Instrumentation and Detectors
Characterization of Stitched Prototypes Chip for the ALICE ITS3 Upgrade
Michele Rignanese
During LHC Long Shutdown 3, the ALICE experiment will replace the three innermost layers of its Inner Tracking System (ITS2) with a new vertex detector, the ITS3. This new detector will be assembled using wafer-scale, stitched Monolithic Active Pixel Sensors (MAPS) fabricated using a 65nm CMOS technology node, which will be thinned and bent to form truly cylindrical layers around the beam pipe. To validate the new technology, several prototypes were developed and extensively characterized. This work focuses on the results of a test beam campaign performed at the CERN PS in September 2024, using a \SI{10}{\giga\eV} pion beam, to estimate detection efficiency and spatial resolution of the babyMOSS prototype, a smaller version of the MOnolithic Stitched Sensor (MOSS). Both non-irradiated and irradiated chips are tested, and the results confirm that the prototypes meet the ITS3 requirements, demonstrating a detection efficiency above 99%, with a fake-hit rate below 10$^{-6}$ hits/pixel/event and a spatial resolution around \SI{5}{\micro\meter}.
Read the full abstract ▾
Fluid Dynamics
A comparison of different image analysis techniques for mapping spatiotemporal pH and carbon dissolution in density-driven convection of CO2 in water
Yao Xu, Marcel Moura, Eirik Grude Flekkøy et al. (+1 more)
Density-driven convection enhances the carbon dissolution rate, which is significant for the geological carbon storage. This process will also influence the spatiotemporal pH and carbon concentrations of the underground fluid. To illuminate the convection mechanism, it is critical to understand the
evolution of those properties within the porous media. However, determining the spatiotemporal pH and concentration within porous media is always challenging. This study employed a combination of three pH indicators that can track a wide range in pH from 4 to 9.5 in a convection experiment. Furthermore, we compared three image-processing techniques: Hue, gray-difference, and angular representation of RGB color space $\mathbf{(\phi,\theta)}$ for quantifying color changes from the universal $\text{pH}$ indicator arising from the carbon convection. The characterized colors were mapped into pH by calibrating against
benchmark solutions. The comparative results demonstrate that the color quantified by the Hue technique is most robust, showing invariance to fluid thickness, camera settings, and LED luminance. In the convection experiments, it produces a continuous spatial distribution of pH and concentration level in the system. In contrast, the $\mathbf{(\phi,\theta)}$ and gray-difference techniques were more sensitive to environmental variations. They also have significant limitations for $\text{pH}$ interpolation in the critical range due to their non-monotonic calibration paths. Although all methods ultimately produced similar estimates of total dissolved carbon, the Hue technique offers greater stability and universality for high-resolution, dynamic measurements of pH and carbon concentration in the convection experiments.
Read the full abstract ▾
All authors Yao Xu, Marcel Moura, Eirik Grude Flekkøy, Knut Jørgen Måløy
Plasma Physics
Collisionless Larmor Coupling and Blob Formation in a Laser-Plasma Expanding into a Magnetized Ambient Plasma
Lucas Rovige, Robert S. Dorst, Ari Le et al. (+8 more)
Collisionless Larmor coupling is a fundamental process in space and astrophysical
plasmas that enables momentum transfer between an expanding
plasma and a magnetized ambient medium. In this paper, we report on the laboratory experimental study of Larmor coupling leading to the formation of a
plasma blob associated with a
laser-driven, super-Alfvénic
plasma flow on the Large
Plasma Device at the University of California, Los Angeles. The high-repetition rate enables systematic spatial and temporal scans of the
plasma evolution using Doppler spectroscopy, as well as measurements of the
magnetic field, electrostatic field, and self-emission of both debris and ambient ions using filtered imaging. We observe the self-focusing of the
laser-produced
plasma and the formation of a secondary diamagnetic cavity associated with a blob composed of background ions. Doppler spectroscopy reveals the transverse velocity distribution of the background ions, providing direct evidence of ion energization via Larmor coupling. The systematic spatial and temporal scans enabled by the high-repetition rate experiment allow for a detailed characterization of the ion dynamics. These experimental observations are supported by numerical simulations that provide more insight into the kinetic-scale physics associated with blob formation as well as the role of the ambient
plasma density.
Read the full abstract ▾
All authors Lucas Rovige, Robert S. Dorst, Ari Le, Carmen G. Constantin, Haiping Zhang, David J. Larson, Stephen Vincena, Shreekrishna Tripathi, Misa M. Cowee, Derek B. Schaeffer, Christoph Niemann
Biological Physics
Lagrangian for Navier-Stokes equations of motion: SDPD approach
Tetiana Kornylova, Anna Shokhina, Timothy Nerukh et al. (+1 more)
The conditions necessary and sufficient for the Smoothed Dissipative Particle Dynamics (SDPD) equations of motion to have a Lagrangian that can be used for deriving these equations of motion, the Helmholtz conditions, are obtained and analysed. They show that for a finite number of SDPD particles the conditions are not satisfied; hence, the SDPD equations of motion can not be obtained using the classical Euler-Lagrange equation approach. However, when the macroscopic limit is considered, that is when the number of particles tends to infinity, the conditions are satisfied, thus providing the conceptual possibility of obtaining the Navier-Stokes equations from the principle of least action.
