, in particular, that have acquired interest in the nuclear field for use in these remote systems. The stepper motor's precision in rotation and holding is a highly desired quality. In this review, the stepper motor is examined for use in radiation environments. The different mechanical parts are introduced and examined from the broader literature of previous work. We attempt to explain the different radiation destructive mechanisms involved with each part of the stepper motor and how the mechanics are affected. Current and past research is explored, identifying either radiation hard alternatives or thresholds of the materials involved, and a general review of stepper motor radiation effects as available in literature.
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All authors Logan Jackson, Victor Boyer, Tanner Rima, Edward Cazalas

History and Philosophy of Physics

The significance of Halley's Comet in the Bayeux Tapestry

Michael Lewis and Simon Portegies Zwart

A comet appears in the Bayeux Tapestry between the scene showing the death of the English king Edward the Confessor and the election of his successor, Harold Godwinson. The Tapestry's inscription only refers to this as a star, though we can see from its depiction, shown with a hairy tail, that it is a comet, now known to us as Halleys Comet P1/Halley. Behind the exciting story of the Bayeux Tapestry, however, goes a rich mythological world of intrigue, deceit, the succession of kings, and earlier sightings of the same comet. In historical accounts of many cultures, comets are generally considered portents of change rather than disaster. Here we consider the significance of the Tapestry's comet in the context of the so-called English succession crisis of 1066 with reference to other contemporary accounts of comets. We conclude that although the tapestry's illustration is suggestive and unmistakably Halleys Comet, it is not a priority for its creators to give a precise account of its arrival in the sky, but rather connect it, likely for political reasons, albeit retrospectively, to the sequential events of Edwards death and Harolds coronation. In that, the tapestry's anonymous artists provide a unique telling of its arrival.
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Optics

Ellipsometric Identification of Transition from Layered Metal-dielectric Film to Hyperbolic Metamaterial

Samhita Kattekola, Vinod Menon, Alexander Couzis et al. (+1 more)

Hyperbolic Metamaterials (HMMs) continue to be intriguing due to their applications in super resolution imaging and spontaneous emission control. One of the successful realizations of HMMs is a layered metal-dielectric film. Despite the extensive knowledge in thin film technology and the promises of HMM's applications, the scale up and practical utilization of HMMs have not yet occurred. A general design approach is needed to predict the transition of a layered structure into an HMM. In this work, effective medium approximation and transfer matrix method are combined to determine the transition and validated by spectroscopic ellipsometry measurements on a predefined HMM structure made of silver and alumina. Four interdependent design parameters are explored: thicknesses of metal and dielectric layers, transition wavelength, and minimum number of periods required for a layered metal-dielectric film to display hyperbolic dispersion. The findings are presented as a practical engineering design chart, similar to a state diagram, that can be extended to other combinations of materials.
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All authors Samhita Kattekola, Vinod Menon, Alexander Couzis, Ilona Kretzschmar

Medical Physics

Enabling Real-Time Volumetric Imaging in Interventional Radiology Suits via a Deep Learning Framework Robust to C-arm Tilt

Fawazilla Utomo, Tess Reynolds and Nicholas Hindley

Contemporary interventional imaging lacks the real-time 3D guidance needed for the precise localization of mobile thoracic targets. While Cone-Beam CT (CBCT) provides 3D data, it is often too slow for dynamic motion tracking. Deep learning frameworks that reconstruct 3D volumes from sparse 2D projections offer a promising solution, but their performance under the geometrically complex, non-zero tilt acquisitions common in interventional radiology is unknown. This study evaluates the robustness of a patient-specific deep learning framework, designed to estimate 3D motion, to a range of C-arm cranial-caudal tilts. Using a 4D digital phantom with a simulated respiratory cycle, 2D X-ray projections were simulated at five cranial-caudal tilt angles across 10 breathing phases. A separate deep learning model was trained for each tilt condition to reconstruct 3D volumetric images. The framework demonstrated consistently high-fidelity reconstruction across all tilts, with a mean Structural Similarity Index (SSIM) > 0.980. While statistical analysis revealed significant differences in performance between tilt groups (p < 0.0001), the absolute magnitude of these differences was minimal (e.g., the mean absolute difference in SSIM across all tilt conditions was ~0.0005), indicating they were not functionally significant. The magnitude of respiratory motion was found to be the dominant factor influencing accuracy, with the impact of C-arm tilt being a much smaller, secondary effect. These findings demonstrate that a patient-specific, motion-estimation-based deep learning approach is robust to geometric variations encountered in realistic clinical scenarios, representing a critical step towards enabling real-time 3D guidance in flexible interventional settings.
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Optics

Universal Routing of Light via Optical Thermodynamics

Hediyeh M. Dinani, Georgios G. Pyrialakos, Abraham M. Berman Bradley et al. (+6 more)

Understanding and exploiting the dynamics of complex nonlinear systems is nowadays at the core of a broad range of scientific and technological endeavors. Within the optical domain, light evolution in a nonlinear multimode environment presents a formidable problem, as its chaotic evolution often hinders predictive insights. Recently, an optical thermodynamic framework has been put forward that, in a systematic manner, can not only predict but also harness the intricate behavior of these systems. In this work, by deploying entropic principles, we demonstrate a counterintuitive optical process in which light, launched into any input port of a judiciously designed nonlinear array, universally channels into a tightly localized ground state, a response that is completely unattainable in linear conservative arrangements. This phenomenon arises from the interplay between lattice structure and the way the kinetic and nonlinear Hamiltonian components unfold, leading to two optical thermal processes: a Joule-Thomson-like expansion followed by mode thermalization. Experimentally, this effect is demonstrated in properly configured nonlinear time-synthetic mesh lattices, where the optical temperature approaches near zero, causing light to condense at a single spot, regardless of the initial excitation position. The effect demonstrated here opens new avenues for applying the principles of optical thermodynamics in realizing novel optical functionalities, such as all-optical beam steering, multiplexing, and nonlinear beam shaping in high-power regimes, while also offering a greater understanding of the remarkable physics of light-matter interactions in multimode nonlinear systems.
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All authors Hediyeh M. Dinani, Georgios G. Pyrialakos, Abraham M. Berman Bradley, Monika Monika, Huizhong Ren, Mahmoud A. Selim, Ulf Peschel, Demetrios N. Christodoulides, Mercedeh Khajavikhan

