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Physics Physics

physics Watch Physics

Tuesday 17 February

Fluid Dynamics

Physics-informed data-driven inference of an interpretable equivariant LES model of two-dimensional incompressible fluid turbulence

Matteo Ugliotti, Brandon Choi, Mateo Reynoso et al. (+2 more)

Restrictive phenomenological assumptions limit the accuracy and generality of subgrid-scale models of fluid turbulence, especially in flows where coherent structures and bidirectional energy transfer play an important dynamical role. This paper introduces a symbolic, physically-informed data-driven subgrid-scale closure for two-dimensional incompressible turbulence. The closure is inferred from filtered direct numerical simulation data using symmetry-constrained sparse regression, together with dimensional-consistency constraints on the inferred coefficients. While the model is inferred using LES-style spatial coarse-graining, its structure is found to be more similar to RANS models, as it employs an additional field to describe the dynamics of unresolved scales. For the range of two-dimensional benchmark flows considered here, the inferred model substantially improves upon widely used LES models, yielding accurate predictions of subgrid-scale stresses, local and global fluxes between different scales, and other key quantities in both a priori and a posteriori benchmarks.
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All authors Matteo Ugliotti, Brandon Choi, Mateo Reynoso, Daniel R. Gurevich, Roman O. Grigoriev

Optics

Singular value decomposition to describe bound states in the continuum in periodic metasurfaces

Nikita Ustimenko, Ivan Fernandez-Corbaton and Carsten Rockstuhl

Understanding how bound states in the continuum (BICs) emerge in periodic metasurfaces is essential for the controlled design of high-Q resonances and their systematic manipulation. Here, we investigate the singular value decomposition (SVD) of the effective transition matrix and the scattering matrix of periodic metasurfaces within a parameter range where the metasurface sustains a BIC. Our analysis yields general and practically applicable conditions on the singular values and singular vectors that enable BIC formation. At the BIC eigenfrequency, the inverse of the largest singular value of both matrices vanishes, and the corresponding left (right) singular vector is orthogonal to outgoing (incoming) plane waves that propagate in the directions of open diffraction orders. Our SVD-based approach predicts the spectral position of the BIC and provides detailed information about its properties, including the expansion coefficients in the multipole and plane-wave bases, as well as its behavior under perturbations that transform the BIC into a quasi-BIC. The approach is numerically validated by considering both symmetry-protected and accidental BICs in arrays of scatterers supporting electromagnetic or acoustic multipole resonances. The presented SVD framework offers a broadly applicable foundation for engineering BICs and quasi-BICs in complex metasurfaces, potentially enabling new routes for wave-based devices with tailored radiative properties.
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Physics and Society · Cross-listed from cs.SI

SVD Incidence Centrality: A Unified Spectral Framework for Node and Edge Analysis in Directed Networks and Hypergraphs

Jorge Luiz Franco, Thomas Peron, Alcebiades Dal Col et al. (+4 more)

Identifying influential nodes and edges in directed networks remains a fundamental challenge across domains from social influence to biological regulation. Most existing centrality measures face a critical limitation: they either discard directional information through symmetrization or produce sparse, implementation-dependent rankings that obscure structural importance. We introduce a unified spectral framework for centrality analysis in directed networks grounded in the Singular value decomposition of the incidence matrix. The proposed approach derives both vertex and edge centralities via the pseudoinverse of Hodge Laplacians, yielding dense and well-resolved rankings that overcome the sparsity limitations commonly observed in betweenness centrality for directed graphs. Unlike traditional measures that require graph symmetrization, our framework naturally preserves directional information, enabling principled hub/authority analysis while maintaining mathematical consistency through spectral graph theory. The method extends naturally to hypergraphs through the same mathematical foundation. Experimental validation on real-world networks demonstrates the framework's effectiveness across diverse domains where traditional centrality measures encounter limitations due to implementation dependencies and sparse outputs.
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All authors Jorge Luiz Franco, Thomas Peron, Alcebiades Dal Col, Fabiano Petronetto, Filipe Alves Neto Verri, Eric K. Tokuda, Luiz Gustavo Nonato

Atomic Physics

Microscopic Rydberg electron orbit manipulation with optical tweezers

Homar Rivera-Rodríguez, Matthew T. Eiles, Tilman Pfau et al. (+1 more)

Laser cooling and trapping of atomic matter waves in optical potentials has enabled rapid progress in quantum science, particularly when combined with Rydberg excitation of the atoms to induce long-range interactions. Here, we propose the local manipulation and spatio-temporal sculpting of the electronic matter wave of a Rydberg atom by a laser field focused so that its beam width is smaller than the Rydberg electron orbit. We compute the electronic eigenstates in the presence of a sharply focused Gaussian laser beam, and find strong Rydberg state mixing leading to large kilo-Debye dipole moments. These can be modulated with high bandwidth controlled by the local tweezer intensity. Oscillations in the position-dependent level shifts, analogous to the potential wells allowing ultralong-range Rydberg molecules to form, provide opportunities for eccentric radial trapping of the Rydberg electron via ponderomotive forces acting on sub-orbital length scales.
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All authors Homar Rivera-Rodríguez, Matthew T. Eiles, Tilman Pfau, Florian Meinert

