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Physics Physics

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Saturday 8 November

Fluid Dynamics

Turbulence at Low Reynolds Numbers

Ziyue Yu, Xinyu Si and Lei Fang

Turbulence – ubiquitous in nature and engineering alike [1-5] – is traditionally viewed as an intrinsically inertial phenomenon, emerging only when the Reynolds number (Re), which quantifies the ratio of inertial to dissipative forces [6], far exceeds unity [7, 8]. Here, we demonstrate that strong energy flux between different length scales of motion – a defining hallmark of turbulence [9] – can persist even at Re ~ 1, thereby extending the known regime of turbulent flows beyond the classical high-Re paradigm. We show that scale-to-scale energy transfer can be recast as a mechanical process between turbulent stress and large-scale flow deformation. In quasi-two-dimensional (quasi-2D) flows driven by electromagnetic forcing, we introduce directionally biased perturbations that enhance this interaction, amplifying the spectral energy flux by more than two orders of magnitude, even in the absence of dominant inertial forces. This study establishes a new regime of 2D Navier-Stokes (N-S) turbulence, challenging long-standing assumptions about the high Re conditions required for turbulent flows. Beyond revising classical belief, our results offer a generalizable strategy for engineering multiscale transport in flows that lack inertial dominance, such as those found in microfluidic [10, 11] and low-Re biological [12-15] systems.
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Chemical Physics

Unifying Decoherence and Phase Evolution in Mixed Quantum-Classical Dynamics through Exact Factorization

Jong-Kwon Ha, Seong Ho Kim and Seung Kyu Min

We propose mixed quantum-classical equations of motion that unify electronic coherence and phase evolution simultaneously within the exact factorization framework. Our derivation shows that incorporating the second-order electron-nuclear correlation terms from the exact coupled time-dependent Schrödinger equations is essential to recover both correct phase dynamics and complete electronic (de)coherence, including their effect on nuclear forces. Benchmark calculations on one- and two-dimensional model systems confirm that the approach accurately captures key nonadiabatic features. The equations therefore provide a rigorous first-principles foundation for mixed quantum-classical description of coupled electron-nuclear dynamics, bringing electronic coherence and phase evolution-long treated through separate heuristic corrections-into a single unified and systematically derived framework.
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Friday 7 November

Chemical Physics

Differentiable Electrochemistry: A paradigm for uncovering hidden physical phenomena in electrochemical systems

Haotian Chen, Chenyang Huang, Alexander Rodríguez et al. (+2 more)

Despite the long history of electrochemistry, there is a lack of quantitative algorithms that rigorously correlate experiment with theory. Electrochemical modeling has had advanced across empirical, analytical, numerical, and data-driven paradigms. Data-driven machine learning and physics based electrochemical modeling, however, have not been explicitly linked. Here we introduce Differentiable Electrochemistry, a mew paradigm in electrochemical modeling that integrates thermodynamics, kinetics and mass transport with differentiable programming enabled by automatic differentiation. By making the entire electrochemical simulation end-to-end differentiable, this framework enables gradient-based optimization for mechanistic discovery from experimental and simulation data, achieving approximately one to two orders of improvement over gradient-free methods. We develop a rich repository of differentiable simulators across diverse mechanisms, and apply Differentiable Electrochemistry to bottleneck problems in kinetic analysis. Specifically, Differentiable Electrochemistry advances beyond Tafel and Nicholson method by removing several limitations including Tafel region selection, and identifies the electron transfer mechanism in Li metal electrodeposition/stripping by parameterizing the full Marcus-Hush-Chidsey formalism. In addition, Differentiable Electrochemistry interprets Operando X-ray measurements in concentrated electrolyte by coupling concentration and velocity theories. This framework resolves ambiguity when multiple electrochemical theories intertwine, and establishes a physics-consistent and data-efficient foundation for predictive electrochemical modeling.
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All authors Haotian Chen, Chenyang Huang, Alexander Rodríguez, Aashutosh Mistry, Venkatasubramanian Viswanathan

Chemical Physics

Omics-scale polymer computational database transferable to real-world artificial intelligence applications

Ryo Yoshida, Yoshihiro Hayashi, Hidemine Furuya et al. (+103 more)

