Optics · Cross-listed from cond-mat.dis-nn
Experimental realization of the complete seven-phase Anderson-localization landscape
Yao Qin, Chao Yang, Yuzhe Zhang et al. (+2 more)
Anderson localization has evolved far beyond the conventional dichotomy between extended and localized states. Modern localization theory predicts a complete transport hierarchy comprising extended, critical, and localized phases together with all coexistence phases among them, forming a seven-phase Anderson-localization landscape. Despite its fundamental importance, this hierarchy has never been experimentally realized within a single system. Here we realize the complete seven-phase Anderson-localization landscape in a one-dimensional Floquet photonic
lattice. By engineering quasiperiodic hopping profiles containing inhomogeneously distributed hopping zeros, we generate critical states and enable their coexistence with extended and localized sectors. The resulting transport regimes are directly resolved through their distinct spatiotemporal dynamics, including ballistic expansion, confined critical oscillations, and persistent localization. We observe all seven phases, including the elusive triply coexisting extended-critical-localized phase, and experimentally track the phase transitions connecting them. Our results establish the first complete experimental map of the Anderson-localization landscape and provide a unified platform for investigating mobility edges, multifractality, and programmable coherent transport.
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All authors Yao Qin, Chao Yang, Yuzhe Zhang, Yucheng Wang, Jingyun Fan
Physics and Society · Cross-listed from cs.MA
Selective Control under Noisy Perception: Governance Failures Hidden by Aggregate Metrics in Modular Networks
Igor Itkin
A content-moderation system can score well on every standard accuracy metric and still cause real harm, if its mistakes fall on the few users who connect otherwise separate communities. We show this in an
agent-based model where N=240 learning
agents on a community-structured network each post harmless, productive, or dangerous content, and a regulator removes or penalizes whatever a noisy classifier flags. Overall usefulness barely moves as the noise changes (one-way ANOVA, p=0.96): by aggregate measures, nothing looks wrong. The damage instead concentrates on these bridge users, whose useful posts are wrongly suppressed and whose dangerous posts are wrongly spared. A governance loss (L_gov) that prices these two mistakes separately from the cost of enforcement more than doubles under false-positive-heavy noise. Aggregate accuracy hides who is harmed, and the cheap quantity to audit is how many connections a user has (degree), a near-perfect proxy for the betweenness that defines a bridge (r=0.96).
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Physics and Society
Physics of anticipatory active matter, with application to crowd dynamics
Alexis Raulin-Foissac and Alexandre Nicolas
Statistical Physics has traditionally dealt with entities that interact merely based on the present, and possibly past, configurations. This reactive framework is inefficient in many situations involving living beings, such as predators chasing a prey, pedestrians, or even
robots. This paper introduces a statistical physical framework for the dynamics of anticipatory
agents, whose present-time dynamics depend on the prospective system state that they anticipate. We clarify how these dynamics can be expressed in terms of a cost function constructed based on observations and we show that the dynamics of an anticipatory
agent in d dimensions can be mapped onto the dynamics of a (non-anticipatory) chain in d + 1 dimensions, with fluctuations acting transversely on the chain to account for the uncertainty about the future state. Insights from
polymer Physics help us characterize the dynamics of these chains and delineate an anticipation horizon beyond which the blurry future can be handled in a mean-field way. The foregoing framework is successfully applied to pedestrian dynamics, leading to a seamless integration of operational and tactical levels in an
agent-based model. Even with a minimal expression of the cost, the model succeeds in reproducing various experimental scenarios which are challenging for state-of-the-art models, such as crossing cluttered environments or alighting from a crowded train. The transparent and flexible basis of the model allows the straightforward incorporation of additional mechanisms.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci
A Multi-Level Architecture for Reusable Materials Ontologies – The OntoCrafter Ceramics Ontology (OCO) as Reference Implementation
Thomas Pannek and Wolfgang Grond
The Materials Science and Engineering ontology landscape is fragmented along multiple axes simultaneously. Horizontally: a recent survey identified 94 ontologies of which over 40 are structurally incompatible; each new application domain – ceramics,
polymers, batteries, smart materials – typically restarts ontology design from scratch. Vertically: EU regulation (CSRD, CSDDD, PPWR, CBAM, R2R, AI Act, ESPR) forces material, manufacturing, supply-chain, and lifecycle data into integrated digital product passports, leaving ontologies that only address horizontal fragmentation incomplete for any contemporary consumer. And mechanistically: a vocabulary that records that BNT-BT has $d_{33} \approx 580$ pC/N stores a fact but cannot surface why – Bi-6s$^2$ lone-pair stereo-activity, anomalous Born effective charges, soft modes, defect chemistry – without a systematic explanation skeleton. We propose a multi-level modular architecture with two independent classification axes – level of abstraction (L0 bridges, L1 material-agnostic laboratory-notebook, L2 material-class-specific, L3 categorical
reasoning) and consumer audience (material vs. compliance) – in which the material-specific level is internally organised by a seven-tier mechanistic-explanation skeleton (
Symmetry, Energy/DFT, Thermo/CALPHAD, Kinetics, Microstructure, Defect chemistry, Bonding) applicable to any crystalline ionic
oxide. The level-and-audience modularity dissolves the horizontal fragmentation, the compliance audience absorbs the vertical regulation pressure, and the seven-tier organisation of Level 2 delivers the mechanistic explanation depth. We instantiate the architecture as the OntoCrafter Ceramics Ontology (OCO v0.94): 5,196 classes across 44 modules; 167,348 OWL axioms (40,454 logical); 1,674 properties; 829 cross-ontology bridge mappings; 1,172 SHACL shapes; 163 published competency questions.
