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Physics Physics

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Tuesday 28 July

Fluid Dynamics

On the scaling of bubble interactions in dynamic turbulence: theoretical, numerical, and experimental study

Vivek Kumar, Prasoon Suchandra, Shivam Prajapati et al. (+2 more)

This study investigates dilute bubbly decaying homogeneous isotropic turbulence at high Reynolds number using theory, direct numerical simulation, and experiments. The turbulent kinetic energy and dissipation rate follow power-law decay, while the bubble population reorganizes relative to the evolving Hinze scale. When the dissipation decays sufficiently rapidly, the Hinze scale grows faster than the characteristic bubble diameter, driving the population from super-Hinze toward sub-Hinze sizes. The system passes through a mixed regime in which coalescence dominates but breakup remains active, followed by a pure-coalescence regime. Residual breakup in the mixed regime increases the number of small bubbles and enhances coalescence, leading to faster growth of the characteristic bubble size. DNS of dilute bubble-laden turbulence shows decay exponents close to single-phase turbulence and a bubble-size distribution that shifts toward smaller diameter relative to the Hinze scale. Before the transition, the distribution exhibits two power-law ranges associated with capillary effects and inertial breakup; after the transition, it approaches a single capillary-dominated scaling. Theory and DNS predict distinct growth laws for bubble diameter in the mixed and pure-coalescence regimes, together with corresponding scalings for number density, interfacial area, and coalescence rate. These predictions are further assessed in a spatially developing pump-driven bubbly duct flow at higher Reynolds number. Despite confinement, inhomogeneity, and wall production, the measured trends agree with the theoretical and DNS-based scalings. The results identify Hinze-scale drift as the organizing mechanism for bubble interactions in both idealized and practical decaying turbulent flows, and provide guidance for population-balance and interfacial-area-transport models.
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All authors Vivek Kumar, Prasoon Suchandra, Shivam Prajapati, Suhas S. Jain, Cyrus K. Aidun

Chemical Physics

Structured High-Angular-Momentum Coulomb Tensors from Real and Complex Solid-Harmonic Integral Engines: A Perspective

Bo Peng

Electron-repulsion integrals describe the Coulomb interaction between charge distributions built from orbital basis functions. Most integral algorithms generate these quantities through Cartesian Gaussian functions, whose angular shapes are written as powers of $x$, $y$, and $z$, and then transform the result to spherical functions. This route is effective, but from $d$ shells onward the Cartesian representation contains more functions than the spherical space required by the calculation. Direct real or complex solid-harmonic engines work in that target space from the beginning. They therefore produce a smaller final Coulomb tensor while preserving the ordering, phase, and magnetic-quantum-number labels that describe its angular structure. Following this structure beyond integral evaluation reveals direct connections to the algorithms that use the tensor. Simple analytical counts quantify tensor size, angular blocks, radial Slater–Condon parameters, and pair-space work. These quantities guide low-rank factorization, local Hamiltonian construction, quantum simulation, and transformations to spinor or effective-model bases. In this way, solid-harmonic integral engines provide a direct bridge between efficient integral generation and structured many-electron computation.
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Data Analysis and Statistics

Visibility graph-based characterization of extreme values in time series

Juliane T. Moraes, Lucas Lacasa and Cristina Masoller

Complex dynamical systems often display extreme fluctuations of an observed variable that constitute significant deviations from the long-term average, and which are often associated with severe impacts on the system. By definition, extreme events are therefore usually explored from time series recordings. In this work, we characterize extreme values in time series using visibility graphs, a method that non-parametrically maps a time series onto a network, whose topological structure is known to inherit important characteristics of the original time series dynamics. Unlike threshold-based approaches, extreme values in this framework can be identified without the need to introduce external parameters and can be applied to time series generated by both stationary and nonstationary processes. For stationary processes, we exploit a known property of visibility graphs in which the degree of a node is monotonically and nonlinearly related to the corresponding data value. This nonlinear amplification enhances the contribution of large values while suppressing noise, while the monotonic relationship enables a direct ranking of data points according to node degree. This procedure identifies global extreme values and locally prominent ones. For nonstationary processes, the degree ranking in the visibility graph still provides a robust indicator of relative importance. We validate our findings with synthetic time series and with real climatological data. Our results show that extreme-value characterization in stationary time series is enhanced when combining standard methods with visibility-graph-based detection, whereas for nonstationary data, where conventional approaches are often ill-posed, visibility graphs provide an effective alternative. We discuss how sub-sampling the time series using only peak values preserves the ability to identify extreme values while reducing computational cost.
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Computational Physics · Cross-listed from math.NA

Parallelisation of Discrete Exterior Calculus via Representation Theory on Curved and Three-Dimensional Meshes

Leon D. da Silva, Marcelo P. Santos, José D. da Silva et al. (+1 more)

