Optics
Intracellular luminescence thermometry: A story of disagreement, trust, and hope
Araceli de Aquino Samper, Liyan Ming, Daniel Jaque et al. (+1 more)
Intracellular luminescence thermometry has long promised to reveal how heat is generated, dissipated, and regulated inside living
cells. Yet, despite substantial progress, the field remains shaped by disagreement over the magnitude and physical plausibility of reported intracellular temperature gradients. In this manuscript, we discuss luminescence thermometry as a powerful approach for probing temperature at subcellular length scales, while emphasizing the experimental care required to make such measurements meaningful. After outlining the field's development, we outline the relevant heat-transfer concepts, before introducing luminescence thermometry and the performance metrics used to describe precision and accuracy. We then examine how thermometer design, intracellular localization, calibration, microscopy configuration, and data treatment influence the final thermal readout. Particular
attention is given to two recurrent sources of error: bias, arising from measurement conditions and optical distortions, and cross-sensitivity, arising when the probe responds to parameters other than temperature, such as pH, viscosity, ionic strength, or biomolecular interactions. Finally, we outline practical directions for improving reproducibility, including multi-feature readouts, machine-learning-assisted analysis, and FAIR data practices, while suggesting future research directions.
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All authors Araceli de Aquino Samper, Liyan Ming, Daniel Jaque, Riccardo Marin
Fluid Dynamics
Manifold-adapted radial basis functions for reduced-order modelling of chaotic flows
Miguel Pérez Cuadrado, Giorgio Maria Cavallazzi and Alfredo Pinelli
Chaotic systems often evolve on a low-dimensional attractor whose geometry varies from one region to another. We propose a non-intrusive reduced-order model that reads this local geometry by clustering and uses it to shape a radial basis library whose kernels adapt to each region. Fitting the reduced velocity onto this library by one global least-squares solve gives an explicit, differentiable vector field that reproduces the long-term statistics without any use of the governing equations. A radial basis field decays away from the data and cannot by itself return an escaped state. The integration is therefore stabilised by a kinematic corrector, whose reported magnitude measures how far each result rests on the learned field. On Lorenz-63 the model recovers the attractor, its marginal densities and its Lyapunov spectrum. On Lorenz-96 its valid prediction time matches typical configurations of neural-network and reservoir-computing forecasters and trails their best-tuned ones, and the invariant measure is reproduced on both the full state and on a reduced observable. On the Kuramoto–Sivashinsky equation and the quasiperiodic Kolmogorov flow the model matches the energy distribution and spectrum of an intrusive quantised-local Galerkin model and improves on a global Galerkin projection of the same reduced dimension. The recovery is dictated by the distance from a state to its nearest kernels, not by the one-step regression error.
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Optics
Broadband silicon photonic phase shifters driven by gradient optical forces
Guillermo Arregui, Sander Jæger Linde, Magnus Vejby Nielsen et al. (+4 more)
While initially deployed for optical interconnects, silicon photonics is increasingly being explored as a hardware platform for programmable optical systems, including linear optical processors, neuromorphic photonic networks,
quantum photonic
circuits and multiplexed sensor arrays. Common to most existing implementations is that light is controlled with electronics, and even basic demonstrations wherein light directly controls light remain limited. Here we demonstrate a broadband all-optical silicon photonic phase shifter based on an optomechanically mediated light-light interaction arising from the gradient optical force. Our device concept relies on slot-mode waveguides suspended by subwavelength gratings, which provide mechanical support while preserving optical confinement. We demonstrate all-optical phase shifting using a guided pump beam co-propagating with the signal beam, with only 60 $\mu$W required to achieve a $\pi$ phase shift in a 178.6 $\mu$m-long device. In addition, we measure the required pump power across a wide parameter space and find quantitative agreement with a lumped force-
equilibrium model. Since the actuation relies on an all-optical
geometric deformation rather than on material-index tuning, the approach avoids local electrical connections to the active element, carries no Kramers-Kronig absorption penalty, and is naturally compatible with cryogenic
quantum photonic platforms.