Chemical Physics

Analytical Nuclear Gradients for State-Averaged Configuration Interaction Singles Variants: Application to Conical Intersections

Takashi Tsuchimochi

We derive analytical nuclear gradients for state-averaged orbital-optimized configuration interaction singles (SACIS) and its spin-projected extension (SAECIS), enabling efficient geometry optimization and minimum-energy conical intersection (MECX) searches within a low-cost CIS-based framework. The formulation employs a Lagrangian approach and explicitly removes null-space contributions in the coupled perturbed equations to ensure numerically stable gradients. For twisted-pyramidalized ethylene, both SACIS and SAECIS qualitatively reproduce the correct conical intersection topology, in sharp contrast to conventional CIS and ECIS. Benchmark calculations on twelve MECXs demonstrate that both methods reproduce geometries with mean RMSDs below 0.1~Å relative to high-level reference methods. SACIS captures the essential degeneracy through variational orbital relaxation, which alleviates ground-state Hartree–Fock (HF) orbital bias and effectively incorporates static correlation through localization effects; notably, spin projection is found to be non-essential for the qualitative description of these intersections. Overall, SACIS and SAECIS provide qualitatively reliable CX descriptions at mean-field computational cost in a black-box manner. Given their comparable accuracy and the additional overhead associated with spin projection, SACIS offers a more favorable cost-performance balance for general applications, whereas SAECIS may become advantageous when higher excited states with significant double-excitation character are involved.
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Medical Physics

Dosimetric Study of Lung Modulation and Motion Effects in Carbon ion Therapy for Lung Cancer

Maria Chiara Martire, Lennart Volz, Marco Durante et al. (+1 more)

Carbon-ion radiotherapy provides high dose conformity for lung cancer, but its benefit is limited by two sources of uncertainties: interplay between scanned beam delivery and tumor motion, and dose modulation from heterogeneous lung tissue. This study quantifies the separate and combined dosimetric impact of these effects using the GSI TRiP4D treatment planning system. Eighteen lung cancer 4DCT datasets from TCIA were analyzed. A modulation power ($P_{\mathrm{mod}}$) was assigned to lung voxels. Three values were sampled from a Gaussian distribution ($200\mu\mathrm{m} \pm 67\mu\mathrm{m}$), and an extreme value of $750\mu\mathrm{m}$ was tested. Interplay doses were computed by combining scanned-beam delivery with patient-specific respiratory motion. Four scenarios were studied: static, static with modulation, interplay, and interplay with modulation. Metrics included $D95\%$, $V95\%$, homogeneity index (HI), lung $V16\mathrm{Gy}$, and heart $V20\mathrm{Gy}$. Interplay reduced target coverage by $5.2 \pm 1.5$ pp ($D95\%$), $12.1 \pm 5.9$ pp ($V95\%$), and $8.3 \pm 2.4$ pp (HI). Extreme $P_{\mathrm{mod}}$ alone caused small degradations. When combined with interplay, it partially compensated the loss. This effect decreased with 4D optimization. Fractionation mitigated interplay, leaving lung modulation as the main residual effect.
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All authors Maria Chiara Martire, Lennart Volz, Marco Durante, Christian Graeff

Fluid Dynamics · Cross-listed from math.AP

Quantitative enstrophy bounds for measure vorticities

Luigi De Rosa and Margherita Marcotullio

We consider the two-dimensional incompressible Navier-Stokes equations with measure initial vorticity. By means of improved Nash inequalities, we establish quantitative estimates for the enstrophy depending on the absolute vorticity decay on balls. The bounds are optimal in several aspects and yield to a conjecturally sharp rate of the dissipation in the Delort's class.
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Atomic Physics

State-selected preparation of molecular ions for precision measurements in radio-frequency traps

Daniel Y. Knapp and Maximilian Beyer

The application of mass-analyzed threshold ionization (MATI) for the state-selective preparation of molecular ions is presented. Based on photoexcitation of long-lived high-$n$ Rydberg states, molecular ions are prepared in a single rovibronic level by pulsed-field ionization. We present a theoretical analysis and a recipe for obtaining an optimal energy ratio between such selected ions and molecular ions in unwanted rovibronic states, created by direct photoionization. It is shown that the second-order chromatic aberration of a dc quadrupole bender can be used to isolate the state-selectively prepared molecular ions. The phase-space properties of ions prepared by MATI are ideally suited for axial injection into a linear radio-frequency trap. A modified approach for carrying out MATI within such an ion trap is also described.
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Optics · Cross-listed from quant-ph

Generating quantum entanglement from sunlight

Cheng Li, Jasvinder Brar, Michael Küblböck et al. (+3 more)