Developing large-scale foundational datasets is a critical milestone in advancing artificial intelligence (AI)-driven scientific innovation. However, unlike AI-mature fields such as natural language processing, materials science, particularly polymer research, has significantly lagged in developing extensive open datasets. This lag is primarily due to the high costs of polymer synthesis and property measurements, along with the vastness and complexity of the chemical space. This study presents PolyOmics, an omics-scale computational database generated through fully automated molecular dynamics simulation pipelines that provide diverse physical properties for over $10^5$ polymeric materials. The PolyOmics database is collaboratively developed by approximately 260 researchers from 48 institutions to bridge the gap between academia and industry. Machine learning models pretrained on PolyOmics can be efficiently fine-tuned for a wide range of real-world downstream tasks, even when only limited experimental data are available. Notably, the generalisation capability of these simulation-to-real transfer models improve significantly as the size of the PolyOmics database increases, exhibiting power-law scaling. The emergence of scaling laws supports the "more is better" principle, highlighting the significance of ultralarge-scale computational materials data for improving real-world prediction performance. This unprecedented omics-scale database reveals vast unexplored regions of polymer materials, providing a foundation for AI-driven polymer science.
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All authors Ryo Yoshida, Yoshihiro Hayashi, Hidemine Furuya, Ryohei Hosoya, Kazuyoshi Kaneko, Hiroki Sugisawa, Yu Kaneko, Aiko Takahashi, Yoh Noguchi, Shun Nanjo, Keiko Shinoda, Tomu Hamakawa, Mitsuru Ohno, Takuya Kitamura, Misaki Yonekawa, Stephen Wu, Masato Ohnishi, Chang Liu, Teruki Tsurimoto, Arifin, Araki Wakiuchi, Kohei Noda, Junko Morikawa, Teruaki Hayakawa, Junichiro Shiomi, Masanobu Naito, Kazuya Shiratori, Tomoki Nagai, Norio Tomotsu, Hiroto Inoue, Ryuichi Sakashita, Masashi Ishii, Isao Kuwajima, Kenji Furuichi, Norihiko Hiroi, Yuki Takemoto, Takahiro Ohkuma, Keita Yamamoto, Naoya Kowatari, Masato Suzuki, Naoya Matsumoto, Seiryu Umetani, Hisaki Ikebata, Yasuyuki Shudo, Mayu Nagao, Shinya Kamada, Kazunori Kamio, Taichi Shomura, Kensaku Nakamura, Yudai Iwamizu, Atsutoshi Abe, Koki Yoshitomi, Yuki Horie, Katsuhiko Koike, Koichi Iwakabe, Shinya Gima, Kota Usui, Gikyo Usuki, Takuro Tsutsumi, Keitaro Matsuoka, Kazuki Sada, Masahiro Kitabata, Takuma Kikutsuji, Akitaka Kamauchi, Yusuke Iijima, Tsubasa Suzuki, Takenori Goda, Yuki Takabayashi, Kazuko Imai, Yuji Mochizuki, Hideo Doi, Koji Okuwaki, Hiroya Nitta, Taku Ozawa, Hitoshi Kamijima, Toshiaki Shintani, Takuma Mitamura, Massimiliano Zamengo, Yuitsu Sugami, Seiji Akiyama, Yoshinari Murakami, Atsushi Betto, Naoya Matsuo, Satoru Kagao, Tetsuya Kobayashi, Norie Matsubara, Shosei Kubo, Yuki Ishiyama, Yuri Ichioka, Mamoru Usami, Satoru Yoshizaki, Seigo Mizutani, Yosuke Hanawa, Shogo Kunieda, Mitsuru Yambe, Takeru Nakamura, Hiromori Murashima, Kenji Takahashi, Naoki Wada, Masahiro Kawano, Yosuke Harada, Takehiro Fujita, Erina Fujita, Ryoji Himeno, Hiori Kino, Kenji Fukumizu

Fluid Dynamics

Quaternion wavefunction theory bridges quantum formalism and classical fluid dynamics: a zero-parameter derivation of sphere drag

Farrukh A. Chishtie

We present a quaternion wavefunction formulation that reduces the incompressible Euler equations to a single nonlinear Schrödinger-type equation with a holomorphic constraint, revealing hidden geometric structure connecting quantum and classical fluid mechanics. The velocity field emerges from a complex quaternion wavefunction $\Psi \in \mathbb{C} \otimes \mathbb{H}$ satisfying a constrained Gross-Pitaevskii equation, with incompressibility enforced through quaternion analyticity conditions that generalize the Cauchy-Riemann equations to three dimensions. This geometric structure provides a selection principle for physically realized Euler solutions, resolving D'Alembert's 270-year-old paradox through geometry rather than phenomenology. The key insight is that incompressibility corresponds to quaternion holomorphicity, known as the Cauchy-Riemann-Fueter conditions, which selects physical solutions from among the infinitely many weak solutions established by De~Lellis and Székelyhidi. Application to steady flow past a sphere yields the Newton regime drag coefficient $C_{D,\infty} = 4/9 \approx 0.44$ as a zero-parameter prediction from quaternion orthogonality constraints, achieving 0.04% agreement with experiment. This represents the first derivation of this fundamental fluid mechanics constant from first principles. The mechanism parallels how the Kutta condition determines airfoil circulation: quaternion orthogonality constraints break fore-aft pressure symmetry, producing finite drag within inviscid theory.
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Physics and Society

Analyzing the Impact of Service Frequency and On-time Performance on Transit Ridership in Miami-Dade County

Duanya Lyu and Xiang Yan

This study investigates the impact of transit service attributes, focusing on service frequency and on-time performance (OTP), on bus ridership in Miami-Dade County. We obtained route-level ridership from automated passenger counter (APC) data and service performance metrics from the General Transit Feed Specification Real Time (GTFS-RT) data. The panel dataset allows us to effectively isolate the independent effects of OTP and frequency on bus ridership, contributing to a better understanding of how to improve service quality and support ridership. Our analysis examines both a pre-COVID period (January 2018-December 2019) and a post-COVID recovery period (July 2021-July 2023). Descriptive analysis reveals a steady ridership decline before the pandemic, followed by a sharp drop during the pandemic and a gradual recovery to pre-pandemic levels by late 2022. This recovery, however, varied by route and was accompanied by significant temporal fluctuations in service performance measures. To analyze these dynamics, we developed two-way fixed effects (2FE) models. Model outputs show that while frequency consistently influences ridership over time, OTP becomes an increasingly important determinant in the post-COVID recovery period. The observed significant interaction between frequency and OTP in the recovery period further suggests that improving reliability is particularly effective on frequent routes. Our study also highlights the need for targeted ridership-boosting strategies that differ by time of day, with a focus on punctuality during AM-peak and frequency during midday and PM-peak, to better support ridership growth and improve network performance.
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General Physics

Einstein and Debye temperatures, electron-phonon coupling constant and a probable mechanism for ambient-pressure room-temperature superconductivity in intercalated graphite

