Instrumentation and Detectors
Time-Aligned Multichannel Coherence Estimation under Intermittent Observations
Thammarat Yawisit and Pittaya Pannil
Time misalignment and intermittent readout can bias multichannel dependence estimates by mixing timing error with missing data. Time-Aligned Multichannel Coherence Estimation (TAMCE) reports a causal network coherence statistic G together with an explicit observation-support state Q using normalized recursive channel states, independent timing calibration, and confidence-weighted correlation. A non-saturated
benchmark with 16 independent seeds compares coincidence, zero filling, pairwise-complete correlation, causal hold-last completion, non-causal interpolation, diagonal intermittent-observation Kalman filtering, and TAMCE. At channel-correlated missingness 0.60, TAMCE obtains AUC 0.749 and latent-target RMSE 0.554, versus 0.723 and 0.713 for aligned zero filling and 0.826 and 0.418 for Kalman filtering. The TAMCE-zero-fill AUC difference is not statistically significant (p = 0.087). Same-record statistic ablations and selective risk-coverage tests show that Q is useful for abstention but carries essentially the same availability information as direct mask-derived pair support. Heavy-tail and drift stresses do not reverse the Kalman fidelity advantage. TAMCE is therefore supported as a model-light coherence-and-provenance interface for online monitoring and data-quality logic, not as a universally superior
estimator.
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Fluid Dynamics
Spectral Reconstruction for Under-Resolved Turbulence Measurements Using a Variational Cutoff Dissipation Model
Rishabh Mishra
This technical note addresses the challenge of accurate
turbulence characterization using robust, bandwidth-limited sensors which fail to resolve the high-wavenumber dissipation range. To correct the resulting underestimation of turbulent kinetic energy (TKE), a novel analytical spectral model is derived from a variational principle governing cascade resistance, yielding a Ginzburg-Landau domain wall solution. Unlike classical asymptotic decay formulations such as the Pao or Pope models, the proposed formulation features bounded spectral support with a hard energetic cutoff at the Kolmogorov wavenumber ($k_{\eta}$) and requires no adjustable parameters beyond the Kolmogorov constant ($C_K$). Validation against high-Reynolds-number experimental data confirms that the model accurately captures the spectral rolloff and achieves superior TKE recovery, restoring over 98% of the variance from spectra truncated as early as $k\eta=0.15$, thereby offering a robust tool for industrial and aeroacoustic flow diagnostics.
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Applied Physics · Cross-listed from cs.IT
Visual Event Detection over AI-Edge LEO Satellites with AoI Awareness
Chathuranga M. Wijerathna Basnayaka, Haeyoung Lee, Pandelis Kourtessis et al. (+5 more)
Non terrestrial networks (NTNs), particularly low Earth orbit (LEO) satellite systems, play a vital role in supporting future mission critical applications such as disaster relief. Recent advances in artificial intelligence (AI)-native communications enable LEO satellites to act as intelligent edge nodes capable of on board learning and task oriented inference. However, the limited link budget, coupled with severe path loss and fading, significantly constrains reliable downlink transmission. This paper proposes a deep joint source-channel coding (DJSCC)-based downlink scheme for AI-native LEO networks, optimized for goal-oriented visual inference. In the DJSCC approach, only semantically meaningful features are extracted and transmitted, whereas conventional separate source-channel coding (SSCC) transmits the original image data. To evaluate information freshness and visual event detection performance, this work introduces the age of misclassified information (AoMI) metric and a threshold based AoI analysis that measures the proportion of users meeting application specific timeliness requirements. Simulation results show that the proposed DJSCC scheme provides higher inference accuracy, lower average AoMI, and greater threshold compliance than the conventional SSCC baseline, enabling semantic communication in AI native LEO satellite networks for 6G and beyond.
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All authors Chathuranga M. Wijerathna Basnayaka, Haeyoung Lee, Pandelis Kourtessis, John M. Senior, Vishalya P. Sooriarachchi, Dushantha Nalin K. Jayakody, Marko Beko, Seokjoo Shin
Data Analysis and Statistics · Cross-listed from cs.SI
Needles in a haystack: using forensic network science to uncover insider trading
Gian Jaeger, Wang Ngai Yeung and Renaud Lambiotte
Although the automation and digitisation of anti-financial crime investigation has made significant progress in recent years, detecting insider trading remains a unique challenge, partly due to the limited availability of labelled data. To address this challenge, we propose using a data-driven networks approach that flags groups of corporate insiders who report coordinated transactions that are indicative of insider trading. Specifically, we leverage data on 2.9 million trades reported to the U.S. Securities and Exchange Commission (SEC) by company insiders (C-suite executives, board members and major shareholders) between 2014 and 2024. Our proposed
algorithm constructs weighted edges between insiders based on the temporal similarity of their trades over the 10-year timeframe. Within this network we then uncover trends that indicate insider trading by focusing on central nodes and anomalous subgraphs. To highlight the validity of our approach we evaluate our findings with reference to two null models, generated by running our
algorithm on synthetic empirically calibrated and shuffled
datasets. The results indicate that our approach can be used to detect pairs or clusters of insiders whose behaviour suggests insider trading and/or
market manipulation.