Read the full abstract ▾
All authors Tetiana Kornylova, Anna Shokhina, Timothy Nerukh, Dmitry Nerukh
Optics
Frequency Conversion Characteristics of Spatiotemporal Josephson Metasurfaces for Quantum Applications
Sajjad Taravati
This presentation explores the various characteristics of a nonreciprocal, frequency-converting Josephson metasurface operating at millikelvin temperatures. Leveraging the unique properties of Josephson junctions, which support supercurrent flow without resistance, this metasurface enables efficient manipulation of nonlinear wave interactions, facilitating both frequency conversion and amplification of incident
photons.
Read the full abstract ▾
Plasma Physics
Hydrodynamic simulations of expanded warm dense foil heated by pulsed-power
Luc Revello, Laurent Videau, Frédéric Zucchini et al. (+3 more)
Warm Dense Matter lies at the frontier between condensed matter and
plasma, and plays a central role in various fields ranging from planetary science to inertial confinement fusion. Improving our understanding of this regime requires experimental data that can be directly compared with theoretical and numerical models over a broad range of conditions. In this work, a pulsed-power experiment is described in which thin metallic foils, confined within a sapphire
cell, are Joule-heated to achieve the expanded warm dense matter regime. Designing such an experiment is challenging, as it requires simultaneously predicting the electrical response of the pulsed-power driver and the hydrodynamic
evolution of the heated material. To tackle this challenge, a modeling framework has been developed that couples an electrical description of the pulsed-power system, including the driver, the switching stages and the load with a one-dimensional hydrodynamic code. This coupling allows the electrical energy deposition and the load thermodynamic
evolution to be consistently linked through the material electrical conductivity. This approach takes advantage of the simplicity of a 1D geometry while retaining the essential physics and allowing to reproduce various measurements with good accuracy, such as expansion velocity, current and voltage. This numerical approach therefore constitutes a robust and efficient method for designing and optimizing future Warm Dense Matter experiments using pulsed-power facilities.
Read the full abstract ▾
All authors Luc Revello, Laurent Videau, Frédéric Zucchini, Mathurin Lagrée, Christophe Blancard, Benjamin Jodar
Optics
Energy Transport Velocity in Photonic Time Crystals
Kyungmin Lee, Younsung Kim, Kun Woo Kim et al. (+1 more)
Steep or near-vertical Floquet dispersion in photonic time
crystals (PTCs) is often read as fast, even apparently superluminal, transport. Here, we demonstrate that this anomaly arises from modulation-driven
geometric drift, not energy flow. By deriving a Maxwell-flux Hellmann-Feynman relation, we prove that the cycle-averaged energy velocity remains strictly bounded. We further establish a universal velocity-product law conserved throughout the passband, $ v_E v_g=\langle v_{\rm ph}^2\rangle_T $, fixing transport solely by the temporal average of the inverse permittivity. The divergent group velocity is then traced to a mismatch between electric and
magnetic geometric phase connections, revealing apparent superluminality as a
geometric effect of temporal modulation.
Read the full abstract ▾
All authors Kyungmin Lee, Younsung Kim, Kun Woo Kim, Bumki Min
Applied Physics · Cross-listed from cond-mat.other
Nanoscale spin-wave frequency-selective limiter for 5G technology
Kristýna Davídková, Khrystyna Levchenko, Florian Bruckner et al. (+10 more)
Power limiters are essential devices in modern
radio frequency (RF) communications systems to protect highly sensitive input channels from large incoming signals. Nowadays-used
semiconductor limiters suffer from high electronic noise and switching delays when approaching the GHz range, which is crucial for the modern generation of 5G communication technologies aiming to operate at the EU 5G high band (24.25-27.5 GHz). The proposed solution is to use ferrite-based Frequency Selective Limiters (FSLs), which maintain their efficiency at high GHz frequencies, although they have only been studied at the macroscale so far. In this study, we demonstrate a proof of concept of nanoscale FSLs. The devices are based on
spin-wave transmission affected by four-
magnon scattering phenomena in a 97-nm-thin Yttrium Iron Garnet (YIG) film.