Energy consumption is becoming a serious bottleneck for integrating quantum technologies within the existing global information infrastructure. In photonic architectures, considerable energy overheads stem from using lasers, whose high coherence was long considered indispensable for quantum state preparation. Here, we demonstrate that natural, incoherent sunlight can successfully produce quantum-entangled states via spontaneous parametric down-conversion. We detect polarization-entangled photon pairs with a concurrence of $0.905\pm0.053$ and a Bell state fidelity of $0.939\pm0.027$. Importantly, the system violates Bell's inequality with $S=2.5408\pm0.2171$, exceeding the classical threshold of 2, while maintaining generation rates comparable to laser-based setups. These findings pave the way for sustainable quantum applications in resource-limited environments like interplanetary missions.
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All authors Cheng Li, Jasvinder Brar, Michael Küblböck, Jeremy Upham, Hanieh Fattahi, Robert W. Boyd

Instrumentation and Detectors · Cross-listed from hep-ex

The COHERENT Experiment: 2026 Update

M. Adhikari, M. Ahn, D. Amaya Matamoros et al. (+107 more)

The COHERENT experiment measures neutrino-induced recoils from coherent elastic neutrino-nucleus scattering (CEvNS) with multiple nuclear targets at the Spallation Neutron Source (SNS) at the Oak Ridge National Laboratory (ORNL), USA. Several successful CEvNS measurements have been achieved in recent years with tens-of-kg detector masses, with a CsI scintillating crystal, a liquid argon single-phase detector, and high-purity germanium spectrometers. For the next phase, COHERENT aims at high-statistics detection of CEvNS events for precision tests of the standard model of particle physics, and to probe new physics beyond-the-standard model. Percent-level precision can be achieved by lowering thresholds, reducing backgrounds, and by scaling up the detector masses. It goes hand in hand with benchmarking the neutrino flux from the SNS. Further detectors will measure CEvNS in additional nuclei, including lighter target nuclei such as sodium and neon, to continue to test the expected neutron-number-squared dependence of the cross section. COHERENT can furthermore study charged-current and neutral-current inelastic neutrino-nucleus cross sections on various nuclei at neutrino energies below $\sim$50 MeV. Many of these cross sections have never been measured before, but are critical input for the interpretation of core-collapse supernova detection in large-scale neutrino experiments such as DUNE, Super-K, Hyper-K, and HALO.
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All authors M. Adhikari, M. Ahn, D. Amaya Matamoros, P.S. Barbeau, V. Belov, I. Bernardi, C. Bock, A. Bolozdynya, R. Bouabid, J. Browning, B. Cabrera-Palmer, N. Cedarblade-Jones, S. Chen, A.I. Colón Rivera, V. da Silva, J. Daughhetee, Y. Efremenko, S.R. Elliott, A. Erlandson, L. Fabris, M.L. Fischer, S. Foster, A. Galindo-Uribarri, E. Granados Vazquez, M.P. Green, B. Hackett, J. Hakenmüller, M. Harada, M.R. Heath, S. Hedges, Y. Hino, H. Huang, W. Huang, H. Jeong, B.A. Johnson, T. Johnson, A. Khromov, D. Kim, L. Kong, A. Konovalov, Y. Koshio, E. Kozlova, A. Kumpan, O. Kyzylova, Y. Lee, S.M. Lee, G. Li, L. Li, Z. Li, J.M. Link, J. Liu, Q. Liu, X. Lu, M. Luxnat, D.M. Markoff, J. Mattingly, H. McLaurin, K. McMichael, N. Meredith, Y. Nakajima, F. Nakanishi, J. Newby, B. Nolan, J. O'Reilly, A. Orvedahl, D.S. Parno, D. Pérez-Loureiro, D. Pershey, C.G. Prior, J. Queen, R. Rapp, H. Ray, O. Razuvaeva, D. Reyna, D. Rudik, J. Runge, D.J. Salvat, J. Sander, K. Scholberg, H. Sekiya, J. Seligman, A. Shakirov, G. Simakov, J. Skweres, W.M. Snow, V. Sosnovtsev, Q. Stefan, M. Stringer, C. Su, T. Subedi, B. Suh, B. Sur, R. Tayloe, Y.-T. Tsai, J. Vaccaro, E.E. van Nieuwenhuizen, C.J. Virtue, G. Visser, K. Walkup, E.M. Ward, R. Wendell, T. Wongjirad, C. Yang, Y. Yang, J. Yoo, C.-H. Yu, Y. Yu, A. Zaalishvili, J. Zettlemoyer, Y. Zheng

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

Planar Structures of Medium-Sized Gold Clusters Become Ground States upon Ionization

Mohammad Ismaeil Safa, Ehsan Rahmatizad Khajehpasha and Stefan Goedecker

This study investigates the structural stability of ionized gold clusters of sizes ranging from 22 to 100 atoms, contrasting compact, cage and planar structures. While it is well known that neutral clusters in the upper part of this size range predominantly favor compact structures, our results reveal that positively ionized gold clusters exhibit structural transitions in which planar structures become energetically preferred once the charge is sufficiently large. In addition, we study the finite-temperature stability of the structures and find that thermodynamic effects further stabilize planar configurations relative to their compact counterparts. To explore the potential energy surface, we use the Minima Hopping algorithm combined with a machine-learned potential. Since the machine-learned potential does not apply to ionized clusters, we introduce a charge-correction term to incorporate Coulomb interactions and charge screening.
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Fluid Dynamics