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Applied Physics · Cross-listed from cond-mat.soft
Effect of the repulsion between twin granular impactors on crater's aspect ratio: preliminary findings
P. Altshuler, R. Pupo-Santos, A. Rivera et al. (+1 more)
We study the role of repulsive granular interactions between identical intruders as they impact a granular bed. We demonstrate experimentally that repulsion does have a measurable effect in the aspect ratio of binary craters. Furthermore, we show that the protocol followed for the preparation of the granular bed plays a crucial role in the output of table-top experiments on doublet craters.
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All authors P. Altshuler, R. Pupo-Santos, A. Rivera, E. Altshuler
Popular Physics · Cross-listed from astro-ph.IM
Optical SETI at ESO in the 2040s
Valenitn D. Ivanov
The searches for other life and for intelligence are fundamental problems that science faces today. Most searches so far have been focused on
radio, but optical
laser communication is an alternative, well suited for a ground-based observatory. A project to search for artificial
laser communications with the current and future extreme multiplexity spectroscopic facilities that ESO may develop by the 2040s is outlined. The monochromatic light is a clearly identifiable technosignature. The enormous corollary outreach potential of this initiative is underlined.
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Chemical Physics
A Fixed-Volume Variant of Gibbs-Ensemble Monte Carlo Yields Significant Speedup in Binodal Calculation
Sanbo Qin and Huan-Xiang Zhou
Gibbs-ensemble Monte Carlo (GEMC) is a powerful method for calculating the gas-
liquid binodals of simple models and small molecules, but is too demanding computationally for realistic models of
proteins. Here we discover that the main reason for long simulations is that volume exchange is very slow to achieve, and develop a variant GEMC without volume exchange. The key is to determine an appropriate initial density. Test of this fixed-volume GEMC method on Lennard-Jones and patchy particles shows enormous speedup without any loss of accuracy in predicted binodals. The fast speed of fixed-volume GEMC promises many applications.
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Physics Education
Making Quantum Accessible: A Seven-Category Framework for K-12 Quantum Education
Rhea Fernandez, Sarah Hagstrom, Liesel Malanos et al. (+4 more)
We conducted a literature review and expert interviews to determine the most common methods being used to teach
quantum physics and
quantum computing concepts to primary and secondary students. Based on the findings of this review, we provide a framework of seven categories of teaching approaches for teaching mathematically accessible
quantum concepts; they are Defamiliarization,
Quantum Picturalism,
Spin-First Approach, Einstein-First Approach, Many Paths Approach, Historical Development Approach and Game-based
Quantum Learning. We summarise each of these teaching methods and overview their advantages and disadvantages of each method. Our framework makes it easy for physics educators to embrace the diverse methods of teaching
quantum physics and
quantum computing at the primary and secondary level.
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All authors Rhea Fernandez, Sarah Hagstrom, Liesel Malanos, Lachlan McGinness, Madeline Mitchell, Saskia Schultz, Elizabeth Sexton
Medical Physics
A physics-informed, plug-and-play dose engine for gradient-based radiotherapy treatment planning
Attila Simkó, Matthias Kronsteiner, Simon Glatzer et al. (+11 more)
Radiotherapy treatment planning remains a time-intensive iterative process requiring expert intervention in commercial treatment planning system (TPS). While machine learning approaches have demonstrated promise, most remain depedent on TPS-based dose calculation or surrogate dose models, preventing direct optimization of deliverable treatment plan parameters. We propose PyDoseRT (PDRT), a physics-informed, GPU-accelerated dose engine implemented in PyTorch that computes dose distributions directly from treatment delivery parameters (i.e., MLC leaf positions, jaw positions, gantry angles, and monitor units). The engine preserves gradient information throughout the dose computation pipeline, enabling gradient-based optimization of hardware-constrained treatment plans without the reliance on a commercial TPS. PDRT was evaluated on 19 and 162 clinical VMAT prostate cancer plans from two hospitals (with different treatment machines). When recalculating clinical plans, PDRT achieved high 3D gamma pass rates (mean 96.8% for 2%/2 mm and 98.9% for 3%/3 mm, depending on cohort). All optimized plans converged to clinically acceptable solutions and passed deliverability verification when imported into a commercial TPS. This physics-informed framework eliminates TPS dependency for radiotherapy optimization research by enabling gradient-based planning while ensuring that delivery parameters remain in the machine-feasible range. The gradient-enabled dose engine allows exploration of novel optimization strategies and objective functions while maintaining clinical validity. The proposed approach provides a research platform for investigating real-time adaptive radiotherapy concepts, automated planning workflows, and TPS-independent optimization strategies, and democratizing radiotherapy research, by exposing gradient-enabled, hardware-aware, open-source dose computation.
