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Physics Physics

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Wednesday 13 May

Applied Physics

Monolithic axial InGaAs quantum dot emitters in GaAs-based nanowires via Sb-mediated facet engineering

Hyowon W. Jeong, Aris Koulas-Simos, Imad Limame et al. (+6 more)

GaAs-based nanowires hosting active quantum heterostructures provide a promising route toward monolithic integration of single-photon sources on silicon, a key requirement for scalable quantum photonics. However, ultrathin axial quantum-emitter formation is often hindered by facet-dependent growth dynamics and rotational twins, which induce lateral overgrowth and compromise interface abruptness. Here, we develop InGaAs-based quantum emitters by tailoring facet evolution via dilute Sb incorporation, which efficiently suppresses twins and promotes confined axial insertion at the growth-front facet. This approach significantly enhances the probability of obtaining abrupt, few-nanometer-thin quantum dots at the nanowire tip. Single-nanowire optical spectroscopy reveals intense, spatially localized emission from the active region with lifetimes as short as (0.51 $\pm$ 0.02) ns, and second-order photon-correlation measurements consistently exhibit pronounced antibunching with $g^{(2)}(0)<0.4$, confirming single-photon emission. These results establish a strong correlation between twin density and axial heterostructure formation, identifying defect control as a key factor in realizing monolithically integrated nanowire single-photon sources.
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All authors Hyowon W. Jeong, Aris Koulas-Simos, Imad Limame, Markus Döblinger, Sang Kyu Kim, Chirag C. Palekar, Jonathan J. Finley, Stephan Reitzenstein, Gregor Koblmüller

Instrumentation and Detectors

GPU-Accelerated Simulation of 3D Diamond Sensors Using the TeRABIT Infrastructure

Lucio Anderlini, Clarissa Buti, Elia Eredi et al. (+1 more)

Diamond detectors with electrodes orthogonal to the surface, engraved via laser-induced graphitization, are full-carbon sensors of interest for a wide range of applications, spanning from High Energy Physics to Nuclear Medicine and dosimetry. In recent years, significant progress has been made in graphitization techniques, enabling the fabrication of lower-resistance electrodes. This has resulted in faster sensors, achieving time resolutions better than 100 ps. However, simulating signal formation in these devices remains a challenge. The effects of fluctuations in energy deposition, carrier transport, signal propagation, and readout electronics intertwine in a way that is non-trivial to disentangle. We have developed an innovative simulation approach based on an extension of the Ramo-Shockley theorem, modeling propagation effects in a theoretically sound manner by introducing time-dependent weighting potentials. These are obtained by solving a third-order partial differential equation derived as a quasi-static approximation of Maxwell's laws. The numerical solution of this equation emerged as the main challenge of the new approach. In this contribution, we discuss an innovative solver that uses fundamental solutions to impose boundary conditions and spectral methods to extend the solution to the bulk of the diamond detector. We report on how the solver has recently been ported to GPUs and distributed across multiple computing sites, leveraging the TeRABIT HPC Bubbles and the InterLink protocol. This drastically reduces time-to-insight and effectively enables what-if studies on sensor geometry.
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All authors Lucio Anderlini, Clarissa Buti, Elia Eredi, Giovanni Passaleva

Biological Physics · Cross-listed from q-bio.CB

Kin-ematic Exclusion in Active Matter: Modelling Mutual Inhibition in Pseudomonas aeruginosa Sibling Colonies

Dario Buonomo, Francesco Imperi, Fabio Bruni et al. (+2 more)

The striking variety of macroscopic morphologies displayed by bacterial colonies depends on microscopic environmental and behavioural details in a manner that is currently not well understood. A surprising example is sibling inhibition, whereby isogenic bacterial colonies spreading in soft agar hydrogels tend to avoid each other and form sharp demarcation lines when growing nearby. Here we investigate this effect with the common pathogen Pseudomonas aeruginosa, by combining quantitative density measurements with a minimal biophysical model. Our results show that the phenomenon does not depend on gel compression, lethal inhibition or quorum sensing-dependent cell communication. Instead, colony separation is driven by localised nutrient depletion through a dynamic feedback between growth and motility. The model, which is calibrated using experimental data, captures key observations including the dependence of inhibition strength on the initial nutrient concentration. This work establishes nutrient availability and non-lethal motility inhibition as central factors underlying sibling inhibition, providing a generalisable framework for microbial spatial dynamics with implications for understanding bacterial interactions in tissues, soils and engineered microbiomes.
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All authors Dario Buonomo, Francesco Imperi, Fabio Bruni, Marco Polin, Barbara Capone

Fluid Dynamics · Cross-listed from math.NA

ViT-K: A Few-Shot Learning Model for Coupled Fluid-Porous Media Flows with Interface Conditions

Mengjia Chen, Changxin Qiu, Zhiping Mao et al. (+1 more)