Equilibrium statistical mechanics of waves in inhomogeneous moving media

Alexandre Tlili and Basile Gallet

We adapt the microcanonical framework of equilibrium statistical mechanics to predict the statistics of short waves in inhomogeneous moving media. For steady inhomogeneities and background flow, we compute the wave spectrum at any location in the domain based on an ergodic prescription for the action density in phase space, constrained by conservation of absolute frequency. We illustrate the method for shallow-water waves subject to a background flow or to topographic inhomogeneities, and for deep-water surface capillary waves over a background flow, validating the predicted maps of rms surface elevation and interfacial slope against numerical simulations.
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Computational Physics

Neural-POD: A Plug-and-Play Neural Operator Framework for Infinite-Dimensional Functional Nonlinear Proper Orthogonal Decomposition

Changhong Mou, Binghang Lu and Guang Lin

AI for science (AI4Science) models often suffer from discretization: learned representations remain tied to the training grid, limiting transfer across resolutions, solvers and applications. We introduce Neural Proper Orthogonal Decomposition (Neural-POD), a plug-and-play neural operator that learns nonlinear, orthogonal basis functions directly in function space and can be integrated in both projection-based reduced order models and operator-learning frameworks such as DeepONet. Neural-POD replaces SVD-derived, resolution-dependent linear modes with continuous, resolution-invariant bases learned via sequential residual minimization, analogous to Gram-Schmidt orthogonalization. The framework supports training under task-specific norms (e.g., $L^2$, $L^1$), improves out-of-distribution generalization to unseen parameter regimes, and captures nonlinear structure in complex systems. Because the learned bases are interpretable and reusable, Neural-POD serves as a general representation module for AI4Science workflows. We demonstrate Neural-POD on Burgers' and Navier-Stokes equations.
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Biological Physics · Cross-listed from cond-mat.stat-mech

Fastest first-passage time for multiple searchers with finite speed

Denis S. Grebenkov, Ralf Metzler and Gleb Oshanin

We study analytically and numerically the mean fastest first-passage time (fFPT) to an immobile target for an ensemble of $N$ independent finite-speed random searchers driven by dichotomous noise and described by the telegrapher's equation. In stark contrast to the well-studied case of Brownian particles – for which the mean fFPT vanishes logarithmically with $N$ – we uncover that the mean fFPT is bounded from below by the minimal ballistic travel time, with an exponentially fast convergence to this bound as $N \to \infty$. This behavior reveals a dramatic efficiency advantage of physically realistic, finite-speed searchers over Brownian ones and illustrates how diffusive macroscopic models may be conceptually misleading in predicting the short-time behavior of a physical system. We extend our analysis to anomalous diffusion generated by Riemann-Liouville-type dichotomous noises and find that target detection is more efficient in the superdiffusive regime, followed by normal and then subdiffusive regimes, in agreement with physical intuition and contrary to earlier predictions.
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Fluid Dynamics · Cross-listed from cond-mat.soft

Deformation and orientation of a capsule with viscosity contrast in linear flows: a theoretical study

Paul Regazzi and Marc Leonetti

We develop a perturbation theory to study the shape and the orientation of an initially spherical capsule of radius R with a viscosity contrast, a surface tension {\sigma} and a bending rigidity $\kappa$ in linear flows. The elastic mechanical response of membrane to deformations is described by three elastic constitutive law which are either Hookean, Neohookean or Skalak type leading to the introduction of a surface shear elastic modulus $G_s$ and the Poisson ratio (or analog quantities). At the leading order, the deformation, i.e. the so-called Taylor parameter is proportional to the elastic capillary number Ca which evaluates the ratio between the external viscous stress and the elastic membrane response. In this linear regime, the results do not depend on the elastic constitutive law as expected. Without surface tension and bending rigidity, we recover the results of Barthes-Biesel & Rallison (1981) and notably the fact that the Taylor parameter does not depend on the viscosity contrast $\lambda$ contrary to the case of a viscous droplet. In our more general model, the deformation does no longer depend on $\lambda$ at the upper order. Now, the Taylor parameter also depends on two other dimensionless numbers: the surface elastocapillary ratio $\sigma/G_s$ and the dimensionless bending rigidity $B= \kappa/G_sR^2$. At the further order, the angle of inclination of the capsule with the direction of the shear flow, the analog of the Chaffey and Brenner equation for droplets is determined in each case. The results are in excellent agreement with the numerical ones performed with a code based on the boundary integral method providing an useful method to valid numerical developments.
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Atomic Physics

Relativistic nuclear recoil effects in hyperfine splitting of hydrogenic systems

Jakub Hevler, Andrzej Maroń and Krzysztof Pachucki

Finite nuclear mass $(Z\,\alpha)^2\,m/M\,E_F$ corrections to the hyperfine splitting in hydrogenic systems are calculated using a combined relativistic heavy particle and nonrelativistic quantum electrodynamics. The obtained results are in disagreement with previous calculations by Bodwin and Yennie [Phys. Rev. D 37, 498 (1988)]. The comparison of improved theoretical predictions with the corresponding measurements in hydrogen reveals $2\,\sigma$ discrepancy, which may indicate problems with the proton structure corrections.
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Applied Physics · Cross-listed from cs.RO