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All authors Attila Simkó, Matthias Kronsteiner, Simon Glatzer, Minh Vu, Josef A. Lundman, Joakim Jonsson, Jörgen Olofsson, Kristina Sandgren, Wolfgang Lechner, Dietmar Georg, Tommy Löfstedt, Tufve Nyholm, Anders Garpebring, Gerd Heilemann
Computational Physics · Cross-listed from quant-ph
El Agente Cuantico: Automating quantum simulations
Ignacio Gustin, Luis Mantilla Calderón, Juan B. Pérez-Sánchez et al. (+8 more)
Quantum simulation is central to understanding and designing
quantum systems across physics and chemistry. Yet it has barriers to access from both computational complexity and computational perspectives, due to the exponential growth of
Hilbert space and the complexity of modern software tools. Here we introduce{\cinzel El Agente Cuántico}, a multi-
agent AI system that automates
quantum-simulation workflows by translating natural-
language scientific intent into executed and validated computations across heterogeneous
quantum-software frameworks. By
reasoning directly over library documentation and APIs, our agentic system dynamically assembles end-to-end simulations spanning state preparation, closed- and open-system dynamics, tensor-network methods,
quantum control,
quantum error correction, and
quantum resource estimation. The developed system unifies traditionally distinct simulation paradigms behind a single natural-
language interface. Beyond reducing technical barriers, this approach opens a path toward scalable, adaptive, and increasingly autonomous
quantum simulation, enabling faster exploration of physical models, rapid hypothesis testing, and closer integration between theory, simulation, and emerging
quantum hardware.
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All authors Ignacio Gustin, Luis Mantilla Calderón, Juan B. Pérez-Sánchez, Jérôme F. Gonthier, Yuma Nakamura, Karthik Panicker, Manav Ramprasad, Zijian Zhang, Yunheng Zou, Varinia Bernales, Alán Aspuru-Guzik
Optics
Simulation Driven Design of a Multilayer Plasmonic Sensor Using Cu Ni and BaTiO3 for Waterborne Pathogen Detection
R. Runthala, V. K. Venkatesh, D. Gupta et al. (+1 more)
We present a simulation guided design for a multilayer surface plasmon resonance (SPR) based biosensor capable of detecting refractive index changes in a target induced by analytes. Surface plasmons are excited using a hybrid Kretschmann configuration with a calcium fluoride (CaF2) prism under transverse
magnetic polarization illumination. In the sensing architecture, copper (Cu) serves as the plasmonic metal and is overlaid with a thin nickel (Ni) layer to prevent oxidation. To enhance analyte coupling and electromagnetic field confinement, a dielectric layer of barium titanium
oxide (BaTiO3) along with a monolayer of
graphene oxide (GO) is incorporated. The multilayer structure is iteratively optimized using the transfer
matrix method for angular interrogation at a wavelength of 1064 nm, focusing on key performance parameters such as sensitivity, minimum reflectivity, and figure of merit (FOM). Finite element method based simulations confirm efficient surface plasmon excitation, with optimal layer thicknesses of 30 nm for Cu and 5 nm for BaTiO3. The proposed SPR based sensor (CaF2 Cu Ni BaTiO3 GO) achieves a sensitivity of 157.8 deg per RIU and a figure of merit of 17.48 RIU minus one while detecting the presence of Escherichia coli bacteria in water, demonstrating its potential for waterborne pathogen sensing applications.
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All authors R. Runthala, V. K. Venkatesh, D. Gupta, P. Arora
Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Controllable Probabilistic Forecasting with Stochastic Decomposition Layers
John S. Schreck, William E. Chapman, Charlie Becker et al. (+6 more)
AI weather prediction ensembles with latent noise injection and optimized with the continuous ranked probability score (CRPS) have produced both accurate and well-calibrated predictions with far less computational cost compared with
diffusion-based methods. However, current CRPS ensemble approaches vary in their training strategies and noise injection mechanisms, with most injecting noise globally throughout the network via conditional normalization. This structure increases training expense and limits the physical interpretability of the
stochastic perturbations. We introduce
Stochastic Decomposition Layers (SDL) for converting deterministic machine learning weather models into probabilistic ensemble systems. Adapted from StyleGAN's hierarchical noise injection, SDL applies learned perturbations at three decoder scales through latent-driven modulation, per-pixel noise, and channel scaling. When applied to WXFormer via transfer learning, SDL requires less than 2% of the computational cost needed to train the baseline model. Each ensemble member is generated from a compact latent tensor (5 MB), enabling perfect reproducibility and post-inference spread adjustment through latent rescaling. Evaluation on 2022 ERA5 reanalysis shows ensembles with spread-skill ratios approaching unity and rank histograms that progressively flatten toward uniformity through medium-range forecasts, achieving calibration competitive with operational IFS-ENS. Multi-scale experiments reveal hierarchical uncertainty: coarse layers modulate synoptic patterns while fine layers control mesoscale variability. The explicit latent parameterization provides interpretable uncertainty quantification for operational
forecasting and
climate applications.
