Instrumentation and Detectors
Systematic study of high performance GeSn photodiodes with thick absorber for SWIR and extended SWIR detection
Quang Minh Thai, Rajesh Kumar, Abdulla Said Ali et al. (+13 more)
Germanium-tin (GeSn) photodiodes potentiate a viable solution to integrate SWIR and extended SWIR detection technology into CMOS processing line. However, challenges in the growth of thick, high quality GeSn limit the device absorber thickness, making it impossible to ascertain the performance limit of GeSn photodiodes. An in-depth understanding of their device physics and a clear optimization pathway towards commercial-grade devices remain elusive. This work presents a systematic empirical study of GeSn photodiodes with thick absorber (2 to 8% Sn content, up to 2630 nm thick), showing high responsivity up to 0.59 A.W-1 at 1.55 {\mu}m and 0.43 A.W-1 at 2 {\mu}m wavelengths, low dark current density down to 2 x 10-2 A.cm-2, and high detection cutoff wavelengths up to 2.1 and 2.5 {\mu}m at 5% and 8% Sn, respectively. Using specific doping design (P-i-N and N-i-P), an in-depth analysis is presented on the impact of junction position, p-type background carrier concentration, bulk/ surface defects and photocarrier
diffusion length - on photodetection performance. Different optimization strategies for GeSn photodiodes, in particular at high Sn content, are proposed.
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All authors Quang Minh Thai, Rajesh Kumar, Abdulla Said Ali, Justin Rudie, Steven Akwabli, Yunsheng Qiu, Mourad Benamara, Hryhorii Stanchu, Kushal Dahal, Xuehuan Ma, Sudip Acharya, Chun-Chieh Chang, Gregory T. Forcherio, Bruce Claflin, Wei Du, Shui-Qing Yu
Physics Education
Do we have a quantum computer? Expert perspectives on current status and future prospects
Liam Doyle, Fargol Seifollahi and Chandralekha Singh
The rapid growth of
quantum information science and technology (QIST) in the 21st century has created both excitement and uncertainty about the field's trajectory. This qualitative study presents perspectives from leading
quantum researchers, who are educators, on fundamental questions frequently posed by students, the public, and the media regarding QIST. Through in-depth interviews, we explored several issues related to QIST including the following key areas: the current state of
quantum computing in the noisy intermediate-scale
quantum (NISQ) era and timelines for fault-tolerant
quantum computers, the feasibility of personal
quantum computers in our pockets, and promising
qubit architectures for future development. Our findings reveal diverse yet convergent perspectives on these issues. While experts agree that the current machines with physical
qubits that are being built currently should be called
quantum computers, most estimated that it will take a decade to build a small fault-tolerant
quantum computer, and several decades to achieve scalable systems capable of running Shor's factoring
algorithm with
quantum advantage. Regarding carrying a
quantum computer in the pocket, experts viewed
quantum computers as specialized tools that will remain in central locations such as data centers and can be accessed remotely for applications for which they are particularly effective compared to classical computers.
Quantum researchers suggested that multiple platforms show promise, with no clear winner emerging. These insights provide valuable guidance for educators, policymakers, and the broader community in establishing realistic expectations for developments in this exciting field. Our findings can provide valuable information for educators to clarify student doubts about these important yet confusing issues related to
quantum technologies.
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Optics · Cross-listed from quant-ph
Near-Infrared and Telecommunication-Wavelength Photon-Pair Source in Optical Fiber
Keshav Kapoor, Dong Beom Kim, Kriti Shetty et al. (+1 more)
We present a
photon-pair source in commercially available optical fiber that produces paired
photons at telecommunication and near-infrared (NIR) wavelengths. The highly nondegenerate pairs are 700 nm apart: one in the 1500 nm E- and S-band telecommunication range and the other in the 830 nm NIR range. The high non-degeneracy means the
photon pairs are far-detuned from Raman noise, resulting in a high coincidence-to-accidental ratio even while operating at room temperature. The source produces two spectrally and spatially distinct phase-matched processes with low spectral cross-talk, distinct transverse spatial modes in the NIR, and a single fundamental spatial mode in the telecommunication range. The source's room-temperature operation, off-the-shelf materials, and multiplexing potential make it promising for deployment in
quantum networks.
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All authors Keshav Kapoor, Dong Beom Kim, Kriti Shetty, Virginia O. Lorenz
Accelerator Physics
Basics of RF Electronics
Amos Christopher Dexter
The focus of this educational text is selected examples of high-frequency electronic
circuits and their components employed for the accurate phasing and synchronisation of accelerator cavities. Examples have been chosen to describe the basics of RF electronics. The starting point is transmission lines, connectors, discontinuities, and the handling of reflection. The application of simple surface mount components is discussed. The use of the Kuroda identities for converting lumped
circuit designs to printed
circuit designs is demonstrated. The accelerator example used to demonstrate the use of components is a
circuit designed for the synchronisation of the CLIC crab cavities. This example employs co-planar waveguide, SMA connectors, Wilkinson splitters, and surface-mount double-balanced mixers. For the control of cavity phase and amplitude, the benefit of I&Q controllers will be explained. The text will then discuss the operation and use of I&Q modulators and VCOs.