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All authors Guillermo Arregui, Sander Jæger Linde, Magnus Vejby Nielsen, Bingrui Lu, Nikolaj B. Hougs, Babak Vosoughi Lahijani, Søren Stobbe
Optics
Optimal slit width for high-precision orbital angular momentum measurement using angular double-slit interferometry
Yu Jian, Xin Wang, Jiyang Zhang et al. (+4 more)
We demonstrate an optimization of angular double-slit interferometry for accurate measurement of orbital angular momentum (OAM) of
vortex beams. By scanning the dynamic double slits, the topological charge (TC) magnitude is directly determined from the oscillation frequency of the on-axis intensity. Based on repeated experimental investigations, we establish a critical criterion for slit width selection: to avoid phase truncation or period overlap, the angular width of each slit must exactly match the spiral phase period 2{\pi}/|l|. Under this optimal condition, the interference pattern exhibits the highest visibility and the measurement error is minimized. Experiments for l = 5, 10, and 15 are performed as representative examples, and the universality of this criterion is confirmed. Furthermore, by introducing an additional phase shift, the sign of the TC is unambiguously determined, as demonstrated for l = 10 and l = -15. This simple, robust method provides a high-precision pathway for OAM metrology.
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All authors Yu Jian, Xin Wang, Jiyang Zhang, Tao Chen, Manpeng Chang, Chen Liu, Weimin Wang
Physics and Society · Cross-listed from cs.SI
Rumour Spreading In Community Based Networks
Zhaoxi Cui and Anthony O'Hare
Many real-world networks have the characteristic that they are comprised of distinct groups or communities whose members contain many links within the community but with fewer connections to others. It is important to accurately model these types of networks to correctly predict the outcome of important spreading processes such as disease transmission, or the flow of information etc. Our motivating example is a network of traders within several investment institutions such as hedge funds. We assume an idealised scenario where traders within the same institution have many contacts and can share information quickly and easily but have fewer contacts to traders in other institutions, relying on personal networks, allowing for information to flow easily within a community and less-so between communities. In this paper we investigate a particular spreading process, the spread of a rumour, on a community based network that is characterised by two parameters; the within-group connectivity, and the between-group connectivity. We show that such networks have different characteristics to small-world or random networks that are often used to model the types of systems and that the network
topology has a small but not insignificant effect on the spread of rumours on the network.
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Biological Physics
Open-source MRI-informed computational model of human cortical folding
Anne Kerachni, Thomas Lavigne, Stéphane Urcun et al. (+3 more)
The human cerebral cortex, initially smooth, progressively folds during fetal
brain development in utero, giving rise to cortical convolutions. Atypical cortical folding patterns can be associated with neurodevelopmental and neurological disorders. To better understand these conditions, it is crucial to first examine the factors governing healthy cortical folding. Computational modeling provides a powerful way for this purpose and has already helped understanding the influence of key biomechanical parameters on the folding pattern. However, most existing models use simplified geometries, limiting calibration and validation with fetal and neonatal
brain Magnetic Resonance Imaging (MRI) and neglecting the influence of initial geometry on fold development. On the other hand, simulations on realistic
brain geometries introduce additional challenges, including collision handling, fold characterization, and additional computational cost. Furthermore, model parameters are often difficult to interpret, complicating comparison, clinical translation, and calibration. Finally, computational models of cortical folding also remain rarely accessible. In this work, we introduce a novel computational model of cortical folding, developed using the open-source code FEniCS to simulate folding on a whole-
brain geometry generated from fetal MRI data. We also propose a modular, interpretable, and scalable simulation framework built around this computational model and openly available to the community. It uses fetal MRI data to generate realistic input
brain meshes and estimate key biomechanical parameters such as cortical growth rate. The framework also integrates a spectral metric for cortical surface analysis to optimize folding pattern predictions from an healthy fetal MRI
dataset.