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All authors John S. Schreck, William E. Chapman, Charlie Becker, David John Gagne II, Dhamma Kimpara, Nihanth Cherukuru, Judith Berner, Kirsten J. Mayer, Negin Sobhani
Biological Physics
Endoplasmic Reticulum Structure Determines Optimal Ribosome Density
Benjamin Tang
Recent work has shown an increasing interest in understanding the structure of the endoplasmic reticulum (ER) and how ribosomes are displayed on it. Here we present a model that explains a physical reason for why the
cell creates different structures of the ER. Due to the
diffusion of biomolecules, we find that flat sheets and a
matrix of tubules have different regimes of optimized capture efficiency. We extend the model to explain the observed difference in density of ribosomes on the structures of the ER. Due to the capture efficiency of tubules, less ribosomes are needed on those structures. For flat sheets, more ribosome coverage at biological separation distance is needed to match the same fraction of relative flux. We then push the model to predict that depending on the future life of the translated
protein and overall demand for
protein expression, the
cell will utilize one structure of the ER over another. Predictions are compared with experimental data.
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Space Physics
Energetically-dominant Sunward-Propagating Alfvén Waves Near 1 au and Their Relation to Large-scale Magnetic Switchbacks
Nickolas Giardetti, Sofiane Bourouaine and Jean C. Perez
In this letter, we investigate the population of energetically-dominant sunward-propagating Alfvén waves (SAWs) using more than 20 years of data provided by the Wind spacecraft near 1 au. We refer to SAWs as energetically-dominant sunward-propagating Alfvén waves within inertial range scales. Key parameters such as normalized cross helicity,
plasma incompressibility, and
magnetic incompressibility are used to determine the SAWs. Incorporating the polarity of the heliospheric
magnetic field, AW modes are identified, which enables the determination of the propagation direction. Occurrence rates of SAWs vary from 1% to 14% depending on the time scale and
solar wind stream type considered. Particularly, the relationship between large-scale
magnetic field switchbacks (SBs) and SAWs (for a 1-hour long time scale) is investigated. A methodology utilizing pitch angle distributions of suprathermal electron strahl is employed to identify inverted
magnetic field
topology. The intervals containing SAWs are cross-referenced and examined with intervals identified as SBs. For a sample of 1636 1-hour SAW intervals, 17.5% are associated with
magnetic field switchbacks occurring at scales larger than one hour. The analysis lends support to the idea of switchbacks as one of the candidate sources for a portion of the SAW population.
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Classical Physics
Point Charges in Classical Electrodynamics
Jonathan Baxter
LaTeX transcription (2025) of a 1989 honours thesis (University of Adelaide) on point charges in classical electrodynamics and the Lorentz-Dirac radiation-reaction equation. The thesis reviews the retarded field of an arbitrarily moving charge, energy-momentum conservation, and derives the Lorentz-Dirac equation via momentum balance. It discusses self-interaction and mass renormalization, and presents world-line self-field definitions including retarded averaging and an analytic continuation approach. Appendices include Mathematica listings used to obtain near-world-line expansions of the field and related quantities.
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Optics
A Segmented Heater-Driven, Low-Loss, Reconfigurable Photonic Phase-Change Material-Based Phase Shifter
Ranjeet Dwivedi, Agraj Yadav, Regis Orobtchouk et al. (+4 more)
Phase-change material (PCM)-based non-volatile multilevel phase shifters are key components in photonic integrated
circuits. Electrically, multiple phase levels can be encoded by controlling the heater power and employing different microheater architectures to induce varying degrees of PCM amorphization. However, encoding a large number of levels is not straightforward. In this work, we first investigate a phase shifter structure based on a GeSe PCM integrated on top of a silicon-on-
insulator waveguide, employing a simple rectangular-shaped heater under pulse-width modulation (PWM). We numerically demonstrate that multilevel phase shifts can be achieved because of non-uniform heating in the GeSe PCM layer. However, the resulting phase levels for this basic configuration are highly non-linear because of the uniform power dissipation along the light propagation direction characterized by the same cross-section. To overcome this limitation, we designed a novel PCM-based phase shifter with a segmented heater whose width gradually increases along the light propagation direction. This configuration enables the encoding of hundreds of well-spaced phase levels between 0 and $\pi$, facilitated by smoother amorphization arising from the combined effects of non-uniform heating across segments and within each segment, while achieving an insertion loss of only 0.6 dB in the worst case. Furthermore, when evaluating both heater architectures under pulse amplitude modulation (PAM) at a fixed pulse duration, we observe behavior consistent with the trends observed for PWM, confirming the superior performance of the segmented heater design.