The numerical simulation of interaction between free flow and porous media, governed by coupled Stokes/Navier–Stokes–Darcy flows, is critical for understanding fluid filtration and physiological transport, yet it is hindered by the high computational cost of resolving interface heterogeneities and the instability of long-term predictions. While deep learning offers surrogate modeling potential, existing frameworks often suffer from exponential error accumulation and poor convergence in multi-physics regimes. To address these limitations, we propose ViT-K, a novel few-shot learning model designed to learn the spatiotemporal evolution of coupled flows from sparse datasets. The ViT-K framework effectively reconstructs the global flow physics on a low-dimensional manifold by combining Vision Transformers (ViT) to capture heterogeneous interfacial features with the Koopman operator to linearize temporal dynamics. By lifting nonlinear dynamics into a globally linear observable space, the ViT-K model provides stability by design, ensuring that prediction errors grow linearly rather than exponentially over time. This theoretical property enables reliable long-term extrapolation even in small-sample regimes. Numerical experiments on benchmark coupled systems demonstrate that ViT-K not only captures complex interface physics with high fidelity but also exhibits exceptional robustness against measurement noise by acting as an implicit spectral filter. The proposed method significantly outperforms traditional solvers in inference speed while maintaining physical consistency, offering a robust paradigm for real-time multiphysics forecasting.
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All authors Mengjia Chen, Changxin Qiu, Zhiping Mao, Menghui Xu

Optics

Integrated ytterbium gain for visible-near-infrared photonics

Tianyi Zeng, Erik W. Masselink, Tsung-Han Wu et al. (+9 more)

Rare-earth gain media form the foundation of modern optical communications, emerging quantum hardware, and ultrafast optics. While chip-scale integration can enable fiber-like, and potentially beyond-fiber, functionality with unprecedented scalability, development in the visible and near-infrared remains in its early stages. Here, we demonstrate ytterbium-based optical gain integrated into an aluminum oxide photonic platform, achieving both single-mode lasing and optical amplification in the near-infrared regime. This platform delivers optical amplification with output powers exceeding 0.5 W, an optical-to-optical conversion efficiency above 70%, and a noise figure of 3.3 dB, approaching the quantum limit for phase-insensitive amplification. Furthermore, we achieve femtosecond pulse amplification to a record peak power of 14 kW, enabling supercontinuum generation with visible dispersive waves extending from 780 to 476 nm in conjunction with nonlinear photonic devices. This platform is compatible with heterogeneous integration into standard photonic circuits, laying the foundation for scalable visible-near-infrared photonic systems, including coherent laser arrays, mode-locked lasers, optical clocks, and microwave oscillators.
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All authors Tianyi Zeng, Erik W. Masselink, Tsung-Han Wu, Nathan Brooks, Peter Chang, Grisha Spektor, Zachary L. Newman, Danxian Liu, Scott B. Papp, David R. Carlson, Scott A. Diddams, Kiyoul Yang

Chemical Physics · Cross-listed from cs.LG

Reducing cross-sample prediction churn in scientific machine learning

Gordan Prastalo and Kevin Maik Jablonka

Scientific machine learning reports predictive performance. It does not report whether the same prediction would survive a different draw of training data. Across $9$ chemistry benchmarks, two classifiers trained on independent bootstraps of the same training set agree on aggregate accuracy to within $1.3\text{--}4.2$ percentage points but disagree on the class label of $8.0\text{--}21.8\%$ of test molecules. We call this gap cross-sample prediction churn. The standard parameter-side techniques (deep ensembles, MC dropout, stochastic weight averaging) do not reduce this gap; two data-side methods do. The first is $K$-bootstrap bagging, which cuts the rate $40\text{--}54\%$ on every dataset at no accuracy cost ($K{\times}$-ERM compute). The second is twin-bootstrap, our proposal: two networks trained jointly on independent bootstraps with a sym-KL consistency loss between their predictions, which at matched $2{\times}$-ERM compute reduces churn a further median $45\%$ beyond bagging-$K{=}2$. Cross-sample prediction churn deserves a column alongside predictive performance in scientific-ML benchmark reports, because without it the parameter-side and data-side methods are indistinguishable on the metric they actually differ on.
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Computational Physics · Cross-listed from cond-mat.str-el

Parallel Scan Recurrent Neural Quantum States for Scalable Variational Monte Carlo

Ejaaz Merali, Mohamed Hibat-Allah, Mohammad Kohandel et al. (+2 more)

Neural-network quantum states have emerged as a powerful variational framework for quantum many-body systems, with recent progress often driven by massively parallel architectures such as transformers. Recurrent neural network quantum states, however, are frequently regarded as intrinsically sequential and therefore less scalable. Here we revisit this view by showing that modern recurrent architectures can support fast, accurate, and computationally accessible neural quantum state simulations. Using autoregressive recurrent wave functions together with recent advances in parallelizable recurrence, we develop variational ansätze, called parallel scan recurrent neural quantum states (PSR-NQS), which can be trained efficiently within variational Monte Carlo in one and two spatial dimensions. We demonstrate accurate benchmark results and show that, with iterative retraining, our approach reaches two-dimensional spin lattices as large as $52\times52$ while remaining in agreement with available quantum Monte Carlo data. Our results establish recurrent architectures as a practical and promising route toward scalable neural quantum state simulations with modest computational resources.
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All authors Ejaaz Merali, Mohamed Hibat-Allah, Mohammad Kohandel, Richard T. Scalettar, Ehsan Khatami

Computational Physics · Cross-listed from cs.CE

Elastica++: A high-performance, multiphysics framework for large interacting assemblies of Cosserat rods

Tejaswin Parthasarathy, Seung Hyun Kim, Songyuan Cui et al. (+1 more)