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Fluid Dynamics
Scalar dissipation anomaly and scalar-gradient scaling in turbulence: A joint velocity-scalar multifractal view
Dhawal Buaria
We revisit the problem of scalar dissipation anomaly and scaling of scalar gradients in passive scalar
turbulence using theory and data from well-resolved direct numerical simulations (DNS) on grid sizes of up to $8192^3$, spanning Taylor-scale Reynolds numbers $Re_\lambda=140-1000$ and Schmidt numbers $Sc = 1-512$. The theory is based on a joint multifractal description of longitudinal velocity increments and scalar increments, constrained by Yaglom's law and extended to gradients via a fluctuating Batchelor cutoff scale. The DNS data show that the normalized mean scalar dissipation approaches a single asymptotic value as both $Re_\lambda$ and $Sc$ increase, although larger $Sc$ requires larger $Re_\lambda$ to reach this state. In the multifractal framework, this corresponds to an effective scalar Hölder exponent tending to zero, associated with sharp cliff-like scalar fronts, and saturation of inertial-range scaling scalar structure-function exponents. The joint velocity-scalar fractal dimension of the dissipative structures is inferred to approach $7/3$, indicating a non-space-filling support. The framework further predicts that for fixed $Re_\lambda$, higher-order central moments of scalar gradients are independent of $Sc$. This prediction is confirmed by DNS data and by the collapse of standardized probability distributions of scalar-gradient across Schmidt numbers. These results suggest that the $Sc$-scaling of scalar gradients is dictated solely by scalar dissipation anomaly. In contrast, their $Re_\lambda$-dependence reflects strong intermittency, which can be directly related to mixed velocity-scalar structure function exponents.
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Biological Physics · Cross-listed from q-bio.NC
Implications of hierarchical Markov models of behavior: on irreversibility, predictability, and dimensionality
John J. Vastola and Kanaka Rajan
The maturation of quantitative tools for studying the high-level structure of animal behavior, and especially tools which represent spontaneous behavior as a sequence of stereotyped and neurally well-defined 'syllables', demands that the field revisit a fundamental theoretical question: if the coarse structure of behavior can be accurately described by Markov models, what do these models really tell us about behavior? In this work, we explore the theoretical implications of these models and discuss how they allow us to quantitatively formulate questions about the sequence-like nature and effective dimensionality of behavior. One important insight is that the
eigenvalues and eigenvectors of various model-associated
matrices furnish interpretable time scales and modifications of behavior that occur on those time scales. We illustrate our points using both toy examples and Markov models fit to real data. By analyzing the consequences of Markov representations, we clarify the theoretical meaning of progress in quantifying behavior.
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Chemical Physics · Cross-listed from cond-mat.soft
Interfacial mass transfer resistance at fluid-fluid interfaces
Hyeongjoo Row, Brandon J. Wallace, Joshua B. Fernandes et al. (+2 more)
Complex chemistry in nano- and microscale compartments is often governed by how quickly reagents transit a fluid-fluid interface. Mass transport across interfaces is commonly modeled by assuming local
equilibrium, enforcing continuity of chemical potential across the interface. While adequate at large scales, this approximation may break down at the microscale, where interfacial processes can become rate-limiting. Here, we extend linear irreversible thermodynamics to describe nonequilibrium interfacial mass transport. We identify an interface-limited regime, in which transport is governed by interfacial resistance and exhibits exponential relaxation. Combining microfluidic and spectroscopic techniques, we introduce an experimental technique that explores this regime and provides a direct measurement of the interfacial mass transfer coefficient. For a model system consisting of acetonitrile transport across a surfactant-stabilized water-oil interface, we obtain an interfacial transport coefficient ${M \sim 7\,{\rm nm/s}}$. These results establish interfacial mass transfer resistance as a governing mechanism in microscale transport and provide a framework to predict, control and measure mass transport in multiphase systems at microscale.
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All authors Hyeongjoo Row, Brandon J. Wallace, Joshua B. Fernandes, Kevin R. Wilson, Kranthi K. Mandadapu
Computational Physics · Cross-listed from cond-mat.soft
Percolation of a rod-like particle in a static bed of spheres: trapping and passing
Juan C. Petit, Julio M. Ottino, Richard M. Lueptow et al. (+1 more)
We numerically investigate percolation of independent frictionless glued-sphere rod-like particles under
gravity through a disordered static bed of larger spheres. We identify two distinct regimes: a trapping regime, where rods stop after percolating a limited distance in the bed and a passing regime, where rods percolate continuously with constant mean velocity. The transition between these regimes is governed by the length of the rod and the geometrical trapping threshold for spherical particles based on the rod diameter and the minimum pore throat diameter defined by three touching large spheres. The percolation velocity for all rod geometries, including the single sphere limit, collapses onto a single curve when scaled with the gravitational acceleration and the bed sphere diameter. The results also demonstrate that short rods percolate nearly twice as fast as long rods due to the
geometric constraints associated with the disordered pore structure of the static bed. Consequently, long rods are more susceptible to trapping via specific contact configurations with the bed spheres, which differ from those for short rods. These results reveal how shape anisotropy introduces dynamical constraints and thresholds in granular percolation, with implications for predicting segregation in mixtures of non-spherical particles.