Spin waves were excited and detected using coplanar waveguide (CPW) transducers of the smallest feature size of 250 nm. The FSLs are tested in the frequency range up to 25 GHz, and the key parameters are extracted (power threshold, power limiting level, insertion losses, bandwidth) for different
spin-wave modes and transducer lengths. An analytical theory has been formulated to describe the fundamental physical processes, and a numerical model has been developed to quantitatively describe the insertion losses and power characteristics of the FSLs. Additionally, the perspective of the
spin-wave devices is discussed, including the possibility of simultaneously integrating three devices into one: a frequency-selective limiter, an RF filter, and a delay line, allowing for more efficient use of space and energy.
Read the full abstract ▾
All authors Kristýna Davídková, Khrystyna Levchenko, Florian Bruckner, Roman Verba, Fabian Majcen, Qi Wang, Morris Lindner, Carsten Dubs, Vincent Vlaminck, Jan Klíma, Michal Urbánek, Dieter Suess, Andrii Chumak
Medical Physics
Accelerated Electromagnetic Simulation of MRI RF Interactions with Graphene Microtransistor-Based Neural Probes for Electrophysiology-fMRI Integration
Suchit Kumar, Alejandro Labastida Ramirez, Samuel M Flaherty et al. (+6 more)
Implementing electrophysiological recordings within an MRI environment is challenging due to complex interactions between recording probes and MRI-generated fields, which can affect both safety and data quality. This study aims to develop and evaluate a hybrid electromagnetic (EM) simulation framework for efficient and accurate assessment of such interactions. Methods: A hybrid EM strategy integrating the Huygens' Box (HB) method with sub-gridding was implemented in an FDTD solver (Sim4Life). RF coil models for mouse and rat head were simulated with and without intracortical (IC) and epicortical (EC)
graphene-based micro-transistor arrays. Three-dimensional multi-layered probe models were reconstructed from two-dimensional layouts, and transmit field ($B_{1}^{+}$), electric field ($E$), and specific absorption rate (SAR) distributions were evaluated. Performance was benchmarked against conventional full-wave multi-port (MP) simulations using Bland-Altman analysis and voxel-wise percentage differences. Results: HB simulations reduced computational time by approximately 70-80%, while preserving spatial patterns of $|B_{1}^{+}|$, $|E|$, and SAR, including transmit-field
symmetry and localized high-field regions. Deviations from MP were minimal for $|B_{1}^{+}|$ (median $\Delta$% 0.02-0.07% in mice, -3.7% to -1.7% in rats) and modest for $|E|$ and SAR, with absolute SAR values remaining well below human safety limits.
Graphene-based arrays produced negligible effects on RF transmission and SAR deposition. Conclusion: The HB approach enables computationally efficient, high-resolution evaluation of EM interactions involving microscopic probes in MRI environments, supporting simulations that are otherwise impractical with full-wave MP modeling.
Read the full abstract ▾
All authors Suchit Kumar, Alejandro Labastida Ramirez, Samuel M Flaherty, Anton Guimera Brunet, Nerea Alvarez de Eulate, Kostas Kostarelos, Ben Dickie, Rob C Wykes, Louis Lemieux
Computational Physics
Neural Hodge Corrective Solvers: A Hybrid Iterative-Neural Framework
Arjun Puthli, Somdatta Goswami and Souvik Chakraborty
We introduce the Neural Hodge Corrective Solver (NHCS), a hybrid iterative-neural framework for partial differential equations that embeds learned corrective operators within the Discrete Exterior Calculus (DEC) formulation. The method combines classical Jacobi-Richardson iterations with data-driven corrections to refine numerical solutions while preserving the underlying topological and metric structure. NHCS employs a two-phase training strategy. In the first phase, DEC operators are learned through relative residual minimization from data. In the second phase, these operators are integrated into the iterative solver, and training targets the improvement of convergence through learned corrective updates that remain effective even for inaccurate intermediate solutions. This staggered training enables stable, progressive refinement while maintaining the structure-preserving properties of DEC discretizations. To improve multiscale adaptivity, NHCS introduces a convolutional neural network-based correction term capable of capturing fine-scale solution features via localized updates informed by global context, improving scalability over mesh component-wise neural approaches. Moreover, the proposed framework substantially reduces computational cost by avoiding Newton-Raphson-based training and the associated Jacobian evaluations of parameterized operators. The resulting solver achieves improved efficiency, robustness, and accuracy without compromising numerical stability.
