Optics
Ultra-high-speed chemiluminescence tomography of spinning-mode detonation waves
Amit K. Singh, Mateo Gomez, Kevin Y. Cho et al. (+2 more)
This work presents a chemiluminescence
tomography campaign to reconstruct time-resolved, three-dimensional reacting structures in detonation waves propagating through ethylene-based mixtures at 1 atm. Images of chemiluminescence are recorded simultaneously by five cameras through a cylindrical sapphire test section, and a custom calibration procedure is developed to account for refraction through the cylinder. The images are combined to reconstruct an effective emission source term field at megahertz rates. Reconstructions are reported for a persistent spinning detonation, a failed spinning detonation, and a case with counter-propagating transverse fronts. The reconstructed fields enable visualization of wave morphologies, determination of the axial and azimuthal wave speeds, and estimation of key
geometric and kinematic parameters. These results demonstrate time-resolved chemiluminescence
tomography as a non-intrusive tool for resolving volumetric detonation dynamics that are difficult to infer from point, planar, or line-of-sight diagnostics.
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All authors Amit K. Singh, Mateo Gomez, Kevin Y. Cho, Aaron W. Skiba, Samuel J. Grauer
Applied Physics
NSF Future Manufacturing Data Challenge: A Multimodal DED Dataset for Probabilistic Representation and Prediction of Laser-Track Geometry
Abhishek Hanchate, Himanshu Balhara and Satish T. S. Bukkapatnam
We introduce a
multimodal directed energy deposition (DED)
dataset for predicting the probabilistic local
geometric variation of single
laser tracks produced on stainless-steel 316L substrates. The
dataset supports the NSF Future Manufacturing Data Challenge and contains three complementary modalities: in-situ thermal image sequences from a Stratonics ThermaViz melt-pool sensor, scanning electron microscopy (SEM) images acquired using a Zeiss EVO MA10 system, and full-field height maps acquired using a Bruker ContourGT-K white-light 3D optical profilometer. Each experiment is a bead-on-plate scan at one of four
laser powers, 200, 300, 350, and 400 W, with a fixed scan speed of 10 mm/s. The release includes a
multimodal coordinate convention linking thermal, SEM, and height-map measurements over a common physical 20–100 mm window, with the raw
dataset available on Zenodo and participant-facing notebooks, reusable code, and documentation available on GitHub.
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Chemical Physics · Cross-listed from cond-mat.stat-mech
Equilibrium in a Reaction Network of Assemblies
Giampaolo Folena and Germán Kruszewski
We study a mean-field reaction network whose species are assemblies built from identical atoms by reversible coagulation and fragmentation. Each assembly is an ordered binary tree, so the number of species of a given length grows combinatorially, as the Catalan numbers. The model nonetheless admits an explicit
equilibrium and tractable
stochastic dynamics. A finite volume $V$ sets a crossover length $l_c \sim \ln V$ that splits the
equilibrium into two sectors. Below $l_c$ each assembly occurs in many copies and the rank-frequency distribution is Zipf-like; above $l_c$ individual species are rare and fluctuation-dominated. The statistical weight of the rare sector decays slowly with volume, controlling the finite-size scaling of diversity, Shannon
entropy, and other assembly-weighted observables. The
equilibrium also admits a transparent grand-canonical description in terms of a bond energy and an atomic chemical potential. Together these results make the model a controlled neutral baseline against which selection and driving in richer assembly networks can be measured.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Evaluating the Generalizability of Foundation Models for Extreme Environmental Events: Case Study of California Wildfire PM2.5
Yongcan Huang, Li Jiang and Ze Yu Liu
Wildfire smoke events produce extreme PM$_{2.5}$ concentrations that pose severe public health risks, yet
forecasting rare, hazardous-level spikes remains a fundamental challenge. Time series foundation models (TSFMs), pretrained models offering zero-shot inference and efficient adaptation, perform strongly on general
benchmarks, but their behavior under extreme out-of-distribution conditions is poorly understood. We present the first systematic
benchmark comparing six TSFM configurations (zero-shot TimesFM, Chronos-2, Moirai-2, and Time-MoE, plus LoRA fine-tuned Chronos-2 and Time-MoE) against fully-trained baselines (LSTM, BiLSTM,
Transformer) and naive persistence on a 12-year (2013–2025) hourly PM$_{2.5}$
dataset covering 1,375 wildfire incidents across 79 California monitoring sites. A leave-one-incident-out (LOIO) protocol evaluates generalization to unseen fires, using MAE, RMSE, and exceedance F1 at EPA AQI thresholds across 6-, 12-, and 24-hour horizons. Results reveal a consistent hierarchy. The BiLSTM achieves the lowest MAE ($5.16\,\mu g/m^3$) and the highest exceedance F1 at every threshold, including the Hazardous band ($>225.5\,\mu g/m^3$), reaching 0.63 versus at most 0.54 for any foundation model. Zero-shot TSFMs improve on persistence only modestly, and zero-shot Chronos-2 exhibits severe RMSE tail instability ($23.4\,\mu g/m^3$, negative $R^2$) from sporadic large errors. LoRA fine-tuning substantially improves both adapted families and largely repairs this instability, yet no foundation model surpasses the trained recurrent baselines on any metric. These findings challenge the assumption that larger pretrained models universally dominate environmental
forecasting and provide actionable deployment guidance for wildfire air quality prediction.