Soft, slender structures are ubiquitous in natural and engineered systems, with broad application potential from biomimetic materials to soft robotics. However, there is a notable lack of computational tools that simultaneously preserve high-fidelity continuum rod mechanics, scale to large interacting ensembles, and remain flexible across diverse biophysical settings. Here we introduce Elastica++, an open-source, high-performance implementation of the Cosserat-rod model for large-scale simulations of slender-body dynamics. Elastica++ combines performance-oriented kernels with shared-memory parallelism to sustain teraflop-scale throughput despite complex discretization domains and physical interactions. The framework further interoperates with external numerical solvers, supporting efficient multiphysics workflows. We demonstrate robustness and breadth through case studies spanning passive nest-like metamaterials, collective active-matter dynamics, cilia carpets, soft magnetic microrobots, and schooling swimmers. Elastica++ thus provides a missing foundation for high-throughput studies of emergent behavior in interacting assemblies of elastic slender structures.
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All authors Tejaswin Parthasarathy, Seung Hyun Kim, Songyuan Cui, Mattia Gazzola

Instrumentation and Detectors

Application of exhaustive simulation flow for advanced performance prediction of monolithic active pixel sensors

E. Sacchetti, M. Babeluk, T. Bergauer et al. (+86 more)

Monolithic active pixel sensor (MAPS) developments have pushed the detection performance in various directions, especially relative to timing where nanosecond-level precision is now considered. This evolution calls for a simultaneous upgrade of the simulation tools. We have developed a simulation flow that covers steps from the signal creation in the sensitive volume to the output of the pixel digital logic that performs the time-of-arrival and time-over-threshold (ToA/ToT) measurements. This approach adds several new features to the traditional use the of the TCAD - Allpix Squared duo, among which : the integration of the pixel wells from the layout in order to precisely describe the pixel key characteristics such as leakage and punch-through currents and the coupling of Monte Carlo simulations (Allpix Squared) with high precision electrical simulations (SPICE). The first (Allpix Squared) for the precise description of the current induced at the collection electrode and the second (SPICE) to guarantee high precision simulation of the front-end electronics using realistic signal events. Irradiation is also modeled, both from the charge propagation side (charge trapping) and from the front-end response side (high input signal discharge). We have applied this methodology to the MAPS developed in the context of the Belle II vertex detector upgrade. In this contribution, we detail the key features of the exhaustive simulation flow, present the outcome of the comparison with the TJ-Monopix2 measurements and discuss the interest of the methodology for the development of modern MAPS.
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All authors E. Sacchetti, M. Babeluk, T. Bergauer, M. Friedl, C. Irmler, B. Pilsl, R. Russo, C. Schwanda, L. Gaioni, V. Re, E. Riceputi, G. Traversi, S. Giroletti, L. Ratti, G. F. Benfratello, S. Bettarini, F. Bosi, G. Casarosa, L. Corona, F. Forti, A. Gabrielli, M. Massa, L. Massaccesi, M. Minuti, A. Moggi, S. Mondal, G. Rizzo, M. Rovini, A. Taffara, M. Barbero, P. Barrillon, R. Boudagga, P. Breugnon, D. Fougeron, P. Pangaud, J. Serrano, V. Vobbilisetti, D. Xu, D. Auguste, J. Bonis, Y. Peinaud, M. Winter, J. Baudot, G. Bertolone, A. Dorokhov, G. Dujany, L. Federici, C. Finck, A. Himmi, C. Hu-Guo, A. Kumar, M. Maushart, F. Morel, H. Pham, I. Ripp-Baudot, R. Sefri, P. Stavroulakis, I. Valin, F. Bernlochner, C. Bespin, J. Dingfelder, T. Kishishita, H. Kruger, L. Schall, M. Vogt, M. Karagounis, Y. Buch, A. Frey, B. Schwenker, M. Schwickardi, K. Hara, D. Jeans, K. R. Nakamura, Y. Okazaki, T. Higuchi, Y. Onuki, S. Wang, C. Lacasta, C. Marinas, J. Mazorra de Cos, L. Molina-Bueno, A. Bevan, M. Bona, D. Howgill, W. Song, J. Gong, X. Gao, A. Fernandez Prieto, A. Gallas Torreira

Accelerator Physics

Beam-Driven Transverse Deflecting Structure for Femtosecond Electron-Beam Diagnostics

S. Tomin, D. Bazyl, W. Decking et al. (+1 more)

High-resolution longitudinal phase-space (LPS) diagnostics are essential for X-ray free-electron lasers and advanced accelerators. Conventional radio-frequency transverse deflecting structures (TDSs) provide direct femtosecond-scale LPS measurements, but their substantial RF-power and infrastructure requirements strongly limit their deployment at multi-GeV beam energies. Here, we propose a beam-driven transverse deflecting structure in which a leading driver bunch, separated by one RF bucket from a trailing witness bunch under study, excites long-lived wakefields in a resonant cavity array. By placing the witness bunch near a zero crossing of the wakefield, the bunch experiences an approximately linear time-dependent transverse kick. Electromagnetic simulations of the resonant structure, combined with start-to-end beam-dynamics simulations based on European XFEL parameters at a final beam energy of 14 GeV, demonstrate a temporal resolution of $\sim 1.6$ fs for a 500 pC driver bunch, with a clear scaling toward the sub-femtosecond regime at higher charge.
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All authors S. Tomin, D. Bazyl, W. Decking, I. Zagorodnov