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All authors Anne Kerachni, Thomas Lavigne, Stéphane Urcun, Mireia Alenya, Oscar Camara, Julien Lefèvre François Rousseau
Physics and Society
The geopolitics of knowledge: tipping points, national fingerprints, and the unequal globalization of science
Irina Vorobeva, Maxime Lenormand, Germana Berlantini et al. (+1 more)
Science is often portrayed as a universal and self-contained system, driven solely by the internal logic of knowledge accumulation and isolated from the turbulences of the socio-political world. In this paper, we challenge this narrative by providing systematic quantitative evidence that the global scientific ecosystem is deeply shaped by geopolitical transformations. Using a large-scale
dataset of scientific publications drawn from the OpenAlex database, spanning over five decades and covering virtually all countries and disciplinary areas, we track the
evolution of national research profiles and show that geopolitical dynamics shape scientific agendas at multiple scales. At the global level, intrinsic scientific change is slow and cumulative, but exogenous shocks, such as Chernobyl, September 11, and COVID-19, produce rapid disruptions that synchronously reconfigure the priorities of many countries at once. At the country level, we document a broad globalization of knowledge, yet deeply heterogeneous: while Global North countries converge toward a shared international agenda, Global South countries display strong dependence on international resources alongside locally distinctive research interests. Among emerging Southern economies, scientific power is increasingly asserted through specialized and independent agendas. Finally, we observe a reorganization of global scientific influence toward a more polycentric structure, with the emergence of a Southern cluster gravitating around Brazil and Indonesia as new regional hubs.
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All authors Irina Vorobeva, Maxime Lenormand, Germana Berlantini, Floriana Gargiulo
Fluid Dynamics
Hele-Shaw Flow With Pressure and Shear Rate Dependent Viscosity
Benedetta Calusi and Liviu Iulian Palade
This paper investigates the behaviour of a fluid characterized by a viscosity simultaneously depending on pressure and shear rate within a Hele-Shaw
cell featuring a sharp corner geometry. The study extends previous analyses conducted on purely pressure-dependent (piezo-viscous) and yield-stress fluids, providing a new perspective on confined complex flows. Motivated by practical applications related to designing biomedical devices and flows of relevance to biomedicine area, thin film technologies, injection molding – to name only a few – the flow configuration considered here can highlight essential features of complex fluid behavior in narrow-gap geometries around a sharp edge. Starting from the governing equations for an incompressible generalized Newtonian fluid and employing an appropriate rheological model, we derive the modified flow equations adapted to the Hele-Shaw flow. A particular solution is obtained near the corner region. Numerical simulations complement the theoretical results, illustrating the influence of the rheological parameters on the flow behavior.
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Computational Physics
Repurposing acquisition devices into trigger-based timing synchronization of breakdown events during MITICA high voltage holding experiments
Andrea Rigoni Garola, Luca Lotto, Gabriele Manduchi et al. (+8 more)
A critical requirement for MITICA – a full-scale prototype of the heating Neutral Beam Injectors hosted at the Consorzio RFX Neutral Beam Test Facility for the ITER experiment – is the capability to withstand a continuous voltage of 1MV across the
vacuum gaps insulating the beam source from the grounded vessel. To validate such feature, a dedicated voltage-holding test campaign was conducted throughout 2024 and 2025 using a full-scale mock-up of the beam source. The tests also involved an accurate characterization of the associated breakdown events:
vacuum dielectric failures which result in rapid potential drops and generate strong current discharges. This contribution will present a relative time reconstruction architecture based on cost-effective, embedded RedPitaya (Zynq-7000 FPGA) devices repurposed as timing hubs. These nodes function as configurable trigger multiplexers while simultaneously recording trigger signals as transients to facilitate the offline reconstruction of event sequences. The method allows self-calibration through measuring the static intrinsic delays of the optical fibers and internal logics, generating delay offsets to synchronize acquired waveforms across a sparse, connected-graph
topology of both acquisition devices and hubs themselves.