Optics

Anisotropic Dielectric Function of Graphite Probed by Far- and Near-Field Spectroscopies

A. Toksumakov, G. Ermolaev, D. Grudinin et al. (+7 more)

Graphite is a cornerstone material for revolutionary technologies, from energy storage to the entire field of two-dimensional materials. Despite its foundational role, the predictive power required for engineering emergent optical behavior in van der Waals heterostructures is severely constrained by persistent discrepancies in reported optical constants. We resolve this long-standing ambiguity by deploying a multi-modal approach that synergizes far-field spectroscopic ellipsometry with nanoscale near-field optical probing (s-SNOM) and micro-reflectance spectroscopy. We have established a new, self-consistent set of optical constants (n and k) for both in-plane and out-of-plane crystallographic directions across the ultraviolet-to-near-infrared spectrum. This work presents a unified set of optical constants that addresses inconsistencies in the existing literature. By establishing this definitive reference, we provide the essential foundation for the quantitative modeling and engineering of light-matter interactions in the evolving landscape of carbon-based nanophotonics.
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All authors A. Toksumakov, G. Ermolaev, D. Grudinin, A. Slavich, N. Pak, G. Tikhonowski, A. Vyshnevyy, G. Tselikov, A. Arsenin, V. Volkov

Optics

Probing Local Topology in a Disordered Higher-Order Topological Insulator

Johannes Düreth, Simon Widmann, Philipp Gagel et al. (+13 more)

Higher-order topology is prized for its ability to realize lower-dimensional boundary states which are stable beyond fine-tuning. However, disorder presents a failure mechanism that can destroy topological in-gap states. Here, we investigate a disordered two-dimensional polariton lattice and employ the spectral localizer framework to define a real-space topological index rooted in crystalline spatial symmetries. This framework enables direct real-space mapping of topology beyond conventional momentum-space classifications, confirming the presence of corner and edge modes in this generalized Su-Schrieffer-Heeger model. Furthermore, it can directly quantify topological protection of a state. We leverage the versatility of our platform to experimentally realize normally distributed, random disorder and find that the corner states persist until the spectral gap closes. Experimentally, this corresponds to a disorder strength of approximately one quarter of the spectral gap. The spectral localizer accurately identifies the disorder strength at which the bandgap closes, establishing the framework as a predictive tool for every finite size system. Our results broaden the design principles for higher-order topological insulators and open the way towards imple menting disorder-resilient devices for robust lasing, light-routing, and quantum computation.
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All authors Johannes Düreth, Simon Widmann, Philipp Gagel, Siddhartha Dam, Simon Betzold, Monika Emmerling, Christian G. Mayer, David Laibacher, Martin Kamp, Oleg A. Egorov, Ulf Peschel, Tobias Hofmann, Ronny Thomale, Alexander Cerjan, Sven Höfling, Sebastian Klembt

Physics and Society

Friendship-paradox paradox: Do most people's friends really have more friends than they do?

Sang Hoon Lee

The classical friendship paradox asserts that, on average, an individual's neighbors have a higher degree than the individual. This statement concerns network-level means and does not describe how often a typical node is locally dominated by its neighbors. Motivated by this distinction, we develop a framework that separates mean-based friendship paradox inequalities from two majority-type quantities: a global fraction measuring how many nodes have a degree smaller than the mean degree of their neighbors, and a local fraction based on hub centrality that measures how many nodes are dominated in a median-based sense. We show that neither fraction is constrained by the classical friendship paradox and that they can behave independently of each other. A simple example and two empirical networks illustrate how quadrant patterns in the joint distribution of a node's degree and its neighbors' degree determine the signs and magnitudes of the two fractions, and how left- or right-skewed degree distributions of neighboring nodes can yield opposite conclusions for mean-based and median-based comparisons. The resulting framework offers a clearer distinction between population averages and local majority relations and provides a foundation for future analyses of local advantage, disadvantage, and perception asymmetry in complex networks.
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Instrumentation and Detectors

A Full Rank Pileup Deconvolution Scheme Suitable for Calorimeter Online Trigger Primitive Generation

Jin-yuan Wu

In this document, a pileup deconvolution scheme not relying on any mathematics guessing is presented. In high energy physics experiment, as the luminosity increases, pile-up issues on detectors such as calorimeters become non-negligible. Deconvolution approaches developed for data taken from DAQ systems are usually rank-deficient or underdetermined, having less equations than unknowns, even with the ADC values from multiple beam crossings are collected. These deconvolution approaches need mathematic pre-assumptions such as Sparse Representation. For online computation tasks such as for trigger primitive creation, signal availability is significantly different as in offline data analysis stage, and therefore, it is possible to use different (yet simpler) algorithms. In this situation, number of ADC values of the calorimeter outputs is the same as the number of beam crossings (or 4 times number of beam crossings, depending on the ADC sampling rate), and therefore, the number of equations can be arranged to be the same as number of unknowns. This way, a determined deconvolution scheme with a full-rank squared convolution (and deconvolution) matrix becomes possible. The robustness of deconvolution over long time windows is also studied in this paper.
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