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All authors Juan C. Petit, Julio M. Ottino, Richard M. Lueptow, Paul B. Umbanhowar
Atmospheric and Oceanic Physics
ENSO and the Temperature of the North Equatorial Counter Current: An Ensemble Study
David John Webb
An ensemble study using the CESM
climate model is used to investigate the response of the atmosphere to changes in sea surface temperatures along the path of the North Equatorial Counter Current. The results support those of a previous study which concentrated on a single run, confirming the sensitivity of deep convection in the central Pacific to the temperature of the counter current, and its impact on the Hadley Circulation, the Southern Oscillation and the equatorial winds in the Pacific. A comparison with the ECMWF ERA5 data, finds that the atmospheric reanalysis fields show similar correlation with the temperature of the counter current.
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Plasma Physics
Parametric instabilities of the inhomogeneous near SOL tokamak plasma, driven by the coupled effect of the high harmonic fast wave and of the ion and electron temperatures gradients, and anomalous heating of the near SOL ions
V. V. Mikhailenko, V. S. Mikhailenko and Hae June Lee
Electrostatic parametric instabilities in the inhomogeneous near-SOL tokamak
plasma, driven by the combined action of a high-harmonic fast wave (HHFW) with a frequency near the 30th ion-cyclotron (IC) harmonic and electron and ion temperature gradients, are investigated numerically. The results indicate the parametric decay of the HHFW into a HHIC (Bernstein) wave and HHIC quasimode. The instability is found to exist within a finite wavelength range of the HHFW. The development of the parametric HHIC quasimode decay instability leads to the onset of parametric
turbulence accompanied by anisotropic ion heating, with the ion heating rate across the
magnetic field significantly exceeding that along the
magnetic field.
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Computational Physics
Spin disorder competing with positional symmetry breaking governs the metal-insulator behavior in oxide paramagnets
Jia-Xin Xiong, Xiuwen Zhang and Alex Zunger
Numerous transition-metal
oxides have low-temperature, long-range-ordered
antiferromagnetic (AFM) states that are generally insulating, and high-temperature, disordered paramagnetic (PM) phases. The latter can be either insulating (predicted here for NaFeO3), or metallic (predicted here and previously observed in NaOsO3). Similar distinctions have been traditionally affected in strongly correlated models by the value used for Coulomb repulsion U. Here we show an alternative, strong-correlation-free (U=0) view suggesting that the distinction between insulating and metallic PM phases is governed by the competition between local
magnetic moment disorder and the polymorphous distribution of off-center atomic displacements. Such parameter-free, energy-lowering
symmetry breaking density functional calculations provide a framework for understanding metal-
insulator behaviors across different
quantum materials in terms of measurable local structural and
magnetic parameters.
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Geophysics
Towards unified Geophysical Data Requirements for Magnetic Navigation (MagNav)
Regupathi Angappan, Kimberly Moore and Sriharsha Thoram
Magnetic Navigation (MagNav) has emerged as a vital alternative Positioning,
Navigation, and Timing (PNT) solution, leveraging Earth's
magnetic field for robust
navigation in GPS/GNSS-degraded or denied environments. Despite its potential, the successful deployment of MagNav is currently hindered by the lack of standardized, high-fidelity geomagnetic reference maps. Existing
datasets, primarily designed for geological exploration or academic research, do not meet the distinct operational requirements of
navigation systems regarding spatial resolution, error quantification, and global accessibility. This paper initiates a community-focused dialogue on future geophysical data requirements for MagNav, grounded in extensive real-world flight trials. We distinguish between two primary use cases with divergent data needs: Operational MagNav, which requires globally consistent, queryable, and uncertainty-aware
datasets for field deployment, and MagNav R&D, which demands comprehensive access to raw survey data to foster innovation. We provide a prioritized set of recommendations for future data requirements, including the development of cohesive, merged
datasets, the inclusion of localized 3D uncertainty estimates, and the expansion of the World
Magnetic Model (WMM) core field model to spherical harmonic degree 13 to improve consistency. Finally, we emphasize the strategic necessity of designated test ranges to validate these requirements and ensure the operational robustness of MagNav infrastructure.
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Optics
Scalable Fabrication of Thermally Reconfigurable Ge Metasurfaces Using Stencil Lithography for Mid-Infrared Molecular Sensing
Shovasis Kumar Biswas, Samir Rosas, Wihan Adi et al. (+4 more)
Mid-infrared (mid-IR) spectroscopy enables label-free molecular detection and is widely employed in biomedical, environmental, and chemical sensing; however, its broader deployment remains limited by bulky instrumentation and insufficient analytical sensitivity. Photonic metasurfaces supporting strong mid-IR resonances provide a promising route toward compact on-chip spectrometers and enhanced molecular sensing, yet their practical implementation is often constrained by limited spectral coverage and fabrication complexity. Here, we present a scalable, resist-free stencil lithography approach for fabricating arrays of Ge pillar metasurfaces on CaF2 substrates that support polarization-insensitive Mie resonances dominated by electric dipole modes. By varying the
geometric design parameters during fabrication, we engineered metasurface arrays with discrete resonances spanning the 950-1700 cm^-1 molecular fingerprint region. Furthermore, leveraging the thermo-optic response of Ge, we achieved dynamic tuning of these discrete resonances, demonstrating continuous and reversible resonance shifts of approximately 36 cm^-1 per metasurface over 300-500 K, corresponding to a tuning rate of 0.18 cm^-1/K. The thermally induced spectral sweeping enables multiplexed detection of poly(methyl methacrylate) vibrational modes and continuous reconstruction of its absorbance spectrum across 1100-1215 cm^-1. These results establish a scalable dielectric metasurface platform with spectrally reconfigurable mid - IR modes for molecular sensing across the fingerprint region and compact infrared sensor technologies.