E.F. Talantsev

Recently, Ksenofontov et al (arXiv:2510.03256) observed ambient pressure room-temperature superconductivity in graphite intercalated with lithium-based alloys with transition temperature (according to magnetization measurements) $T_c=330$ $K$. Here, I analyzed the reported temperature dependent resistivity data $\rho(T)$ in these graphite-intercalated samples and found that $\rho(T)$ is well described by the model of two series resistors, where each resistor is described as either an Einstein conductor or a Bloch-Grüneisen conductor. Deduced Einstein and Debye temperatures are $\Theta_{E,1} \approx 250$ $K$ and $\Theta_{E,2} \approx 1,600$ $K$, and $\Theta_{D,1} \approx 300$ $K$ and $\Theta_{D,2} \approx 2,200$ $K$, respectively. Following the McMillan formalism, from the deduced $\Theta_{E,2}$ and $\Theta_{D,2}$, the electron-phonon coupling constant $\lambda_{e-ph} = 2.2 - 2.6$ was obtained. This value of $\lambda_{e-ph}$ is approximately equal to the value of $\lambda_{e-ph}$ in highly compressed superconducting hydrides. Based on this, I can propose that the observed room-temperature superconductivity in intercalated graphite is localized in nanoscale Sr-Ca-Li metallic flakes/particles, which adopt the phonon spectrum from the surrounding bulk graphite matrix, and as a result, conventional electron-phonon superconductivity arises in these nano-flakes/particles at room temperature. Experimental data reported by Ksenofontov et al (arXiv:2510.03256) on trapped magnetic flux decay in intercalated graphite samples supports the proposition.
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Optics

Stokes microcombs in silicon nitride microresonators

Artem E. Shitikov, Alina N. Golodukhina, Nikita Yu. Dmitriev et al. (+4 more)

Silicon nitride microresonators have become an ubiquitous platform for cutting-edge photonics applications. Improvement in silicon nitride fabrication techniques, providing ultra-high quality-factor values up to $10^7$, has opened up new possibilities for nonlinear effects realizations in such structures. Here we report for the first time to our knowledge on the observation of the Stokes microcombs in silicon nitride on-chip microresonators exhibiting normal group velocity dispersion. Moreover, using different pump schemes, namely, a tunable laser with an isolator and a stabilized diode laser, we demonstrate on-chip stimulated Raman frequency combs including dark-pulse Raman states. We reveal a complex interplay between Kerr and Raman nonlinearities and elaborate effective method of controllable switching between predominantly Kerr-comb and predominantly Raman-comb operation. We prove the Raman-induced platicon formation by numerical model which shows perfect agreement with experimental results. These findings are of special importance for silicon nitride photonics and provide a basis for novel photonic devices.
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All authors Artem E. Shitikov, Alina N. Golodukhina, Nikita Yu. Dmitriev, Darya M. Sokol, Valery E. Lobanov, Igor A. Bilenko, Dmitry A. Chermoshentsev

Physics Education

"Niñas Atómicas" (Atomic Girls): An initiative that generates opportunities for young girls in STEM

Giovanna Cottin and Francisca Garay

We report on an initiative that seeks to encourage high school girls to develop critical thinking and transferable skills widely used in scientific work, as well as to generate a concrete space of opportunities for girls to experience how real science is done. Our "Niñas Atómicas" workshop combines the teaching of particle physics, electronics, programming and scientific methodology through building and operating a dedicated experiment: a muon counter. Girls from all over Chile can apply to this workshop, where every year they are guided by female scientists for two weeks. We report on the contents and methodology of our workshop and provide details on how to build the muon detector. We report results on muon flux and proper lifetime, two muon properties which can be extracted from the data collected by the girls with the muon detectors they built themselves. Insights into the girl's experiences during the 2024 and 2025 editions of the workshop are also detailed, with the aim to contribute to the wider physics education research and outreach communities.
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2511.05754 · 7 Nov · 10 pages, 9 figures. In v2, updated figures, text and references. v3 matches published version in Giovanna Cottin and Francisca Garay 2026 Phys. Educ. 61 035051, DOI 10.1088/1361-6552/ae65fa. Conclusions unchanged. Associated files can be found at https://github.com/gfcottin/Atomicas

Abstract PDF $MUON ×5

Computational Physics · Cross-listed from cond-mat.dis-nn

Cluster percolation in the three-dimensional $\pm J$ random-bond Ising model

Lambert Münster and Martin Weigel

Based on extensive parallel-tempering Monte Carlo simulations, we investigate the relationship between cluster percolation and equilibrium ordering phenomena in the three-dimensional $\pm J$ random-bond Ising model as one varies the fraction of antiferromagnetic bonds. We consider a range of cluster definitions, most of which are constructed in the space of overlaps between two independent real replicas of the system. In the pure ferromagnet that is contained as a limiting case in the class of problems considered, the relevant percolation point coincides with the thermodynamic ordering transition. For the disordered ferromagnet encountered first on introducing antiferromagnetic bonds and the adjacent spin-glass phase of strong disorder this connection is altered, and one finds a percolation transition above the thermodynamic ordering point that is accompanied by the appearance of /two/ percolating clusters of equal density. Only at the lower (disordered) ferromagnetic or spin-glass transition points the densities of these two clusters start to diverge, thus providing a percolation signature of these thermodynamic transitions. We compare the scaling behavior at this secondary percolation transition with the thermodynamic behavior at the corresponding ferromagnetic and spin-glass phase transitions.
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Optics · Cross-listed from quant-ph

Quantum Nanophotonic Interface for Tin-Vacancy Centers in Thin-Film Diamond

Hope Lee, Hannah C. Kleidermacher, Abigail J.M. Stein et al. (+10 more)