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All authors Ranjeet Dwivedi, Agraj Yadav, Regis Orobtchouk, Benoit Charbonnier, Stephane Malhouitre, Pierre Noé, Fabio Pavanello
Medical Physics
Quantitative ultrasound imaging of bone: anatomical images, tissue structural quality, and pulsatile blood flow
Gabrielle Laloy-Borgna, Nastassia Navasiolava, Pim Hutting et al. (+12 more)
We propose an ultrasound approach which provides, with one single examination and one single device, access to three bone biomarkers: anatomy, tissue quality and blood flow. It unlocks ultrasound imaging inside bone by accounting for ultrasound wave speed heterogeneity and anisotropic wave refraction. This study reports the first in vivo evaluation with a comparison to peripheral Quantitative Computed
Tomography (pQCT) and modulations of blood flow. Anatomical multi-layer bone-corrected reconstruction was validated at the tibia of healthy volunteers against pQCT and showed agreement on bone cortex interfaces. Estimation of axial and radial ultrasound wave speeds in cortical bone tissue (i.e. along the tissue
symmetry axis and normal to it) demonstrated good reproducibility and positive correlation with bone mineral density measured by pQCT. Pulsatile blood flow was mapped and quantified in cortical and medullary regions. A directional ray selection method was developed to enhance blood signal extraction by reducing strong specular reflections originating from the outer and inner surfaces of the bone cortex. Physiological and non-physiological modulations of blood flow, namely head-up/head-down tilt table maneuvers and arterial occlusions, demonstrated the method sensitivity to blood flow variations. For the first time, reactive hyperemia was observed inside bone cortex. These results demonstrate the feasibility of a portable, non-ionizing, and quantitative ultrasound approach for structural, anatomical, and vascular characterization of bone tissue. This approach may offer new diagnostic capabilities for bone disorders, for instance osteoporosis, delayed fracture healing or osteonecrosis.
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All authors Gabrielle Laloy-Borgna, Nastassia Navasiolava, Pim Hutting, Andréa Bertona, Amadou S. Dia, Sébastien Salles, Anthony Augé, Alice Mazzolini, Quentin Grimal, Olivier Lucidarme, Hervé Locrelle, Jacques-Olivier Fortrat, Laurence Vico, Marc-Antoine Custaud, Guillaume Renaud
Accelerator Physics · Cross-listed from cs.CL
From Natural Language to Control Signals: A Conceptual Framework for Semantic Channel Finding in Complex Experimental Infrastructure
Thorsten Hellert, Nikolay Agladze, Alex Giovannone et al. (+5 more)
Modern experimental platforms such as particle accelerators, fusion devices,
telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels accumulated over decades of
evolution. Operators and AI systems rely on informal expert knowledge, inconsistent naming conventions, and fragmented documentation to locate signals for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and
language-model-driven interfaces. We formalize semantic channel finding-mapping natural-
language intent to concrete control-system signals-as a general problem in complex experimental infrastructure, and introduce a four-paradigm framework to guide architecture selection across facility-specific data regimes. The paradigms span (i) direct in-context lookup over curated channel dictionaries, (ii) constrained hierarchical
navigation through structured trees, (iii) interactive
agent exploration using iterative
reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale-from compact free-electron
lasers to large synchrotron light sources-and diverse control-system architectures, from clean hierarchies to legacy environments. These implementations achieve 90-97% accuracy on expert-curated operational queries.
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All authors Thorsten Hellert, Nikolay Agladze, Alex Giovannone, Jan Jug, Frank Mayet, Mark Sherwin, Antonin Sulc, Chris Tennant
Fluid Dynamics
Discrete inflow and drainage dynamics of a thin film over a stalagmite of variable shape
Justine Parmentier, Vincent E. Terrapon and Tristan Gilet
Stalagmites in karstic caves preserve valuable palaeoclimate records through calcium-rich layered deposits, presenting
curvature variations both across and within individual stalagmites. Stalagmites always remain covered by a thin water film fed by a discrete inflow of drops, which bring in new ions in solution for the stalagmites to grow. However, the
gravity-induced drainage of this film and its response to the stalagmite underneath shape and the discrete drop inflow remain poorly characterised in existing growth models. To address these limitations, we develop a theoretical framework that captures the combined effects of shape
curvature and discrete drop inflow on thin film drainage dynamics, starting from Reynolds lubrication theory expressed in curvilinear coordinates. From there, we show that the limiting cases of thickness-dominated and inclination-dominated drainage translate into distinct scaling laws for both the front propagation position and stationary film thickness. We further validate these results by numerically solving the governing equations. Finally, experimental measurements conducted in both cave and lab settings confirm the predicted stationary film thickness. Our findings provide insights into the influence of substrate shape and inflow dynamics on thin film drainage, with implications for stalagmite growth modelling and other
gravity-driven surface flows.