Read the full abstract ▾
Plasma Physics
Effect of static magnetic island on ITG of ADITYA-U tokamak
Vibhor Kumar Singh, Amal R Biju, Jaya Kumar Alageshan et al. (+10 more)
Magnetic islands play a crucial role in regulating
plasma confinement in tokamaks by interacting with micro-instabilities, such as the ion temperature gradient (ITG) mode. This work presents a detailed investigation of the effects of static
magnetic islands on ITG instability, relevant to the ADITYA-U tokamak, using the Global Gyrokinetic Code in Cylindrical Coordinates (G2C3), a particle-in-
cell (PIC) framework that employs a neural-network-assisted projection scheme. A two-phase simulation strategy is adopted. In the first phase, static
magnetic islands with mode numbers (m, n) = (2, 1) and (3, 1) are introduced by perturbing the
equilibrium magnetic flux functions. Particle dynamics within these modified
topologies result in the flattening of
plasma density profiles in the island regions, confirming island formation and its impact on the
equilibrium profiles. In the second phase, the flattened profiles serve as new
equilibria for linear electrostatic gyrokinetic simulations with adiabatic electrons, enabling the study of the modified ITG behavior.
Magnetic islands significantly restructure the ITG mode, producing a spatial redistribution of potential fluctuations within and around the island region. Moreover, as the island width increases, the growth rates of different toroidal ITG modes converge, suggesting a universal stabilization trend. A comparison between the (2,1) and (3,1) islands indicates that higher-q islands lead to a more spatially extended ITG mode structure, reflecting the longer
magnetic connection lengths and weaker
curvature drive at outer flux surfaces. These results demonstrate the pivotal role of island-induced
equilibrium modifications in determining ITG stability and mode structure in tokamak
plasmas.
Read the full abstract ▾
All authors Vibhor Kumar Singh, Amal R Biju, Jaya Kumar Alageshan, Kaushalender Singh, Deepti Sharma, Joydeep Ghosh, Nishant Sirse, Abhijit Sen, Sarveshwar Sharma, Manjunatha Valmiki, Sandeep Agrawal, Sanjay Wandhekar, Animesh Kuley
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Accelerating Complex Materials Discovery with Universal Machine-Learning Potential-Driven Structure Prediction
Yuqi An and Zhenbin Wang
Universal machine-learning interatomic potentials (uMLIPs) have become powerful tools for accelerating computational materials discovery by replacing expensive first-principles calculations in
crystal structure prediction (CSP). However, their effectiveness in identifying new, complex materials remains uncertain. Here, we systematically assess the capability of a uMLIP (i.e.,M3GNet) to accelerate CSP in quaternary
oxides. Through extensive exploration of the Sr-Li-Al-O and Ba-Y-Al-O systems, we show that uMLIP can rediscover experimentally known materials absent from its training set and identify seven new thermodynamically and dynamically stable compounds. These include a new polymorph of Sr2LiAlO4 (P3221) and a new disordered phase, Sr2Li4Al2O7 (P1_bar). Furthermore, our results show stability predictions based on the semilocal PBE functional require cross-validation with higher-level methods, such as SCAN and RPA, to ensure reliability. While uMLIPs substantially reduce the computational cost of CSP, the primary bottleneck has shifted to the efficiency of search
algorithms in navigating complex structural spaces. This work highlights both the promise and current limitations of uMLIP-driven CSP in the discovery of new materials.
Read the full abstract ▾
Fluid Dynamics
How Spontaneous Electrowetting and Surface Charge affect Drop Motion
Chirag Hinduja, Benjamin Leibauer, Rishi Chaurasia et al. (+5 more)
Water drops sliding on hydrophobic surfaces spontaneously separate charges at their rear. It is unclear how this charge separation affects the contact angles of a sliding drop. We slide grounded and insulated drops on hydrophobic surfaces at low capillary numbers (\leq 10^{-4}). We find that drop charge leads to spontaneous electrowetting, which decreases the contact angles. Additionally, the deposited charges lead to a surface charge effect and decrease the contact angle. Both phenomena compensate each other at the receding contact line, resulting in an insignificant change in the receding contact angle of a sliding drop.
Read the full abstract ▾
All authors Chirag Hinduja, Benjamin Leibauer, Rishi Chaurasia, Nikolaus Knorr, Aaron D. Ratschow, Shalini Singh, Hans-Jürgen Butt, Rüdiger Berger
Geophysics
Scaling laws for rockfall impact fragmentation emerging from diverse lithologies
Alvaro Vergara, Sergio Palma and Raul Fuentes
Impact-induced fragmentation is a fundamental dissipative process in geosciences, yet its
stochastic nature makes predicting debris
evolution a persistent challenge. Here, we introduce a discrete element framework to resolve fragmentation mechanics across a diverse lithological spectrum, from high-strength siliciclastic units to massive carbonates, validated against high-resolution field data from documented rockfall events. Our results reveal that, despite the inherent randomness of impact dynamics, fragment size distributions consistently follow a universal Weibull scaling law, independent of lithology or initial kinetic energy. By applying a relative breakage index, we demonstrate a remarkable collapse of fragmentation data onto a single statistical signature, bridging the gap between grain-scale fracture and macroscopic debris
evolution. We find that this Weibullian signature acts as a proxy for lithological sensitivity, reflecting distinct efficiencies in converting kinetic energy into new fracture surfaces. This framework explicitly resolves the energy partitioning between surviving blocks and comminuted debris, providing a robust predictive link between impact mechanics and structural resilience. From an engineering perspective, our findings enable a shift from idealised single-block impact assumptions toward a realistic assessment of distributed energy in fragmented particle clouds, offering a physical basis for optimising protective galleries and hazard mitigation strategies in complex mountainous terrains.