The negatively charged tin-vacancy center in diamond (SnV$^-$) is an excellent solid state qubit with optically-addressable transitions and a long electron spin coherence time at elevated ($\sim1.7$ K). However, implementing scalable quantum nodes with high-fidelity optical readout of the electron spin state requires efficient photon emission and collection from the system. In this manuscript, we report a quantum photonic interface for SnV$^-$ centers based on one-dimensional photonic crystal cavities fabricated in diamond thin films. Furthermore, we provide a rigorous description of the spontaneous emission dynamics of our system, taking into account individual contributions from both the C and D transitions of the emitter. This allows for determination of Purcell factors per transition and, by extension, the C/D branching ratio SnV$^{-}$ zero phonon line. We observe quality factors up to $\sim$6000 across this sample, and measure up to a 12-fold lifetime reduction, which translates into a Purcell factor of $F_C=26.2\pm1.5$ for a targeted C transition. By considering the cavity mode polarization alignment with the C and D transition dipole moments, we validate the C/D branching ratio to be $\eta_{\text{BR}}=0.75\pm0.01$, in line with previous theoretical and experimental findings.
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All authors Hope Lee, Hannah C. Kleidermacher, Abigail J.M. Stein, Hyunseok Oh, Lillian B. Hughes Wyatt, Casey K. Kim, Luca Basso, Andrew M. Mounce, Yongqiang Wang, Shei S. Su, Michael Titze, Ania C. Bleszynski Jayich, Jelena Vučković

Chemical Physics

Performance of Automatic Active Space Selection for Electronic Excitation Energies

Reza G. Shirazi, Alexander Zech, Peter Pinski et al. (+1 more)

Computation of electronic spectra is one of the most important applications of methods capturing static electron correlation, including complete-active-space self-consistent field (CASSCF) and post-CASSCF theories. Performance of these techniques critically depends on the active space construction, both in terms of accuracy and computational effort. In this work we benchmark the performance of automatic active space construction, as implemented in the Active Space Finder software, for the computation of electronic excitation energies. The multi-step procedure constructs meaningful molecular orbitals and selects the most suitable active space based on information from more approximate correlated calculations. It aims to tackle a key difficulty in computing excitation energies with CASSCF: choosing active spaces that are balanced for several electronic states. The Active Space Finder is tested with several established data sets of small and medium-sized molecules and shows encouraging results. We evaluate multiple setting configurations and provide practical recommendations.
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All authors Reza G. Shirazi, Alexander Zech, Peter Pinski, Vladimir V. Rybkin

Optics · Cross-listed from astro-ph.IM

Fundamental Limits to Phase and Amplitude Estimation in the High-Strehl Regime

Jacob Trzaska and Amit Ashok

Context: Ground-based telescopes are susceptible to seeing, an atmospheric phenomenon that reduces the resolving power of large observatories to that of a home telescope. Compensating these effects is therefore critical to realizing the potential of upcoming extremely large telescopes, a challenging task that requires precise wavefront control. Ultimately, this precision is limited by one's wavefront sensor (WFS) and its capacity to accurately encode phase and amplitude aberrations. Aims: Our attention is on photon noise-limited wavefront sensing in the high-Strehl regime. In particular, we seek fundamental limits to phase and amplitude estimation in addition to a WFS that saturate these bounds. Methods: Information theory is employed for deriving minimum-achievable residual errors, as stipulated by a metric called the Holevo Cramer-Rao bound. Holevo's bound is closely related to another metric called the quantum Cramer-Rao bound, which has already been applied to phase estimation on nearly-corrected wavefronts. Results: We present a WFS that can perfectly extract and phase shift a telescope's piston mode. We show how this phase can be used to tune the apparatus' sensitivity to phase and amplitude, and provide a closed-form expression for the optimal phase shift. For circular apertures, this implementation saturates the fundamental limits, but it can be easily modified to work with arbitrary pupils. Moreover, our proposal uses optics that are manufactureable today and is readily achromatized with geometric phase shifters.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci

Surface acoustic wave enabled all-optical determination of the interlayer elastic constants of van der Waals interface

N.Yu. Frolov, A.Yu. Klokov, A. I. Sharkov et al. (+2 more)

Understanding the properties of two-dimensional materials interfaces with the substrate is necessary for device applications. Surface acoustic wave propagation through the layered material flake on a substrate could provide unique information on the transverse rigidity of the flake-to-substrate interaction. We generate ultrasonic waves by a focused femtosecond laser pulse at the surface of the model system – fused silica with h-BN flake transferred above. Using an all-optical spatially resolved pump-probe interferometric technique, we measure the spatial dependencies of the surface vertical velocity profiles. Our measurements reveal the appearance of the surface acoustic wave dispersion in the hBN flake region compared to fused silica surface. Multilayer modeling allows us to gain access to longitudinal and shear elastic coupling constants $c^*_{33}$ and $c^*_{44}$ between hexagonal BN and substrate.
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All authors N.Yu. Frolov, A.Yu. Klokov, A. I. Sharkov, M.V. Pugachev, A.Yu. Kuntsevich

Accelerator Physics

About maximum energy acquired by a charged particles in the field of a plane electromagnetic wave

V. A. Balakirev and I. N. Onishchenko

The energy characteristics of a relativistic charged particle in the field of a plane electromagnetic wave of a given amplitude are studied. The dependence of the particle's energy on its phase coordinate is obtained. The maximum value of the particle's energy during acceleration, as well as the acceleration length and time, are determined. The transverse displacement of the particle over the maximum acceleration length is determined.
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Chemical Physics

Baker-Campbell-Hausdorff expansion in creation-only coupled cluster

Ramón Alain Miranda-Quintana

We study the properties of the exponential ansatz formed by strings of creation operators. We discuss the conditions under which we can recover a structure similar to traditional coupled cluster methods. We pay particular attention to the Baker-Campbell-Hausdorff expansion of these operators.
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Optics