Grip as Needed, Glide on Demand: Ultrasonic Lubrication for Robotic Locomotion

Mostafa A. Atalla, Daan van Bemmel, Jack Cummings et al. (+3 more)

Friction is the essential mediator of terrestrial locomotion, yet in robotic systems it is almost always treated as a passive property fixed by surface materials and conditions. Here, we introduce ultrasonic lubrication as a method to actively control friction in robotic locomotion. By exciting resonant structures at ultrasonic frequencies, contact interfaces can dynamically switch between "grip" and "slip" states, enabling locomotion. We developed two friction control modules, a cylindrical design for lumen-like environments and a flat-plate design for external surfaces, and integrated them into bio-inspired systems modeled after inchworm and wasp ovipositor locomotion. Both systems achieved bidirectional locomotion with nearly perfect locomotion efficiencies that exceeded 90%. Friction characterization experiments further demonstrated substantial friction reduction across various surfaces, including rigid, soft, granular, and biological tissue interfaces, under dry and wet conditions, and on surfaces with different levels of roughness, confirming the broad applicability of ultrasonic lubrication to locomotion tasks. These findings establish ultrasonic lubrication as a viable active friction control mechanism for robotic locomotion, with the potential to reduce design complexity and improve efficiency of robotic locomotion systems.
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All authors Mostafa A. Atalla, Daan van Bemmel, Jack Cummings, Paul Breedveld, Michaël Wiertlewski, Aimée Sakes

Fluid Dynamics

Influence of the Inhalation Route on Tracheal Flow Structures in Patient-Specific Airways using 3D PTV

Benedikt H. Johanning-Meiners, Luca Mayolle, Dominik Krug et al. (+1 more)

The tracheal flow field shapes particle transport into the lower airways and thus influences both the spread of inhaled pathogens and the effectiveness of aerosol-based therapies. Identifying how different inhalation routes modify the flow field is therefore crucial for understanding lower-airway disease transmission and for guiding targeted drug delivery. To gain a detailed understanding of the influence of the inhalation route on the flow structures in the human trachea, the flow field in the trachea is investigated in vitro in a non-compliant, refractive-index matched silicone model of the human respiratory tract. The investigations comprise steady inhalation, and oscillatory flow to simulate calm breathing. A realistic breathing pattern is approximated by a sinusoidal waveform for two Reynolds numbers of $Re_{Tr} = [400, 1200]$, based on the bulk velocity at maximum volume flux and the hydraulic diameter of the trachea and two Womersley numbers of $Wo = [3, 4.5]$, representing the oscillation time scales. To capture the inherently three-dimensional and asymmetric nature of the flow field, 3D particle-tracking velocimetry measurements are performed using the Shake-The-Box algorithm. Using a refractive-index matched fluid consisting of water and glycerin, the complex flow structures inside the trachea are fully resolved. The PTV measurements confirm that the nasal and/or oral cavity must be considered when analyzing the flow field in the lower respiratory tract. In particular, we find that the presence of both cavities significantly alters the flow field compared to idealised, fully developed inflow conditions. However, velocity profiles in the sagittal and coronal plane in the trachea as well as contour plots of the of the normalized velocity magnitude evidence nearly identical flow structures for oral and nasal inhalation, indicating minimal influence of the inhalation route.
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All authors Benedikt H. Johanning-Meiners, Luca Mayolle, Dominik Krug, Michael Klaas

Atomic and Molecular Clusters · Cross-listed from cond-mat.quant-gas

Stability of Bose-Fermi mixtures in two dimensions: a lowest-order constrained variational approach

Pietro Cordioli, Leonardo Pisani and Pierbiagio Pieri

We investigate the problem of mechanical stability in two-dimensional Bose-Fermi mixtures at zero temperature, focusing on systems with a tunable Bose-Fermi (BF) interaction and a weak but finite boson-boson (BB) repulsion. The analysis is carried out within the framework of the lowest-order constrained variational (LOCV) approach, which allows for a non-perturbative treatment of strong interspecies correlations while retaining analytical transparency. The BF interaction is modeled by a properly regularized attractive contact potential, enabling the exploration of both the attractive and repulsive energy branches. We determine the minimal BB repulsion required to ensure mechanical stability of the mixture by evaluating the inverse compressibility matrix over the full range of BF coupling strengths, within the domain of validity of the LOCV approximation. The interaction contribution to the energy is benchmarked against available experimental data and Quantum Monte Carlo results in the single-impurity limit, showing good agreement. Our analysis reveals how the critical BB coupling depends on interaction strength, density imbalance, and mass ratio. In particular, we find that mixtures with equal boson and fermion masses exhibit enhanced stability, requiring the smallest BB repulsion to prevent mechanical instability. In this case, a relatively small BB interaction is sufficient to stabilize attractive mixtures for all values of the BF interaction. These results provide a theoretical framework for assessing stability conditions in experimentally realizable two-dimensional Bose-Fermi mixtures with tunable interactions.
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Fluid Dynamics