Read the full abstract ▾
Atmospheric and Oceanic Physics
Addressing the World War 2 Warm Anomaly in HadSST.4.2.0.0
Caroline Sandford and Nick Rayner
We present an update to the Hadley Centre Sea-Surface Temperature
dataset (HadSST.4.2.0.0) that addresses residual warm bias during the Second World War (WW2). Using an existing quantitative definition of the WW2 warm anomaly we identify Engine Room Intake (ERI) bias corrections as the dominant factor in this warm bias in HadSST4, and use this to propose new constraints on ERI bias estimates prior to 1950. In addition, we implement corrections for truncation bias in observations from the Japanese Kobe Collection, spanning the period from 1933 to 1961. We evaluate the effects of these changes with respect to the previous version of HadSST and compare with the most recent iterations of other SST
datasets including ERSSTv6, COBE-SST3 and DCENT. We show that it is possible to remove the WW2 warm anomaly using a physically-based approach that maintains the independence of HadSST from land surface temperature records, and preserves structural diversity within the range of available global SST
datasets.
Read the full abstract ▾
Optics
Synthetic topological device for advancing elastic energy harvesting
Jiamin Guo, Zhongming Gu, Lei Fan et al. (+4 more)
High-efficiency energy harvesting of ultrasonic elastic waves are crucial for powering electric gadgets in many emerging technologies such as wearable devices, wireless sensing, and biomedical implants. Although topological phononic metamaterials have recently been demonstrated as a promising paradigm for confining and guiding elastic waves through robust bound states, achieving ultrahigh-Q topological resonance with enhanced energy conversion efficiency remains a challenge. In this work, we propose a synthetic-dimensional higher-order topological
insulator by engineering the flexural bands of elastic metamaterials, featuring highly localized topological hinge states in the bulk bands. This topological hinge mode stems from the nonzero combination of the bulk polarization and the Chern number in the synthetic-dimensional band structure, thus giving rise to a strong elastic-to-electric energy conversion at the corner of the phononic plate. Through numerical simulations and experimental validations, straightforward evidence of the localized modes with robust protection and consequent abilities in activating the light-emitting diodes (LEDs) array have been demonstrated. Our findings open a new avenue for topological-physics-enabled ultrasonic devices and present promising prospects for applications in weak-signal detection and self-powered sensors.
Read the full abstract ▾
All authors Jiamin Guo, Zhongming Gu, Lei Fan, Jie Liu, Yafeng Chen, Zhongqing Su, Jie Zhu
Medical Physics · Cross-listed from stat.ML
Multiparameter Uncertainty Mapping in Quantitative Molecular MRI using a Physics-Structured Variational Autoencoder (PS-VAE)
Alex Finkelstein, Ron Moneta, Or Zohar et al. (+4 more)
Quantitative imaging methods, such as
magnetic resonance fingerprinting (MRF), aim to extract interpretable pathology biomarkers by estimating biophysical tissue parameters from signal evolutions. However, the pattern-matching
algorithms or neural networks used in such inverse problems often lack principled uncertainty quantification, which limits the trustworthiness and transparency, required for clinical acceptance. Here, we describe a physics-structured variational autoencoder (PS-VAE) designed for rapid extraction of voxelwise multi-parameter posterior distributions. Our approach integrates a differentiable
spin physics simulator with self-supervised learning, and provides a full covariance that captures the inter-parameter correlations of the latent biophysical space. The method was validated in a multi-
proton pool chemical exchange saturation transfer (CEST) and semisolid magnetization transfer (MT) molecular MRF study, across in-vitro phantoms, tumor-bearing mice, healthy human volunteers, and a subject with glioblastoma. The resulting multi-parametric posteriors are in good agreement with those calculated using a brute-force
Bayesian analysis, while providing an orders-of-magnitude acceleration in whole
brain quantification. In addition, we demonstrate how monitoring the multi-parameter posterior dynamics across progressively acquired signals provides practical insights for protocol optimization and may facilitate real-time adaptive acquisition.