We establish a universal block-diagonalization framework for Discrete Exterior Calculus (DEC) operators on symmetric meshes, enabling embarrassingly parallel solvers with provable FLOP reductions. We prove that the two fundamental DEC operators, the discrete exterior derivative $d$ and the Hodge star $\star$, are equivariant under isometric finite group actions on simplicial complexes. The proof exploits the permutation representation induced on cochain spaces by the group action. As a consequence, any operator assembled from $d$ and $\star$ (including the Hodge Laplacian, the codifferential, Maxwell-type operators, and elasticity operators) inherits a block-diagonal structure in a single symmetry-adapted basis, which is computed only once per mesh. Unlike spectral methods restricted to flat Platonic domains, the framework applies natively to curved manifolds and is applicable in principle to computational electromagnetism and geometric fluid simulation on symmetric domains. Numerical experiments on a geodesic sphere ($I_h$ symmetry) and a hexagonal torus ($D_{6h}$ symmetry) yield FLOP-based parallel speedups, relative to a dense direct factorization, of up to $62\times$ and $182\times$, respectively. A further experiment on a body-centred-cubic (BCC) tessellation of the flat 3-torus $T^3$ with $T_d$ symmetry confirms equivariance of the exterior derivative, Hodge star, and Hodge Laplacian at machine precision for form degrees $k=0,1,2$ across three mesh resolutions. The FLOP-based sequential speedup approaches its theoretical asymptote of $\approx 9.07\times$, which a standard Schur-multiplicity reduction deepens by a further factor of order $|G|$. These results show that a single symmetry-adapted basis reduces the linear-solve cost of structure-preserving DEC computations on curved and three-dimensional meshes.
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All authors Leon D. da Silva, Marcelo P. Santos, José D. da Silva, Gilson Ferreira Jr

Fluid Dynamics · Cross-listed from math.AP

Turbulent Flame Speed Can Increase under Curvature Smoothing

Hung V. Tran, Jack Xin and Yifeng Yu

Curvature effects are expected to smooth flame-front wrinkles and thereby reduce turbulent flame speed. We construct a smooth three-dimensional periodic shear flow for which introducing Markstein curvature diffusivity instead increases the effective flame speed predicted by the level-set G-equation. This gives the first counterexample, within this model, to monotone slowdown under curvature smoothing and contrasts with the rigorous monotonicity result for two-dimensional shear flows. The example reveals a genuinely multidimensional mechanism in which local curvature smoothing can enhance, rather than suppress, large-scale front propagation.
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Atomic Physics · Cross-listed from quant-ph

Dissipation Enables Strongly Detuning-Dependent Interference in Pulsed Dynamical Decoupling

Kenneth DeRose, Jonah Glick, Kefeng Jiang et al. (+6 more)

One of the defining features of pulsed dynamical decoupling is its suppression of a driven qubit's sensitivity to static detuning errors between the drive field and qubit resonance. In this paper, we show that dissipation, in the form of excited-state decay, can change this behavior entirely, producing an interference signal with a strong detuning dependence. This signal arises from decay during driven evolution and relies on coherence retained by the qubit after such a decay event. We develop analytical and numerical models that capture the underlying mechanism and observe this same dissipation-induced detuning dependence experimentally in both a free-space strontium atom interferometer and a superconducting transmon qubit system. We also use this dissipation-induced detuning dependence as the basis for a new spectroscopic technique called Dissipative Carr-Purcell Spectroscopy (DCPS) and compare it with a traditional Ramsey sequence. Our results establish a regime of pulsed dynamical decoupling in which dissipation reshapes, rather than merely degrades, coherent control, and we expect these dynamics to be relevant to a wide range of quantum systems.
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All authors Kenneth DeRose, Jonah Glick, Kefeng Jiang, Hans Johnson, Tanay Roy, Sharika Saraf, Anya Abraham, Hardeep Singh, Tim Kovachy

Instrumentation and Detectors

Machine-Learning-Based Waveform Discrimination in the Front-End Electronics of the Belle II Central Drift Chamber for Cross-Talk Noise Reduction

Yun-Tsung Lai, Taichiro Koga, Yu Nakazawa et al. (+2 more)

Machine learning (ML) inference on FPGAs has been widely adopted in real-time triggering of collider experiments for detector signature identification. In contrast, the ML application in Front-End Electronics (FEE) has not yet been fully explored, primarily due to constraints such as limited FPGA resources, power consumption, and localized detector coverage. In this work, we develop an ML-based waveform discrimination method for the Central Drift Chamber (CDC) of the Belle II experiment to suppress cross-talk noise at the front-end level. The Belle II CDC is a key charged-particle tracking detector for both offline and the real-time hardware trigger. During Belle II operation, background wire hits have been observed in the CDC FEE, where multiple hits occur in neighboring anode wires by large energy deposit. The hardware track trigger employs a Hough transformation based on track segments formed by combining hits from multiple wire layers. Due to the reduced information, the track trigger is sensitive to cross-talk noise, hence resulting in an increased fake trigger rate with higher luminosity in the future. We employ compact and fast Boosted Decision Tree models implemented in a Xilinx Virtex-5 FPGA of the CDC FEE, where waveform is processed independently for each wire channel in a fully pipelined manner. Offline studies show that the cross-talk noise can be reduced by approximately a factor of two while maintaining a signal efficiency above 98%. The firmware validation during dedicated Belle II calibration runs demonstrated reductions of up to 50% in track segment and trigger rates while preserving the trigger acceptance for events containing tracks within 10%. This work demonstrates the technical feasibility of compact and low-latency ML inference in detector FEE and highlights its potential for future intelligent detector readout systems in high-energy physics experiments.
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All authors Yun-Tsung Lai, Taichiro Koga, Yu Nakazawa, Nanae Taniguchi, Keisuke Yoshihara