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Chemical Physics
Coherent vibrational wave packet motion in ErCry4a proteins monitors the redox state of the flavin chromophore
Krishan Kumar, Daniel Timmer, Maryam Khazani et al. (+8 more)
Cryptochromes are blue-light-sensitive flavoproteins that play central roles in biological function. In European robin (Erithacus rubecula) ErCry4a
proteins, optical excitation of their flavin chromophore forms a long-lived radical pair through a sequence of electron transfer steps across a tetradic chain of tryptophan residues, making them primary candidates for magnetoreception in night migratory songbirds. Recent
quantum chemical calculations indicate that nonadiabatic couplings play a central role in the energy and charge transfer processes initiated by optical excitation. Here, we study these dynamics in ErCry4a using ultrafast transient absorption spectroscopy with 10-fs time resolution in the 450-nm spectral range. We uncover a rapid, sub-50 fs red shift in stimulated emission, quenched within 360 fs by electron transfer from a nearby tryptophan moiety. While high-frequency excited state vibrations are rapidly damped, coherent motion involving several low-frequency vibrations persists during both the initial energy relaxation and the subsequent electron transfer. This is evidenced by probing the coherent vibrational motion of the formed FAD$^{\bullet-}$ radical anion and is independently validated by blocking the electron transfer through site-selective tryptophan mutation. Our results only provide insight into the role of nonadiabatic couplings for the initial steps of cryptochrome photoactivation and suggest a general strategy for redox-state-specific monitoring of charge transfer dynamics by probing coherent vibrational motion.
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All authors Krishan Kumar, Daniel Timmer, Maryam Khazani, Glen Dautaj, Sophie Brinkmann, Jan P. Götze, Peter Saalfrank, Boris F. Gribakin, Antonietta De Sio, Henrik Mouritsen, Christoph Lienau
Optics
Probing individual phonon-polaritonic nanoparticle-on-mirror cavities by infrared nanospectroscopy
Isabel Pascual Robledo, Iker Herrero León, Karol Kołataj et al. (+4 more)
Nanoparticle-on-mirror (NPoM) cavities enable extreme light confinement and strong light-matter interactions, but their realization with
phonon-polariton materials in the mid-infrared spectral range remains largely unexplored. Here, we use nano-FTIR spectroscopy to study the near-field response of individual phononic NPoM cavities formed by gold nanoparticles on a quartz substrate supporting
phonon-polaritons. By placing a metal tip on top of the NPoM and recording the tip-scattered field, we observe two reproducible cavity resonances, identified as the fundamental and a second-order
antenna modes by numerical simulations. The calculations show that, in absence of the tip, the NPoM cavity exhibits ultrasmall mode volumes ($V \sim 10^3$ nm$^3$) and high quality factors ($Q \sim 100$), resulting in extraordinary field intensity enhancements ($F \sim 10^4$) and Purcell factors ($P_F \sim 10^9$). They also indicate that the nano-FTIR tip enables efficient excitation and readout of these phononic NPoM modes without perturbing them, while enhancing the intrinsic local field intensity in the NPoM gap by two orders of magnitude. Our results establish phononic NPoM cavities as a promising platform for mid-infrared nanophotonics and pave the way for ultrasensitive vibrational spectroscopy based on nano-FTIR measurements of individual cavities.
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All authors Isabel Pascual Robledo, Iker Herrero León, Karol Kołataj, Guillermo P. Acuna, Javier Aizpurua, Philippe Roelli, Rainer Hillenbrand
Chemical Physics
Atomistic Modeling for Electro-chemical Reactions
K. Doblhoff-Dier, B. Ballotta, L. Bonati et al. (+16 more)
Computational modeling plays a central role in advancing our understanding of electro-chemical reactions and may thus guide the rational development of sustainable energy technologies. Despite significant methodological progress, achieving predictive and quantitatively reliable simulations of electrified solid-
liquid interfaces under operando conditions remains a major challenge. Recently, the European COST Action EU-CONCERT (EUropean COllaborative Network on electroCatalysis for Efficient Renewable Technologies) was launched with the aim of advancing atomistic modeling of electrochemical reactions through systematic benchmarking and cross-validation. This position paper outlines the consortium's view of the current state of the art, identifies the priority methodological challenges to be addressed, and defines the
benchmark tests that are urgently needed. This paper should serve as a guide to the community and a roadmap for the EU-CONCERT COST Action.