Uni-Flow: a unified autoregressive-diffusion model for complex multiscale flows

Xiao Xue, Tianyue Yang, Mingyang Gao et al. (+7 more)

Spatiotemporal flows govern diverse phenomena across physics, biology, and engineering, yet modelling their multiscale dynamics remains a central challenge. Despite major advances in physics-informed machine learning, existing approaches struggle to simultaneously maintain long-term temporal evolution and resolve fine-scale structure across chaotic, turbulent, and physiological regimes. Here, we introduce Uni-Flow, a unified autoregressive-diffusion framework that explicitly separates temporal evolution from spatial refinement for modelling complex dynamical systems. The autoregressive component learns low-resolution latent dynamics that preserve large-scale structure and ensure stable long-horizon rollouts, while the diffusion component reconstructs high-resolution physical fields, recovering fine-scale features in a small number of denoising steps. We validate Uni-Flow across canonical benchmarks, including two-dimensional Kolmogorov flow, three-dimensional turbulent channel inflow generation with a quantum-informed autoregressive prior, and patient-specific simulations of aortic coarctation derived from high-fidelity lattice Boltzmann hemodynamic solvers. In the cardiovascular setting, Uni-Flow enables task-level faster than real-time inference of pulsatile hemodynamics, reconstructing high-resolution pressure fields over physiologically relevant time horizons in seconds rather than hours. By transforming high-fidelity hemodynamic simulation from an offline, HPC-bound process into a deployable surrogate, Uni-Flow establishes a pathway to faster-than-real-time modelling of complex multiscale flows, with broad implications for scientific machine learning in flow physics.
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All authors Xiao Xue, Tianyue Yang, Mingyang Gao, Leyu Pan, Maida Wang, Kewei Zhu, Shuo Wang, Jiuling Li, Marco F.P. ten Eikelder, Peter V. Coveney

Optics · Cross-listed from quant-ph

Theory of temporal three-photon interference

Nilakshi Senapati, Girish Kulkarni and Anand K. Jha

The recent demonstrations of cascaded PDC (CPDC) and the hopeful prospects of realizing third-order PDC (TOPDC) for the generation of three-photon entangled states are paving the way for experimental studies on genuine three-photon interference. In this article, we formulate three-photon interference in terms of “each three-photon interfering only with itself.” We show that although a generalized two-alternative three-photon interference setup based on CPDC or TOPDC involves eight different length parameters, the interference can be fully characterized in terms of only three independent parameters. The first parameter is the three-photon path-length difference, which has a direct analog in the one-photon and two-photon cases, and the other two parameters quantify the path-asymmetry length. Unlike two-photon interference, which requires only one parameter to quantify path-asymmetry, two independent parameters are needed in three-photon interference. This results in a broader class of nonclassical three-photon effects, including three-photon HOM-type effects. Our work provides the theoretical basis for existing and future three-photon interference experiments exploring the rich and complex quantum correlations associated with three-particle entanglement and potentially enabling the development of novel protocols for harnessing those correlations.
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Fluid Dynamics

Novel distance-based masking and adaptive alpha-shape methods for CNN-ready reconstruction of arbitrary 2D CFD flow domains

Mehran Sharifi, Gorka S. Larraona and Alejandro Rivas

Interpolating scattered CFD datasets onto a uniform Cartesian grid can distort the true geometry, producing a convex-hull type envelope and activating nonphysical regions. This work presents a reconstruction framework that recovers physically consistent masks before exporting CNN-ready fields. It introduces two novel strategies, distance-based masking and an adaptive alpha-shape formulation that normalizes alpha using local data resolution, and evaluates them against classical alpha-shape boundary recovery. A quantitative, topology-aware metric suite is introduced to assess retention, suppression of unsupported regions, overlap consistency, and connectivity. The novel distance-based method is robust across the geometries considered under the same threshold rule, with tau set to the minimum CFD grid spacing, and achieves 500-800 times speedups over classical alpha-shapes. The adaptive alpha-shape remains stable when its control parameter is set to 1 and is 1.7-2.6 times faster than the classical variant, which requires geometry-specific alpha tuning. A lightweight boundary inflation post-process using a minimal dilation further improves retention by up to 2.96% with negligible unsupported activation (less than 0.08%). Overall, the distance-based method is recommended as the default due to its accuracy, stability, minimal tuning, and low cost, while the adaptive alpha-shape is a strong alternative when grid-spacing information for threshold selection is unavailable. A companion web application operationalizes the workflow end to end, enabling 2D ASCII dataset upload, parameter tuning, mask and boundary generation, and export of CNN-ready outputs.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci

Reactive Coarse Grained Force Field for Metal-Organic Frameworks applied to Modeling ZIF-8 Self-Assembly