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Instrumentation and Detectors
Quantitative mobile gamma-ray spectrometry through Bayesian inference
David Breitenmoser, Alberto Stabilini, Malgorzata Magdalena Kasprzak et al. (+1 more)
Accurate quantitative mapping of gamma-ray emitters is critical for applications ranging from radiological emergency response and environmental monitoring to
nuclear security and deep space exploration. Here, we show that such mapping can be achieved by combining mobile gamma-ray spectrometry with high-fidelity Monte Carlo simulations and full-spectrum
Bayesian inference. Using 6 s of single-pass mobile spectrometry data benchmarked against independent in-situ and laboratory assays, we demonstrate decisive source mixture identification ($>\!\!5\sigma$), meter-scale source localization, and recovery of source activities with percent-level accuracy. The developed method marks a critical advance in quantitative gamma-ray sensing, enabling improved radiological situational awareness, enhanced terrestrial geophysical and geochemical mapping, as well as more robust constraints on radionuclide abundances on extraterrestrial bodies across the
Solar System.
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All authors David Breitenmoser, Alberto Stabilini, Malgorzata Magdalena Kasprzak, Sabine Mayer
Biological Physics · Cross-listed from q-bio.MN
Quantifying the Emergence of Selection Prior to Biological Evolution
Michael Jirasek, Abhishek Sharma, Mary Wong et al. (+2 more)
Selection is central to biological
evolution, yet there has been no general experimental framework for quantifying selection in chemical systems before life. Here we demonstrate that selection in a prebiological chemical system can be directly quantified. Assembly Theory predicts that selection corresponds to a transition from undirected to directed exploration of chemical possibility space, measurable through the amount of Assembly, A, which integrates molecular assembly index with observed copy number. By analysing peptide ensembles produced under diverse polymerisation conditions, we show that undirected reactions explore sequence space almost uniformly, yielding exploration ratios of 0.85-0.95, whereas reactions influenced by evolved proteases generate markedly lower ratios (0.51-0.75) and elevated A, consistent with selective reinforcement of specific assembly pathways. Across multiple environments and amino-acid combinations, the exploration ratio and ensemble assembly A robustly distinguish directed from undirected exploration, establishing a general, experimentally tractable metric for detecting and measuring selection in chemical
evolution.
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All authors Michael Jirasek, Abhishek Sharma, Mary Wong, Jennifer Munro, Leroy Cronin
Geophysics
Linear and nonlinear stability of rate-and-state faults
Robert C. Viesca and Dmitry I. Garagash
Models of faults incorporating slip rate- and state-dependent friction have reproduced phenomena from spontaneous slow, aseismic slip to earthquake-generating dynamic rupture. Numerical explorations of model parameter space show sudden transitions in behavior. However these boundaries are poorly constrained analytically, with commonly used scalings derived assuming unrepresentative conditions of uniform sliding on an infinite, homogeneous fault. In this work, we demonstrate that an analysis of linear stability can reflect model conditions. We examine two scenarios that move beyond the classical case: an asperity driven by the steady creep of its surroundings, and a finite fault experiencing a constant rate of shear loading. We identify the critical fault dimension $L_c$ at which point linear stability is lost. Beyond this linear regime, the non-linear nature of the friction law implies the loss of
memory of loading conditions as instability progresses and the existence of universal solutions describing this process. We refine prior analyses of this non-linear instability and find the minimum fault size that can support self-sustaining, unstable acceleration towards dynamic rupture. We examine the role of the state
evolution law and delineate conditions under which faults may be linearly stable but non-linearly unstable, requiring finitely large perturbations to trigger instability. For both the linear and non-linear analysis, we consider scenarios of two- and three-dimensional deformation. On the basis of numerical solutions, approximate but accurate algebraic expressions for the transition boundaries are presented. These results provide means for careful model design and to delimit plausible regions of parameter space when considering physical observations of stable creep, aseismic (slow slip) or seismic transients.
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Optics
Line lasing in a two-dimensional lattice of orbital photonic resonators
Tony Mathew Blessan, Bastian Real, Marijana Milicevic et al. (+8 more)
The engineering of specialty
lasers with unconventional mode structures is one of the modern challenges in the development of integrated coherent sources. Examples include the use of bound states in the continuum, microlasers with orbital angular momentum, Dirac-band
lasers and topological
lasers. In this work we engineer a two-dimensional
lattice of coupled micropillars with lasing line modes. We use a convenient combination of orbital photonic modes to design photonic bands which are flat in one direction and dispersive in the perpendicular one giving rise to line lasing modes. Such an architecture opens the possibility of implementing densely packed lasing
matrices in compact two dimensional
lattices.