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All authors Andrea Rigoni Garola, Luca Lotto, Gabriele Manduchi, Tommaso Patton, Raffaele Ghiraldelli, Cesare Taliercio, Marco Boldrin, Luca Trevisan, Paolo Cinetto, Paolo Barbato, Giuseppe Chitarin
Atmospheric and Oceanic Physics
New features of the sea-surface slope distribution revealed by IASI observations: Directional properties, influence of the wave height, large wave tilts
Charles-Antoine Guérin, Virginie Capelle and Jean-Michel Hartmann
By analysis of the reflected
solar contribution to mid-infrared radiance spectra collected by the IASI instrument, we investigate the influences of both the wind and significant wave height on the wave-slope probability distribution function (PDF). We show that, at equal wind speed, smaller wave heights enhance the directional (upwind-downwind and upwind-crosswind) asymmetries of the probabilities. We also point out that the sea-surface mean square slopes slightly decrease as the wave height increases (by about $5\%$ per meter for winds slower than 6 m/s), an original result for which we propose possible causes (short-scale damping by long waves and/or effect of compounding statistical processes). We also investigate the so far practically unstudied case of steep slopes and find large deviations from the quasi Gaussian behavior of the central part of the PDF, with a quite universal exponential decay of the probabilities with increasing tilt. We here observe larger probabilities in the downwind direction, but similar values in the up- and cross-wind ones. The physical mechanisms responsible for these trends are discussed. Finally, we propose refined parametrizations of the mean square slope versus wind-speed, which departs from the Cox and Munk linear relationships at moderate wind speed (5-8 m/s).
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Space Physics
Photon Acceleration in Magnetized Plasma: A Mechanism for Fast Radio Bursts
Sergei V. Bulanov, Gabriele Maria Grittani, Marcel Lamac et al. (+7 more)
We propose a mechanism for fast
radio bursts based on
photon acceleration by relativistic shocks propagating through highly magnetized electron–positron
plasmas, as expected in magnetar magnetospheres. Density modulations at the shock front create relativistically moving refractive-index perturbations that transform low-frequency electromagnetic precursors into amplified high-frequency radiation. We show that the predicted frequencies, durations, and energetics of the resulting fast
radio bursts are consistent with the
magnetic-field strengths, shock Lorentz factors, and characteristic spatial scales expected in magnetar magnetospheres.
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All authors Sergei V. Bulanov, Gabriele Maria Grittani, Marcel Lamac, Petr Valenta, Stepan S. Bulanov, Timur Zh. Esirkepov, Gianluca Gregori, Brandon K. Russell, Alexander G. R. Thomas, Arno Vanthieghem
Optics
Doubly resonant enhancement of second-harmonic generation with in-plane phase matching in plasmonic metasurfaces on an AlInP slab waveguide
Timo Stolt, Huayu Bai, Seyed Ahmad Shahahmadi et al. (+3 more)
Nonlinear metasurfaces have attracted significant interest by offering the possibility to circumvent conventional phase-matching requirements of bulk nonlinear
crystals, opening the way to efficient frequency conversion over ultrashort propagation distances. Here, we experimentally demonstrate metasurfaces in which second-harmonic generation is strongly enhanced by in-plane phase matching of high-Q guided-mode resonances. To achieve this enhancement, we use hybrid metasurfaces composed of periodic arrays of gold nanodiscs on a slab waveguide made of aluminum indium phosphide (AlInP) - a low-loss epitaxial III-V
semiconductor material. The metasurfaces are found to exhibit guided-mode resonances with Q factors exceeding 400 and 900 at the visible and near-infrared wavelengths, respectively, demonstrating the unique capabilities of hybrid metal-dielectric structures to support high-Q resonances despite the presence of lossy plasmonic components. Moreover, our frequency and momentum-resolved measurements demonstrate a two-orders-of-magnitude enhancement of second-harmonic generation at doubly resonant conditions. We reproduce the experimental results using numerical simulations, showing that the in-plane phase matching and spatial mode overlap are the main factors governing the enhancement. Our findings demonstrate a promising strategy to realize efficient metasurface-based frequency converters, enabling their potential applications in compact photonic systems.
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All authors Timo Stolt, Huayu Bai, Seyed Ahmad Shahahmadi, Jani Oksanen, Andriy Shevchenko, Radoslaw Kolkowski
Atomic Physics
Fourier imaging of collective spontaneous emission modes in superradiant cold atomic clouds
Adrien Gavalda, Guillaume Tremblier, Martin Poitrinal et al. (+3 more)
We measure the spatial pattern associated with the superradiant emission from a cloud of cold 87Rb atoms using
Fourier imaging. We observe a highly directional, ring-shaped emission structure, which corresponds to a single collective jump operator associated to the most superradiant mode of the ensemble. Using spatial filtering, we isolate this channel and find the typical superradiant burst with superlinear scaling of the intensity with atom number. We compare our results to two models that describe the competition between the various decay channels, finding good agreement. Our work shows that the collective jump operators introduced by Carmichael et al. [Optics Communications 179, 417 (2000)] can be measured and manipulated.