Plasma Physics

Statistical structure of canonical kinetic equilibrium with sheared flow

Daniel W Crews

In isothermal kinetic equilibrium of a plasma with sheared flow, the electrostatic potential is the cumulant generating function of the velocity distribution, encoding all non-Maxwellian statistics. Consequently, of the polynomial-form flux-function equilibrium flows, only the linear one is admissible, and every other equilibrium sheared flow has non-zero cumulants to all orders. The identity is shown for a sheared-flow screw pinch and specialized to the Z pinch, theta pinch, and Harris sheet. A simple sheared-flow Bennett pinch illustrates the principal results, namely weaker magnetization yields more non-Maxwellian features, and co- and counter-current flow shear have distinct statistics. The identity also yields a method for initializing kinetic simulations.
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Fluid Dynamics

Numerical simulations and universal saturation profiles for viscous fingering patterns in Hele-Shaw flow

Irio M. Coutinho, Liam C. Morrow and Scott W. McCue

Hele-Shaw flows with an interface are known to give rise to complex pattern formation, whereby the Saffman-Taylor instability triggers a viscous fingering process accompanied by tip splitting and branching. The most popular of these experiments involves a radial configuration with a less viscous fluid injected into a more viscous fluid. In an attempt to characterize the resulting complexity in such an experiment, Beeson-Jones and Woods (2019) have proposed a type of simple empirical model that aims to predict the saturation profile of the invading fingers as a function of a radial coordinate. We revisit the proposed saturation model and test its validity over a broad parameter range using fully nonlinear numerical simulations computed with a level set method. We find that the saturation model is very effective at predicting some near-universal properties of the viscous fingering patterns for one-phase flows, where the invading fluid is neglected, with a sufficiently small surface tension parameter. For larger values of this parameter and for two-phase flows, there are discrepancies between the model and our observations. We explain these differences by studying the morphology of the advancing fingers, including pinching at the base and the rate of tip splitting. Overall, our study shows that the Beeson-Jones-Woods saturation model serves as a valid description of DLA-like patterns, but is not universal over two-phase flows, where surface tension and viscosity ratio substantially alter finger morphology and the resulting saturation profile.
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Monday 27 July

Applied Physics · Cross-listed from eess.SP

RIS-Aided Wireless Multiport Sensing: Multiplexed De-Embedding of an RIS-Programmable Over-the-Air Fixture

Philipp del Hougne

Wireless multiport sensing aims to remotely retrieve the scattering matrix of a multiport device under test (DUT) connected to not-directly-accessible (NDA) antennas, based on scattering parameters measured with remotely located accessible antennas that couple over the air (OTA) to the NDA antennas. A central bottleneck is that the required number of accessible antennas grows with the number of unknowns in the DUT's scattering matrix. Here, we address this bottleneck by using a reconfigurable intelligent surface (RIS) to generate measurement diversity during the DUT characterization. We interpret the setup as measuring the DUT via an RIS-programmable OTA fixture. We first characterize the RIS-programmable OTA fixture using a specific known tunable load network to terminate the NDA antennas. Then, we reconstruct the DUT's scattering matrix by multiplexed de-embedding of the RIS-programmable OTA fixture, using measurements of the DUT acquired across multiple RIS configurations. Based on our system model formulated in terms of multiport-network theory, we quantify and maximize the diversity of our measurement sequence by optimizing the deployed ensemble of RIS configurations. We validate our approach experimentally at 2.45 GHz in a rich-scattering radio environment. We systematically examine the influence of the number of accessible antennas, the number of RIS configurations, and the optimization of the RIS configurations. For a SISO link (two accessible antennas), optimized RIS configurations reduce the median reconstruction mean-squared error for 100 DUT measurements by 45% from $1.57{\times}10^{-3}$ to $8.59{\times}10^{-4}$. These results demonstrate that RIS diversity can compensate for a limited number of accessible antennas, paving the way toward low-cost wireless multiport sensing for industrial, biomedical, and smart-environment RFID systems.
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Geophysics

Spatiotemporal Analysis for Frequency-Magnitude Distribution of Earthquakes Across Mainland China: Comparing Classical and b-positive b-values Across Tectonic Regimes

Yuxin Zhou, Huai Zhang and S. Mostafa Mousavi

The Gutenberg-Richter power-law relationship essentially governs the frequency-magnitude distribution (FMD) of seismic activity. The b-value, as the slope of this distribution, is widely recognized not only as a quantifier of the relative proportion of small to large events but also as a diagnostic precursor of crustal differential stress and potential big to huge earthquakes. This study investigates the spatiotemporal evolution of b-values across major tectonic regions in mainland China, for instance, the Sichuan-Yunnan, North China, and Northwest regions. Our analysis of over 50 years of seismic records systematically examines b-value variations across major seismogenic zones in mainland China to evaluate their utility as precursors for moderate-to-strong earthquakes. Moreover, our comparison suggests that the b-positive estimator is less affected by changes in detection capability and short-term aftershock incompleteness than the classical b-value estimator in the cases examined. While the Sichuan-Yunnan region displays a complex "mosaic" of high and low b-values reflecting fluid-driven processes and localized locking, the North China Plain and Northwest regions exhibit consistently lower b-values, suggesting high background stress and rigid crustal integrity. We also find that several of the rupture areas of moderate-to-large earthquakes in our catalog coincide with localized low-b patches identified in earlier long-term windows. This study provides a foundation for systematic, prospective evaluation of b-value-based precursor monitoring in mainland China.
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Atmospheric and Oceanic Physics · Cross-listed from math.OC