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All authors Shovasis Kumar Biswas, Samir Rosas, Wihan Adi, Aidana Beisenova, Vaishakh Unnikrishnan, Furkan Kuruoglu, Filiz Yesilkoy
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Lattice dynamics and the spectroscopic signatures of H-bond disorder in $\delta$-AlOOH
Chenxing Luo, Sangjoon Lee, Hongjin Wang et al. (+2 more)
Raman and infrared anomalies associated with H-bond symmetrization in $\delta$-AlOOH, including mode softening and linewidth broadening at 5-10 GPa, occur at significantly lower pressures than predicted by static harmonic theory. To resolve this discrepancy, we combine harmonic
phonon calculations with strongly constrained and appropriately normed (SCAN)-based deep-potential molecular dynamics and
phonon quasiparticle analysis at 300 K. This framework extracts temperature- and pressure-dependent frequencies and lifetimes from long-time trajectories, capturing the branch reorganization and rapid linewidth growth characteristic of the disordering regime. Incorporating quasiparticle renormalization and directional longitudinal-optical-transverse-optical (LO-TO) splitting further yields near-quantitative agreement with the ambient-pressure OH-stretching Raman multiplet. These results identify finite-temperature dynamical effects and the progressive loss of spectral coherence as the origin of the spectroscopic signatures of H-bond symmetrization.
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All authors Chenxing Luo, Sangjoon Lee, Hongjin Wang, Zhen Zhang, Renata Wentzcovitch
Applied Physics · Cross-listed from cond-mat.supr-con
Tailoring the properties of YBa$_{2}$Cu$_{3}$O$_{7-\delta}$ thin films by 30-keV He$^+$ irradiation: An enabling route to superconducting device nanopatterning
Bernd Aichner, Simon Koch, Philipp A. Korner et al. (+8 more)
Focused helium ion beam (He-FIB) irradiation with 30-keV ions is a key tool for nanoscale patterning and defect engineering in high transition temperature (Tc) cuprate superconducting devices, yet its usable fluence window is constrained by the competing requirements of reliable superconductivity suppression and minimal structural degradation. In this work, we provide a comprehensive
dataset on the effects of large-area 30-keV He+ ion exposure on the electric transport and superconducting properties of epitaxial YBa2Cu3O7 (YBCO) thin films. X-ray diffraction shows a fluence-driven loss of crystalline order accompanied by an out-of-plane
lattice expansion and an orthorhombic-to-tetragonal transition, culminating in predominant amorphization at the highest fluence of 1 x 10^16 cm^-2. Raman spectra exhibit increasing disorder while lacking signatures of oxygen depletion, indicating that irradiation mainly generates oxygen-related Frenkel defects rather than changing the carrier concentration. Consistently, with increasing fluence, the normal-state resistivity \rho_N(T) at temperature T above Tc increases strongly, while d \rho_N/d T remains nearly unchanged at moderate fluence. The suppression of Tc is accurately described by Abrikosov-Gor'kov pair breaking and reaches complete quenching of superconductivity at 4.5 x 10^15 cm^-2. The anisotropic upper critical fields decrease approximately exponentially with increasing fluence, the
vortex activation energy is reduced, and the anisotropy drops, in contrast to oxygen-depleted YBCO.
Hall-angle analysis confirms a nearly constant carrier density but a systematic increase in defect scattering and reduced mobility, consistent with a crossover toward the dirty limit at high fluence. These results establish quantitative fluence thresholds and a practical operational window for He-FIB nanopatterning of YBCO
quantum circuits.
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All authors Bernd Aichner, Simon Koch, Philipp A. Korner, Max Karrer, Katja Wurster, Christoph Schmid, Ulrich Kentsch, Reinhold Kleiner, Edward Goldobin, Dieter Koelle, Wolfgang Lang
Fluid Dynamics
Wave turbulence theory of odd fluids and solids: kinetic equations and solutions
Xander M. de Wit, Léo Touzo, Sébastien Galtier et al. (+3 more)
The theory of wave
turbulence describes the properties of physical systems composed of a set of weak-amplitude random waves interacting nonlinearly. Here, we study odd wave
turbulence, which arises in
chiral media subjected to non-reciprocal stresses, notably odd viscosity and odd elasticity. In both cases, we consider simple models for which we can derive and solve analytically the kinetic equations describing the long-term statistical behavior of spectral quantities such as energy or wave action. For odd viscosity, we consider a three-dimensional model that exhibits wave
turbulence involving three-wave interactions, which gives rise to a direct energy cascade characterized by an anisotropic Kolmogorov-Zakharov (KZ) spectrum. For odd elasticity, we consider a quasi-one-dimensional overdamped model that exhibits much slower dynamics involving six-wave interactions. In that case, the KZ spectrum corresponding to a forward cascade of a conserved quantity we call odd energy, is nonlocal and therefore does not constitute a physical solution. However, the other KZ solution, which describes an inverse cascade of wave action, is only marginally non-local and is therefore valid up to a logarithmic correction. These two analytical theories provide a rigorous interpretation of direct numerical simulations, where the KZ spectrum is observed both in the case of odd viscosity (forward cascade) and of odd elasticity (inverse cascade).