Self-focusing of high-intensity beams with grid structures

Jiaqi Wang, Yang Xu, Saumya Choudhary et al. (+2 more)

Laser beams with high optical power propagating in a Kerr medium can undergo self-focusing when their power exceeds a critical power determined by the optical properties of the medium. The highly concentrated energy close to the in the region of the self-focus can lead to other nonlinear phenomena and cause significant irreversible damage to the material. We propose a transverse grid beam structure that effectively suppresses self-focusing even in the absence of other competing effects through the redistribution of optical power by inter-beamlet nonlinear interaction. We find that a beam with a $N \times N$ grid structure with optimized lattice spacing undergoes a dimension-dependent multi-stage self-focusing. We also identify specific grid layouts that can increase the total transmitted power beyond that permitted by the critical level of self-focusing for each beamlet. Lastly, we derive a general numerical relation between the optimal grid lattice spacing and the size of beamlets. Our results could potentially inform the use of beam shaping to prevent damage to optical components in high-powered and directed-energy applications.
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All authors Jiaqi Wang, Yang Xu, Saumya Choudhary, Omid Mozafar, Robert Boyd

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

Single-Atom Photocatalysts on TiO2 : Insights from X-ray Absorption Spectroscopy

Yingying Li, David Morris and Peng Zhang

Surface modification of TiO2 with single-atom catalysts (SACs) is an effective strategy for enhancing photocatalytic efficiency. However, thorough characterization of SACs at the atomic scale remains challenging. X-ray absorption spectroscopy (XAS) offers unique advantages for the in-depth analysis of TiO2-supported SACs. By employing XAS, the local atomic structure, oxidation state, and electronic properties of the SACs, as well as the underlying photocatalytic mechanism, can be revealed. Herein, we present a short review on the application of XAS in studying TiO2-supported SACs. We first elucidate the key role of XAS in simultaneously probing the structure and electronic properties of monometallic SACs across different periods. Next, we discuss XAS studies of bimetallic SACs from the perspective of each constituent element and highlight the element-specific capabilities of XAS for analyzing multi-element SACs. Finally, we demonstrate how in situ XAS can effectively monitor structural and electronic property changes in SACs under real photocatalytic reaction conditions. Additionally, we provide practical suggestions for utilizing XAS more efficiently in the analysis of various SAC systems.
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Optics

Sputtered AlN buffer layer for low-loss crystalline AlN-on-sapphire integrated photonics

Samuele Brunetta, Samantha Sbarra, Brandon Shuen Yi Loke et al. (+4 more)

In recent years, aluminum nitride (AlN) has emerged as an attractive material for integrated photonics due to its low propagation losses, wide transparency window, and presence of both second- and third-order optical nonlinearities. However, most of the research led on this platform has primarily focused on applications, rather than material optimization, although the latter is equally important to ensure its technological maturity. In this work, we show that voids, which are commonly found in crystalline AlN-on-sapphire epilayers, have a detrimental role in related photonic structures, as they can lead to propagation losses exceeding 30 dB cm$^{-1}$ at 1550 nm. Their impact on light propagation is further quantified through finite-difference time-domain simulations that reveal that void-related scattering losses are strongly dependent on their size and density in the layer. As a possible solution, we demonstrate that when introducing a thin sputtered AlN buffer layer prior to initiating AlN epitaxial growth, void-free layers are obtained. They exhibit intrinsic quality factors in microring resonators as high as $2.0\times 10^6$, corresponding to propagation losses lower than 0.2 dB cm$^{-1}$ at 1550 nm. These void-free layers are further benchmarked for high-power applications through second-harmonic and supercontinuum generation in dispersion-engineered waveguides. Such layers are highly promising candidates for short-wavelength photonic integrated circuit applications, particularly given the strong potential of AlN for visible photonics. Given that volumetric scattering losses scale as $\lambda^{-4}$, the platform quality becomes increasingly critical in the visible and ultraviolet range, where our improved layers are expected to deliver enhanced performance.
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All authors Samuele Brunetta, Samantha Sbarra, Brandon Shuen Yi Loke, Jean-François Carlin, Nicolas Grandjean, Camille-Sophie Brès, Raphaël Butté

Accelerator Physics · Cross-listed from cs.SE

Accelerating Control Systems with GitOps: A Path to Automation and Reliability

M. Gonzalez and M. Acosta

GitOps is a foundational approach for modernizing infrastructure by leveraging Git as the single source of truth for declarative configurations. The poster explores how GitOps transforms traditional control system infrastructure, services and applications by enabling fully automated, auditable, and version-controlled infrastructure management. Cloud-native and containerized environments are shifting the ecosystem not only in the IT industry but also within the computational science field, as is the case of CERN [1] and Diamond Light Source [2] among other Accelerator/Science facilities which are slowly shifting towards modern software and infrastructure paradigms. The ACORN project, which aims to modernize Fermilab's control system infrastructure and software is implementing proven best-practices and cutting-edge technology standards including GitOps, containerization, infrastructure as code and modern data pipelines for control system data acquisition and the inclusion of AI/ML in our accelerator complex.
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Instrumentation and Detectors

Transmission Efficiency of the Recoil Mass Spectrometer EMMA at TRIUMF

B. Davids, N.E. Esker, J. Jaeyoung et al. (+3 more)

The mean transmission efficiency of the EMMA recoil mass spectrometer at TRIUMF has been measured with 6 different angular apertures at 17 kinetic energy/charge deviations with respect to the central, reference trajectory. Measurements performed using a 148Gd alpha source installed at the target position of the spectrometer are compared to ion-optical calculations and Monte Carlo simulations. The transmission efficiency as a function of angle and kinetic energy/charge is described empirically using piecewise Gaussian functions whose parameters are fit to the data.
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All authors B. Davids, N.E. Esker, J. Jaeyoung, Y.K. Kim, K. Pak, M. Williams