Climate-model factor separation with Shapley values and efficient sampling

Abel Jansma

Climate models often feature nonlinear responses to changes in model parameters or boundary conditions. Factor separation asks how much of the resulting change should be assigned to altered factors and their interactions. Lunt et al. (2010) showed that two factor attribution methods, the linear-sum and shared-interaction methods, coincide for $n\le 4$ factors and conjectured this holds for arbitrary $n$. We show that the linear-sum and shared-interaction formulas are respectively the permutation and Harsanyi-dividend representations of the Shapley value. Their equality therefore follows from a classical theorem in cooperative game theory. To our knowledge, this is the first explicit identification of the Stein–Alpert and Lunt climate-model factor-separation methods with Möbius/Harsanyi coefficients and Shapley values. The result imports many established and efficient Shapley sampling methods into climate-model experimental design, and extends to vector-valued responses.
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Atmospheric and Oceanic Physics

Wave-induced erosion and notch development at the Fimbul Ice Shelf front

Wenjun Lu, Lotte Wendt, Behnam Ghadimi et al. (+8 more)

Ocean waves erode the waterline of Antarctic ice-shelf fronts and carve a thermo-erosional notch. The notch is hidden from satellites, yet it preconditions front collapse and footloose calving, so the link between notch growth and observable front retreat matters for how wave-exposed ice shelves lose mass. We study this link at the Fimbul Ice Shelf, East Antarctica, in January-February 2024. The widely used White (1980) erosion formulation is extended in two directions: a component-wise spectral treatment of irregular seas, and a breaking-aware wave profile that accounts for shoaling over the submerged ice foot revealed by remotely operated vehicle (ROV) profiling. Forced with hourly ERA5 waves, the extended model predicts about 110 m of cumulative waterline erosion over the matched 7 January-27 February window. Satellite observations show considerably more retreat: about 264 m from an S1-guided Sentinel-2 plateau-break method, and 266 m from manually digitised Sentinel-1 fronts over a slightly longer window. Under the baseline assumptions (alpha = 1, Delta T_wi = 1 degree C), the model therefore falls short of the observed retreat by a factor of about 2.4. Part of this residual may be hydrodynamic, since post-breaking turbulence is not represented; part may be mechanical, because collapse and footloose calving can convert notch erosion into larger observable retreat. Unmeasured near-ice thermal driving remains a first-order uncertainty, and front-position observations alone cannot separate these contributions.
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All authors Wenjun Lu, Lotte Wendt, Behnam Ghadimi, Shovon Jubair, Dominique Mouaze, Marianne Font, Rémi Lambert, Harvey Goodwin, Geir Moholdt, Raed Lubbad, Sveinung Løset

Applied Physics · Cross-listed from cs.LG

Learning to Resolve Neutron Resonances with Fully Convolutional Neural Networks

Nataly R. Panczyk, Athanasios Stamatopoulos, Josef Svoboda et al. (+1 more)

This work investigates the feasibility of augmenting traditional R-Matrix codes with a robust machine learning framework for automatically detecting neutron resonances in transmission spectra. Neutron transmission data are often complex and noisy, making them difficult to analyze using traditional peak-identification methods. The state-of-the-art R-Matrix codes currently used by physicists to fit these data often depend on prior evaluations and require substantial manual effort. This preliminary study demonstrates a method for accelerating the post-experimental processing of neutron transmission data and reducing bias associated with dependence on prior evaluations. We employ a fully convolutional neural network to classify individual points as belonging to resonance or non-resonance regions in seven transmission spectra—two evaluated and five experimental. Although the model achieves classification accuracies in the range of 93%, further analysis shows that this metric overstates its ability to generalize. Building on our prior analysis in PHYSOR 2026, we find that, despite the inclusion of additional training data, the method does not generalize reliably to previously unseen isotopes. To address these limitations, future work should evaluate whether a larger and more diverse training dataset can produce a generalizable model and should incorporate known physical characteristics of neutron resonances to improve model performance.
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All authors Nataly R. Panczyk, Athanasios Stamatopoulos, Josef Svoboda, Majdi I. Radaideh

Classical Physics

Multibranched parametric resonance and swallowtail catastrophe in electromechanical oscillators with nonlinear friction

P. Y. Chan, L. Huang, X. Dong et al. (+2 more)

Parametric resonance underpins the operation of a wide range of physical systems, from nanomechanical resonators to quantum-information systems and Ising machines. As an archetypal class of driven-dissipative systems, parametric oscillators are generally expected to exhibit a single pair of stable period-two states with opposite phases. This bistable behavior enables both the simulation of spin Hamiltonians and the preparation of superconducting cat states. Whether multiple pairs of such states can coexist in a single oscillator, however, remains an open question. Here, we show experimentally and theoretically that conventional controlled nonlinear friction can induce the coexistence of two distinct pairs of period-two states in a micromechanical oscillator. The friction is implemented via a canonical approach, utilizing a drive-induced resonant coupling that transfers two vibrational quanta from the oscillatory mode to a faster decaying mode. We demonstrate that the onset of multistability is governed by a swallowtail catastrophe and quantitatively map the associated bifurcation structure. Our results broaden the understanding of parametric resonance and establish micro- and nano-mechanical oscillators as a versatile platform for studying catastrophe theory and multistable nonequilibrium dynamics.
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All authors P. Y. Chan, L. Huang, X. Dong, M. I. Dykman, H. B. Chan