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All authors K. Doblhoff-Dier, B. Ballotta, L. Bonati, V. J. Bukas, F. Calle-Vallejo, C. S. Cucinotta, K. S. Exner, M. García-Melchor, L. Giordano, K. Honkala, N. Hörmann, G. Kastlunger, M.M. Melander, Zehra B. Öcal, A. A. Reka, S. Steinmann, M. Vandichel, J.-X. Zhu, G. Cicero
Applied Physics · Cross-listed from cond-mat.mes-hall
Gate induced strain on a two-dimensional hole gas in silicon
D. van der Bovenkamp, C.S.A. Müller, B.D. Pantiru et al. (+7 more)
We show the effect of gate-induced strain on the valence band of a silicon (Si) metal
oxide semiconductor (MOS) confined two-dimensional hole gas (2DHG). Increasing aluminum gate thickness, and thereby the strain in the channel, results in the onset of a second subband contributing to Shubnikov-de Haas oscillations. Temperature-dependent magnetotransport measurements reveal distinct cyclotron masses of $m_c^*=(0.36\pm0.04)m_0$ and $m_c^*=(0.49\pm0.02)m_0$. The measured cyclotron masses differ from those expected for an idealized heavy-hole (HH)/light-hole (LH) picture, reflecting the combined influence of
quantum confinement, strain, and HH-LH mixing on the valence band.
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All authors D. van der Bovenkamp, C.S.A. Müller, B.D. Pantiru, I. Bošnjak, M. Cignoni, Q. Torrent Nicolau, M.E. Bal, S. Wiedmann, J. Ridderbos, F.A. Zwanenburg
Atomic Physics
Dual-Platform Precision Measurement of the $3^2D_{5/2}$ to $4^2S_{1/2}$ $g$-Factor Ratio in $^{40}\text{Ca}^+$
Brian J. McMahon, Vikram S. Sandhu, John M. Gray et al. (+5 more)
We report precision measurements of the ratio of Landé $g$ factors between the $3^2D_{5/2}$ and $4^2S_{1/2}$ states of a single trapped $^{40}\text{Ca}^+$ ion. The measurements are performed in two distinct ion trap apparatus: a cryogenic surface electrode radiofrequency Paul trap and a room-temperature permanent magnet Penning trap. The Penning trap measurements rely on resonant microwave excitation of
magnetic sublevels and yield a ratio of $0.599~488~813~3(2)$, which is a more than 40-fold uncertainty reduction compared to previous work. The radiofrequency trap measurements utilize optical electric quadrupole transitions and yield a concurring value of $0.599~488~813(6)$. We estimate that systematic shifts for each system are well below the respective statistical uncertainty.
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All authors Brian J. McMahon, Vikram S. Sandhu, John M. Gray, Creston D. Herold, Christopher M. Seck, Gilles Buchs, Kenton R. Brown, Brian C. Sawyer
Fluid Dynamics · Cross-listed from astro-ph.SR
Cluster-Weighted Training of Deep Surrogate Models for Subgrid Turbulent Transport
Rimsha Hameed Syeda, Dustin Kempton, Viacheslav Sadykov et al. (+2 more)
Turbulence in the
solar interior and atmosphere plays a crucial role in energy transport, yet modeling its subgrid-scale effects remains a major challenge. This study leverages machine learning (ML) models to predict components of the Reynolds stress tensor using high-resolution StellarBox simulations of the quiet Sun. Previously, we have compared a Multi-Layer Perceptron (MLP) and a 3D Convolutional Neural Network (CNN) against physics-based baselines to achieve a lower Mean Squared Error (MSE) and better generalization across various heights and depths in the
solar atmosphere. To enhance learning, in this work, we investigate cluster-weighted training using K-Means and Hierarchical Agglomerative Clustering (HAC). By weighing the loss function based on cluster-specific prediction errors, we direct the model's
attention to high-error regions. It significantly improves CNN performance, achieving 34% lower MSE and a significantly higher R2 score indicating that integrating deterministic clustering with ML is a promising technique for modeling subgrid
turbulence, in particular, and regression in diverse environments, in general.
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All authors Rimsha Hameed Syeda, Dustin Kempton, Viacheslav Sadykov, Irina Kitiashvili, Rafal Angryk
Biological Physics · Cross-listed from cond-mat.soft
Understanding quorum sensing self-organization: Clustering and defect-induced ordering of diffusing particles
Feifei Liu, Vyacheslav R. Misko, Yunyun Li et al. (+1 more)
Quorum sensing (QS) is known in biology as a form of intercellular communication mediated by signaling molecules called autoinducers. The QS protocol governs the transition from individual to collective
cell behavior once a critical population density is reached. Using numerical simulations, we investigate how defects influence the QS transition and the structural organization of the resulting colonies. Our model system consists of a mixture of slow ("cold") and fast ("hot") diffusing colloidal particles that obey the QS protocol, together with defect particles characterized by a constant diffusivity. A striking reentrant solidification of QS particles, characterized by long-range order, is induced by hot defects, whereas cold defects give rise to amorphous structures with only short-range order. These findings deepen our understanding of the QS interaction and provide a mechanism to control the degree of organization in QS systems, with potential applications in robotics, social sciences, and medicine – for instance, in overcoming antimicrobial resistance.