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Fluid Dynamics
Time-resolved X-ray radiography of through-thickness liquid transport in partly saturated needle-punched nonwovens
Patrick Wegele, Zisheng Yao, Jonas Tejbo et al. (+7 more)
Nonwoven fibre networks underpin filtration, insulation and geotextiles, where
liquid uptake, redistribution and release govern performance. In needle-punched felts, barbed needles mechanically entangle fibres and partially reorient them toward the thickness direction ($z$), creating out-of-plane "pillars" and heterogeneity. While mechanical and structural consequences of needling are well documented, dynamic $z$-direction transport in partly saturated networks remains difficult to access due to opacity and sub-second timescales. Here we combine micro-CT ($\mu$CT) of dry structure with time-resolved X-ray radiography during droplet addition to quantify through-thickness transport as a function of saturation and needling intensity, using a compact Washburn-type descriptor for dynamics. Results show an exponential dependence of $z$-directional
liquid transport on saturation, consistent with previous models for in-plane relative permeability of nonwoven networks. Additionally, increased needle-punch intensity reorients fibres toward the $z$-direction, forming preferential flow pathways that enhance through-thickness transport, even as single-phase permeability decreases. These findings underscore needle-punch as a key design parameter for tuning
liquid transport in nonwoven fibre networks. The approach provides an experimental and modelling framework for dynamic, capillarity-driven transport in opaque fibrous materials.
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All authors Patrick Wegele, Zisheng Yao, Jonas Tejbo, Julia K. Rogalinski, Tomas Rosén, Alexander Groetsch, Kim Nygård, Eleni Myrto Asimakopoulou, Pablo Villanueva-Perez, L. Daniel Söderberg
Medical Physics · Cross-listed from eess.SP
Large elements and advanced beamformers for increased field of view in 2-D ultrasound matrix arrays
Mick Gardner and Michael L. Oelze
Three-dimensional (3D) ultrasound promises various medical applications for abdominal, obstetrics, and breast imaging. However, ultrasound
matrix arrays have extremely high element counts limiting their field of view (FOV). Current reduced element count architectures, such as row-column arrays, diverging lenses, or sparse arrays, suffer from limited resolution and high side- and grating-lobe levels. This work seeks to demonstrate an increased field-of-view using a reduced element count array design. The approach is to increase the element size and use advanced beamformers to maintain image quality. The delay and sum (DAS), Null Subtraction Imaging (NSI), directional coherence factor (DCF), and Minimum Variance (MV) beamformers were compared. K-wave simulations of the 3D point-spread functions (PSF) of NSI, DCF, and MV display reduced side lobes and narrowed main lobes compared to DAS. Experiments were conducted using a multiplexed 1024-element
matrix array on a Verasonics 256 system. Elements were electronically coupled to imitate a larger pitch and element size. Then, a virtual large aperture was created by using a positioning system to collect data in sections with the
matrix array. Resolution and contrast was also assessed on a rabbit liver in vivo. Resolution was maintained using coupling numbers up to four, doubling the FOV while reducing the element count. The NSI and DCF beamformers demonstrated the best resolution performance in simulations, in a phantom with the virtual aperture, and in vivo on a rabbit liver. Our results demonstrate how larger
matrix arrays could be constructed with larger elements, with resolution maintained by advanced beamformers.
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Fluid Dynamics · Cross-listed from math.AP
Multi-Sink Solutions to the Self-Similar Euler Equations
Hyungjun Choi and Matei P. Coiculescu
We construct examples and provide a classification of self-similar solutions to the two-dimensional incompressible Euler equations whose pseudo-velocity fields possess more than one stagnation point. These solutions are also homogeneous steady states of the Euler equations. In contrast, we prove that any homogeneous self-similar solution with bounded vorticity away from the origin necessarily admits only a single stagnation point, located at the origin. The solutions we construct develop velocity cusps along rays from the origin, and this allows for additional stagnation points of the pseudo-velocity field.
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Fluid Dynamics
Mohammad-Reza Alam
The brachistochrone, the curve of fastest descent under
gravity, is a cycloid when friction is absent.
Underwater, however, buoyancy, viscous drag, and the added mass of entrained fluid fundamentally alter the problem. We formulate and solve the brachistochrone for a body moving through a dense fluid, incorporating all three effects together with a Reynolds-number-dependent drag coefficient. The classical cycloid becomes increasingly suboptimal as the body density approaches the fluid density, and below a critical density ratio it fails to reach the endpoint altogether. Near the critical Reynolds number for the drag crisis, the optimal trajectory is acutely sensitive to the density ratio and object size; constant-drag approximations can yield qualitatively incorrect paths. A decomposition of physical effects shows that neglecting drag and added mass together yields a predicted transit time roughly half the realised minimum, and that omitting added mass alone underestimates the transit time by approximately 20%. We extend the formulation to a three-point brachistochrone in which the trajectory must pass through an intermediate waypoint, revealing a finite reachable domain that is absent in the classical problem. The
underwater brachistochrone as presented here provides a simple planning tool for short-range trajectories of buoyancy-driven
underwater vehicles.