Physics and Society

The Co-evolution of Costly Signaling and Cooperation in Social Dilemmas

Mahdi Abolhasani, Saman Moghimi-Araghi and Mohammad Salahshour

Costly cooperation and costly signaling are both difficult to reconcile with simple fitness maximization, yet both are common in biological and social systems. We study a model in which agents emit costly signals and condition their actions on the signals they observe. Across the Prisoner's Dilemma (PD), Snowdrift (SD), and Stag Hunt (SH) games, we ask when this coevolutionary process can sustain cooperation and how it changes across well-mixed populations, spatial lattices, and fluctuating strategic environments. The simulations show that signals are selected less by their raw production costs than by the cooperative responses they currently elicit. In well-mixed populations, the mechanism sustains partial cooperation in PD and SD and drives near-complete cooperation in SH. On lattices, cooperation is strengthened further by local assortment. A reduced mean-field analysis explains why average population feedback is already sufficient in SD and SH, but not in the PD. To account for the PD dynamics, the reduced theory must include transient correlations associated with rare signals, inheritance, or spatial clustering. Our results therefore delineate a class of settings in which costly signals persist because they transiently organize cooperative responses and thereby reshape the effective strategic environment.
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Optics

Intensity-noise suppression due to longitudinal mode coupling in multimode intracavity-doubled lasers

Thomas M. Baer

Multimode intracavity frequency-doubled lasers can reach states of intensity-noise suppression orders of magnitude beyond the predictions of independent-mode partition statistics. I show that the ḩi}(2) coupled-wave dynamics in the doubling crystal obey a dissipation inequality: a fourth-moment functional of the intracavity intensity decreases monotonically under each forward nonlinear pass, driving the mode ensemble toward a constant-intensity manifold. This per-pass result is a strict Lyapunov inequality, and round-trip simulations show attraction to the same low-M4, nearly constant-intensity state under the full cavity dynamics. I confirm the mechanism in an intracavity frequency-doubled Nd:YVO4/LBO laser, observing a 100x contrast between full and Fabry-Perot-filtered output noise at fixed detector bandwidth, well beyond the sqrt(N/N_f) statistical-averaging baseline. The argument depends only on the algebraic structure of the coupling: a coherent superposition of oscillators that share a quadratic dissipative channel. It therefore points to a general Lyapunov route to intensity-noise suppression in coupled oscillator systems, beyond the intracavity-doubled laser.
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Optics · Cross-listed from cond-mat.mtrl-sci

Giant optical spin-orbit interactions in ferroelectric van der Waals waveguides

Ding Xu, Saeed Rahmanian Koshkaki, Vicente Galicia et al. (+14 more)

Optical spin-orbit interactions (SOI) link photonic spin to momentum, offering a route toward on-chip polarization control and beam steering. Nevertheless, achieving sufficient optical SOI and nonlinearities on sub-micrometer scales - a prerequisite for dense photonic integration - remains an outstanding challenge. Here, we show that highly birefringent van der Waals (vdW) waveguides provide an ideal, chip-compatible platform to address this limitation. We focus on the ferroelectric semiconductor NbOI2, which exhibits record optical nonlinearities and dielectric anisotropy. Using femtosecond optical microscopy, we image light propagation and harmonic conversion beyond the total internal reflection barrier over tens of micrometers in NbOI2 slab waveguides. We report giant optical spin-splitting through the optical spin Hall effect, which facilitates spatial separation of optical spin currents on sub-micrometer scales, in quantitative agreement with a microscopic light-matter interaction model. We further leverage optical spin-momentum locking to realize polarization-controlled waveguide steering. We generalize these observations across various vdW waveguides and empirically confirm a scaling law linking dielectric anisotropy to geometric spin-splitting. Our results establish highly anisotropic vdW waveguides as an ideal platform for densely integrated opto-spintronic technologies.
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All authors Ding Xu, Saeed Rahmanian Koshkaki, Vicente Galicia, Chun-Ying Huang, Victoria Quirós-Cordero, Jakhangirkhodja A. Tulyagankhodjaev, André Koch Liston, Daniel G. Chica, Emma Lian, Amirhosein Amini, Yongseok Hong, Taketo Handa, P. James Schuck, Xiaoyang Zhu, Xavier Roy, Arkajit Mandal, Milan Delor

Atomic Physics · Cross-listed from quant-ph

Floquet engineering of nonreciprocal light-induced dipolar interactions

Livia Egyed, Murad Abuzarli, Manuel Reisenbauer et al. (+3 more)

Tweezer arrays of polarizable objects are a promising platform for assembling quantum matter and building next-generation quantum sensors. Light-induced dipolar interactions have emerged as a method to couple their motion, thereby establishing a new paradigm for controlling collective mechanical degrees of freedom. Here, we extend these into the regime of Floquet-driven interactions, combined with the intrinsic nonreciprocity of optical forces. We demonstrate beamsplitter, single-, and two-mode squeezing operations, as well as signatures of a negative-mass-like oscillator arising from the nonreciprocity. Moreover, we show that a programmable combination of these operations enables continuous tuning of complex eigenfrequencies. These results establish a toolbox of quantum operations of nonreciprocal interactions that are essential for investigating non-Hermitian many-body physics and collective quantum optomechanics.
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All authors Livia Egyed, Murad Abuzarli, Manuel Reisenbauer, Iurie Coroli, Benjamin A. Stickler, Uroš Delić

Atomic Physics · Cross-listed from quant-ph

Decoherence of spatial superpositions along stationary worldlines

Clemens Jakubec, Aaron Bartleson, Peter W. Milonni et al. (+1 more)