Read the full abstract ▾
All authors Alex Finkelstein, Ron Moneta, Or Zohar, Michal Rivlin, Moritz Zaiss, Dinora Friedmann Morvinski, Or Perlman
Physics and Society · Cross-listed from nlin.AO
Emergence and coexistence of periodic and unstructured motion in future-avoiding random walks
A. Schmaus, K. Stiller and N. Molkenthin
Self-avoiding random walks on graphs can be seen as walkers interacting with their own past history. Here, we consider a complementary class of dynamics, mutual future-avoiding random walks (MFARWs), where stochastically driven walkers are avoiding each other's planned future trajectories. Such systems arise naturally in conceptual models of shared mobility. We show that periodic behavior emerges spontaneously in two different MFARWs, and that periodic and unstructured behavior coexist, providing an example of chimera like behavior of nonoscillatory paths on networks. Further, we analytically describe and predict the onset of structure. We find that the transition from unstructured to periodic behavior is driven by a mechanism of self-amplifying coupling to the periodic components of the
stochastic drivers of the system. In the context of shared mobility applications, these states imply a regime of naturally stable coexistence between flexible and line-based public transport.
Read the full abstract ▾
Applied Physics
Physics-Based Learning of the Wave Speed Landscape in Complex Media
Baptiste Hériard-Dubreuil, Emma Brenner, Benjamin Rio et al. (+4 more)
Wave velocity is a key parameter for imaging complex media, but in vivo measurements are typically limited to reflection geometries, where only backscattered waves from short-scale heterogeneities are accessible. As a result, conventional reflection imaging fails to recover large-scale variations of the wave velocity landscape. Here we show that
matrix imaging overcomes this limitation by exploiting the quality of wave focusing as an intrinsic guide
star. We model wave propagation as a trainable multi-layer network that leverages optimization and deep learning tools to infer the wave velocity distribution. We validate this approach through ultrasound experiments on tissue-mimicking phantoms and human breast tissues, demonstrating its potential for tumour detection and characterization. Our method is broadly applicable to any kind of waves and media for which a reflection
matrix can be measured.
Read the full abstract ▾
All authors Baptiste Hériard-Dubreuil, Emma Brenner, Benjamin Rio, William Lambert, Foucauld Chamming's, Mathias Fink, Alexandre Aubry
Physics and Society · Cross-listed from stat.OT
Six-Minute Man Sander Eitrem 5:58.52 – first man below the 6:00.00 barrier
Nils Lid Hjort
In Calgary, November 2005, Chad Hedrick was the first to skate the 5,000 m below 6:10. His world record time 6:09.68 was then beaten a week later, in Salt Lake City, by Sven Kramer's 6:08.78. Further top races and world records followed over the ensuing seasons; up to and including the 2024-2025 season, a total of 126 races have been below 6:10, with Nils van der Poel's 2021 world record being 6:01.56. The appropriately hyped-up canonical question for the friends and followers and aficionados of speedskating has then been when (and by whom we for the first time would witness a below 6:00.00 race. In this note I first use extreme value statistics modelling to assess the state of affairs, as per the end of the 2024-2025 season, with predictions and probabilities for the 2025-2026 season. Under natural modelling assumptions the probability of seeing a new world record during this new season is shown to be about ten percent. We were indeed excited but in reality merely modestly surprised that a race better than van der Poel's record was clocked, by Timothy Loubineaud, in Salt Lake City, November 14, 2025. But Six-Minute Man Sander Eitrem's outstanding 5:58.52 in Inzell, on January 24, 2026, is truly beamonesquely shocking. I also use the modelling machinery to analyse the post-Eitrem situation, and suggest answers to the question of how fast the 5,000 m ever can be skated.
Read the full abstract ▾
Instrumentation and Detectors
Production of GEM-like structures for cryogenic applications, using laser-cutting techniques
D. Rodas-Rodríguez, A. F. V. Cortez, M. Kuźniak et al. (+16 more)
A novel concept for electroluminescence (EL) structures was recently proposed. In it, a wavelength-shifting material is deposited inside the holes of GEM-like structures which, after suitable optical treatment of its electrodes, improves the light collection and detection efficiency in noble gas TPCs. This new development directly addresses problems related with the scalability of future dual-phase TPCs for rare-event searches, matching (and potentially exceeding) the performance of conventional EL techniques. We report the newest developments on the production of such structures using
laser-based techniques, namely the manufacture of a first batch of the so-called FAT-GEMs. This process allows low-cost and reproducible manufacturing of a high volume of such structures. In addition to the detailed description of the production, we present a performance assessment in pure argon, at a gas density close to the one expected in LAr conditions. An energy resolution of 23.5$\pm$1~% (FWHM) at 5.9~keV was obtained, indicating a consistent improvement over previous batch. The optical treatment of the electrode surfaces has been greatly simplified and modestly improved, while charging-up effects arising from the use of laminates eliminated.