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Computational Physics
Code-Verification Techniques for Particle-in-Cell Simulations with Direct Simulation Monte Carlo Collisions
Brian A. Freno, William J. McDoniel, Christopher H. Moore et al. (+1 more)
Particle-in-
cell methods with
stochastic collision models are commonly used to simulate collisional
plasma dynamics, with applications ranging from hypersonic flight to
semiconductor manufacturing. Code verification of such methods is challenging due to the interaction between the spatial- and temporal-discretization errors, the statistical sampling noise, and the
stochastic nature of the collision
algorithm. In this paper, we introduce our code-verification approaches to apply the method of manufactured solutions to
plasma dynamics, and we derive expected convergence rates for the different sources of discretization and statistical error. For the particles, we incorporate the method of manufactured solutions into the equations of motion. We manufacture the particle distribution function and inversely query the cumulative distribution function to obtain known particle positions and velocities at each time step. In doing so, we avoid modifying the particle weights, eliminating risks from potentially negative weights or modifications to weight-dependent collision
algorithms. For the collision
algorithm, we average independent outcomes at each time step and we derive a corresponding manufactured source term for the velocity change for each particle. By having known solutions for the particle positions and velocities, we are able to compute the error in these quantities directly instead of attempting to compute differences in distribution functions. These approaches are equally valid for particle-in-
cell simulations with Monte Carlo collisions and direct simulation Monte Carlo simulations of neutral gas flows. We demonstrate the effectiveness of our approaches in three dimensions for different couplings between the particles and field, with and without binary elastic collisions, and with and without coding errors.
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All authors Brian A. Freno, William J. McDoniel, Christopher H. Moore, Neil R. Matula
Chemical Physics
A CPD-enabled low-scaling environment solver in a coupled cluster based static quantum embedding theory
Karl Pierce, Muhammad Talha Aziz, Avijit Shee et al. (+1 more)
We incorporate a canonical polyadic decomposition (CPD) based low-level solver as a means to accelerate the environment-level solver for the recently developed MPCC
embedding framework. Using CPD, we both factorize the three dominant order-three density-fitting two-electron integral (DF TEI) tensors and develop a novel formulation that reduces the storage complexity of the low-level solver from ${O}(N^3)$ to $O(NR)$, where $R$ is the CPD rank, and the computational scaling of the most time-consuming contractions from ${O}(N^4)$ to ${O}(NR^2)$. We provide
benchmarks on representative chemical environments, namely water clusters $\mathrm{{(H_2O)_n}}$ with $n = 1$ to $6$ and linear alkane chains $\mathrm{{C_nH_{2n+2}}}$ with $n = 1$ to $6$. For both test sets, using the CPD-compressed DF TEI tensors reproduces the DF reference convergence behavior of the low-level solver, the subsequent high-level step, and the fully self-consistent MPCC iterations, while introducing only small, rank-controlled shifts in absolute energies. At a fixed tolerance in the absolute MPCC energy, the CP ranks required for these tensor approximations increase linearly with system size. Chemically relevant energy differences are likewise preserved, as demonstrated for water-cluster dissociation energies and in a proof-of-concept
embedding calculation of methane in a four-water cluster.
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All authors Karl Pierce, Muhammad Talha Aziz, Avijit Shee, Fabian M. Faulstich
Biological Physics
Bringing calorimetry (back) to life
Faezeh Khodabandehlou, Christian Maes and Édgar Roldán
Micro-calorimetry offers significant potential as a quantitative method for studying the structure and function of biological systems, for instance, by probing the excess heat released by cellular or sub-cellular structures, isothermal or not, when external parameters change. We present the conceptual framework of nonequilibrium calorimetry, and as illustrations, we compute the heat capacity of biophysical models with few degrees of freedom related to ciliar motion (rowing model) and molecular motor motion (flashing ratchets). Our quantitative predictions reveal intriguing dependencies of the (nonequilibrium) heat capacity as a function of relevant biophysical parameters, which can even take negative values as a result of biological activity.
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Instrumentation and Detectors
Real-time graph neural networks on FPGAs for the Belle II electromagnetic calorimeter
I. Haide, M. Neu, Y. Unno et al. (+19 more)
We present the development and evaluation of a real-time Graph Neural Network-based trigger module for the electromagnetic calorimeter of the Belle~II experiment at the SuperKEKB
collider. The
algorithm processes calorimeter trigger
cells as graph nodes to perform clustering, feature extraction, and per-cluster signal classification with deterministic latency. The model predicts cluster positions and energies and provides a signal classification score, enabling a more flexible clustering strategy than the baseline trigger
algorithm. Implemented on an FPGA and integrated into the Belle~II trigger readout infrastructure for synchronous operation, the system sustains the MHz trigger throughput with an end-to-end latency of $3.168\,\mu$s. The performance is evaluated on simulated events and collision data. The energy resolution is comparable to the baseline trigger, while the position resolution for high-energy clusters improves by up to 18% in the central detector region. Cluster purity increases by up to 20% at low energies for isolated clusters, and cluster efficiency improves by up to 20% for overlapping clusters. The signal classifier enables additional background suppression at fixed signal retention. These results demonstrate a first step towards GNN-based real-time reconstruction on FPGAs in a
collider trigger. While the end-to-end latency exceeds the trigger decision budget, the system already sustains full operational conditions with 100% uptime.