We analyze the decoherence of a particle's spatial superposition moving along a stationary worldline through the Minkowski vacuum. The particle is modeled via an internal degree of freedom that couples to a scalar field, and an external degree of freedom, i.e., its quantized center-of-mass motion around the stationary worldline. Assuming a separation of time scales between the particle's internal and external dynamics, we first obtain an effective red-shifted polarizability of the particle, characterizing the trajectory-dependent linear response of the internal oscillator to the field. We then derive a quantum Brownian motion master equation for the particle's center of mass, under the Born-Markov approximation, which describes its decoherence in the position basis, as well as, Hamiltonian modifications corresponding to a dispersive potential. The resulting decoherence has two components: (1) arising from a modified field spectrum observed by the particle; and (2) due to a differential time-dilation over the particle's extended spatial wavefunction. For stationary trajectories, both contributions take an effectively thermal form. We evaluate the decoherence rates for two specific cases of hyperbolic and uniform circular motion.
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All authors Clemens Jakubec, Aaron Bartleson, Peter W. Milonni, Kanu Sinha

Fluid Dynamics · Cross-listed from math-ph

Stochastic modeling of Fourier modes in two-dimensional turbulence via filtered white noise

Paolo Cifani, Franco Flandoli and Andrea Zanoni

Modeling turbulent flows by a random Fourier decomposition is a classical procedure in order to use simplified models of turbulence in heat transport and other applications. We investigate the Fourier time series of two-dimensional Navier-Stokes equations with friction and damping, forced at intermediate scales, and identify significant statistical structures. In particular, we find the existence of a typical time correlation length, and propose a stochastic model for the Fourier components. Finally, we compute the transport of a passive scalar under advection-diffusion dynamics by means of direct numerical simulation of the stochastic damped Navier-Stokes equation and compare it with analytical predictions of the effective diffusion produced by the stochastic model.
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Optics · Cross-listed from cs.CV

HADAR-Based Thermal Infrared Hyperspectral Image Restoration

Cheng Dai, Jiale Lin, Bingxuan Song et al. (+4 more)

Thermal-infrared (TIR) hyperspectral imagery (HSI) provides critical scene information for various applications. However, its practical utility is severely limited by unique sensor degradations beyond the capabilities of existing restoration methods, which are ignorant of underlying thermal physics. Here, we propose HAIR (HADAR-based Image Restoration) as a physics-driven framework for ground-based TIR-HSI restoration. HAIR utilizes the HADAR rendering equation (HRE) and combines it with the atmospheric downwelling radiative transfer equation (RTE) to model TIR-HSI using temperature, emissivity, and texture (TeX) physical triplets. This physical model leads to a TeX decompose-synthesize strategy that guarantees physical consistency and spatio-spectral noise resilience, in stark contrast to existing approaches. Moreover, our framework uses a forward-modeled atmospheric downwelling reference, along with spectral smoothness of emissivity and blackbody radiation, to enable spectral calibration and generation that would otherwise be elusive. Our extensive experiments on the outdoor DARPA Invisible Headlights dataset and in-lab FTIR measurements show that HAIR consistently outperforms state-of-the-art methods across denoising, inpainting, spectral calibration, and spectral super-resolution, establishing a benchmark in objective accuracy and visual quality.
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All authors Cheng Dai, Jiale Lin, Bingxuan Song, Yifei Chen, Jiashuo Chen, Xin Yuan, Fanglin Bao

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

High-Pressure XRD Study of Ti-3Al-2.5V Titanium Alloy: Intermediate Transition Pressure and Composition Trends in Ti-Al-V Alloys

D. Errandonea, R. Turnbull, P. Botella et al. (+3 more)

High-pressure X-ray diffraction experiments were performed on Ti-Al-V alloys to investigate the effect of composition on structural stability, focusing on Ti-3Al-2.5V and comparing with pure Titanium and Ti-6Al-4V. Measurements using different pressure-transmitting media show a phase transition in Ti-3Al-2.5V at 17-19 GPa, intermediate between pure Ti (5-10 GPa) and Ti-6Al-4V (~30 GPa). Despite variations arising from the choice of pressure medium, the transition pressure shows a clear and systematic increase with higher Al and V content. Equation-of-state analysis indicates that the bulk modulus remains nearly unchanged across compositions. This suggests a decoupling between elastic properties and phase stability, with alloying primarily affecting the transition pressure rather than compressibility. These results highlight the role of composition in tuning high-pressure phase transformations in Ti-Al-V based alloys.
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All authors D. Errandonea, R. Turnbull, P. Botella, R. Oliva, C. Popescu, S. MacLeod

Fluid Dynamics

Free-surface deformations induced by three-dimensional turbulence

Michaël Berhanu and Eric Falcon

We report the experimental characterization of free-surface deformations generated by three-dimensional homogeneous and isotropic turbulence. Using Fourier transform profilometry in a jet-forced turbulent tank, we perform spatiotemporal measurements of the surface elevation field over a wide range of turbulence intensities. The standard deviation of surface deformations scales linearly with subsurface velocity fluctuations. The spectra of surface deformations highlight the coexistence of two mechanisms: transient coherent structures (e.g., upwelling) contributing to the low-frequency, large-scale spectral components, and a passive response to subsurface turbulent pressure fluctuations responsible for the power-law spectral scaling. The wavenumber and frequency spectra of surface deformations exhibit similar power-law exponents (-2.5), suggesting the advection of turbulent structures at the free surface. We develop a linear response model based on the transfer function from the free surface to turbulent pressure fluctuations, incorporating wave-turbulent damping. The model successfully predicts the main features of the turbulent surface: spatiotemporal spectrum shape, similar spectrum power-law exponents (-7/3), and dominance of passive response over wave generation. These findings provide new insights into free-surface turbulence in regimes where turbulent velocities remain below the surface-breaking threshold.
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Computational Physics