Instrumentation and Detectors · Cross-listed from astro-ph.IM

Performance of the AstroPix Prototype Module for the Barrel Imaging Calorimeter at the ePIC Detector and in Space-Based Payloads

Bobae Kim, Regina Caputo, Manoj Jadhav et al. (+7 more)

AstroPix is a high-voltage CMOS (HV-CMOS) monolithic active pixel sensor originally developed to enable precision gamma-ray imaging and spectroscopy in the medium-energy regime (approximately 100 keV-100 MeV) based on the groundwork laid by ATLASpix and MuPix. It features a 500 um pixel pitch, in-pixel amplification and digitization, and low power consumption (around 3-4 mW/cm^2), making it scalable for large-area, multilayer telescope detector planes. The detectors have a designed dynamic range of 25 keV to 700 keV. With these features, AstroPix meets the requirements of future space-based high-energy telescopes and the imaging layers of the Barrel Imaging Calorimeter (BIC) in the Electron-Proton/Ion Collider (ePIC) detector at the future Electron-Ion Collider (EIC). For the space-based payload, AstroPix is being integrated into sounding rocket and balloon payloads to demonstrate the technical readiness of the devices. For BIC, AstroPix-based imaging layers interleaved within the lead/scintillating-fiber (Pb/SciFi) sampling calorimeter provide granular shower imaging, enabling key performance features such as electron/pion or gamma/neutral-pion separation. As part of the ongoing detector R&D efforts, we have been testing various AstroPix v3 configurations: the single chip, a quad-chip assembly, a three-layer stack of quad chips, and a nine-chip module that represents the smallest prototype unit of the BIC imaging layer. This presentation will highlight recent performance test results from these AstroPix detector configurations.
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All authors Bobae Kim, Regina Caputo, Manoj Jadhav, Sylvester Joosten, Adrien Laviron, Richard Leys, Jessica Metcalfe, Nicolas Striebig, Daniel Violette, Maria Żurek

Biological Physics

Long-bone microanatomy in elephants: microstructural insights into gigantic beasts

Camille Bader, Rémy Gilardet, Nicolas Rinder et al. (+3 more)

One of the greatest challenges of terrestrial locomotion is resisting gravity. The morphological adaptive features of the limb long-bones of extant elephants, the heaviest living terrestrial animals, have previously been highlighted; however, their bone microanatomy remains largely unexplored. Here we investigate the microanatomy of the six limb long-bones in Elephas maximus and Loxodonta africana, using comparisons of virtual slices as well as robustness analyses, to understand how they were adapted to heavy weight-bearing. We find that the long bones of elephant limbs display a relatively thick cortex and a medullary area almost entirely filled with trabecular bone. This trabecular bone is highly anisotropic with trabecular orientations reflecting the mechanical load distribution along the limb. The respective functional roles of the bones are reflected in their microanatomy through variations of cortical thickness distribution and main orientation of the trabeculae. We find microanatomical adaptations to heavy weight support that are common to other heavy mammals. Despite these shared characteristics, the long bones of elephants are closer to those of sauropods due to their shared columnar posture, which allows a relaxation of morphofunctional constraints, and thus relatively less robust bones with a thinner cortex than would be expected in such massive animals.
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All authors Camille Bader, Rémy Gilardet, Nicolas Rinder, Victoria Herridge, John R Hutchinson, Alexandra Houssaye

Fluid Dynamics · Cross-listed from cs.LG

Physics-Guided Machine Learning for Uncertainty Quantification in Turbulence Models

Minghan Chu and Weicheng Qian

Predicting the evolution of turbulent flows is central across science and engineering. Most studies rely on simulations with turbulence models, whose empirical simplifications introduce epistemic uncertainty. The Eigenspace Perturbation Method (EPM) is a widely used physics-based approach to quantify model-form uncertainty, but being purely physics-based it can overpredict uncertainty bounds. We propose a convolutional neural network (CNN)-based modulation of EPM perturbation magnitudes to improve calibration while preserving physical consistency. Across canonical cases, the hybrid ML-EPM framework yields substantially tighter, better-calibrated uncertainty estimates than baseline EPM alone.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG

SSTODE: Ocean-Atmosphere Physics-Informed Neural ODEs for Sea Surface Temperature Prediction

Zheng Jiang, Wei Wang, Gaowei Zhang et al. (+1 more)

Sea Surface Temperature (SST) is crucial for understanding upper-ocean thermal dynamics and ocean-atmosphere interactions, which have profound economic and social impacts. While data-driven models show promise in SST prediction, their black-box nature often limits interpretability and overlooks key physical processes. Recently, physics-informed neural networks have been gaining momentum but struggle with complex ocean-atmosphere dynamics due to 1) inadequate characterization of seawater movement (e.g., coastal upwelling) and 2) insufficient integration of external SST drivers (e.g., turbulent heat fluxes). To address these challenges, we propose SSTODE, a physics-informed Neural Ordinary Differential Equations (Neural ODEs) framework for SST prediction. First, we derive ODEs from fluid transport principles, incorporating both advection and diffusion to model ocean spatiotemporal dynamics. Through variational optimization, we recover a latent velocity field that explicitly governs the temporal dynamics of SST. Building upon ODE, we introduce an Energy Exchanges Integrator (EEI)-inspired by ocean heat budget equations-to account for external forcing factors. Thus, the variations in the components of these factors provide deeper insights into SST dynamics. Extensive experiments demonstrate that SSTODE achieves state-of-the-art performances in global and regional SST forecasting benchmarks. Furthermore, SSTODE visually reveals the impact of advection dynamics, thermal diffusion patterns, and diurnal heating-cooling cycles on SST evolution. These findings demonstrate the model's interpretability and physical consistency.
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All authors Zheng Jiang, Wei Wang, Gaowei Zhang, Yi Wang