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All authors Xander M. de Wit, Léo Touzo, Sébastien Galtier, Michel Fruchart, Federico Toschi, Vincenzo Vitelli
Atomic Physics
Trap-Quenched Matter-Wave Optics in Space
Gabriel Müller, Timothé Estrampes, Claudia Puertas González et al. (+12 more)
Dual-species atomic sources in space promise to be the testbed for a multitude of searches in
quantum gas physics such as a precise test of the Universality of Free Fall (UFF), few-body physics, cold molecules and
quantum bubbles. These experiments demand exquisite control over the expansion energies of both condensed ensembles as well as over their differential center-of-mass dynamics. We propose a trap-quenched collimation technique featuring in-trap excitations of collective modes compatible with state-of-the-art atom-chip setups. Using NASA's Cold Atom Laboratory aboard the International Space Station, we demonstrate it on a single-species $^{87}$Rb condensate. By controlling the center-of-mass release dynamics, we observe free expansion times up to 700 ms and measure a two-dimensional expansion energy of $k_B \cdot 78\pm 9 \;\mathrm{pK}$ in the imaging plane. A detailed model of the magnetically-induced dynamics indicates that this corresponds to a two-dimensional expansion energy of about $k_B \cdot 15^{+12}_{-5}\; \mathrm{pK}$ along two of the condensate's eigenaxes. Finally, we theoretically study this trap-quenched collimation scheme for a $^{41}$K-$^{87}$Rb mixture, predicting a simultaneous collimation that meets the expansion energy requirements for a state-of-the-art UFF test at the $10^{-15}$ accuracy level.
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All authors Gabriel Müller, Timothé Estrampes, Claudia Puertas González, Jannik Ströhle, David B. Reinhardt, Dana Codruta Marinica, Ethan R. Elliott, Jason R. Williams, Nathan Lundblad, Eric Charron, Ernst M. Rasel, Matthias Meister, Wolfgang P. Schleich, Naceur Gaaloul, Nicholas P. Bigelow
Atmospheric and Oceanic Physics
Regional Climate Model Emulation with Diffusion Approaches: What is the Added Value of Generative Machine Learning?
Mikel N. Legasa, Antoine Doury, Achille Gellens et al. (+4 more)
Emulators provide a cost-effective alternative to regional
climate models (RCMs) by capturing their dynamical downscaling function. They link large-scale predictors simulated by global
climate models (GCMs) to RCM-simulated high-resolution fields of the target variable, here precipitation. Machine learning methods, typically deep learning, are cheaper than running RCMs in computation time and energy. Among them, generative models are appealing because they can simulate ensembles of local high-resolution fields consistent with the predictors. This ensemble, which we call the uncertainty envelope, remains to be properly assessed for added value. Here, we make three contributions. First, we introduce ParamDiffusion, a new two-stage
diffusion-based framework, and compare it with a state-of-the-art
diffusion approach. Second, we expand standard validation through a comprehensive framework aligned with
climate-science needs, examining specific precipitation events, including extremes. Third, within this framework, we assess the added value of
diffusion approaches relative to deterministic methods. We intercompare four deep-learning models: a deterministic model designed to capture the precipitation tail; a parametric probabilistic model based on it; a recently proposed
diffusion approach; and ParamDiffusion, which couples the parametric model with a
diffusion model. Our results show that
diffusion-based approaches reproduce climatological precipitation statistics with high skill, including distributional tails and spatially compounded extremes, while generating spatially detailed fields. However, none of the assessed models consistently accounts for the most extreme RCM-simulated events within its uncertainty envelope.
Diffusion models are therefore promising for probabilistic RCM emulation, but progress is still required before they can reliably represent high-impact precipitation extremes.
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All authors Mikel N. Legasa, Antoine Doury, Achille Gellens, Redouane Lguensat, Clara Naldesi, Soulivanh Thao, Mathieu Vrac
Fluid Dynamics
Scale-Separated Collective Bubble Nucleation and Departure
Rameez Iqbal, Gautier Rouaze, Gio Bellone et al. (+3 more)
Nucleation is classically treated as a local process, yet whether coupling between neighboring sites governs activation and stability remains unexplored. Here we show bubble nucleation is fundamentally collective: sites separated by the hydrodynamic-boundary-layer scale activate more readily and resist deactivation under changing thermal loads, consistent with a non-local hydrodynamic shielding mechanism, whereby neighboring bubbles slow the intervening flow, suppress convective heat removal, and stabilize vapor embryos. Using surfaces with two independently tunable length scales, we isolate this near-wall coupling from a second collective process, coalescence between departing bubble clusters, which transitions through isolated, promotive, and excessive regimes as the departure diameter grows with heat flux. The dominant length scale thus shifts with operating conditions, from boundary-layer coupling near activation to departure-scale coupling once nucleation is established. These results establish a scale-dependent framework for collective nucleation and departure, broadly related to phase change processes on structured surfaces.