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All authors Feifei Liu, Vyacheslav R. Misko, Yunyun Li, Fabio Marchesoni
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Bulk Boundary Condition for Surface Calculations in Density Functional Theory
Sayan Bhowmik, Andrew J Medford and Phanish Suryanarayana
We present a bulk boundary condition formalism for surface calculations in Kohn–Sham density functional theory. The approach exploits the nearsightedness of electronic interactions in real space to restrict the calculation to a localized surface region. Within this region, the electron density is evaluated by leveraging the decay of the density
matrix, with bulk values imposed on the density and electrostatic potential in the interior, and the electrostatic potential solved subject to bulk boundary conditions. The energy and atomic forces are computed using density-
matrix-based expressions. Through representative calculations of surface and adsorption energies, we demonstrate the accuracy and efficiency of the proposed formalism.
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Atmospheric and Oceanic Physics
Global reanalysis from observations alone with machine learning
Peter Lean, Ewan Pinnington, Patrick Laloyaux et al. (+9 more)
Earth system reanalysis
datasets are foundational for weather and
climate research and provide the gridded training data used by most machine learning weather prediction systems. Here we show results from a prototype system that suggest that machine learning models trained only on Earth system observations can potentially be used to generate multi-decade global reanalyses without using physics-based numerical models. The resulting gridded fields capture large-scale atmospheric structure and variability across multiple timescales, while exhibiting signs of physical coherence in several key dynamical diagnostics. Evaluations of the prototype against held-out independent atmospheric observations indicate that the root mean square vector error of upper-level winds is close to that of ERA5 when compared at a consistent resolution, and that the standard deviation of the error at the surface is between that of 4th- and 5th-generation ECMWF reanalyses (ERA-Interim and ERA5). Furthermore, while traditional reanalysis production is computationally expensive, typically taking several years to produce, the reanalysis presented here was generated during the course of a single working day. These results suggest that observation-trained machine learning models offer a promising new approach for reanalysis production from observations alone.
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All authors Peter Lean, Ewan Pinnington, Patrick Laloyaux, Mihai Alexe, Eulalie Boucher, Simon Lang, Tomas Kral, Paul Poli, Hans Hersbach, Niels Bormann, Matthew Chantry, Anthony McNally
Optics · Cross-listed from cond-mat.mtrl-sci
Quantum Dot Moiré from Crossed MoS2 Nanoribbons
Xinting Shuai, Hao Zhang, Wenjing Wu et al. (+22 more)
Twisted atomically thin layers have attracted much
attention for Moiré potential and correlated
quantum phenomena. However, existing Moiré superlattices have largely been limited to extensive wavefunction without lateral confinement. Here we introduce a new platform where 1D nanoribbons of 2D MoS2 grown by vapor deposition can be easily superposed at various angles from stacking and transferring, to form Moiré
quantum dots at their intersections with unique
exciton physics. Angle-dependent Moiré intersections show enhanced
exciton emission at commensurate angle 22 deg, which demonstrates faster relaxation at the cryogenic temperature. A size-dependent study further exhibits a reduced
exciton energy and soften out-of-plane interlayer coupling for smaller Moiré areas. Our results reveal
exciton physics turnability via precise overlapping of 1D nanoribbons.
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All authors Xinting Shuai, Hao Zhang, Wenjing Wu, Chongning Wu, Maryam Amiri, T. A. M. Ragib Shahriar, Dian Pan, Zhi Kai Ng, Tymofii Pieshkov, Leeza Dutta, Yijun Zhou, Rohith Narra, Luke Van Leeuwen, Jishnu Murukeshan, Luyao Shi, Jiawei Lai, Atin Pramanik, Bipin Kumar Gupta, Edwin Hang Tong Teo, Robert Vajtai, Xiang Zhang, Hanyu Zhu, Shengxi Huang, Aditya D. Mohite, Pulickel M. Ajayan
Plasma Physics
Analysis of collisional and facility effects in a magnetic nozzle plasma expansion
Manuel Cortés-Hernán, Mario Merino, Diego García-Lahuerta et al. (+1 more)
An axisymmetric, quasineutral three-fluid model is proposed to study the
plasma expansion in a
magnetic nozzle under the presence of neutrals coming either from the
plasma source or as an homogeneous background. As a difference with other models, electron cooling in the plume is achieved by treating the electron energy flux as mainly convective and without the need to postulate any anomalous resistivity. Solutions are presented for the electron high-magnetization limit, in which the electron main magnitudes can be integrated along
magnetic lines. Ionization, elastic and charge-exchange collisions with neutrals do not change the main qualitative features of the
plasma expansion, known from previous collisionless models. Ionization enhances the
plasma flow in the nozzle, and leads to additional electron cooling, which decreases the electric potential fall along the nozzle. The efficiency of the nozzle is quantified in terms of the gain of
magnetic thrust and the plume divergence angle. Two types of boundary conditions are discussed for the electron flow: local current ambipolarity conditions at the nozzle throat and global current-free conditions at the outer boundary (i.e., metallic
vacuum chamber walls). These last ones are shown to be physically more reliable: they introduce the influence of the chamber walls on the
plasma expansion by shaping the ambipolar electric field; they permit the extrapolation to undisturbed free space conditions; and they approximate better experimental trends with the background pressure.