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All authors Adrien Gavalda, Guillaume Tremblier, Martin Poitrinal, Sara Pancaldi, Antoine Browaeys, Igor Ferrier-Barbut
Atomic Physics
Efficient photo-ionizing elimination of detrimental electric fields for Rydberg atoms
Zhou-Chen Deng, Hao-Nan Lin, Yu-Cheng Duan et al. (+10 more)
Rydberg atoms are highly sensitive to external electric fields due to their exaggerated electronic properties. This unique feature lays the foundation for many of their applications in
quantum science. However, an uncontrolled stray electric field can be detrimental, severely degrading their
quantum control. In this work, we demonstrate a universal scheme that relies on the efficient creation of an in-
vacuum plasma source by photo-ionizing
laser-cooled atoms to eliminate detrimental electric fields in a Rydberg-atom tweezer array platform, requiring only readily available resources. With this method, we began with a Stark-ionized Rydberg continuum spectrum caused by a large, unknown stray electric field and ultimately recovered stable, coherent excitation of an individual Rydberg state after fully eliminating the field. Our method is directly applicable to existing Rydberg-atom platforms and can also be useful in other experiments sensitive to stray electric fields.
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All authors Zhou-Chen Deng, Hao-Nan Lin, Yu-Cheng Duan, Qi Zhang, Xiang-Can Cheng, Yang Liu, Zhao-Yang Yuan, Jie Li, Peng Liu, Zhan Wu, Chao-Yang Lu, Jun Rui, Jian-Wei Pan
Plasma Physics · Cross-listed from astro-ph.SR
Collisionless and collisional kinetics of a plasma atmosphere with spatially and temporally intermittent heating at its base
Luca Barbieri, Pascal Démoulin and Filippo Pantellini
The
solar corona exhibits a pronounced temperature inversion, with
plasma temperatures increasing by nearly two orders of magnitude from the chromosphere to the corona. We investigate how spatially sparse and temporally intermittent
stochastic heating at the base of the transition region shapes the temperature and density structure of coronal loops within a kinetic framework.
Stochastic thermal boundary conditions and surface coarse graining are introduced. Analytical solutions are derived in the collisionless limit for heating-event time scales shorter or longer than the particle crossing time, and Coulomb collisions are incorporated through a reduced kinetic model describing the thermalization of suprathermal particles. In the short-time-scale regime, spatial filling factor and temporal intermittency combine into a single effective parameter controlling the suprathermal population, producing a transition region and a hot corona both within individual loops and after coarse graining. Collisions preserve this thermal structure while reducing the coronal density through progressive thermalization. In the long-time-scale regime, individual loops are nearly isothermal and the temperature inversion emerges only after coarse graining, depending solely on the spatial filling factor. Here, Coulomb collisions and optically thin radiative losses have only minor effects, while density and temperature profiles remain broadly consistent with coronal observations. These results show that sparse, intermittent heating naturally generates suprathermal particle distributions and reproduces the observed thermal structure of the
solar corona within a kinetic framework, highlighting the different sensitivity of the two regimes to collisional effects.
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Fluid Dynamics
On the rectification of oscillatory flows by flexible leaflets in a confined geometry
Omar Abukabsha, Simon Gsell and Martin Brandenbourger
Inspired by biological systems, extensive research has explored how fluid-structure interactions in compliant channels and confined geometries control fluid transport. While local nonlinearities can be induced by individual components, arranging these elements into larger architectures gives rise to increasingly complex, collective responses. Predicting these collective behaviors, however, remains largely restricted to steady-state characterization, as the dynamic coupling between time-varying flows and multiple interacting structures is difficult to model. In this paper, we investigate numerically the collective interaction of multiple asymmetric leaflets within a channel at low-Reynolds number. By utilizing symmetrically oscillating plates rather than a pressure-driven flow to isolate the system from background asymmetries, we characterize how these interacting structures generate a net fluid transport. We develop an analytical framework to evaluate transport in the steady limit, which we subsequently extend to account for time-dependent channel oscillations, providing a complete dynamic description of the coupled fluid-structure system. Our results demonstrate that high leaflet densities maximize collective interactions and net transport. Furthermore, we define an elastoviscous number comparing viscous hydrodynamic forces to the restorative elastic forces of the leaflets, and uncover an optimal value that maximizes the net flow. This framework establishes a foundation for analyzing how collective slender structures interact dynamically within viscous environments, laying the groundwork for future studies on flow control in biological fluid transport and microfluidic design.