Fluid Dynamics

Rediscovering shallow water equations from experimental data

Kjell S. Heinrich, Douglas S. Seth, Mats Ehrnstrom et al. (+1 more)

New data-driven methods have advanced the discovery of governing equations from observations, enabling parsimonious models for complex systems. Here, we 'rediscover' a shallow-water equation closely related to Korteweg–de Vries (KdV) using only video recordings of solitons in a simple flume. Two fundamentally different approaches – weak-form sparse identification of nonlinear dynamics (WSINDy) and a novel Fourier-multiplier method – recover the same PDE, demonstrating that the equation is inherent in the data and robust to the choice of method. Both identify the same terms with comparable magnitudes and errors. To validate the models, we solve the discovered equations forward in time and compare them with additional experimental cases that were not used in the discovery. Based on the results, we discuss absolute and cumulative errors, as well as the strengths and limitations of the two discovery approaches. Together, these results demonstrate the potential of equation discovery from everyday experiments ('GoPro physics') and highlight shallow-water waves as an ideal test bed for developing and benchmarking new methods.
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All authors Kjell S. Heinrich, Douglas S. Seth, Mats Ehrnstrom, Simen Å. Ellingsen

Instrumentation and Detectors · Cross-listed from cs.NE

Quantization Effects of Artificial Neural Networks for Embedded Edge-Computing Applications

Alperen Aksoy, Ilja Bekman, Vesselin Dimitrov et al. (+6 more)

This paper examines the use of Quantized Neural Networks (QNNs) for two resource-constrained scientific applications: automated calibration of semiconductor quantum bits (qubits) and scientific particle detectors. We evaluate the trade-offs between Post-Training Quantization (PTQ), Quantization-Aware Training (QAT), and ultra-low-bit Binary Neural Networks (BNNs) with respect to latency and resource usage. Our results demonstrate that PTQ and QAT are easily implementable solutions achieving a four-fold reduction in memory usage for Ushaped CNN (U-Net) architectures, whereas BNNs are better suitable for use cases with challenging latency requirements. For the training of non-differentiable custom BNNs, we propose a novel, hardware-constrained learning approach using Genetic Algorithms (GAs). We showcase a Look-Up Table (LUT)-based BNN architecture suitable for direct conversion to Very High-Speed Integrated Circuit Hardware Description Language (VHDL) via the HCL4BNN framework. This method achieves nanosecond-scale inference latencies at 10 ns to 15 ns without requiring specialized Digital Signal Processor (DSP) or Block RAM (BRAM) resources.
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All authors Alperen Aksoy, Ilja Bekman, Vesselin Dimitrov, Qader Dorosti, Chimezie Eguzo, Sarah Fleitmann, Fabian Hader, Andre Zambanini, Stefan van Waasen

Biological Physics

Glassy dynamics in active epithelia emerge from an interplay of mechanochemical feedback and crowding

Sindhu Muthukrishnan, Phanindra Dewan, Tanishq Tejaswi et al. (+6 more)

Glassy dynamics in active biological cells remain a subject of debate, as cellular activity rarely slows enough for true glassy features to emerge. In this study, we address this paradox of glassy dynamics in epithelial cells by integrating experimental observations with an active vertex model. We demonstrate that while crowding is essential, it is not sufficient for glassy dynamics to emerge. A mechanochemical feedback loop (MCFL), mediated by cell shape changes through the contractile actomyosin network, is required to drive glass transition in dense epithelial tissues, as revealed via a crosstalk between actin-based cell clustering and dynamic heterogeneity in experiments. Incorporating MCFL into the vertex model reveals contrasting results from those previously predicted by theories – we show that the MCFL can counteract cell division-induced fluidisation and enable glassy dynamics to emerge through active cell-to-cell communication. Furthermore, our analysis reveals, for the first time, the existence of novel collective mechanochemical oscillations that arise from the crosstalk of two MCFLs. Together, we demonstrate that an interplay between crowding and active mechanochemical feedback enables the emergence of glass-like traits and collective biochemical oscillations in epithelial tissues with active cell-cell contacts.
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All authors Sindhu Muthukrishnan, Phanindra Dewan, Tanishq Tejaswi, Michelle B Sebastian, Tanya Chhabra, Soumyadeep Mondal, Soumitra Kolya, Sumantra Sarkar, Medhavi Vishwakarma

Instrumentation and Detectors · Cross-listed from hep-ex

Identification of tau leptons using a convolutional neural network with domain adaptation

CMS Collaboration

A tau lepton identification algorithm, DeepTau, based on convolutional neural network techniques, has been developed in the CMS experiment to discriminate reconstructed hadronic decays of tau leptons ($\tau_\mathrm{h}$) from quark or gluon jets and electrons and muons that are misreconstructed as $\tau_\mathrm{h}$ candidates. The latest version of this algorithm, v2.5, includes domain adaptation by backpropagation, a technique that reduces discrepancies between collision data and simulation in the region with the highest purity of genuine $\tau_\mathrm{h}$ candidates. Additionally, a refined training workflow improves classification performance with respect to the previous version of the algorithm, with a reduction of 30$-$50% in the probability for quark and gluon jets to be misidentified as $\tau_\mathrm{h}$ candidates for given reconstruction and identification efficiencies. This paper presents the novel improvements introduced in the DeepTau algorithm and evaluates its performance in LHC proton-proton collision data at $\sqrt{s}$ = 13 and 13.6 TeV collected in 2018 and 2022 with integrated luminosities of 60 and 35 fb$^{-1}$, respectively. Techniques to calibrate the performance of the $\tau_\mathrm{h}$ identification algorithm in simulation with respect to its measured performance in real data are presented, together with a subset of results among those measured for use in CMS physics analyses.
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Atomic Physics · Cross-listed from quant-ph