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All authors Manuel Cortés-Hernán, Mario Merino, Diego García-Lahuerta, Eduardo Ahedo
Computational Physics · Cross-listed from math-ph
Kime-Representation Formulations of Three Open Problems in the Foundations of Classical Mechanics: Uncertainty, Invariant Entropy, and Directional Degrees of Freedom
Ivo D. Dinov
We give mathematically self-contained formulations, in the complex-time (kime) representation, of three open problems from the foundations of classical mechanics: (I) the extension of the classical entropic uncertainty principle to non-canonical variables and to multiple degrees of freedom; (II) the characterization of coordinate-invariant measures and
entropies, i.e., the question of why continuous physical quantities must be paired for an invariant
entropy to exist; and (III) the construction of a classical relativistic directional degree of freedom (a classical analogue of a
spin-1/2 system). Throughout, the kime phase is interpreted {statistically as a latent circular random variable whose law \Phi models the intrinsic trial-to-trial variability of repeated, identically controlled experiments indexed by the kime magnitude. The mathematical bridge is an exact
symplectic identification of the kime cone with the action-angle chart of a one-degree-of-freedom phase space, under which the kime measure is the Liouville measure and the phase law becomes the angular conditional of a Liouville density. Specifically, we (i) prove a sharp entropic uncertainty relation on the kime cylinder whose extremal family is von Mises x Gaussian, together with a sharp circular Fisher-information inequality saturated exactly by von Mises laws; (ii) prove an exact non-canonical uncertainty relation in which the correction term is the
geometric mean of the Poisson bracket, clarifying the conjectured role of the expected bracket; (iii) prove aggregate multi-degree-of-freedom bounds via the Williamson normal form and Fischer's inequality, and isolate the per-degree-of-freedom refinement as a precise open problem of
symplectic Schur-Horn type; (iv) prove that
diffusion of the kime phase produces monotone
entropy growth with the equipartitioned (Haar-uniform) phase law.
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Chemical Physics · Cross-listed from quant-ph
Quantum Sensors for Chemistry and Materials Science
Piotr Put, Arjun Pillai, Xuan Hoang Le et al. (+2 more)
The advancement of chemistry and materials science relies on transformative analytical tools which can overcome the sensitivity, spatial resolution, and throughput limitations of conventional techniques. This review explores the application of
quantum sensors - specifically optically pumped magnetometers (OPMs) and nitrogen-vacancy (NV) centers in diamond - as robust platforms for molecular and materials analysis. We contrast the extreme
magnetic sensitivity of macroscopic OPM ensembles with the atomic-scale resolution and
multimodal capabilities of solid-state NV centers. We highlight their deployment in zero- to ultralow-field and nanoscale NMR spectroscopy, real-time reaction monitoring, and transient radical and pH detection. Furthermore, we discuss their integration into high-throughput chemical assays and non-destructive materials diagnostics, such as operando battery monitoring. With the ongoing commercialization of these technologies and advances in
quantum-enhanced sensitivities,
quantum sensors are poised to routinely address complex real-world analytical challenges.
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All authors Piotr Put, Arjun Pillai, Xuan Hoang Le, Mikhail D. Lukin, Hongkun Park
Atomic and Molecular Clusters · Cross-listed from quant-ph
Multi-channel collective dissipation via the symmetric irreducible representation of SU(4)
M. Lutsukh, M. Bazarsana, T. Begzjav et al. (+1 more)
We specialize Agarwal's multi-level collective spontaneous-emission formalism to the four-level case by formulating it in the fully symmetric \SU(4) representation of $N$ identical atoms. In the irreducible representation $(N,0,0)$, the occupation-number basis forms a tetrahedral weight
lattice on which the six embedded $\mathfrak{su}(2)$ transition subalgebras act as ladder operators. From these algebraic factors we obtain a compact Pauli-type population-rate equation and a closed-form expression for the total emitted intensity that apply to any combination of open dipole channels. The formalism is then specialized to the seven dipole-allowed four-level
topologies – tripod, inverted tripod, Y, inverted Y, double-$\Lambda$, closed cascade, and diamond – and the resulting rate equations are solved numerically for atom numbers up to $N=50$. In every case the emitted intensity develops a delayed cooperative burst whose peak height obeys a power law $I_{\mathrm{peak}}=aN^{p}$ with
topology-dependent parameters $(a,p)$; the fitted exponents lie in the range $1.81\lesssim p\lesssim 1.92$, indicating a superlinear. The \SU(4) tetrahedral flow and the seven configuration-dependent transients together provide a unified
geometric picture of multi-channel collective dissipation in four-level atomic ensembles.
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All authors M. Lutsukh, M. Bazarsana, T. Begzjav, G. O. Ariunbold
Computational Physics
Scaling WaterLily.jl with MPI and an improved geometric multigrid solver
Bernat Font, Marin Lauber, Tzu-Yao Huang et al. (+1 more)
We present recent performance-oriented developments in WaterLily, a scale-resolving incompressible flow solver written in pure Julia that runs seamlessly on CPUs and GPUs of any vendor. Supported by the newly added MPI-based parallelism, strong-scalability tests display a near-ideal linear trend, and weak-scaling efficiency is kept above 85% before node
memory-concurrency contention dominates parallel performance. Inter-node weak scalability is sustained above 96% with grid size up to 1 billion
cells. We further
benchmark improvements to the
geometric multigrid Poisson solver enabled by an adaptive under-relaxed red-black Gauss-Seidel smoother together with anisotropic coarsening operators.