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Optics
Flexible Inverse Design of Optical Multilayer Coatings Using Discrete-Continuous Flow Matching
Zhiyi Li, Yuheng Jin, Yidan Huang et al. (+3 more)
Optical multilayer coatings are used in imaging optics,
lasers, telecommunications,
solar cells, and radiative cooling, where the spectral response required by each application is achieved by a well-designed layer structure. However, existing design methods have limitations. Local methods refine a starting design efficiently but depend on its quality, and global searches require up to millions of transfer-
matrix evaluations per target. Existing deep-learning inverse-design models are fast, but they are trained for a fixed set of materials and a fixed wavelength band, and they either optimize the thicknesses for a fixed material sequence or choose them from a discrete grid. In this paper, we present IrisFlow, a generative model that addresses these limitations by taking each candidate material as its optical constants and the target spectrum together with its wavelengths as input. It generates the material and the continuous thickness of every layer jointly, by coupled discrete and continuous flow matching in a single network. We demonstrate its performance through design with materials outside the training library and on bands beyond the training range, and through comparisons with classical optimizers and an existing deep-learning model. We also demonstrate its usability in a practical design workflow by designing four colored
solar-reflective coatings with the calibrated optical constants of an existing deposition system. Combined with a local refinement of its ten best designs, it reduces the number of transfer-
matrix evaluations about 500-fold relative to needle optimization at comparable accuracy. The code, trained model, and training and test data are publicly available.
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All authors Zhiyi Li, Yuheng Jin, Yidan Huang, Nan Chen, Hongyan Fu, Yikun Bu
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Polycrystalline ferroelectric croconic acid for multisource environmental energy harvesting
Gloria P. Moreno-Martínez, Hari K. Mishra, Xabier García-Casas et al. (+5 more)
The development of organic ferroelectric materials through scalable and simplified fabrication routes remains a major challenge for next-generation energy-harvesting technologies. Here, polycrystalline croconic acid (CA) thin films are fabricated by
vacuum sublimation onto Ar
plasma-treated flexible substrates and stabilized by in situ encapsulation with an adamantane-based remote
plasma polymer. This solvent-free strategy effectively suppresses surface degradation under ambient conditions, providing long-term stability. Piezoresponse force microscopy confirms robust ferroelectricity with an oblique polarization orientation, well-defined domains, and low nanoscale coercive fields. The films were integrated into multilayer piezoelectric and pyroelectric devices. The piezoelectric performance strongly depends on film thickness, while
embedding the CA layer between dielectric polymeric films significantly improves the macroscopic response, reaching power densities of up to 37 microW m-2 for ca. 2 micrometer CA films. Despite the common assumption that high crystallinity is required to sustain ferro-, piezo-, and pyroelectricity, these polycrystalline CA films exhibit remarkable RT pyroelectricity, a property not previously demonstrated in CA-based devices. A pyroelectric coefficient of ca. 10 microC m-2 K-1 highlights a functional response comparable to that of well-established organic and inorganic pyroelectric materials, demonstrating the potential of CA thin films for thermal energy harvesting. Beyond their functional performance, the proposed low-T fabrication route combines deposition and encapsulation in a single in situ process, simplifying device fabrication. Its compatibility with scalable
vacuum technologies, flexible substrates, and further process optimization makes this approach highly promising for developing low-cost, lead-free, multisource energy-harvesting systems.