Read the full abstract ▾
All authors D. Rodas-Rodríguez, A. F. V. Cortez, M. Kuźniak, D. González-Díaz, P. A. O. C. Silva, A. Gnat, G. Nieradka, T. Sworobowicz, E. Alario, C. D. R. Azevedo, K. T. Floethner, P. Gasik, J. Llerena, C. M. B. Monteiro, R. Oliveira, A. Pallas, D. Tenreiro, V. Peskov, J. M. F. dos Santos
Accelerator Physics
Computational Tools in EN-MME: Implicit and Explicit Finite-Element Simulations
Federico Carra, Giuditta Coladonato, Audrey Piccini et al. (+2 more)
This paper recalls the principles of the finite-element methods (FEM) theory and declines its application in the EN-MME group, for the numerical modelling and study of particle accelerator equipment. Implicit and explicit methods are compared, and practical examples of their use are given.
Read the full abstract ▾
All authors Federico Carra, Giuditta Coladonato, Audrey Piccini, Joanna Sylwia Swieszek, Nikolina Vejnovic
Physics and Society · Cross-listed from cs.SI
Link Fraction Mixed Membership Reveals Community Diversity in Aggregated Social Networks
Gamal Adel, Eszter Bokányi, Eelke M. Heemskerk et al. (+1 more)
Community detection is a critical tool for understanding the mesoscopic structure of large-scale networks. However, when applied to aggregated or coarse-grained social networks, disjoint community partitions cannot capture the diverse composition of community memberships within aggregated nodes. While existing mixed membership methods alleviate this issue, they may detect communities that are highly sensitive to the aggregation resolution, not reliably reflecting the community structure of the underlying individual-level network. This paper presents the Link Fraction Mixed Membership (LFMM) method, which computes the mixed memberships of nodes in aggregated networks. Unlike existing mixed membership methods, LFMM is consistent under aggregation. Specifically, we show that it conserves community membership sums at different scales. The method is utilized to study a population-scale social network of the Netherlands, aggregated at different resolutions. Experiments reveal variation in community membership across different geographical regions and
evolution over the last decade. In particular, we show how our method identifies large urban hubs that act as the melting pots of diverse, spatially remote communities.
Read the full abstract ▾
All authors Gamal Adel, Eszter Bokányi, Eelke M. Heemskerk, Frank W. Takes
Optics
Pushing and Pulling Ponderomotive Forces in Wavepackets and Beat Waves
Yury Bliokh
We consider ponderomotive forces acting on small particles in propagating wave packets (pulses). Specifically, we analyze simple point particles as well as composite dipole and dumbbell particles in the fields of forward-propagating (parallel phase and group velocities) and backward-propagating (antiparallel phase and group velocities) wave packets. Depending on the characteristics of the wave packet, particles may be pushed away from the wave source or pulled toward it. We also examine particle dynamics in the field of a beat wave generated by two forward-propagating waves with slightly different frequencies. Such a beat wave can emulate a periodic sequence of either forward- or backward-propagating pulses. In particular, this provides a simple mechanism for realizing pulling forces as employed in optical and acoustic `tractor beams'.
Read the full abstract ▾
Applied Physics · Cross-listed from cs.RO
A thin and soft optical tactile sensor for highly sensitive object perception
Yanchen Shen, Kohei Tsuji, Haruto Koizumi et al. (+7 more)
Tactile sensing is crucial in robotics and wearable devices for safe perception and interaction with the environment. Optical tactile sensors have emerged as promising solutions, as they are immune to electromagnetic interference and have high spatial resolution. However, existing optical approaches, particularly
vision-based tactile sensors, rely on complex optical assemblies that involve lenses and cameras, resulting in bulky, rigid, and
alignment-sensitive designs. In this study, we present a thin, compact, and soft optical tactile sensor featuring an
alignment-free configuration. The soft optical sensor operates by capturing deformation-induced changes in speckle patterns generated within a soft silicone material, thereby enabling precise force measurements and texture recognition via machine learning. The experimental results show a root-mean-square error of 40 mN in the force measurement and a classification accuracy of 93.33% over nine classes of textured surfaces, including Mahjong tiles. The proposed speckle-based approach provides a compact, easily fabricated, and mechanically compliant platform that bridges optical sensing with flexible shape-adaptive architectures, thereby demonstrating its potential as a novel tactile-sensing paradigm for soft robotics and wearable haptic interfaces.
Read the full abstract ▾
All authors Yanchen Shen, Kohei Tsuji, Haruto Koizumi, Jiseon Hong, Tomoaki Niiyama, Hiroyuki Kuwabara, Hayato Ishida, Jun Hiramitsu, Mitsuhito Mase, Satoshi Sunada
History and Philosophy of Physics
Does classical thermodynamics need a third law? Securing the second law at absolute zero
José-María Martín-Olalla
This paper elaborates on the implications of the relationship between the Second and Third Laws and provides a comprehensive formal and historical justification for the logical redundancy of the Nernst heat
theorem. By revisiting the Nernst-Einstein debate, the underlying hypotheses that lead to the traditional view of the Third Law as an independent postulate are examined. It is argued that the historical rejection of Nernst's proof – motivated by Einstein's insistence on the practical non-performability of cycles at absolute zero – overlooks the fact that a universal Second Law already precludes such cycles, rendering an independent Third Law an unnecessary complexity. Ultimately, the Nernst
theorem is shown to be an essential consistency regulator rather than an independent physical discovery.