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All authors Bernat Font, Marin Lauber, Tzu-Yao Huang, Gabriel D. Weymouth
Applied Physics · Cross-listed from nlin.AO
Impact of Channel Dynamics on Higher-order Interactions of Oscillators
Gabriel Marghoti, Isabela A. Martins, Giovana S. Spezzatto et al. (+3 more)
Modeling higher-order interactions (HOIs) in nonlinear networks with static
topologies is often physically restrictive. We demonstrate that standard 3-body Kuramoto couplings are mathematically equivalent to pairwise connections modulated by latent variables of transmission channels. While standard HOI
topologies emerge in the adiabatic limit of these variables, relaxing this constraint reveals that latent channel timescales dictate collective macroscopic states. Specifically, transmission inertia drives bistability for symmetric interaction tensors and anti-phase cluster synchronization for antisymmetric ones. Furthermore, dynamically induced clustering in global
topologies emerges as a finite-size effect of the dynamics of the local channels. Ultimately, we show that relying exclusively on static
topologies restricts interaction modeling. Integrating latent variables captures the transient inertia and fundamental asymmetry of physical networks, bridging the analytical utility of higher-order functions with the reality of the underlying transmission medium.
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All authors Gabriel Marghoti, Isabela A. Martins, Giovana S. Spezzatto, Emanuel B. S. A. Cambraia, Sergio R. Lopes, Thiago L. Prado
Atomic Physics
Hadronic vacuum polarization in hydrogen-like atoms and ions amid the interplay of recoil and finite-size effects
Franziska Hagelstein, Vadim Lensky, Bogdan Malaescu et al. (+1 more)
Hadronic
vacuum polarization (hVP) enters simple atomic systems at a level that is small yet decisive for the precision spectroscopy now underway. We evaluate the hVP contributions to the Lamb shift and the hyperfine splitting (HFS) in ordinary and muonic hydrogen (H and $\mu$H) and hydrogen-like helium-3 ions ($^3$He$^+$ and $\mu^3$He$^+$), using the dispersive data-driven approach and state-of-the-art empirical parametrizations of the $R$ ratio. At the centre of the analysis is the interplay of
recoil and finite-size effects: the
recoil corrections that dominate the HFS in muonium (Mu), where both constituents are pointlike, are shown to be suppressed by the
nuclear elastic form factors (FFs). Our results for the leading hVP contribution to the Lamb shift agree with the literature within uncertainties. Furthermore, we present a first evaluation of the subleading $O(Z^5\alpha^6)$ hVP-finite-size correction, which is by no means negligible in $\mu^3$He$^+$. Our results for the hVP contribution to the HFS deviate significantly from all previous evaluations. For the ground-state HFS, we obtain $2.153(11)~\mu$eV in $\mu$H and $-15.19(57)~\mu$eV in $\mu^3$He$^+$, as well as $0.0860(4)~$kHz and $-0.476(17)~$kHz in ordinary H and $^3$He$^+$, respectively. Notably, our result for $\mu$H differs from previous evaluations by roughly ten times the experimental precision anticipated by the upcoming CREMA and FAMU measurements.
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All authors Franziska Hagelstein, Vadim Lensky, Bogdan Malaescu, Vladimir Pascalutsa
Optics
Predicting Multi-Order Magnetic Polariton Resonances for Radiative Properties Tailoring by Distributed Circuit Model
Hangjie Li and Junming Zhao
Surface plasmon polaritons (SPPs) and
magnetic polaritons (MPs) are fundamental resonance modes that are widely used to tailor the thermal radiation properties of micro/nanostructured metamaterials. Lumped
circuit models (LCMs) are usually constructed empirically to describe the MP resonance conditions, and different LCMs have to be constructed for different orders of MPs, but these are difficult to be built for high-order MP modes due to the complex electromagnetic field distribution. This work proposes a new type of
circuit model, distributed
circuit model (DCM), to describe and predict multi-order MP resonances inside the structure based on the minimum total impedance condition. This allows both fundamental and high-order MP resonances to be predicted with a unified
circuit, significantly simplifying the analysis of high-order MPs. More importantly, the DCM shares a similar and clear physical picture as the LCM for describing MPs. The MP resonance conditions for four typical structures are derived. Theoretical predictions based on DCMs are compared with and validated by rigorous numerical simulations. This study deepens the understanding and facilitates the design of MP-based thermal radiation metamaterials.
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Fluid Dynamics · Cross-listed from astro-ph.EP
Extra Invariant in Magnetohydrodynamics of Planets and Stars
Alexander M. Balk
The paper establishes extra invariant in magnetohydrodynamics (MHD) of rotating and stratified fluid layer. This invariant is conserved adiabatically, i.e. approximately over long time. The existence of the invariant is interesting by itself, as such invariants are extremely rare. However, in addition, this invariant appears to be connected to the famous dynamo phenomenon.