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All authors Gloria P. Moreno-Martínez, Hari K. Mishra, Xabier García-Casas, María Alcaire, Vanda Godinho, Juan R. Sanchez-Valencia, Ana Borras, Angel Barranco
Optics
Inverse-designed meta processing units for multi-task near-field photonic computing
Chu Wu, Zeyu Cai, Songtao Yang et al. (+5 more)
Integrated photonic neural networks require optical operators that are simultaneously compact,
matrix-general and compatible with task-level reconfigurability. Here we introduce a meta processing unit (MPU), an inverse-designed near-field photonic device that implements local complex
matrix transformations within a shallow-etched silicon region. Each 2x2 operator occupies 9.6 umx4.8 um and is designed as a reusable passive
matrix primitive that can be combined with reconfigurable MZI
neurons. We demonstrate a 3-bit quantized MZI-equivalent
unitary device library with an effective reconstruction precision of 3.32 bits. Beyond
unitary operators, we validate arbitrary complex 2x2
matrix fitting and a cascaded 4x4
matrix operation with 92.7% fidelity. We further integrate the MPU with active photonic components and hardware-in-the-loop training, achieving test accuracies of 83.5% and 80.9% on dual-task vowel recognition. In large-scale EMNIST simulations, a fine-grained
neuron-level MPU replacement strategy reaches 87.64% average accuracy at 90% shared-MPU replacement, outperforming a layer-level baseline by 7.26 percentage points. These results establish inverse-designed MPUs as compact passive
matrix operators for heterogeneous, hardware-adaptive photonic neural networks.
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All authors Chu Wu, Zeyu Cai, Songtao Yang, Ruoyu Shen, Yinan Zhao, Haiou Zhang, Wei Chu, Xing Lin
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Bright and Dark Excitons in CrSBr: Local Ligand-Field Character and Band-Coherent Optical Selection Rules
Swagata Acharya, Jessica McDivitt, Dimitar Pashov et al. (+3 more)
Magnetic van der Waals
semiconductors such as CrSBr host an intricate
exciton landscape whose physical interpretation has converged only recently. A many-body Feynman diagrammatic approach based on quasiparticle self-consistent GW with electron-hole ladder vertex corrections to the screened Coulomb interaction has established the electronic band gap, excitonic orbital character, real-space extent, binding energies, and bosonic-coupling signatures of the bright XA
exciton near 1.34 eV and the higher XB
manifold near 1.8 eV. These results agree well with ARPES and magneto-optical experiments and supersede the early Rydberg-like assignment of the
excitons. What has remained unresolved is why these intense bright
excitons coexist, within a few tens of meV, with companion states that are several orders of magnitude darker despite drawing from essentially the same single-particle transition
manifold. Here we show that brightness is a band-coherent property of the excitonic eigenfunctions: bright and dark partners are sublattice-symmetric and sublattice-antisymmetric superpositions of the same ligand-field-like Bloch transitions across the two Cr atoms of the orthorhombic primitive
cell. The commonly used Frenkel and Wannier-Mott labels describe what an
exciton is made of, but brightness requires a
symmetry-adapted interference rule between transition dipoles. Disentangling this bare excitonic structure is a prerequisite for interpreting the optical response of CrSBr once
magnon,
phonon, and
photon couplings are included.
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All authors Swagata Acharya, Jessica McDivitt, Dimitar Pashov, Mark van Schilfgaarde, Justin C. Johnson, Jeffrey L. Blackburn
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Bond, orbital and spin order in d4/d6/d7 perovskite oxides: successes and limitations of foundation interatomic potentials
Swagata Acharya, Dimitar Pashov, Mark van Schilfgaarde et al. (+1 more)
Foundation machine-learning interatomic potentials (MLIPs) are rapidly replacing density-functional theory (DFT) for modeling structure and
nuclear dynamics, making their fidelity in strongly correlated systems an urgent question. We test three foundation potentials on the low-temperature order of three correlated, isostructural ABO3 perovskite
oxides: LaMnO3 (d4), LaCoO3 (d6), and NdNiO3 (d7). We run molecular dynamics for 1 ns on 80- and 160-atom supercells from 50 to 300 K with no system-specific training. These
oxides expose three distinct classes of low-temperature order that define a hierarchy of difficulty for the potentials. The scalar class, represented by NdNiO3, has a simple
geometric fingerprint and is captured. The vector class, represented by LaMnO3, requires identifying which Cartesian axis carries the long bond at each site, and is captured in magnitude but not in
symmetry. The on-site class, represented by the low-
spin to high-
spin crossover in LaCoO3, is a purely local multiplet population shift with no spatial order parameter and remains inaccessible to present-day MLIPs.