Physics and Society

The Evolutionary Dynamics of AI, Politicization, Contestation, and Trust in Science Funding

Animesh Ray

Economic stability and progress in modern technological societies depend on vigorous and independent public funding of science and engineering research. When peer review or funding decisions are perceived as politically directed, scientists, funding agencies, and the public react in coupled and conflicting ways. We an evolutionary game-theoretic model to analyze how perceived political interference in science funding affects the interrelated behaviors of scientists, funding agencies, and the public. The model simulates scientists choosing to refuse peer reviews and retaliate, agencies responding by adopting AI-assisted review and altering reviewer pay, and the public accepting or rejecting these AI systems. Through numerical simulations, five principal findings are identified: (1) Operational capacity and institutional legitimacy are governed by separate conditions and can fail independently. (2) Legitimacy of the process is bistable, meaning final states are determined by the public's acceptance of AI. (3) Since the career cost for researchers refusing to review is generally low, resistance/retaliation cascades can readily ignite, leading identical institutions to entirely opposite fates. (4) Increasing reviewer pay only stabilizes participation within a strict budget-solvency frontier, and emergency pay can paradoxically erode the legitimacy it aims to protect. (5) Finally, finite-population simulations reveal that baseline scenarios partition into either legitimacy recovery without capacity or joint failure, confirming that the fundamental separation of capacity and legitimacy outcomes is a dominant structural feature driven primarily by initial scientific resistance and politicization levels. This theoretical work quantifies issues for future work in science policy.
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Chemical Physics

Lewis-labeled graphs: curly arrows and fishhooks as executable electron transfers

Tieu-Long Phan

The curly-arrow formalism is the lingua franca of organic reaction mechanisms, but it is not executable. Molecular graphs used in rule-based modeling encode atomic connectivity while omitting lone pairs, radical electrons, and distinct sigma and pi components. Topological matching therefore cannot determine whether a reactive center holds the electrons a step consumes, while matching on derived formal charge can reject centers that do hold them. We introduce the Lewis-labeled graph (LLG), whose atom labels carry lone-pair and radical populations and whose bond labels separate sigma- and pi-bond occupancies. Bond order, formal charge, and valence electron inventory are derived from these fields. Chemical transformations become resource-constrained double-pushout rules, and curly arrows and coupled fishhooks become locus-sorted electron transfers committed atomically from a common pre-state. For a specified event group, we prove that its execution, application of its induced rule, and the corresponding integral occupancy update are equivalent. Every admissible event conserves valence electrons and net formal charge, and bond-centered fishhook coupling follows from integrality rather than drawing convention. Bidirectional replay recovers all 39,732 mapped reference endpoints, while LLG admits 96 fewer forward and 818 fewer inverse unique outcomes than conventional atom-bond rules. Ten radical records require manual annotation corrections. After review, transition construction succeeds for 101,313 of 101,314 records. The remaining case requires an endpoint atom-map correction rather than an arrow edit. Strict replay accepts all 160 reviewed steps and rejects all 1,120 controlled corruptions. These results establish a common executable state space for molecular graphs, reaction rules, and electron-flow annotations, prior to questions of kinetic or thermodynamic feasibility.
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Physics and Society

Emergent contagion complexity: Disentangling mechanistic complexity from correlated heterogeneity

Katerina Tang, Daniel Kaiser, William Thompson et al. (+3 more)

Simple and complex contagions differ mechanistically; multiple exposures act synergistically in the latter but independently in the former. Yet correlated mixtures of simple contagions may appear complex when inferring global contagion rules, a phenomenon we call "emergent complexity." We present a measure of contagion complexity and an inferential framework for estimating mixtures of nonparametric contagion rules from time-series data. Our work reframes past studies on complex contagion by offering heterogeneous mixtures of simple contagions as an alternative explanation.
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All authors Katerina Tang, Daniel Kaiser, William Thompson, Jean-Gabriel Young, Laurent Hébert-Dufresne, Nicholas W. Landry

Optics

A geometric approach to QNMs in optics: application to pseudospectrum and structural stability

Lamis Al Sheikh and José Luis Jaramillo

We develop a geometric–spectral framework for the computation and stability analysis of quasi-normal modes (QNMs) in open optical cavities of compact support. The hyperboloidal approach, transferred from gravitational physics to electromagnetism [1], incorporates outgoing boundary conditions directly into the formulation of the optical resonance problem. Dispersive and absorbing media are described by a Lorentz-model permittivity through an auxiliary-field formulation, and the resulting non-Hermitian spectral problem is solved using Chebyshev spectral discretization.Pseudospectrum analysis is then extended to the optical setting following [2] and used to study the stability of optical resonances under perturbations. The pseudospectrum provides information on the sensitivity of the resonances that is not contained in the QNM spectrum alone. Particular attention is given to the role of the norm used to define the pseudospectrum, by comparing the stability properties obtained with different choices of scalar product. The results show that the assessment of spectral stability is closely related to the functional setting in which perturbations are measured. Combining the hyperboloidal formulation with pseudospectrum analysis therefore makes it possible to compute optical QNMs while also studying their spectral stability. The approach extends techniques developed for resonance problems in gravitational physics to dispersive electromagnetism and provides a basis for studying stability and sensitivity in open optical systems.
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Plasma Physics