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Optics
Pic2Spec: Generative Modeling Reconstructs Single Cell Raman Fingerprints from Brightfield Images
Srilakshmi Premachandran, Amit Kumar Bhuyan and Loza F. Tadesse
Single-
cell molecular characterization remains a bottleneck in scalable biological analysis because of labeling requirements, limited multiplexing, and reagents that perturb physiology. Raman spectroscopy addresses these limits by providing chemically specific, label-free vibrational fingerprints, but long acquisition times and specialized instruments restrict high-throughput use. Here, we overcome this barrier by showing that spectral fingerprints can be reconstructed from brightfield microscopy using generative modeling. We introduce Pic2Spec, a framework that learns a shared latent biochemical representation linking image morphology to vibrational spectral structure, enabling virtual Raman spectroscopy without hardware. We validate Pic2Spec across mammalian and bacterial
cells, generating high-fidelity spectra that reproduce measured Raman fingerprints with 98% cosine similarity and Pearson correlations of ~95%, while preserving biochemical peaks and population distributions. Beyond spectral similarity, Pic2Spec provides molecular-level resolution in bacterial systems: generated spectra discriminate mutation-driven transgenic states and predict GFP expression with accuracy approaching true Raman measurements, outperforming conventional image analysis by 20%. These findings establish Pic2Spec as a first demonstration of chemically informative virtual molecular fingerprinting from brightfield images, complementing slow, hardware-intensive spectroscopy with computational inference. By redefining microscopy as an inference-enabled molecular profiling platform, Pic2Spec democratizes label-free biochemical phenotyping and overcomes the hardware and time constraints that have confined spectroscopy to specialized laboratories. This enables high-throughput molecular analysis for clinical diagnostics, screening, and monitoring at the scale and accessibility of standard microscopy.
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Computational Physics
Semilocal exchange functionals from the exact-exchange condition for the hydrogen atom: Hydrogenic exactness and recovery of Rydberg-like bound states
Fumihiro Imoto
In semilocal density functionals the exchange potential decays too rapidly outside atoms and molecules and lacks the correct $-1/r$ tail; as a consequence, functionals from PBE to modern meta-GGAs such as SCAN support no bound Rydberg-like state of an atom. We revisit the gradient-corrected exchange functional that Gill and Pople (GP93) constructed to reproduce the exact exchange potential of the hydrogen atom, solve their equation as an inverse problem, and use the resulting enhancement factor – the GP93 factor – as a tail-generating ingredient of a switched semilocal functional. The GP93 factor is exact on the hydrogen $1s$ density and, by uniform coordinate scaling, on hydrogenic $1s$ ions, where it yields the
eigenvalue $-Z^2/2$ exactly (hydrogenic exactness). Its large-gradient growth has the hydrogen-exact form $O[s(\ln s)^{2/3}]$, distinct from the $s\ln s$ form of Armiento and Kümmel. The factor is combined with a kinetic-energy-density indicator so that its divergent branch acts only in one-electron-like regions; the GP93 ingredient is nonempirical, while a few switching parameters are calibrated to balance tail recovery against self-consistent-field stability. The resulting functional produces Rydberg-like series of bound virtual Kohn–Sham states in systems whose outermost shell is a one-electron-like $s$ shell – all-electron H and He, and Li, Na, and K with large-core pseudopotentials – and moves the highest-occupied
eigenvalue toward the experimental ionization energy. For $p$-shell atoms (Ne, Ar) the switch closes, so the domain of applicability is fixed by design. Fixed-density tests indicate that a reduced-
Laplacian switch distinguishes atomic tails from covalent bond centers, and that a density-only kinetic-energy functional renders the entire switch orbital-independent, so that no generalized Kohn–Sham solver is required.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci
Are Machine Learning Interatomic Potentials Truly Practical? A Benchmark of 23 Mainstream Models
Hanwen Kang, Tenglong Lu, Sheng Meng et al. (+1 more)
Most MLIP
benchmarks reward static accuracy while ignoring inference efficiency and hardware scalability – driving model bloat with unclear real-world value. We
benchmark 23 mainstream open-source MLIPs on a low-cost NVIDIA DGX Spark (128 GB native
memory, capped at 80 GB to mimic ordinary lab hardware), using a fixed 192-atom system under a unified ASE-based pipeline. We evaluate three dimensions: predictive accuracy, MD simulation throughput, and atomic scalability. Our results expose a sharp accuracy-efficiency trade-off: large SOTA models deliver only 3-5 meV/atom more accuracy than lightweight ones, but lose orders of magnitude in throughput – in the worst case, becoming only marginally faster than DFT itself. Lightweight MLIPs, by contrast, sit on the Pareto frontier and run on modest hardware. The lesson is that single-dimensional
benchmarks mislead the field, and that future MLIP development should value efficiency and scalability alongside accuracy.