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All authors I. Haide, M. Neu, Y. Unno, T. Justinger, V. Dajaku, F. Baptist, T. Lobmaier, J. Becker, T. Ferber, H. Bae, A. Beaubien, J. Eppelt, R. Giordano, G. Heine, T. Koga, Y.-T. Lai, K. Miyabayashi, H. Nakazawa, M. Remnev, L. Reuter, K. Unger, R. van Tonder
Atmospheric and Oceanic Physics
IT-DPC-SRI: A Cloud-Optimized Archive of Italian Radar Precipitation (2010-2025)
Gabriele Franch, Elena Tomasi, Uladzislau Azhel et al. (+11 more)
We present IT-DPC-SRI, the first publicly available long-term archive of Italian weather radar precipitation estimates, spanning 16 years (2010–2025). The
dataset contains Surface Rainfall Intensity (SRI) observations from the Italian Civil Protection Department's national radar mosaic, harmonized into a coherent Analysis-Ready Cloud-Optimized (ARCO) Zarr datacube. The archive comprises over one million timesteps at temporal resolutions from 15 to 5 minutes, covering a $1200\times1400$ kilometer domain at 1 kilometer spatial resolution, compressed from 7TB to 51GB on disk. We address the historical fragmentation of Italian radar data - previously scattered across heterogeneous formats (OPERA BUFR, HDF5, GeoTIFF) with varying spatial domains and projections - by reprocessing the entire record into a unified store. The
dataset is accessible as a static versioned snapshot on Zenodo, via cloud-native access on the ECMWF European Weather Cloud, and as a continuously updated live version on the ArcoDataHub platform. This release fills a significant gap in European radar data availability, as Italy does not participate in the EUMETNET OPERA pan-European radar composite. The
dataset is released under a CC BY-SA 4.0 license.
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All authors Gabriele Franch, Elena Tomasi, Uladzislau Azhel, Giacomo Tomezzoli, Alessandro Camilletti, Virginia Poli, Renata Pelosini, Gianfranco Vulpiani, Gabriella Scipione, Giuseppe Trotta, Matteo Angelinelli, Leif Denby, Irene Livia Kruse, Marco Cristoforetti
Physics and Society · Cross-listed from astro-ph.IM
Well-being and career instability across genders in the Spanish Astronomical Society
Maritza A. Lara-Lopez, I. Rebollido, A. Vidal-Garcia et al. (+9 more)
We present the results of a comprehensive survey conducted among members of the Spanish Astronomical Society (Sociedad Espanola de Astronomia, SEA) to assess well-being, professional satisfaction, and family-work balance of researchers in astronomy. The survey addressed multiple aspects of professional life, including happiness, career stability, publication pressure, and access to childcare services during scientific meetings. Responses were examined across gender and career stages to identify trends and sources of dissatisfaction.
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All authors Maritza A. Lara-Lopez, I. Rebollido, A. Vidal-Garcia, A. Rouco Escorial, S. Berlanas, I. Garcia-Bernete, B. Agis-Gonzalez, M. Rodriguez-Baras, N. Barrado-Izagirre, I. Pintos Castro, N. Ospina, S. Bonoli
Plasma Physics
TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics
Tobia Boschi, Andrea Loreti, Nicola C. Amorisco et al. (+13 more)
We present TokaMind, to our knowledge the first open-source foundation model for tokamak
plasma dynamics, based on a Multi-Modal
Transformer (MMT) and pretrained on heterogeneous diagnostics from the publicly available MAST
dataset. TokaMind supports multiple data modalities (time-series, 2D profiles, and
videos) with different sampling rates, robust missing-signal handling, and efficient task adaptation via selectively loading and freezing four model components. To represent multi-modal signals, we use a lightweight fixed-basis Discrete Cosine Transform
embedding (DCT3D) and provide a clean interface for alternative
embeddings (e.g., Variational Autoencoders). We evaluate TokaMind on the recently introduced MAST
benchmark TokaMark, which comprises 14 tasks with heterogeneous reconstruction and
forecasting objectives. Our results show that fine-tuned TokaMind outperforms the strongest
benchmark baseline on all but one task. Compared with training the same architecture from scratch under a matched epoch budget, warm-start adaptation is most beneficial on demanding downstream settings, including long-horizon
forecasting and high-dimensional
equilibrium objectives. These findings highlight the value of multi-modal pretraining for tokamak
plasma dynamics and provide a practical, extensible foundation for future fusion modeling tasks. Training code and model weights are publicly available at github.com/UKAEA-IBM-STFC-Fusion-FMs/tokamind and huggingface.co/UKAEA-IBM-STFC, respectively.