Emergence and Detection of Electron-Scale Current Sheets in Turbulence with MMS Observations and fully kinetic 3D simulations

Zachary Davis, Alexandros Chasepis, Colby Haggerty et al. (+2 more)

The solar wind is characterized by turbulence, where a cascade produces intermittent current structures called current sheets (CS) that efficiently dissipate energy into the plasma. These have been studied with in situ spacecraft observations, but single-spacecraft techniques such as the partial variance of increments (PVI) are inherently limited since they lack spatial context. A combined analysis of in situ observations and numerical simulations can provide significant insight into the properties of intermittent structures forming in heliospheric turbulence. Understanding the size and distribution of these structures is crucial in tracing the pathways of energy dissipation and particle energization in space plasma. Using 3D fully kinetic simulations of magnetized turbulence, we identify CS via machine learning and find a complex broken-power-law distribution for the CS widths, where the power-law breaks separate ion-scale CS from electron-scale CS. Electron-scale CS dominate, with widths peaking near $2d_e$. Comparing simulations with MMS data, we test PVI as a CS detector and show it can infer CS scale, though oblique crossings inflate inferred sizes. The prevalence of electron-scale sheets suggests they may contribute to plasma heating in aggregate.
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All authors Zachary Davis, Alexandros Chasepis, Colby Haggerty, Luca Comisso, Derek Sikorski

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

First-Principles Origins of Charge Transport in Molecular Semiconductors

Tong Jiang and Joonho Lee

Charge transport governs organic transistors and photovoltaics, yet predicting it from atomic structure remains challenging. Electron–phonon interactions span disparate frequencies, strengths and spatial ranges, and collectively generate nonperturbative carrier dynamics. Existing methods regain tractability only by assuming a mechanism or reducing electron–phonon coupling to a few modes. We introduce a parameter-free framework that instead computes transport from ab initio electron–phonon Hamiltonians, propagating carriers across hundreds-of-molecule domains with the full phonon spectrum and letting transport regimes and bottlenecks emerge from nonperturbative Green–Kubo dynamics. Across five representative crystals, it captures measured mobilities, temperature exponents, and optical-conductivity fingerprints. Our results overturn the prevailing microscopic mechanism for DNTT, tracing its transient localization to correlated on-site disorder from acoustic phonons rather than independent hopping fluctuations. The resulting two-axis transport map provides design principles and highlights the underexplored phenacene family, exemplified by the high-mobility picene, as a promising direction.
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Physics and Society

Economic Complexity as a Determinant of Regional Human Development in Brazil: Evidence across Aggregation Scales

Eduardo Moura Zampirolli and Ruben Interian

This study investigates the predictive capacity of models based on Economic Complexity and Complex Network Theory when applied to Brazil's Municipal Human Development Index (IDHM). For this purpose, the Economic Complexity Index was adapted to the Brazilian context. The main objective is to assess the extent to which different approaches to regional development analysis, such as local productive sophistication and structural integration into the national transportation network, determine socioeconomic development. The methodology compares linear regression models (Ridge, LASSO, and Elastic Net) and nonlinear models (Decision Trees and the Explainable Boosting Machine), evaluated through 5-fold cross-validation with grid search. The analyses were conducted at two levels of spatial aggregation: municipalities and Immediate Geographic Regions. The results show that regionally aggregated models exhibit less statistical noise and greater stability, achieving substantially higher coefficients of determination and greater explanatory power for ICE relative to the other variables. Notably, at the Immediate Region level, ICE alone emerges as the main structural determinant of IDHM, suggesting that regional productive sophistication by itself explains a large share of the variation in human development at this territorial scale. In addition, the inclusion of topological metrics from the road infrastructure network generally improved performance. The Explainable Boosting Machine achieved the best predictive performance, reaching R^2 = 0.8196 at the Immediate Region level when network metrics were included.
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Instrumentation and Detectors

Cracking under pressure — investigating mitigation approaches for silicon fractures on ATLAS strip tracker petals at cold temperatures

S.H. Abidi, J.-H. Arling, M.J. Basso et al. (+35 more)

For the High-Luminosity upgrade of the Large Hadron Collider, the ATLAS experiment will replace its current Inner Detector with an all-silicon Inner Tracker (ITk), consisting of pixel and strip detectors. The strip detector will consist of a central region or "barrel" assembled with staves and forward regions or "end-caps" assembled with petals. The ITk will nominally operate with liquid $\textrm{CO}^2$ cooling at $-35\,^\circ\textrm{C}$; however, in the event of cooling system failures, it is possible that sensors will experience temperatures below $-35\,^\circ\textrm{C}$. At these low temperatures, it has been observed that the silicon sensors within modules — the fundamental readout units of the detector — can physically crack, rendering the modules inoperable. Understanding and resolving the issue of sensor cracking was one of the most important and urgent issues for the ITk project. This paper presents part of the mitigation strategies developed for petals. These mitigation strategies are based on modifications to the choice of adhesive and its deposition pattern for module assembly and petal loading. The most promising mitigation strategy presented here prevents cracking to temperatures as low as $-45\,^\circ\textrm{C}$, which can be expected in case of cooling system problems, with a small percentage of cracks observed after being cycled to $-55\,^\circ\textrm{C}$, which can be expected in case of catastrophic cooling system failures.
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All authors S.H. Abidi, J.-H. Arling, M.J. Basso, S. Beaupre, I. Bloch, A.J. Blue, M. Caspar, J. Chen, S. Díez Cornell, U. Epstein, E.K. Filmer, A. Fournier, L. Franconi, A. Gabrielli, J.A. Hallford, S. Heim, C.M. Helling, N.P. Hessey, R.M. Jacobs, T. Kuhl, M. Licht, C.K. Mahajan, S. Manson, K. Mauer, S. Oerdek, V. Platero Montagut, L. Poley, C.O. Sander, K. Ran, S. Sinha, C. Solaz Contell, U. Soldevila Serrano, D. Sperlich, B. Stelzer, A.H. Tigchelaar, E. Torres Reoyo, G. Vallone, L.M. Veloce