Efficient simulation of chemical reaction in DSMC

Hong Deng, Liyan Luo and Lei Wu

A macroscopic mesoscopic, deterministic stochastic coupling strategy is proposed to accelerate the direct simulation Monte Carlo (DSMC) method for chemical reaction. First, a macroscopic synthetic equation is formulated by integrating continuum constitutive relations for diffusion, stress, and heat flux, along with higher order constitutive relations that capture nonequilibrium transport effects. Second, higher order constitutive relations and chemical reaction source terms are sampled from DSMC and embedded into the macroscopic synthetic equation. Third, the macroscopic system is solved to the steady state, whose solution is then employed to correct particle distributions in DSMC intermittently. This coupling features asymptotic preserving, fast converging and noise reduction properties, supporting efficient, accurate simulations with coarse spatiotemporal grids and reduced evolution/sampling steps. Accordingly, it mitigates major computational bottlenecks of DSMC for near continuum flows by several orders of magnitude.
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Fluid Dynamics

Effects of Thermal Boundary Conditions on Natural Convection and Entropy Generation in Non-Newtonian Power-Law Fluids

Lambert Theisen and Satyvir Singh

This study investigates the role of thermal boundary conditions on natural convection and entropy generation in non-Newtonian power-law fluids confined within a square cavity and a concentric cylindrical annulus. Steady, two-dimensional governing equations based on the incompressible power-law model and the Boussinesq approximation are solved using the Gridap.jl finite element framework. The numerical methodology is validated against benchmark solutions for both Newtonian and non-Newtonian convection, showing good agreement in terms of isotherm fields, streamlines, local Nusselt number distributions, and entropy generation. The effects of fluid rheology and heating mode are examined for shear-thinning, Newtonian, and shear-thickening fluids under uniform and non-uniform thermal boundary conditions. The results show that shear-thinning behavior enhances buoyancy-driven circulation, steepens thermal gradients, and increases heat transfer, whereas shear-thickening behavior suppresses convection and promotes conduction-dominated transport. Thermal boundary conditions are found to play an important role in controlling the intensity and spatial distribution of flow, heat transfer, and irreversibility. In both geometries, uniform heating produces stronger and more distributed convective structures, while non-uniform sinusoidal heating localizes thermal forcing and consistently reduces total entropy generation. An entropy analysis further reveals that viscous dissipation dominates irreversibility in shear-thinning fluids, whereas heat-transfer irreversibility becomes dominant as the power-law index increases. The study demonstrates that appropriate thermal boundary design, together with fluid rheology, provides an effective route for controlling heat transfer and minimizing thermodynamic losses in non-Newtonian convection systems. The source code and metadata are publicly available.
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Instrumentation and Detectors

SINAPSE: A lightweight deep learning framework for accurate and explainable neutron-$\gamma$ discrimination

Thomas Carreau, Adrien Matta, Owen Syrett et al. (+10 more)

Traditionally, neutron-$\gamma$ discrimination in organic scintillators relies on techniques such as time-of-flight (ToF) selection and pulse-shape discrimination (PSD). However, particle identification through graphical cuts remains challenging in the low-charge regime due to poor signal-to-noise ratios (SNR). In this work, we propose SINAPSE, a lightweight deep learning framework for accurate and explainable neutron-$\gamma$ discrimination in the low-charge regime. The framework employs a dual-branch architecture that combines a 1-dimensional convolutional autoencoder for waveform denoising with a classifier for particle identification. Random augmentations are applied to high-SNR waveforms to simulate low-charge conditions, enabling robust extrapolation into regimes where conventional PSD labels are unreliable. We show that SINAPSE achieves superior denoising performance compared to conventional digital signal processing techniques, and outputs well-calibrated probabilities, consistent with traditional graphical cuts. Finally, we apply SHAP (SHapley Additive exPlanations) values to show that model decisions are driven by physically meaningful pulse-shape features, confirming consistency with established PSD principles.
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All authors Thomas Carreau, Adrien Matta, Owen Syrett, Benoît Mauss, David Etasse, Cyril Lenain, Pierre Morfouace, Julien Taieb, David Regnier, Patrick Copp, Matthew Devlin, Charlène Surault, Jason Surbrook

Optics

DeepFilters: Scattering-Aware Pupil Engineering with Learned Digital Filter Reconstruction for Extended Depth of Field Microscopy

Joseph L. Greene, Suet YIng Chan, Qilin Deng et al. (+8 more)

Extended depth of field microscopy encodes axial information into a single acquisition through engineered point spread functions, but conventional and deep optics approaches are subject to degradation in scattering tissue. We introduce DeepFilters, a scattering-aware deep optics framework that jointly optimizes a parameterized pupil filter and a digital-filter-based reconstruction network through a calibrated differentiable forward model to achieve broad generalization without retraining. Incorporating empirical scattering kernels, physics-guided regularization, and a hybrid genetic-gradient initialization strategy, DeepFilters extends the PSF from 16 micron to >400 micron in clear media and enables signal recovery beyond 120 micron deep in biological tissues, validated across fixed brain slices and sea urchin embryos.
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All authors Joseph L. Greene, Suet YIng Chan, Qilin Deng, Jeffrey Alido, Alexandra Lion, Guorong Hu, Ruipeng Guo, Tongyu Li, Kivilcim Kiliç, Ian Davison, Lei Tian