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All authors Tobia Boschi, Andrea Loreti, Nicola C. Amorisco, Rodrigo H. Ordonez-Hurtado, Cécile Rousseau, George K. Holt, Eszter Székely, Alexander Whittle, Samuel Jackson, Adriano Agnello, Stanislas Pamela, Alessandra Pascale, Robert Akers, Juan Bernabe Moreno, Vassil Alexandrov, Mykhaylo Zayats
Atmospheric and Oceanic Physics · Cross-listed from cs.LG
PDE foundation models are skillful AI weather emulators for the Martian atmosphere
Johannes Schmude, Sujit Roy, Liping Wang et al. (+10 more)
We show that AI foundation models that are pretrained on numerical solutions to a diverse corpus of partial differential equations can be adapted and fine-tuned to obtain skillful predictive weather emulators for the Martian atmosphere. We base our work on the Poseidon PDE foundation model for two-dimensional systems. We develop a method to extend Poseidon from two to three dimensions while keeping the pretraining information. Moreover, we investigate the performance of the model in the presence of sparse initial conditions. Our results make use of four Martian years (approx.~34 GB) of training data and a median compute budget of 13 GPU hours. We find that the combination of pretraining and model extension yields a performance increase of 34.4% on a held-out year. This shows that PDEs-FMs can not only approximate solutions to (other) PDEs but also anchor models for real-world problems with complex interactions that lack a sufficient amount of training data or a suitable compute budget.
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All authors Johannes Schmude, Sujit Roy, Liping Wang, Theodore van Kessel, Levente Klein, Marcus Freitag, Eloisa Bentivegna, Robert Manson-Sawko, Bjorn Lutjens, Manil Maskey, Campbell Watson, Rahul Ramachandran, Juan Bernabe-Moreno
Optics · Cross-listed from quant-ph
Rotational Quantum Friction via Spontaneous Decay
Nicolas Schüler, O. J. Franca, Michael Vaz et al. (+2 more)
A fascinating effect belonging to the field of
vacuum forces and fluctuations is that of
quantum friction. It refers to the prediction of a dissipative force acting on a moving object due to the
quantum vacuum field. In this work, we investigate rotational
quantum friction where a diatomic polar molecule rotates around its own center of mass in free space. We quantize the rotational motion and investigate the resulting dissipation due to spontaneous decay. We find in the Markovian regime that a friction torque $\propto \Omega^3$ persists even for zero temperature, and in agreement with the classical result in the limit of large rotational
quantum number $l$. Within the non-Markovian short-time regime we find a friction $\propto\Omega$.
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All authors Nicolas Schüler, O. J. Franca, Michael Vaz, Hervé Bercegol, Stefan Yoshi Buhmann
Atomic Physics
Multielectron ionization in O$_2^+$ driven by intense infrared laser pulses
Georgios Petros Katsoulis and Agapi Emmanouilidou
We extend a recently developed three-dimensional semiclassical model [\href{https://journals.aps.org/pra/abstract/10.1103/PhysRevA.109.033106}{Phys. Rev. A 109, 033106 (2024)}] to study multielectron ionization and the formation of highly excited Rydberg states in O$_{2}^+$ driven by intense infrared
laser pulses. Our model fully accounts for the Coulomb interaction between all particles, except for the Coulomb repulsion between bound electrons which is replaced by effective potentials. This replacement overcomes the hurdle of artificial autoinization. In addition, the multielectron motion is treated on an equal footing with
nuclear motion, that is, electrons and
nuclei are both allowed to move at the same time. We focus on triple and double ionization as well as frustrated triple and double ionization. For these processes, we identify and explain the main features of the sum of the kinetic energies of the final ion fragments resulting from the break-up of O$_{2}^+$. We also describe a physical mechanism that underlies frustrated triple ionization.
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Atomic Physics
Sub-part-per-trillion test of the Standard Model with atomic hydrogen
Lothar Maisenbacher, Vitaly Wirthl, Arthur Matveev et al. (+4 more)
Quantum electrodynamics (QED), the first relativistic
quantum field theory, describes light-matter interactions at a fundamental level and is one of the pillars of the Standard Model (SM). Through the extraordinary precision of QED, the SM predicts the energy levels of simple systems such as the hydrogen atom with up to 13 significant digits, making hydrogen spectroscopy an ideal test bed. The consistency of physical constants extracted from different transitions in hydrogen using QED, such as the
proton charge radius $r_\mathrm{p}$, constitutes a test of the theory. However, values of $r_\mathrm{p}$ from recent measurements of atomic hydrogen are partly discrepant with each other and with a more precise value from spectroscopy of muonic hydrogen. This prevents a test of QED at the level of experimental uncertainties. Here we present a measurement of the 2S-6P transition in atomic hydrogen with sufficient precision to distinguish between the discrepant values of $r_\mathrm{p}$ and enable rigorous testing of QED and the SM overall. Our result $\nu^{}_{\text{2S-6P}}$ = 730,690,248,610.79(48) kHz gives a value of $r_\mathrm{p}$ = 0.8406(15) fm at least 2.5-fold more precise than from other atomic hydrogen determinations and in excellent agreement with the muonic value. The SM prediction of the transition frequency (730,690,248,610.79(23) kHz) is in excellent agreement with our result, testing the SM to 0.7 parts per trillion (ppt) and, specifically, bound-state QED corrections to 0.5 parts per million (ppm), their most precise test so far.