Optics

Anisotropic optical chirality and Lipkin's zilch tensor

Ilia Smagin and Sergey Dyakov

Optical chirality density is widely used as a scalar measure for describing the chiral properties of electromagnetic fields and their interaction with isotropic chiral media. However, in anisotropic optically-active media, a single scalar quantity is generally insufficient to capture the full complexity of chiral field-matter coupling. In this work, we go beyond the conventional optical chirality density and introduce a tensor of electromagnetic chirality based on the Lipkin formalism. This tensor provides a richer and more physically transparent description of chiral electromagnetic fields, particularly in the context of their interaction with general magneto-electric media. We discuss the physical meaning of the individual tensor components and provide an expression for the excitation rate of small anisotropically chiral molecules in the presence anisotropically chiral fields.
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Chemical Physics

Electron-Stimulated Desorption of D Atoms from Gibbsite (Al(OD)3) and D2O Ice: Energy and Temperature Dependence of Translational Energy Distributions

William T. P. Denman, Brant M. Jones, Jacob Messner et al. (+5 more)

The electron-stimulated desorption (ESD) of neutral D atoms from gibbsite (\ce{Al(OD)3}) nanoplatelets and amorphous \ce{D2O} ice has been investigated using $2+1$ resonance-enhanced multiphoton ionization (REMPI) time-of-flight mass spectroscopy in a high vacuum chamber at temperatures 15 and 300\,K. Electron irradiation at 540, 250, and 150\,eV produces similar translational energy distributions at $\sim$300\,K, with a dominant intermediate-temperature component ($T \sim 1500$–$2100$\,K). Cooling to 15\,K suppresses the D atom yield by approximately 50% and removes the lowest-temperature (slowest) component. This decrease in yield is consistent with diminished hole mobility and restricted diffusion at cryogenic temperatures. Under identical conditions, \ce{D2O} amorphous solid water ice films produce approximately 20 times greater D atom signal than bare gibbsite, with significantly hotter translational distributions, reflecting the higher deuterium surface density and distinct bonding environments of bulk ice relative to the terminal hydroxyl groups on gibbsite. These results identify hole transport to terminal hydroxyl sites as the rate-limiting step for nonthermal D atom production and provide a mechanistic framework for understanding atomic hydrogen release from aluminum hydroxide phases relevant to radioactive waste storage at the Hanford Site.
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All authors William T. P. Denman, Brant M. Jones, Jacob Messner, Xin Zhang, Micah P. Prange, Greg A. Kimmel, Jay A. LaVerne, Thomas M. Orlando

Optics · Cross-listed from quant-ph

A broadband, individually addressing two- and three-dimensional photonic integrated circuit for trapped-ion qubit control

Daniel Klawson, Yiyang Zhi, Bingran You et al. (+21 more)

Trapped ions provide a high-fidelity platform for quantum information processing, yet delivery of multiple, distinct wavelengths across large networks of interaction zones remains a bottleneck. Conventional free-space light delivery lacks scalability, while on-chip grating couplers suffer from narrow operational bandwidth that increases circuit footprint and optical interfacing complexity. Here we show a broadband photonic integrated circuit capable of addressing individual ions. The circuit combines a planar waveguide lens with a micromirror fabricated using two-photon polymerization at wafer scale. This implementation can address three individual ions from $\lambda$ = 405 - 880 nm with -27 dB average intensity crosstalk at $5\,\mu\mathrm{m}$ pitch. We trap $^{40}\mathrm{Ca}^{+}$ and $^{138}\mathrm{Ba}^{+}$ ions above such devices, characterize optical crosstalk with barium ions, and demonstrate individual repumping of calcium ions. This monolithic photonic architecture brings broadband addressing in an on-chip modality to trapped-ion technology. More generally, integrating additive manufacturing into quantum devices is poised to unlock expanded design space for implementing novel quantum architectures.
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All authors Daniel Klawson, Yiyang Zhi, Bingran You, Michael Bareian, Elijah Mossman, Chun-Yuan Fan, Arkadev Roy, Ke Sun, Jason Lee, Sung Cheol Yoon, Qiming Wu, Lai Jiang, Wenjun Ke, Weiwei Wu, Sirui Tang, Zachary Wall, Jiaxiang Wang, Louis Paul Romero, Sam Vizvary, Steven Diaz, Eric R. Hudson, Wesley C. Campbell, Hartmut Haeffner, Ming C. Wu