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All authors Tony Mathew Blessan, Bastian Real, Marijana Milicevic, Isabelle Sagnes, Aristide Lemaítre, Luc Le Gratiet, Abdelmounaim Harouri, Sylvain Ravets, Jacqueline Bloch, Clément Hainaut, Alberto Amo
Chemical Physics · Cross-listed from cond-mat.mes-hall
Extreme Nanoconfinement Reshapes the Self-Dissociation of Water
Chenyu Wang, Wanjian Yin and Ke Zhou
Water's ability to self-dissociate into H$_3$O$^+$ and OH$^-$ ions is central to acid-base chemistry and bioenergetics. Recent experimental advances have enabled the confinement of water down to the nanometre scale, even to the single-molecule limit, yet how this process is altered at the extreme nanoconfinement remains unclear. Using ab-initio calculations and enhanced-sampling machine-learning potential molecular dynamics, we show that monolayer-confined water exhibits a markedly lower barrier to auto-dissociation than bulk water. Confinement restructures both intramolecular bonding and the intermolecular hydrogen-bond network, while enforcing quasi-2D dipolar correlations that amplify dielectric fluctuations. Our results imply that two-dimensional confined water could act as a superdielectric medium and may exhibit superionic behavior, as observed in recent experiments. These findings reveal confinement as a powerful route to enhanced
proton activity, shedding light on geochemical niches, biomolecular environments, and nanofluidic systems where water's chemistry is fundamentally reshaped.
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Biological Physics
Load-Aware Calibration of EMG-Driven Musculoskeletal Models for Accurate and Generalizable Joint Torque Estimation
Rajnish Kumar, Suriya Prakash Muthukrishnan, Lalan Kumar et al. (+1 more)
Accurate EMG-driven musculoskeletal (MSK) modeling is critical for biomechanics, rehabilitation, and assistive technology. However, most models calibrate parameters under a single load, ignoring the fact that tasks with similar kinematics may differ in mechanical demand. This study introduces a load-aware calibration framework to improve joint torque prediction accuracy and generalizability. Surface EMG and joint kinematics were recorded from eleven participants during elbow flexion-extension under 0, 2, and 4\,kg loads. We evaluated three calibration strategies (load-specific, global, cross-load) and three optimization frameworks (simulated annealing (SA), particle swarm optimization (PSO), and hybrid PSO-pattern search (PSO-PS)). Results indicate that load-specific calibration significantly improves performance, with lower RMSE and higher correlation ($r > 0.75$). Parameters related to muscle force, fiber length, and activation dynamics showed high load sensitivity. PSO-based methods yielded more consistent and physiologically plausible estimates than simulated annealing. The proposed framework enables MSK models to distinguish between visually similar but mechanically distinct tasks, supporting robust subject-specific modeling for clinical and real-world applications.
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All authors Rajnish Kumar, Suriya Prakash Muthukrishnan, Lalan Kumar, Sitikantha Roy
Optics
Sub-nanometer 3D morphometric precision of polarisation-resolved wide-field optical extinction microscopy determines the roundness of individual gold nanospheres
Lukas M Payne, Furqan Alabdullah, Paola Borri et al. (+1 more)
Quantitative polarisation-resolved optical extinction microscopy of individual plasmonic nanoparticles has recently been introduced as a powerful tool to characterise the nanoparticle's morphology with a precision comparable to electron microscopy, while using a simple optical microscope [Nanoscale 12, 16215 (2020)]. Here we provide a step change by adding measurements for radial polarisation in the condenser back focal plane, probing plasmonic resonances polarised in axial direction. The combined linear and radial polarisation measurements provide a significantly enhanced precision of the retrieved 3D morphology, as we show on defect-free ultra-uniform gold nanospheres of 30 nm nominal diameter characterised by transmission electron microscopy. The measured cross-sections are modelled for an ellipsoidal particle, determining the three semi-axes and rotation angles by fitting the measurements. The material permittivity and surface damping providing the best fit are found. The particle aspect ratio is determined with a precision better than 5%, and the size with an impressive precision of 0.1 nm. Notably, corrections to the Rayleigh-Gans ellipsoid model due to retardation are significant even though the particle diameters are more than an order of magnitude smaller than the wavelength in the medium. Taking them into account improves the shape accuracy.