Read the full abstract ▾
Optics
Generalized Time-Varying Drude Model for Dispersive and Lossy Modulations
Antonio Ganfornina-Andrades, J. Enrique Vázquez-Lozano, Iñigo Liberal et al. (+1 more)
We develop a generalization of the time-varying Drude model, treating carrier density, effective mass, and collision rate as explicit functions of time. We derive expressions for polarization, susceptibility, displacement, and permittivity in different domains. Our analysis reveals that non-adiabatic modulations and time-dependent losses induce rich and distinct behaviors, leading to temporal blurring, selective gating and suppression, and low-frequency spectral reshaping. Besides underpinning and upgrading the current framework on photonics of time-varying media, this model may be useful in the design and fitting theoretical models with experimental realizations.
Read the full abstract ▾
All authors Antonio Ganfornina-Andrades, J. Enrique Vázquez-Lozano, Iñigo Liberal, S. A. R. Horsley
Atomic Physics · Cross-listed from cond-mat.quant-gas
Tuning interactions between static-field-shielded polar molecules with microwaves
Christopher J. Ho, Joy Dutta, Bijit Mukherjee et al. (+2 more)
The ability to tune interparticle interactions is one of the main advantages of using ultracold
quantum gases for
quantum simulation of many-body physics. Current experiments with ultracold polar molecules employ shielding with microwave or static electric fields to prevent destructive collisional losses. The interaction potential of microwave-shielded molecules can be tuned by using microwaves of two different polarisations, while for static-field-shielded molecules the tunability of interactions is more limited and depends on the particular species. In this work, we propose a general method to tune the interactions between static-field-shielded molecules by applying a microwave field. We carry out coupled-channel scattering calculations in a field-dressed basis set to determine loss rate coefficients and scattering lengths. We find that both the s-wave scattering length and the dipole length can be widely tuned by changing the parameters of the microwave field, while maintaining strong suppression of lossy collisions.
Read the full abstract ▾
All authors Christopher J. Ho, Joy Dutta, Bijit Mukherjee, Jeremy M. Hutson, Michael R. Tarbutt
Optics
Quantum Trajectory Separation and Attosecond Mapping in Liquid High-Harmonic Generation
Wanchen Tao, Ruisi Zhang, Qihe Guo et al. (+5 more)
High-harmonic generation (HHG) from
liquids offers a potential pathway to attosecond spectroscopy in chemically complex and disordered environments, yet fundamental questions remain open: whether
liquid harmonic emission preserves well-defined attosecond synchronization, and whether harmonic emission can involve simultaneous contributions from multiple
quantum trajectories with distinct excursion times despite strong disorder and scattering. Here, we address these issues experimentally by resolving the trajectory-dependent temporal structure of
liquid HHG. By optimizing the
laser focusing geometry, we achieve clear spatial discrimination of short- and long-trajectory contributions, providing direct evidence for the existence of multiple
quantum trajectories in
liquids. Using a phase-controlled two-color driving field, we independently retrieve the attochirp associated with each trajectory and demonstrate opposite energy-time correlations for short and long trajectories, establishing a trajectory-resolved energy-time mapping in
liquid HHG. All observations are well reproduced by semiclassical recollision simulations. These results place
liquid HHG on the same conceptual footing as gas- and solid-phase HHG and establish a robust foundation for attosecond-resolved spectroscopy of ultrafast electronic and chemical dynamics in
liquid environments.
Read the full abstract ▾
All authors Wanchen Tao, Ruisi Zhang, Qihe Guo, Lixin He, Tao-Yuan Du, Xingdong Guan, Pengfei Lan, Peixiang Lu
Optics
Single acquisition reconstruction of nonlinear susceptibility and Raman tensors at the diffraction limit
Volodymyr Multian, Luigi Bonacina and Jérémie Teyssier
Raman spectroscopy and Second Harmonic Generation (SHG) are complementary, non-destructive techniques that provide rich and distinct insights into the structural and electronic properties of materials. Raman spectroscopy offers detailed information on vibrational modes, phase transitions, temperature, and local stress, while SHG is highly sensitive to
symmetry and orientation, particularly in non-centrosymmetric structures. In this work, in addition to combining both techniques, we propose a novel approach to determine the nonlinear optical tensor, leveraging the spatial and ultra-fast temporal offset of a Bessel-Gaussian
laser beam at the microscope's focal point.
Read the full abstract ▾