Applied Physics · Cross-listed from cs.AR

Mitigating the Impact of Retention Loss on Inference Accuracy in 65 nm Single-Poly Floating-Gate Analog In-Memory Computing

Mirko Brazzini, Giulio Filippeschi, Alessandro Catania et al. (+2 more)

We show with experiments and system-level simulations that it is possible to successfully mitigate the impact of retention loss on inference accuracy degradation by using both circuit-level compensation techniques and batch normalization recalibration at the algorithmic level. Experiments are performed on a single-poly floating-gate (FG) analog non-volatile memory array for analog in-memory computing fabricated in a standard 65 nm CMOS. We use a model of retention-loss statistics calibrated with experiments to evaluate the system-level impact on neural network models such as VGG-10/CIFAR-10 and WideResNet-28-10/CIFAR-100. We show that, after 60 days since programming, combined mitigation techniques enable to recover the baseline inference accuracy within 2-4%
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All authors Mirko Brazzini, Giulio Filippeschi, Alessandro Catania, Sebastiano Strangio, Giuseppe Iannaccone

Fluid Dynamics

Data-driven impeller model for efficient large eddy simulations of metastable von Kármán flows

Quentin Malé, Lucas Amoudruz, Daniel Bulgarini et al. (+5 more)

The von Kármán turbulent swirling flow exhibits intriguing large-scale metastable dynamics, including low-frequency state switching. The study of state switching demands long-duration high-fidelity simulations at high Reynolds numbers that capture the flow generated by the impellers. Blade-resolved Large Eddy Simulations (LES) are computationally prohibitive, limiting access to these slow dynamics. Here, we develop a model for the action of the impellers on the flow using experimental data from Particle Image Velocimetry (PIV) and torque measurements of the von Kármán flow. The impeller-region velocity is parametrized via B-splines and coupled to the LES through momentum forcing. An initial set of B-spline coefficients is inferred using the Optimizing a DIscrete Loss (ODIL) framework constrained by the Reynolds-Averaged Navier–Stokes (RANS) equations, PIV measurements in the optically accessible portion of the device, and impeller torque measurements. The coefficients are then refined by the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), which minimizes the discrepancy between the LES time-averaged velocity and torque and their experimental counterparts. Using the data-driven impeller model, we perform long-duration LES of the von Kármán flow. We find that the simulation reproduces the mean flow in the bulk and displays metastable state-switching dynamics. We further show that these metastable states are not axisymmetric and consist of an alternating four-cell flow pattern that slowly rotates around the axis of the cylindrical vessel. The proposed approach provides a practical and computationally efficient route to investigating large-scale dynamics in impeller-driven turbulent flows.
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All authors Quentin Malé, Lucas Amoudruz, Daniel Bulgarini, Shuolin Xiao, Gregory Eyink, Charles Meneveau, Fabrizio Bisetti, Petros Koumoutsakos

Physics and Society

Structural Analysis of Journal Columns Using Ordinal Patterns and Information-Theoretic Measures

Cynthia Z. Zhou-Lin, José L. Herrera-Diestra and Luciano Stucchi

Source attribution in journalistic text is typically approached through semantic representations, such as term weighting or neural embeddings. These approaches capture topical content, but usually overlook how a text is organized as a sequence. Here, we show that purely structural, content-independent features can discriminate between news sources on their own. We converted articles from fourteen Peruvian online newspapers into numerical sequences using two independent encodings, word length and lexical frequency. Then, we analyzed each of them through ordinal pattern analysis, computing pattern and transition probabilities, permutation entropy, disequilibrium, and statistical complexity. Both encodings yield non-uniform ordinal pattern distributions, well-defined preferential transitions, and coherent entropy complexity signatures across sources. Unsupervised clustering recovers three coherent groups in the feature space, and supervised classifiers trained on these features achieve accuracy up to 0.99, which remains stable even under substantial feature reduction. The consistency of these results across two structurally unrelated encodings strongly indicates that ordinal features capture a genuine dynamical fingerprint of each source's writing style rather than an artifact of either representation, which extends this framework to Spanish-language journalism, a setting that remains comparatively underexplored in complexity-based text analysis.
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Physics and Society

System optimality versus self-organization in metro networks: An optimal transport analysis

Tianyu Dong, Jiazu Zhou and Markus Schläpfer

Urban transportation network design is typically approached through top-down planning grounded in engineering and economics. Yet cities are complex systems characterized by feedback loops between infrastructure and mobility demand: network structure shapes origin-destination (OD) flows, while OD flows adapt and in turn affect network development. Despite this interdependence, computational tools to benchmark real-world networks against alternative generative principles remain limited. Here, we introduce a data-driven framework to compare three types of metro networks: a self-organized (desire-path) network derived from local rules, a system-optimal network derived from global optimization, and the empirical real-world network. We quantify similarities and discrepancies using geometric comparisons and optimal transport theory. Applying the framework to Singapore's Mass Rapid Transit system, we find that the empirical metro network is substantially closer to the self-organized benchmark than to the system-optimal benchmark, with remaining discrepancies largely explained by geographic constraints. These findings highlight that system-wide optimality alone may be inadequate for guiding practical interventions, motivating planning approaches that explicitly incorporate local service needs. The framework is transferable across regions and can diagnose design-use misalignments to support adaptive infrastructure planning.
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