Sangita Mondal, Cecilia M. S. Alvares and Rocio Semino

Decoding the self-assembly mechanism of metal-organic frameworks is a crucial step in reducing trial-and-error tests in their synthesis protocols. Atomistic simulations have proven essential in revealing molecular-level features of MOF nucleation, but they still exhibit limitations in the simulation setups due to size constraints (inability of reaching realistic concentrations or exploring non-stoichiometric metal:ligand ratios). In this contribution, we develop a methodology to derive reactive coarse grained force fields based on multiscale coarse graining methods. We apply our novel methodology to the case of the archetypal zeolitic-imidazolate framework ZIF-8. Our coarse grained force field, which we call nb-CG-ZIF-FF, does not contain any explicit connectivity information, but learns the tetrahedral Zn-connectivity from many body correlations within an atomistic benchmark. nb-CG-ZIF-FF quantitatively reproduces the features of bulk, crystalline ZIF-8 as well as the structural evolution of pre-nucleation species in terms of Zn n-fold coordination populations from the atomistic benchmark. While the range of rings that are formed along the synthesis process are well captured by nb-CG-ZIF-FF, the model cannot exactly reproduce ring populations. Our reactive CG force field fitting approach can be applied to any MOF, opening new research avenues in modeling MOF formation, decomposition, defect dynamics and phase transition processes.
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Plasma Physics

From Coils to Surface Recession: Multiphysics Simulation of Ablation in ICP Wind Tunnels

Sanjeev Kumar, Alessandro Munafo, Blaine Vollmer et al. (+4 more)

This work presents a multi-solver, coupled computational framework for predicting the thermo-chemical material response of thermal protection systems in inductively coupled plasma (ICP) wind tunnels. The framework integrates a high-fidelity Navier-Stokes plasma solver, an electromagnetic field solver, and a discontinuous-Galerkin material response solver using a partitioned coupling strategy. This enables an ab initio, end-to-end simulation of the 350 kW Plasmatron X facility at the University of Illinois Urbana-Champaign (UIUC), including plasma generation, electromagnetic heating, near-wall thermochemistry, and time-accurate material ablation. The model captures key ICP physics such as vortex-mode recirculation, Joule-heating-driven plasma formation, and Lorentz-force-induced flow confinement, and accurately predicts the transition from subsonic to supersonic jet behavior at low pressures. Validation against cold-wall calorimetry shows that predicted stagnation-point cold-wall heat fluxes fall well within experimental uncertainty, while coupled ablation simulations accurately reproduce measured stagnation temperature histories and recession rates with errors below 12% and 10%, respectively. Remaining discrepancies are attributed to uncertainties in power-coupling efficiency, equilibrium ablation modeling, and material property datasets. Sensitivity analyses reveal that a 10% variation in system efficiency can induce changes of up to 11% in steady- state surface temperature and 17% in recession rate, whereas an equivalent variation in material thermal conductivity results in comparatively minor deviations of about 1.5% and 0.5%, respectively. Overall, the framework demonstrates strong predictive capability for ICP wind tunnel environments and provides a foundation for improved design, interpretation, and planning of hypersonic material testing campaigns.
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All authors Sanjeev Kumar, Alessandro Munafo, Blaine Vollmer, Massimo Franco, Kelly A. Stephani, Daniel J. Bodony, Marco Panesi

Physics and Society · Cross-listed from cs.CY

How to Detect Information Voids Using Longitudinal Data from Social Media and Web Searches

Irene Scalco, Francesco Gesualdo, Roy Cerqueti et al. (+1 more)

The model of the attention economy, where content producers compete for the attention of users, relies on two key forces: information supply and demand. This study leverages the feedback loop between these forces to develop a method for detecting and quantifying information voids, i.e., periods in which little or no reliable information is available on a given topic. Using a case study on COVID-19 vaccines rollout in six European countries, and drawing on data from multiple platforms including Facebook, Google, Twitter, Wikipedia, and online news outlets, we examine how information voids emerge, persist and correlate with a decline in the proportion of high-quality information circulating online. By conceptualising information voids as a specific regime of information spreading, we also quantify their counterpart, information overabundance, which constitute a central component of the current definition of infodemic. We show that information voids are associated with a higher prevalence of misinformation, thus representing problematic hotspots in which individuals are more likely to be misled by low-quality online content. Overall, our findings provide empirical support for the inclusion of information voids in mechanistic explanations of misinformation emergence.
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All authors Irene Scalco, Francesco Gesualdo, Roy Cerqueti, Matteo Cinelli

Fluid Dynamics

Fluids You Can Trust: Property-Preserving Operator Learning for Incompressible Flows

Ramansh Sharma, Matthew Lowery, Houman Owhadi et al. (+1 more)