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All authors Rameez Iqbal, Gautier Rouaze, Gio Bellone, Francesco Minola, Lenan Zhang, Zhengmao Lu
Computational Physics · Cross-listed from cs.CE
CANN-EUCLID: unsupervised constitutive artificial neural network model discovery from full-field data
Benjamin Alheit, Siddhant Kumar and Mathias Peirlinck
Constitutive artificial neural networks (CANNs) provide interpretable material model discovery, but have so far been used in stress-supervised settings based on apparent stress-strain data from homogeneous tests. Because each test samples only a narrow loading path and provides homogenized rather than local stress information, robust discovery typically requires multiple loading modes to constrain the multidimensional response. This is challenging for soft biological tissues, where repeated testing, damage, and sample variability limit reliable information from a single specimen. Here, we combine CANNs with the stress-unsupervised full-field discovery framework EUCLID to identify sparse hyperelastic laws directly from displacement fields and reaction forces in one heterogeneity-inducing loading case. CANN-EUCLID minimizes
equilibrium imbalance with sparsity-promoting regularization selecting compact active terms, without local stress measurements or a prescribed law. We evaluate the approach on isotropic and anisotropic
benchmarks with prescribed ground-truth laws. When the ground truth is representable by the chosen CANN basis, our method recovers the correct terms with near-exact accuracy, including exponential terms with embedded parameters. When it is not contained in the basis, the method retains shared terms and approximates missing contributions using available basis functions. Generalization depends strongly on sampled deformation states: exponential strain-stiffening terms can be recovered accurately when sufficiently probed, but can produce large extrapolation errors when the stiffening regime lies outside the sampled domain. Forward FE validation simulations show that the discovered behavior accurately replicates the ground truth. These results establish stress-unsupervised CANN discovery as a promising framework for interpretable full-field constitutive model identification.
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Optics · Cross-listed from quant-ph
Scaling native entanglement generation in layered semiconductors with quasi-phase matching
Benjamin Braun, Andrea Alessandrini, Josip Bajo et al. (+10 more)
Efficient generation of entangled
photons typically relies on spontaneous parametric down-conversion (SPDC) in phase-matched macroscopic nonlinear media. However, generating
entanglement under phase-matching constraints requires additional bulk optics or interferometers. In contrast, ultrathin van der Waals
semiconductors - such as transition metal dichalcogenides (TMDs) - exhibit strong enough optical nonlinearities for SPDC to be observed from subwavelength-thick media, thereby bypassing conventional phase-matching constraints. In this microscopic domain, the intrinsic
crystal symmetry governs the nonlinear optical response, enabling the native generation of polarization-entangled
photon pairs. However, generating these states efficiently has been fundamentally restricted by the material's coherence length ($L_c$), which limits the attainable conversion efficiency. Here, we investigate periodically-poled TMDs (PPTMDs) designed to scale up this interaction via quasi-phase matching. We demonstrate that mechanically flipping the sign of the nonlinearity at precise intervals of $L_c$ introduces quasi-phase matching, that scales the pair-production rate while preserving the pristine,
symmetry-generated polarization
entanglement, with fidelities exceeding 99%. Backed by a rigorous theoretical model, our work clarifies the interplay between
crystal symmetry and propagation effects in thin nonlinear media, providing a new avenue for engineering
quantum light in nanophotonic systems.
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All authors Benjamin Braun, Andrea Alessandrini, Josip Bajo, Philipp K. Jenke, Leone di Mauro Villari, Birui Yang, Zhi Hao Peng, P. James Schuck, Cory R. Dean, Andrea Marini, Philip Walther, Chiara Trovatello, Lee A. Rozema
Fluid Dynamics · Cross-listed from cond-mat.soft
Bacterial adhesion to curved surfaces in fluid flow
Edwina F. Yeo, Benjamin J. Walker, Philip Pearce et al. (+1 more)
Minimising bacterial surface adhesion and subsequent biofilm formation in industrial and medical settings requires understanding how bacteria are transported and adhere to complex surface geometries in the presence of non-uniform flow. In this paper, we consider the transport of a dilute suspension of motile bacteria through a corrugated two-dimensional channel with perfectly adhesive walls. We asymptotically analyse the diffusive boundary layer that forms in high velocity flows using a curvilinear coordinate system based on the fluid streamfunction, presenting a similarity solution to the diffusivity-varying
diffusion-type equation that arises. From this solution, we derive an analytical expression for the bacterial adhesion rate as a function of surface arclength and the spatially varying wall shear rate. Our model predicts that bacterial adhesion becomes localised on curved surfaces, with bacteria showing preferential adhesion to wall `peaks' at lower shear rates and preferential adhesion to wall `valleys' at higher shear rates. More broadly, our results highlight how spatially varying flows generated by complex geometries can lead to localised bacterial adhesion, with potential implications for both enhancing and minimising biofilm formation.
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All authors Edwina F. Yeo, Benjamin J. Walker, Philip Pearce, Mohit P. Dalwadi
Physics and Society
Modeling inhomogeneous spatial point configurations with applications to replicated patterns in real-life waiting crowds
Lars Sickert Karam, Rui M. Castro, Maarten Schoukens et al. (+1 more)
In this article, we connect statistical inference for spatial point processes with the analysis of waiting pedestrian crowds through two interconnected contributions. First, on the methodological side we develop an inference procedure for semiparametric spatial point process models leveraging replicated spatial patterns, i.e., multiple approximately independent realizations from the same process. Second, we show that spatial point processes provide a suitable modeling framework for waiting pedestrians, capturing two key aspects: spatial inhomogeneity driven by location attractiveness and repulsive interactions between pedestrians. These two components are central to the inference problem itself, since spatial point process modeling hinges on disentangling background intensity from interaction. Although replicated spatial patterns are rare in point process literature, they are available here through a unique real-life pedestrian
dataset, thereby directly linking the methodological development to the physical application. We use the proposed methods to fit and evaluate determinantal and Gibbs point processes in a simulation study and a real-world case study. Despite persistent challenges in decoupling the influences of inhomogeneity from interaction, these models are able to reproduce key empirical features of waiting pedestrians.