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All authors Lukas M Payne, Furqan Alabdullah, Paola Borri, Wolfgang Langbein
Atomic Physics · Cross-listed from hep-ph
Collapse of Coulomb Bound States of Vector Bosons
V.V. Flambaum and H. B. Tran Tan
Charged
spin 1 (vector) particles behave very differently from electrons or scalars in a Coulomb field. For an infinitely heavy point-like
nucleus their bound state wave functions fall to the centre, and
embedding the system in a renormalisable electroweak-type theory does not remedy this short-distance pathology. We therefore solve the pure Coulomb problem for a finite
nuclear radius $R$ and recover the point
nucleus limit by letting $R\to 0$. This approach allows us to include the crucial Upsilon term in the wave equations, which for the point-like
nucleus is proportional to delta(r) and was ignored in the previous calculations of the energy spectrum. Several unusual effects emerge: (i) The Upsilon term supports a tower of states located mainly inside the
nucleus. As R -> 0 their number diverges, most lying in the negative energy continuum (energy epsilon < - m c^2). They trigger
vacuum breakdown - particle-antiparticle pair creation that ultimately screens the
nuclear charge. (ii) Ordinary Sommerfeld-like states (with binding energy smaller m c^2) persist, but a finite fraction of each wave function leaks into the
nucleus, even as R -> 0. (iii) Charge density of a negatively charged vector particle changes sign in a vicinity of the
nucleus and becomes positive charge density, whereas the Upsilon term ensures its density inside the
nucleus remains negative. (iv) For weak coupling, Z alpha << 1, yet with mR <Z alpha, the non-relativistic solution differs qualitatively from Schrodinger theory despite binding energies are well below m c^2; agreement is recovered only when Z alpha << mR. These phenomena highlight the distinctive and subtle behaviour of
spin-1 particles in the Coulomb field.
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Physics and Society
Bridging the divide: Economic exchange and segregation in dual-income cities
D. Ortega and E. Korutcheva
Segregation is a growing concern around the world. One of its main manifestations is the creation of ghettos, whose inhabitants have difficult access to well-paid jobs, which are often located far from their homes. In order to study this phenomenon, we propose an extension of Schelling's model of segregation to take into account the existence of economic exchanges. To approximate a geographical model of the city, we consider a small-world network with a defined real estate
market. The
evolution of the system has also been studied, finding that economic exchanges follow exponential laws and relocations are approximated by power laws. In addition to this, we consider the existence of delays in the actions of the
agents, which mainly affect the happiness of those with fewer economic resources. Besides, the size of the economic exchange plays a crucial role in overall segregation. Despite its simplicity, we find that our model reproduces real-world situations such as the separation between favoured and handicapped economic areas, the importance of economic contacts between them to improve the distribution of wealth, and the existence of efficient and cheap transport to break the poverty cycles typical of disadvantaged zones.
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Instrumentation and Detectors · Cross-listed from eess.SP
The Choice of Line Lengths in Multiline Thru-Reflect-Line Calibration
Ziad Hatab, Michael Gadringer and Wolfgang Bösch
This paper presents an analysis and rigorous procedure for determining the optimal lengths of line standards in multiline thru-reflect-line (TRL) calibration of vector network analyzers (VNAs). The solution is obtained through nonlinear constrained optimization of the
eigenvalue problem in multiline TRL calibration. Additionally, we propose a simplified approach for near-optimal length selection based on predefined sparse rulers. Alongside the length calculation, we discuss the required number of lines to meet bandwidth requirements. The proposed methods are validated through measurements of multiple multiline TRL calibration kits on printed
circuit boards of different materials and stackups, covering frequencies up to 150 GHz. A measurement-based Monte Carlo uncertainty analysis, using error boxes derived from impedance standard substrate measurements, demonstrates that the proposed line lengths distribute calibration uncertainty more evenly across lines compared to a commercial calibration kit. Practical examples are provided for various applications, including lossy and dispersive lines, as well as banded solutions for waveguides.
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Plasma Physics
Study of the impact of fast ions on core turbulence at rational surfaces via global gyrokinetic simulations
D. Brioschi, A. Di Siena, R. Bilato et al. (+6 more)
In this work, the interplay between fast ions and safety factor rational surfaces is studied in a turbulent
plasma via global nonlinear gyrokinetic simulations. Initially, the fast particles-induced enhancement of shearing structures from
turbulence self-interaction is analyzed. Our study takes into account the competition between this mechanism and other fast ions effects, i.e. thermal profiles dilution and quasi-resonant interaction. We find the fast ions-induced reduction of destabilization threshold for the zonal modes to be a very efficient way to suppress
turbulence. Indeed, it leads to the formation of regions where turbulent transport is reduced by 90% of its original value. Furthermore, an $n=m=1$ fishbone is driven unstable inside the
plasma and its interaction with
turbulence is studied. We find the beat-driven zonal structure generate by this mode to further reduce
turbulence when its presence does not drastically flatten the thermal profiles.
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All authors D. Brioschi, A. Di Siena, R. Bilato, A. Bottino, T. Hayward-Schneider, A. Mishchenko, E. Poli, A. Zocco, F. Jenko