We present a novel property-preserving kernel-based operator learning method for incompressible flows governed by the incompressible Navier–Stokes equations. Traditional numerical solvers incur significant computational costs to respect incompressibility. Operator learning offers efficient surrogate models, but current neural operators fail to exactly enforce physical properties such as incompressibility, periodicity, and turbulence. Our kernel method maps input functions to expansion coefficients of output functions in a property-preserving kernel basis, ensuring that predicted velocity fields analytically and simultaneously preserve the aforementioned physical properties. We present universal approximation results and worst-case a priori convergence rates for our framework; empirically, the observed convergence rates exceed the pessimistic predictions across most benchmarks, motivating a formulation of more optimistic convergence rates. Another central contribution of this work is a novel computational framework revolving around streaming construction of kernel Gramians and recursive Schur-complement algorithms to solve the large block linear systems arising from property-preserving kernel methods. This kernel-based framework makes operator learning practical at scales up to $10{,}000$ training functions sampled at up to $10{,}000$ spatial locations. We evaluate the method on challenging 2D and 3D, laminar and turbulent, incompressible flow problems. Our method achieves up to six orders of magnitude lower relative $\ell_2$ errors upon generalization and trains up to five orders of magnitude faster compared to neural operators. Moreover, while our method enforces incompressibility analytically, neural operators exhibit large divergence errors. Our results show that our method provides an accurate and efficient surrogate for incompressible flows.
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All authors Ramansh Sharma, Matthew Lowery, Houman Owhadi, Varun Shankar

Physics and Society

The Skeletal Trap: Mapping Spatial Inequality and Ghost Stops in Ankara's Transit Network

Elifnaz Kancan

Ankara's public transport crisis is commonly framed as a shortage of buses or operational inefficiency. This study argues that the problem is fundamentally morphological and structural. The city's leapfrog urban expansion has produced fragmented peripheral clusters disconnected from a rigid, center-oriented bus network. As a result, demand remains intensely concentrated along the Kizilay-Ulus axis and western corridors, while peripheral districts experience either chronic under-service or enforced transfer dependency. The deficiency is therefore not merely quantitative but rooted in the misalignment between urban macroform and network architecture. The empirical analysis draws on a 173-day operational dataset derived from route-level passenger and trip reports published by EGO under the former "Transparent Ankara" initiative. To overcome the absence of stop-level geospatial data, a Connectivity-Based Weighted Distribution Model reallocates passenger volumes to 1 km x 1 km grid cells using network centrality. The findings reveal persistent center-periphery asymmetries, structural bottlenecks, and spatially embedded accessibility inequalities.
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Physics Education

Students' understanding of the 2D Heat Equation: An APOS approach

Maria Al Dehaybes, Johan Deprez, Paul van Kampen et al. (+1 more)

In this paper, we use the APOS theoretical framework to validate a hypothetical learning trajectory of the 2D heat equation, a preliminary genetic decomposition that stresses the conceptual understanding of its mathematical formulation. We design questions to probe specific mental constructions of the preliminary genetic decomposition. We interview 8 students in the second year of the B.Sc. enrolled in either engineering, physics or twin (mathematics and physics) majors. Our findings indicate that students engage with many predicted mental constructions. In particular, coordination and encapsulation of two process conceptions of the Laplacian of the temperature improve understanding although it is challenging. Other parts of the genetic decomposition require refinements. These include mental constructions related to the temperature distribution function, heat flow, and the temperature gradient.
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All authors Maria Al Dehaybes, Johan Deprez, Paul van Kampen, Mieke De Cock

Optics

Fractional optical skyrmions

Yuancong Cao, Ram Nandan Kumar, Hadrian Bezuidenhout et al. (+3 more)

Optical topologies in the form of Skyrmions have attracted significant interest of late, where their integer Skyrmion number has been shown to be robust to complex media. Here we create the first fractional Skyrmions by structuring light as a vectorial superposition of non-integer orbital angular momentum. We unravel the map structure to reveal a new phenomenon, the abrupt transition jumps in skyrmion number, which serves to reinforce the integer nature of skyrmion topologies. Our experimental demonstration agrees well with simulation, opening a new spectrum of optical topologies to explore, with exciting possibilities in optical communication and sensing.
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All authors Yuancong Cao, Ram Nandan Kumar, Hadrian Bezuidenhout, Mingjian Cheng, Lixin Guo, Andrew Forbes

Instrumentation and Detectors

Impact of front-end parameters of the ARCADIA MD3 on charged particle detection

C. Pantouvakis, S. Garbolino, M. Rignanese et al. (+21 more)

The ARCADIA INFN R&D project developed a Fully Depleted Monolithic Active Pixel Sensor (FD-MAPS) using a customized LFoundry 110 nm CIS process. The first in-beam characterization of the ARCADIA Main Demonstrator 3 (MD3) sensor with 200 $\mu$m active thickness has been performed at the Fermilab Test Beam Facility with a 120 GeV proton beam. The Device Under Test (DUT) is tested with a trigger-less telescope composed of two ARCADIA MD3 tracking planes. This early study investigates the effect of the front-end parameters on the tracking performance.
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All authors C. Pantouvakis, S. Garbolino, M. Rignanese, P. Affleck, A. Apresyan, P. Azzi, N. Bacchetta, C. Bonini, D. Chiappara, S. Ciarlantini, D. Falchieri, A. Hayrapetyan, S. Mattiazzo, L. Pancheri, D. Pantano, A. Rivetti, M. Rolo, R. Santoro, R. Turrisi, J. Wyss, S. Xie, A. Zingaretti, I. Zoi, P. Giubilato