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All authors Lothar Maisenbacher, Vitaly Wirthl, Arthur Matveev, Alexey Grinin, Randolf Pohl, Theodor W. Hänsch, Thomas Udem
Chemical Physics
Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces
Nicolaï Gouraud, Côme Cattin, Thomas Plé et al. (+3 more)
Following our previous work (J. Phys. Chem. Lett., 2026, 17, 5, 1288-1295), we propose the DMTS-NC approach, a distilled multi-time-step (DMTS) strategy using non-conservative (NC) forces to further accelerate atomistic molecular dynamics simulations using foundation neural network models such as FeNNix-Bio1. There, a dual-level reversible reference system propagator
algorithm (RESPA) formalism couples a target accurate conservative potential to a simplified distilled representation optimized for the production of non-conservative forces. Despite being non-conservative, the distilled architecture is designed to enforce key physical priors, such as equivariance under rotation and cancellation of atomic force components. These choices facilitate the
distillation process and therefore improve drastically the robustness of simulation, significantly limiting abnormal discrepancies between the two models, thus achieving excellent agreement with the forces data. Overall, the DMTS-NC scheme is found to be more stable and efficient than its conservative counterpart with additional speedups reaching 15-30% over DMTS. Requiring no fine-tuning steps, it is easier to implement and can be pushed to the limit of the systems physical resonances to maintain accuracy while providing maximum efficiency. We obtain additional speedup by combining hydrogen mass repartitioning (HMR), High Hydrogen Friction (HHF) to further extended the largest timestep up to 10fs of our schemes while conserving stability and accuracy. As for DMTS, DMTS-NC is applicable to any neural network potential and can be applied to approaches that are computationally heavier than FeNNix-Bio1. We show a proof of principle applying the approach to the
distillation of MACE-OFF23 with consequent speedups ranging from 3.66 to 5.64 compared to single timestep.
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All authors Nicolaï Gouraud, Côme Cattin, Thomas Plé, Olivier Adjoua, Louis Lagardère, Jean-Philip Piquemal
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Practical and accurate density functionals for transition-metal heterogeneous catalysis
Benjamin X. Shi and Timothy C. Berkelbach
Density functional theory (DFT) underpins modern atomistic simulations of transition-metal surfaces. It can predict key properties linked to catalytic performance, such as adsorption energies and barrier heights, enabling new paradigms in rational catalyst design. These applications require reliable density functionals, however achieving transition-metal chemical accuracy (13 kJ/mol) on these properties remains challenging. We introduce a framework for designing new functionals tailored to catalytic processes on transition-metal surfaces, building on recent non-self-consistent approaches. Within this framework, we develop a hybrid and a double-hybrid functional that achieve unprecedented accuracy, with the latter reaching transition-metal chemical accuracy on average across 39 experimental adsorption reactions. In addition, both functionals demonstrate balanced performance for 17 barrier heights and correct qualitative failures of standard functionals, including CO adsorption on Pt(111) and
graphene on Ni(111). They are computationally efficient, readily integrated into existing DFT codes, and supported by open-source workflows to facilitate adoption. More broadly, this framework provides a systematic route towards improved functionals for heterogeneous catalysis and complex materials.
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Optics · Cross-listed from cond-mat.mtrl-sci
Large Transverse Thermoelectric Effect in Weyl Semimetal TaIrTe$_4$ Engineered for Photodetection
Morgan G. Blevins, Xianglin Ji, Vivian J. Santamaria-Garcia et al. (+4 more)
Anomalous local photocurrent generation via second-order nonlinear and thermoelectric responses is a signature of many topological semimetals. The emergence of these photocurrents is inherently linked to
symmetry breaking and anisotropy of their
crystal lattices. Studies of type-II Weyl semimetals of group C$_{2v}$ (WTe$_2$, MoTe$_2$, TaIrTe$_4$) have reported anomalous, nonlocal photocurrents localized to
crystals edges or far from electrodes, which are highly dependent on the geometry of the material sample. While originally attributed to a nonlinear charge current response, it was recently shown that these currents could instead be attributed to the anisotropic Seebeck coefficients of the materials. Here, we confirm that anomalous photocurrents observed in TaIrTe$_4$ under either visible or far-infrared far-field illumination originate from the large transverse thermoelectric effect. We engineer the mutual orientation of
crystal edges and electrodes as well as the thermal environment of TaIrTe$_4$ to control and amplify its spatial photocurrent response. We show that substrate engineering can locally enhance photocurrent. This framework of thermal device engineering can enable broadband photo detection schemes by leveraging spectral and spatial dependence of photocurrents for applications like wavefront sensing, beam positioning, and edge detection.