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All authors Lars Sickert Karam, Rui M. Castro, Maarten Schoukens, Alessandro Corbetta
Optics
Extreme-ultraviolet optical response of atomically-thin molybdenum disulfide
G. Fiorentini, N. Di Palo, G. Inzani et al. (+18 more)
We report multi-angle reflectivity measurements in the extreme-ultraviolet (XUV) range for mono- and
bilayer MoS$_2$ on a Si$_3$N$_4$ substrate. Using a single-sheet 2D conductivity model, we extract the complex optical response of the MoS$_2$
bilayer between 25 and 90 eV and derive an effective refractive index by introducing a thickness equal to the interlayer spacing. The MoS$_2$ monolayer response is consistently reproduced either by halving the 2D conductivity or the effective thickness, indicating a robust scaling with layer number. The resulting optical constants display a broad resonance at the Mo N$_{2,3}$ edge with no signatures of sharp core-
exciton features despite the reduced dimensionality. First-principles calculations reproduce the experimental results and show that local-field (Hartree) effects dominate the XUV response, while screened-exchange (SEX) contributions remain weak and mainly induce spectral shifts. Our analysis demonstrates that excitonic effects play a minor role in the XUV optical response of atomically thin MoS$_2$, highlighting key differences with respect to the visible and infrared regimes, and calling for a reassessment of the use of Mo-based transition metal dichalcogenides in attosecond spectroscopy and XUV excitonics.
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All authors G. Fiorentini, N. Di Palo, G. Inzani, G. L. Dolso, S. Bonetti, Q. Li, F. Liu, X. Zhu, A. Giglia, N. Mahne, L. Pasquali, M. D'Alessandro, M. Malakhov, M. Camarasa-Gómez, J. J. Esteve-Paredes, J. J. Palacios, R. Borrego-Varillas, M. Nisoli, A. Picón, D. Sangalli, M. Lucchini
Atmospheric and Oceanic Physics
Wind vector retrieval from miniaturized wave-enabled sea-surface drifters
Alexey S. Mironov
Open-ocean in situ winds are sparse, limiting the calibration and validation of satellite wind products. We evaluate wind-vector
retrieval from MELODI (Miniaturized Electronics Lagrangian Oceanographic DrIfter), a compact freely drifting GNSS/IMU wave buoy. Wind speed is inferred from the shape of the measured wave acceleration spectrum. A regularized regression with a gated nonlinear correction (Wind Inversion using Tikhonov Regularization, WITR), trained on scatterometer winds and evaluated by leave-one-buoy-out cross-validation against ASCAT MetOp-B/C and HY-2B/C, gives a root-mean-square difference (RMSD) of 0.91 m/s. Symbolic regression distills the trained model into compact spectrum-only and motion-enhanced equations suitable for onboard use; the reduced drag law gives 0.93-0.94 m/s. Wind direction is estimated, without any fitted reference-wind regression, from IMU-derived directional wave moments in the 0.60-0.90 Hz wind-sea band, with a circular mean absolute angular difference (MAAD) of 9.4 degrees against ASCAT. These differences are comparable to published scatterometer-moored-buoy comparisons and improve substantially on the traditional single-band Toba inversion. Validation is strongest from 4 to 14 m/s and sparse above approximately 16 m/s; stronger winds are assigned low confidence. The results show that small wave-sensing drifters, calibrated to the well-established scatterometer wind scale, can provide useful wind-vector observations for validating satellite wind products and for atmospheric and wave modeling; stronger-wind sampling remains a priority.
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Chemical Physics
A Fixed-Point Neural Operator for Size- and Functional-Transferable Hamiltonian Prediction
Yunhong Lou, Xihang Yue, Xinran Wei et al. (+2 more)
Predicting the Kohn-Sham
Hamiltonian with machine learning can accelerate density functional theory while retaining access to molecular orbitals, energy levels, and electronic-structure observables that energy-only surrogates cannot resolve. Yet element-wise agreement with the converged
Hamiltonian, an implicit fixed point of the self-consistent field iteration, does not determine the occupied subspace that governs orbital energies and densities. Here we present HamEvo, a neural operator that learns the single-step self-consistent update and returns the converged
Hamiltonian as its fixed point. HamEvo is pre-trained on intermediate self-consistent trajectories and calibrated at
equilibrium with density-
matrix supervision. Across
benchmarks from MD17 to drug-like QMugs, HamEvo lowers
Hamiltonian errors by 35-49% over direct-regression and deep-
equilibrium baselines, and predicts QMugs HOMO and LUMO energies with mean absolute errors of 0.036 and 0.053 eV, near the 1 kcal/mol chemical-accuracy scale. Few-shot fine-tuning with only 20 reference conformations extends HamEvo to molecules of up to 122 atoms, well beyond the size range covered by pre-training. With thermal molecular-dynamics sampling, HamEvo captures temperature-dependent HOMO-LUMO gap renormalization beyond the harmonic approximation. Inference is up to 242 times faster than conventional DFT.