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All authors Hanwen Kang, Tenglong Lu, Sheng Meng, Miao Liu
Atomic Physics
Precision spectroscopy of the fine and hyperfine structures of high molecular Rydberg-Stark states: Metrology of molecular hydrogen ions
Ioana Doran, Leon Jeckel, Maximilian Beyer et al. (+2 more)
The Stark effect in autoionizing high-$n$ Rydberg states decouples the Rydberg electron from the ion core through $\ell$ mixing with core-nonpenetrating high-$\ell$ states. The Rydberg states become long-lived, which is ideal for precision spectroscopy, and their structures reflect the fine and hyperfine structures of the ion-core levels. We report on precision measurements, in weak electric fields, of the fine and hyperfine structures of two distinct categories of high autoionizing molecular Rydberg-Stark states differing by the nature of the ion-core angular momentum: Rydberg states of para-H$_2$ (total
nuclear spin $I=0$) with a rotationally excited ($N^+=2$) H$_2^+$ ion core and Rydberg states of ortho-D$_2$ ($I=2$) with a rotationless ($N^+=0$) ion core. The spectra reveal striking differences which are interpreted as arising from the dominance of anisotropic charge-quadrupole interactions between the rotating quadrupolar ion core and the Rydberg electron in para-H$_2$ and the absence of such interactions in rotationless ortho-D$_2$ Rydberg states. In ortho-D$_2$, the dominant interaction, the
magnetic Fermi-contact hyperfine interaction in the ion core, does not significantly affect the motion of the Rydberg electron. By analyzing these spectra based on a treatment combining multichannel
quantum-defect theory and
matrix diagonalization, we derive new experimental values of the hyperfine coupling constant $b_F$ = 139.84(5) MHz of D$_2^+ (v^+=1, N^+=0)$, the
spin-rotation coupling constant $c_e$ = 39.62(11) MHz of H$_2^+ (v^+=1, N^+=2)$ and the fundamental vibrational interval of ortho-D$_2^+$ (47279980.8(1.9) MHz). The approach followed here in the study of molecular Rydberg-Stark states is general and broadly applicable to measurements of the fine and hyperfine structures of molecular cations.
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All authors Ioana Doran, Leon Jeckel, Maximilian Beyer, Christian Jungen, Frédéric Merkt
Applied Physics
Distributed Circuit Model for Predicting the Quality Factor of Magnetic Polariton Resonance
Hangjie Li and Junming Zhao
Existing RLC
circuit model leads to inaccurate predictions of the quality factor (Q-factor) of
magnetic polariton (MP) resonances under imperfect absorption conditions due to the omission of radiation loss. Moreover, the lumped-parameter nature of RLC models also limits their applicability for predicting higher-order MP modes. In this letter, we propose a distributed
circuit model (DCM) for predicting the Q-factor of MP resonances, which overcomes these limitations. By introducing a radiation resistance to characterize radiation loss and establishing a mapping between distributed and lumped parameters, we derive a unified analytical expression for the Q-factor of arbitrary-order MPs. Validation via rigorous coupled-wave analysis (RCWA) demonstrates that this model can accurately predict the Q-factors of MPs of all orders in various metal-
insulator-metal (MIM) structures. This work provides a simple yet effective tool for designing metamaterial emitters/absorbers and advances the understanding of MP loss mechanisms.
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Data Analysis and Statistics · Cross-listed from quant-ph
Analysis of polarization drift of optical signals over deployed aerial-inground fiber connections
Aneesh Ramaswamy, Nageswara S. V. Rao, Joseph C. Chapman et al. (+1 more)
Polarization measurements of a classical 1550-nm signal are collected and analyzed on 15-km hybrid aerial-inground fiber connections over 11 months. The spectral area and spectral moments of mHz-resolution Fast-
Fourier-Transform (FFT) of these measurements are extracted, and related to temperature, humidity, wind speed, and time of day. Spectral area correlations show a strong diurnal structure: daytime maxima align with temperatures/wind speed peaks and humidity dips, with lower levels during the night. These diurnal patterns also show seasonality, with higher mean and variance in summer than winter. A random forest regressor is used to estimate FFT features from environmental measurements, informed by a theoretical model
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All authors Aneesh Ramaswamy, Nageswara S. V. Rao, Joseph C. Chapman, Muneer Alshowkan
Chemical Physics · Cross-listed from cs.LG
Higher-Order Geometric Updates for Levenberg-Marquardt Method via Riemann Normal Coordinates
Jianing Liu and Dong H. Zhang
Nonlinear least-squares objectives form the foundation of scientific machine-learning tasks, yet even
curvature-aware optimizers remain geometrically inconsistent at finite step sizes: Levenberg-Marquardt (LM) derives its direction from local Riemannian metrics but realizes it as a straight parameter update. Here we introduce RNC-LM, which carries the LM direction along a locally constructed curved trajectory in Riemann normal coordinates. A recursive reformulation of the geodesic equation generates arbitrary finite-order corrections while reusing the same damped Gauss-Newton
matrix factorization, and curve length is controlled separately from damping. On a reaction-
diffusion physics-informed neural network
benchmark, RNC-LM reduces relative $L^2$ errors below $8\times10^{-3}$, whereas L-BFGS, LM and LM with geodesic acceleration remain near one. On a large-scale machine-learning potential fitting task with 985,160 configurations, fourth-order RNC-LM reaches a fixed training-error target with a $34\times$ wall-clock speedup over LM. These results establish finite-step
geometric realization as a distinct optimizer design principle.
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