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All authors Morgan G. Blevins, Xianglin Ji, Vivian J. Santamaria-Garcia, Abhishek Mukherjee, Thanh Nguyen, Mingda Li, Svetlana V. Boriskina
Optics
A robust and efficient method to calculate electromagnetic modes on a cylindrical step-index nanofibre
Sebastian Golat and Francisco J. Rodríguez-Fortuño
The accurate calculation of guided electromagnetic modes in optical nanofibres is critical for applications in nanophotonics, from
quantum interfaces to vectorial light sensing. Standard textbook methods rely on solving a $4\times4$
matrix eigenvalue problem to find the modal fields. While widely used, this approach has a subtle but significant flaw: the final determination of the field amplitudes requires finding the numerical null space of a theoretically singular
matrix, an ill-conditioned problem that introduces large relative errors in the small but physically crucial longitudinal field components. In this work, we introduce a fundamentally more robust and efficient semi-analytical method. By starting from the foundational
symmetries of the cylindrical waveguide and employing a judicious normalisation of the field amplitudes, we demonstrate that the problem can be analytically reduced to a much simpler $2\times2$ system. This reformulation yields two decisive advantages: the dispersion relation is obtained numerically from a simple and well-behaved transcendental equation, and more importantly, the modal field amplitudes are subsequently determined analytically. Our approach completely bypasses the numerical null space calculation, thereby ensuring the accuracy of the full vectorial field structure. This method provides a powerful and reliable tool for the design and analysis of nanofibre-based devices, particularly for applications in
chiral quantum optics and nanophotonics where precise knowledge of field polarisation and specifically of the longitudinal components is paramount.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Ferrocene-functionalized covalent organic framework exceeding the ultimate hydrogen storage targets: a first-principles multiscale computational study
Marcus Djokic and Jose L. Mendoza-Cortes
The development of efficient hydrogen storage materials is crucial for advancing the hydrogen economy and meeting the U.S. Department of Energy's targets of 6.5 wt% and 50 g H<sub>2</sub>/L for automotive applications. We present a computational study of ferrocene-functionalized covalent organic frameworks (COFs) for hydrogen storage. Following the <b>M</b>ulti-binding <b>S</b>ites <b>U</b>nited in <b>C</b>ovalent-<b>O</b>rganic <b>F</b>ramework (MSUCOF) approach, we introduce MSUCOF-4-FeCp, designed by incorporating ferrocene (FeCp<sub>2</sub>) moieties into IRCOF-102. Notably, it achieves exceptional performance with gravimetric and volumetric uptakes of 18.0 wt% and 72.6 g H<sub>2</sub>/L at 298 K and 700 bar. The material exhibits optimal binding energies (15-20 kJ/mol) ensuring both high storage capacity and deliverable hydrogen under practical conditions. This work establishes ferrocene functionalization as a cost-effective alternative to precious metal incorporation in COFs.
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Computational Physics
Auxiliary field quantum Monte Carlo at the basis set limit: application to lattice constants
Moritz Humer, Martin Schlipf, Zoran Sukurma et al. (+2 more)
We present a plane-wave (PW) implementation of the auxiliary-field
quantum Monte Carlo (AFQMC) method within the projector augmented-wave (PAW) formalism in the Vienna ab initio Simulation Package (VASP). By employing an exact inversion of the PAW overlap operator, our approach maintains cubic scaling while naturally operating at the complete basis set limit defined by the PW cutoff. We
benchmark this framework by calculating the
equilibrium lattice constants and bulk
moduli of C, BN, BP, and Si. Our analysis demonstrates that AFQMC systematically corrects the lack of long-range screening in MP2 and the missing higher-order exchange in RPA. We identify RPA as the optimal reference method due to the rapid convergence of the remaining short-range correlations with respect to supercell size. The resulting
lattice constants exhibit a mean absolute relative error of 0.14 % relative to experiment, establishing the method as a rigorous
benchmark tool for structural properties in condensed matter systems.
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All authors Moritz Humer, Martin Schlipf, Zoran Sukurma, Sajad Bazrafshan, Georg Kresse
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Sub-1-Angstrom-Resolution Imaging Reveals Phase Contrast Transition in Ice Ih Caused by Basal Stacking Faults
Jingshan S. Du, Suvo Banik, Lehan Yao et al. (+3 more)
Phase-contrast transmission electron microscopy (TEM) of hexagonal ice (Ih) along [0001] sometimes shows a honeycomb-like pattern, often interpreted as individual oxygen columns in single
crystals. Here, we show that this pattern commonly arises from intrinsic basal stacking faults instead. A translational boundary separating domains of comparable thickness, with an in-plane offset of $(\frac{2}{3} a_{1} + \frac{1}{3} a_{2})$, produces this honeycomb-like contrast. Stacking domains translated in nonequivalent directions yields patterns resembling cubic ice (Ic) along [111] but with a 3-fold
symmetry. We imaged this structure at a record-breaking line resolution of 89 picometers, finer than the O-H covalent bond length. These findings highlight the defect tolerance of ice's molecular packing and clarify the structural relationships among hexagonal, stacking-disordered, and cubic ice phases. This resolution milestone opens new avenues for characterizing subtle structural perturbations of water in the solid state.