Optics

Adaptive time-domain simulation of optical cavities with arbitrary dynamics

A. Svizzeretto, J. Casanueva Diaz, B. L. Swinkels et al. (+1 more)

We present a fast time-domain simulator for optical cavities capable of reproducing non-linear dynamical regimes arising from ring-down effect during resonance crossings at high mirror velocities. The model is based on a recursive formulation of the intracavity electric field as a sum over round trips, preserving the cavity memory while maintaining high computational efficiency. The simulator is designed to achieve three main goals. First, the boundary conditions of the cavity can be modified at each simulation step, allowing arbitrary time-dependent variations of both mirror positions and input electric field. Second, the sampling frequency can be flexibly chosen by the user, however, it is internally adjusted before effectively executing the simulation to remain consistent with the cavity round-trip structure. Finally, high computational efficiency was obtained by avoiding the repeated evaluation of the full electric field history. The framework is validated through comparison with experimental data from the Virgo interferometer during a mechanical excitation experiment, showing good agreement in non-adiabatic regimes. Due to its efficiency and flexibility, the simulator provides a versatile tool for time-domain studies of optical resonators and future applications in real-time control and reinforcement-learning-based lock acquisition.
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All authors A. Svizzeretto, J. Casanueva Diaz, B. L. Swinkels, M. Bawaj

Geophysics

Assessing foundational atomistic models for iron alloys under Earth's core conditions

Tianqi Wan, Liangrui Wei, Zepeng Wu et al. (+2 more)

We assess the capability of recently developed foundational atomistic models (FAMs) to simulate iron alloys under the extreme pressures and temperatures of Earth's core. Static equations of state for hexagonal close-packed (hcp) and body-centered cubic (bcc) iron, computed using 17 FAMs, are benchmarked against ab initio calculations. Two representative models, MatterSim and MACE, are further evaluated for their ability to reproduce phonon spectra, liquid structure, and melting relations of iron at core conditions. While both models capture several key properties, MACE substantially overestimates the stability of bcc iron and fails to correctly describe the stability of hcp iron. Their performance is also examined for binary liquids, superionic phases, and a seven-component Fe-Ni-Si-S-O-H-C liquid. Although these FAMs were not explicitly trained on data from core conditions, they can reproduce several structural and dynamical properties across a wide range of compositions. However, none of the tested models consistently reproduces all first-principles benchmarks. By analyzing the origins of these discrepancies, we identify several limitations of current FAMs, particularly the lack of an explicit treatment of thermal electronic excitations, which significantly affect phase stability and thermodynamic properties under core conditions. We further discuss directions for improving FAMs to enable predictive simulations of core-forming materials under extreme conditions.
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All authors Tianqi Wan, Liangrui Wei, Zepeng Wu, Renata M. Wentzcovitch, Yang Sun

Optics

Ghost State of Light

R. M. de Boer, C. Toebes, Jan Klars et al. (+1 more)

We report the observation of a long-lived non-stationary state of light in a single-mode optical cavity. The observed state is a ghost of a saddle-node bifurcation which creates a bottleneck in phase space. While such ghosts are known to exist, accessing them is challenging because it requires a mechanism that steers the relaxation pathway away from the true attractor and into the bottleneck where the ghost emerges. Here we identify such a mechanism, namely a nonlinear response with memory. Our experimental system leverages this mechanism, enabling us to observe ghost states with lifetimes exceeding the cavity photon lifetime by more than ten orders of magnitude, even in the presence of strong fluctuations. The ghost manifests as a plateau in the relaxation dynamics of the cavity transmission, reminiscent of prethermalization. We show how the ghost lifetime depends on the memory time and the distance to the bifurcation, and we observe signatures of scaling in the distribution of ghost lifetimes at fixed driving conditions. Our work establishes minimal conditions for realizing parametrically long-lived non-stationary states.
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All authors R. M. de Boer, C. Toebes, Jan Klars, S. R. K. Rodriguez

Optics · Cross-listed from cond-mat.mtrl-sci

Anisotropic Dopant and Strain Architectures in WS$_2$ Nanocrystals Driven by Growth Kinetics

Frederico B. Sousa, Raphaela de Oliveira, Matheus J. S. Matos et al. (+11 more)

Dopant distribution in two-dimensional semiconductors is typically assumed to be stochastic, limiting deterministic defect engineering. Here, we show that non-equilibrium growth kinetics can be harnessed to define dopant-driven strain architectures in vanadium-doped WS$_2$ monolayers. Using synchrotron X-ray fluorescence, we identify preferential vanadium incorporation, anti-correlated with tungsten content, along crystallographic bisectors. An adsorption-growth-diffusion model with a single kinetic parameter quantitatively captures the dopant segregation arising from preferential corner adsorption and limited diffusion during chemical vapor deposition growth. Hyperspectral Raman imaging demonstrates mechanically induced vibrational responses, revealing localized tensile strain ($\varepsilon \approx0.70\%$) channels associated with the anisotropic dopant distribution. This regime is marked by the depletion of W-site-sensitive in-plane modes and the emergence of a localized $J2$ mode (210~cm$^{-1}$), which our ab-initio calculations attribute to antiphase V$-$V oscillations. These findings establish kinetic segregation as a route to deterministic chemical and strain architectures in 2D semiconductors, enabling programmable defect landscapes and strain engineering during synthesis.
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All authors Frederico B. Sousa, Raphaela de Oliveira, Matheus J. S. Matos, Elizabeth Grace Houser, Igor Ferreira Curvelo, Zhuohang Yu, Mingzu Liu, Felipe Menescal, Gilmar Eugenio Marques, Leandro M. Malard, Mauricio Terrones, Bruno R. Carvalho, Helio Chacham, Marcio D. Teodoro

Instrumentation and Detectors

Upgrade of the Belle II Vertex Detector with Depleted Monolithic CMOS Active Pixel Sensors