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All authors Yunhong Lou, Xihang Yue, Xinran Wei, Tianqi Deng, Linchao Zhu
Atomic Physics
Ultra-broadband Anti-Jamming Communication via a Rydberg Atomic Receiver
Jia-Dou Nan, Jun-Rong Chen, Bang Liu et al. (+11 more)
Ultra-broadband anti-jamming communication represents a promising approach to secure and robust information transfer through spread-spectrum techniques, effectively combatting malicious interference and eavesdropping. Rydberg atoms, enhanced by waveguide coupling, facilitate ultra-broadband spectrum sensing without traditional RF components. This framework provides an experimental platform for ultra-wide anti-jamming communication. Here, we demonstrate real-time signal demodulation based on frequency-hopping spread spectrum (FHSS) in a waveguide-coupled Rydberg receiver, achieving ultra-broad frequency-hopping covering 100 kHz to 20 GHz and a hopping rate of 100 khop/s. When confined to a standard operational band (e.g., the 2.4 GHz ISM band), our system achieves a high channel density of 8 channels per MHz. Beyond this, by leveraging its ultra-broad and continuous bandwidth, the system supports over 150,000 channels. Experimental results reveal a 51 dB enhancement in narrowband interference tolerance compared with single-frequency systems, confirming its outstanding anti-jamming capability. The reported system demonstrates significant potential for secure communications based on
quantum technology, especially communication in complex electromagnetic environments.
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All authors Jia-Dou Nan, Jun-Rong Chen, Bang Liu, Qi-Feng Wang, Yu Ma, Yi-Ming Yin, Tian-Yu Han, Guang-Can Guo, Hao Tian, Li-Hua Zhang, Bo Du, Bin-Bin Wei, Dong-Sheng Ding, Bao-Sen Shi
Applied Physics · Cross-listed from eess.SP
Implications of the Reciprocity Theorem for Reconfigurable Intelligent Surfaces
Uday K Khankhoje and Debidas Kundu
Reciprocity between a transmitter and receiver is a foundational requirement in wireless communications. A few recent works have suggested that reciprocity is broken under reflection by reconfigurable intelligent surfaces (RIS) when the reflection phase becomes incident angle dependent. In this work, we rigorously show that these claims are based on the use of idealized reflection coefficients that ignore mutual coupling between heterogeneous unit
cells, surface-truncation effects, and structural scattering contributions from the RIS. Full-wave electromagnetic simulations of transmit/receive
antennas and a finite-size RIS implemented via a particular unit
cell design are performed to quantitatively demonstrate that reciprocity holds even in the presence of incident-angle dependent reflection phases. To show this, we calculate two-port
antenna scattering parameters and evaluate the electromagnetic reciprocity integral to support our claims.
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Optics
Statistical Methods for Determining Turbulence in Supercontinuum Generation
Mehmet Müftüoglu and Mario Chemnitz
Distinguishing coherent, turbulent, and chaotic operating regimes in supercontinuum generation is important for understanding nonlinear optical dynamics and optimizing broadband light sources. Experimentally identifying the onset of
turbulence remains challenging because the most common metric, first-order coherence, requires access to the complex optical field and cannot be directly obtained from intensity-only measurements. In this work, we investigate whether experimentally accessible statistical observables can identify
turbulence in supercontinuum generation. We compare wavelength-integrated variance and kurtosis with simulation-based first-order coherence over a chirp-controlled pulse-duration sweep implemented through additional $\beta_2$ dispersion. The study combines generalized nonlinear Schrödinger equation simulations with shot-to-shot dispersive
Fourier transform measurements validated against optical spectrum analyzer spectra. Statistical intensity distributions were analyzed using histograms, complementary cumulative distribution functions, and kurtosis measurements across the generated supercontinuum bandwidth. Simulations and experiments both revealed heavy-tailed intensity statistics in the intermediate pulse-duration regime associated with reduced spectral coherence. The integrated kurtosis reached a maximum near 600 fs in simulations and near 700 fs in experiments, while the integrated variance within the first 20 dB spectral range decreased with increasing pulse duration. The agreement between simulations and experiments demonstrates that variance- and kurtosis-based observables can serve as experimentally accessible indicators of
turbulence in supercontinuum generation. These results show that intensity-only statistical measurements can distinguish coherent and incoherent operating regimes without requiring direct field-resolved coherence measurements.
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Instrumentation and Detectors
Seeding and Matching algorithms for the first GPU-based High Level Trigger of the LHCb experiment
Christina Agapopoulou, Lukas Calefice, Álvaro Fernández Casani et al. (+10 more)
We describe the GPU implementation of the Seeding and Matching
algorithms, developed for the first level trigger of the LHCb experiment and key to reconstruct long and very displaced tracks at 40 MHz. The
algorithms have been participating in the data taking during the full Run 3 of LHCb with a very high throughput, increasing the physics reach of the experiment. The Seeding is a standalone pattern recognition
algorithm aiming at finding charged particle trajectories in the most forward tracker of LHCb. These trajectories are then extrapolated backward by the Matching
algorithm which combines them with stubs formed from hits in the first tracker in order to form what we call Long tracks. Hits in the second tracker are then searched for to better define the trajectory and improve the track momentum resolution. This backward approach, complementary to the approach of extrapolating the stubs in the first detector to the forward tracker through the
magnetic field, improves the Long track efficiency at low transverse momenta, increasing the potential of key physics decay channels.
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All authors Christina Agapopoulou, Lukas Calefice, Álvaro Fernández Casani, Vava Gligorov, Arthur Marius Hennequin, Louis Henry, Valerii Kholoimov, Brij Kishor Jashal, Arantza Oyanguren, Lorenzo Pica, Volodymyr Svintozelskyi, Da Yu Tou, Jiahui Zhuo