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All authors Jingshan S. Du, Suvo Banik, Lehan Yao, Shuai Zhang, Subramanian K. R. S. Sankaranarayanan, James J. De Yoreo
Plasma Physics
Data-driven modeling of shock physics by physics-informed MeshGraphNets
S. Zhang, M. Mallon, M. Luo et al. (+4 more)
High-resolution fluid simulations for
plasma physics and astrophysics rely on Particle in
cell (PIC) and hydrodynamic solvers (e.g., FLASH) to resolve shock dominated, multiscale phenomena, but their high computational cost severely limits scalability. This motivates the development of learning based surrogate models, which offer a promising route to accelerate these simulations while preserving physical fidelity. In this work, we study the Sedov Taylor shock propagation problem using a physics informed graph based surrogate model, Physics Informed MeshGraphNet (PhyMGN), designed for grid-based hydrodynamics. By incorporating weak physics constraints derived from the Euler equations using finite difference method, the model captures the self similar shock
evolution and associated flow structures without explicitly solving the full hydrodynamic equations at each timestep. Comparing to the baseline MeshGraphNet model, PhyMGN is able to generalize beyond the training regime with a higher accuracy and preserves differentiability in parameter space while achieving a substantial reduction in computational cost relative to conventional numerical solvers.
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All authors S. Zhang, M. Mallon, M. Luo, J. Thiyagalingam, P. Tzeferacos, R. Bingham, G. Gregori
Fluid Dynamics
Adjoint-based shape optimization of a ship hull using a Conditional Variational Autoencoder (CVAE) assisted propulsion surrogate model
Moloud Arian Maram, Georgios Bletsos, Thanh Tung Nguyen et al. (+3 more)
Adjoint-based shape optimization of ship hulls is a powerful tool for addressing high-dimensional design problems in naval architecture, particularly in minimizing the ship resistance. However, its application to vessels that employ complex propulsion systems introduces significant challenges. They arise from the need for transient simulations extending over long periods of time with small time steps and from the reverse temporal propagation of the primal and adjoint solutions. These challenges place considerable demands on the required storage and computing power, which significantly hamper the use of adjoint methods in the industry. To address this issue, we propose a machine learning-assisted optimization framework that employs a Conditional Variational Autoencoder-based surrogate model of the propulsion system. The surrogate model replicates the time-averaged flow field induced by a Voith Schneider Propeller and replaces the geometrically and time-resolved propeller with a data-driven approximation. Primal flow verification examples demonstrate that the surrogate model achieves significant computational savings while maintaining the necessary accuracy of the resolved propeller. Optimization studies demonstrate that neglecting the propulsion system can result in hull designs whose performance is inferior to that of the initial shape when subsequently validated using a numerically resolved propulsor. In contrast, the proposed method produces shapes that actually achieve more than an 8% reduction in resistance.
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All authors Moloud Arian Maram, Georgios Bletsos, Thanh Tung Nguyen, Ahmed Hassan, Michael Palm, Thomas Rung
Geophysics
Groundwater feedbacks on ice sheets and subglacial hydrology
Gabriel J. Cairns, Graham P. Benham and Ian J. Hewitt
The dynamics of many of Antarctica's glaciers are modulated by a hydrological system at the base of the ice. Sedimentary basins beneath the ice bed contribute to the water budget in this hydrological system by discharging or taking up water. However, sedimentary basins are not included in most current models of ice dynamics, and little is known about their effect. In this paper we develop an idealised model of a glacier whose sliding is coupled to a subglacial hydrological system, which includes a sedimentary basin. We find that groundwater discharge (exfiltration) and recharge (infiltration) are controlled by the shape of the ice sheet and of the sedimentary basin, and that exfiltration promotes sliding whereas infiltration hinders it. Overall, the presence of a sedimentary basin leads to thicker and slower-flowing ice in the steady state. We also find that, when the ice sheet is undergoing retreating, groundwater exfiltration can lead to a positive feedback which accelerates this retreat. Our results shed light on the potential role and importance of Antarctic sedimentary basins, and how these might be incorporated into existing models of ice and subglacial hydrology.
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Instrumentation and Detectors
Review of prototypes developed in a 65 nm CMOS imaging technology in view of vertexing applications at a future lepton collider
Finn King, Matthew Lewis Franks, Yajun He et al. (+21 more)
The OCTOPUS project addresses the development and characterization of monolithic active pixel sensors in the TPSCo 65 nm ISC technology in view of vertexing applications at a future
lepton collider. Meeting the corresponding requirements – outlined in the ECFA detector road map – will necessitate the simulation, design, and testing of prototypes and a demonstrator chip in this very process. This work reviews the literature on existing prototypes, summarizing their design characteristics, properties, and performance in charged-particle detection, and provides an overview of previous simulation efforts. The presented results suggest the feasibility of the endeavor while showcasing challenges, the need for further investigations, and providing a foundation for imminent design choices.
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All authors Finn King, Matthew Lewis Franks, Yajun He, Gianpiero Vignola, Simon Spannagel, Malte Backhaus, Auguste Besson, Dominik Dannheim, Andrei Dorokhov, Ingrid-Maria Gregor, Fadoua Guezzi-Messaoud, Lennart Huth, Armin Ilg, Zdenko Janoska, Monika Kuncova, Anna Macchiolo, Frédéric Morel, Sara Ruiz Daza, Roberto Russo, Judith Schlaadt, Serhiy Senyukov, Peter Švihra, Anastasiia Velyka, Håkan Wennlöf