Helios: A 98-qubit trapped-ion quantum computer

Anthony Ransford, M.S. Allman, Jake Arkinstall et al. (+183 more)

We report on Quantinuum Helios, a 98-qubit trapped-ion quantum processor based on the quantum charge-coupled device (QCCD) architecture. Helios features $^{137}$Ba$^{+}$ hyperfine qubits, all-to-all connectivity enabled by a rotatable ion storage ring connecting two quantum operation regions by a junction, speed improvements from parallelized operations, and a new software stack with real-time compilation of dynamic programs. Averaged over all operational zones in the system, we achieve average infidelities of $2.5(1)\times10^{-5}$ for single-qubit gates, $7.9(2)\times10^{-4}$ for two-qubit gates, and $4.8(6)\times10^{-4}$ for state preparation and measurement, none of which are fundamentally limited and likely able to be improved. These component infidelities are predictive of system-level performance in both random Clifford circuits and random circuit sampling, the latter demonstrating that Helios operates well beyond the reach of classical simulation and establishes a new frontier of fidelity and complexity for quantum computers.
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All authors Anthony Ransford, M.S. Allman, Jake Arkinstall, J.P. Campora III, Samuel F. Cooper, Robert D. Delaney, Joan M. Dreiling, Brian Estey, Caroline Figgatt, Alex Hall, Ali A. Husain, Akhil Isanaka, Colin J. Kennedy, Nikhil Kotibhaskar, Ivaylo S. Madjarov, Karl Mayer, Alistair R. Milne, Annie J. Park, Adam P. Reed, Riley Ancona, Molly P. Andersen, Pablo Andres-Martinez, Will Angenent, Liz Argueta, Benjamin Arkin, Leonardo Ascarrunz, William Baker, Corey Barnes, John Bartolotta, Jordan Berg, Ryan Besand, Bryce Bjork, Matt Blain, Paul Blanchard, Robin Blume-Kohout, Matt Bohn, Agustin Borgna, Daniel Y. Botamanenko, Robert Boutelle, Natalie Brown, Grant T. Buckingham, Nathaniel Q. Burdick, William Cody Burton, Varis Carey, Christopher J. Carron, Joe Chambers, John Children, Victor E. Colussi, Steven Crepinsek, Andrew Cureton, Joe Davies, Daniel Davis, Matthew DeCross, David Deen, Conor Delaney, Davide DelVento, B.J. DeSalvo, Jason Dominy, Ross Duncan, Vanya Eccles, Alec Edgington, Neal Erickson, Stephen Erickson, Christopher T. Ertsgaard, Bruce Evans, Tyler Evans, Maya I. Fabrikant, Andrew Fischer, Cameron Foltz, Michael Foss-Feig, David Francois, Brad Freyberg, Charles Gao, Robert Garay, Jane Garvin, David M. Gaudiosi, Christopher N. Gilbreth, Josh Giles, Erin Glynn, Jeff Graves, Azure Hansen, David Hayes, Lukas Heidemann, Bob Higashi, Tyler Hilbun, Jordan Hines, Ariana Hlavaty, Kyle Hoffman, Ian M. Hoffman, Craig Holliman, Isobel Hooper, Bob Horning, James Hostetter, Daniel Hothem, Jack Houlton, Jared Hout, Ross Hutson, Ryan T. Jacobs, Trent Jacobs, Melf Johannsen, Jacob Johansen, Loren Jones, Sydney Julian, Ryan Jung, Aidan Keay, Todd Klein, Mark Koch, Ryo Kondo, Chang Kong, Asa Kosto, Alan Lawrence, David Liefer, Michelle Lollie, Dominic Lucchetti, Nathan K. Lysne, Christian Lytle, Callum MacPherson, Andrew Malm, Spencer Mather, Brian Mathewson, Daniel Maxwell, Lauren McCaffrey, Hannah McDougall, Robin Mendoza, Michael Mills, Richard Morrison, Louis Narmour, Nhung Nguyen, Lora Nugent, Scott Olson, Daniel Ouellette, Jeremy Parks, Zach Peters, Jessie Petricka, Juan M. Pino, Frank Polito, Matthias Preidl, Gabriel Price, Timothy Proctor, McKinley Pugh, Noah Ratcliff, Daisy Raymondson, Peter Rhodes, Conrad Roman, Craig Roy, Ciaran Ryan-Anderson, Fernando Betanzo Sanchez, George Sangiolo, Tatiana Sawadski, Andrew Schaffer, Peter Schow, Jon Sedlacek, Henry Semenenko, Peter Shevchuk, Susan Shore, Peter Siegfried, Kartik Singhal, Seyon Sivarajah, Thomas Skripka, Lucas Sletten, Ben Spaun, R. Tucker Sprenkle, Paul Stoufer, Mariel Tader, Stephen F. Taylor, Travis H. Thompson, Raanan Tobey, Anh Tran, Tam Tran, Grahame Vittorini, Curtis Volin, Jim Walker, Sam White, Douglas Wilson, Quinn Wolf, Chester Wringe, Kevin Young, Jian Zheng, Kristen Zuraski, Charles H. Baldwin, Alex Chernoguzov, John P. Gaebler, Steven J. Sanders, Brian Neyenhuis, Russell Stutz, Justin G. Bohnet