Belle II VTX Collaboration

The Belle II experiment, operating at the asymmetric SuperKEKB $e^+e^-$ collider, is preparing an upgrade of its vertex detector to cope with an increased luminosity of $6 \times 10^{35}$ cm$^{-2}$s$^{-1}$. The upgraded vertex detector (VTX) will consist of five or six layers of depleted monolithic active pixel sensors (DMAPS), with a total material budget of approximately $3\%$ $X/X_0$. The OBELIX chip, derived from the TJ-Monopix2 sensor and fabricated using Tower-Jazz Semiconductor 180 nm CMOS technology, is being developed for this upgrade. It features a 33 $\mu$m pixel pitch with a time-stamping binning of $50-100$ ns, along with a dedicated digital periphery compatible with the Belle II trigger system, supporting rates up to 30 kHz. The sensor is designed to operate under the high background conditions expected at the target luminosity, with radiation tolerance up to $5 \times 10^{14}$ $n_{eq}$/cm$^2$ and 100 Mrad, while targeting a power density of about 200 mW/cm$^2$. This corresponds to hit rates up to 120 MHz/cm$^2$. Beam test and irradiation studies of TJ-Monopix2 demonstrate that the operating sensor temperature should stay below $40^\circ$C after irradiation up to $5 \times 10^{14}$ $n_{eq}$/cm$^2$. This report reviews the proposed VTX concept, sensor performance, and ongoing R$\&$D activities.
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Medical Physics

Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report

Viktor Rogowski, Maarten L. Terpstra, Niklas Wahl et al. (+30 more)

Radiation therapy (RT) requires precise dose delivery over multiple fractions, with CT fundamental for treatment planning due to its electron density information. Repeated CT acquisitions impose radiation exposure and logistical burdens, MRI lacks electron density, and cone-beam CT (CBCT) requires correction for dose calculation. Synthetic CT (sCT) generation addresses these by converting MRI or CBCT into CT-equivalent images with accurate Hounsfield Unit (HU) values, enabling MRI-only RT and CBCT-based adaptive workflows. Building on SynthRAD2023, SynthRAD2025 benchmarked sCT methods on 2,362 patients from five European centers across head and neck, thorax, and abdomen. Two tasks: MRI-to-CT (890 cases) and CBCT-to-CT (1,472 cases), evaluated via image similarity (MAE, PSNR, MS-SSIM), segmentation (Dice, HD95), and dosimetric metrics from photon and proton plans. With 803 participants and 12/13 valid submissions, Task 1 top performance reached MAE $64.8\pm21.3$ HU, PSNR $\sim$30 dB, MS-SSIM $\sim$0.936, Dice 0.79, photon $\gamma_{2\%/2\text{mm}}>98\%$, proton $\gamma\approx85\%$. Task 2 improved: MAE $48.3\pm13.4$ HU, PSNR 32.6 dB, MS-SSIM 0.968, Dice 0.86, photon $\gamma>99\%$, proton $\gamma\approx89\%$. Strong image–segmentation correlations ($\rho=0.78$–$0.79$) but moderate dose correlations confirmed image quality is insufficient as a dosimetric surrogate. Head-and-neck cases were most consistent; thoracic and abdominal cases showed greater variability. Residual errors at tissue interfaces propagate along beam paths, affecting proton dose more than photon. SynthRAD2025 demonstrates that deep learning yields clinically relevant sCTs, especially for CBCT-to-CT, while identifying persistent MRI-to-CT challenges and underscoring dose-based evaluation as essential for clinical validation.
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All authors Viktor Rogowski, Maarten L. Terpstra, Niklas Wahl, Florian Kamp, Erik van der Bijl, Arthur Jr. Galapon, Christopher Kurz, Bowen Xin, Zhengxiang Sun, Hollie Min, Gregg Belous, Jason Dowling, Yan Xia, Siyuan Mei, Fuxin Fan, Arthur Longuefosse, Javier Sequeiro Gonzalez, Miguel Diaz Benito, Alvaro Garcia Martin, Fabien Baldacci, Valentin Boussot, Cédric Hémon, Jean-Claude Nunes, Jean-Louis Dillenseger, Zhiyuan Zhang, Jinghua Cai, Han Bing, Tan Zuopeng, Ricardo Brioso, Daniele Loiacono, Guillaume Landry, Adrian Thummerer, Matteo Maspero

Fluid Dynamics

Unexpected Marangoni Condensation in Negative Binary Mixtures

Abenezer Abere and Patricia B. Weisensee

Marangoni condensation - where surface tension gradients induce instabilities that lead to condensate film breakup into discrete droplets - has traditionally been thought of being restricted to 'positive' binary mixtures, where the less volatile component has higher surface tension. 'Negative' mixtures were expected to exhibit stable filmwise condensation. Here, we demonstrate unexpected spontaneous Marangoni-driven pseudo-dropwise condensation in 'negative' water-ethylene glycol and water-triethylene glycol mixtures. Strong thermo-diffusion in these dilute mixtures enables preferential glycol enrichment in colder condensate film regions during condensation, generating surface tension gradients that trigger film breakup, leading to over 6x wettability-independent heat transfer enhancement compared to filmwise condensation. Our work challenges the conventional framework that restricts Marangoni condensation to 'positive' mixtures - a superficial classification that oversimplifies the underlying interfacial mechanisms that can trigger robust Marangoni condensation, offering new pathways for enhancing phase change heat transfer in industrial applications without the need for expensive and degradation-prone surface coatings.
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