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All authors Swagata Acharya, Dimitar Pashov, Mark van Schilfgaarde, Alin M. Elena
Data Analysis and Statistics · Cross-listed from quant-ph
Grokking and epoch-wise double descent in quantum neural networks
Daniel Pranjić, Marco Roth and Christian Tutschku
Grokking, the delayed transition from memorization to generalization, is a fundamental phenomenon in gradient-based learning, yet its dynamics within variational
quantum machine learning (QML) remain largely unexamined. In this work, we report the empirical observation of both the grokking transition and epoch-wise double descent in a two-
qubit quantum neural network (QNN) under a complete parameterization of the SU(4)
manifold. We demonstrate that overparameterization via increased
circuit depth improves the probability of successful generalization. Notably, these architectures frequently exhibit an epoch-wise double descent in test error, degrading at a critical epoch before recovering into a generalizing state. Crucially, we identify a generalization decay in late-stage training, where the test error increases significantly despite a stagnant training loss. Bridging this behavior with algorithmic stability theory, our analysis reveals that this decay correlates with an unconstrained increase of the weight-norm, drifting away from sparse, phase-aligned harmonic solutions toward overfitted solutions in the
Hilbert space. We analyze the underlying temporal dynamics of this transition, demonstrating how the onset of generalization is linked to optimization hyperparameters such as learning rate and weight decay. Finally, to mitigate late-stage decay, we introduce a weak explicit weight-norm regularization into the loss function. We demonstrate that this structural anchor stabilizes the post-grokking phase and permanently preserves generalization gains, providing a robust framework for training overparameterized
quantum circuits.
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Data Analysis and Statistics · Cross-listed from nlin.CD
Intrinsic instantaneous coarse-to-fine recoverability in multiscale chaos: The Lorenz-96 system
Zhongfeng Xu and Junfeng Chen
In multiscale chaotic systems, a central question for closure is how much of an unresolved fine-scale target can be inferred from a simultaneous coarse observation. For a specified observation-target pair, we quantify instantaneous recoverability under the invariant snapshot measure as the fraction of target variance explained by conditioning on the retained coarse variables. Evaluating this quantity across scales produces a scale-resolved recoverability map. Applied to the Lorenz-96 system across a range of forcings, the maps reveal a strongly nonuniform landscape: lower-wavenumber targets have little variance explained by the retained lower modes, while a finite band of higher modes exhibits partial recoverability once the retained scales reach the energetically active intermediate range. Recoverability onset is organized around a reference cutoff at which two retained modes can directly couple to the target through the quadratic nonlinearity, although its precise location depends on attractor statistics. Across the tested forcings, this qualitative onset structure persists while recoverability decreases, leaving a larger fraction of target variance unexplained in more strongly driven regimes. This definition identifies the maximal explained-variance fraction attainable by instantaneous deterministic models under squared loss; the estimated maps provide a scale-dependent diagnostic for closure modeling.
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Applied Physics
Design, Modeling, and Validation of Curvature-Based Shape-Aware Flexible Phased Arrays
Yair Dashevsky, Alon Elgarat and Matan Gal-Katziri
Knowledge of the shape of deformed, mechanically flexible phased arrays plays an important role in the ability to maintain their beam pattern. This work presents the design, modeling, and experimental validation of such arrays with integrated
curvature-based shape sensing. We analyze, over a large set of representative deformed shapes, the sensor density required for effective deformation sensing under measurement noise; develop and experimentally validate a physical model relating measured strain to local board
curvature; and demonstrate an end-to-end design of a shape-aware, 6-GHz, eight-element array in conformed and free-hanging scenarios, achieving an average reconstruction accuracy of ~6% while recovering beam-steering performance at radii of
curvature below 3.6 cm. The system utilizes a low-cost, eight-channel, 360$^{\circ}$ digitally controlled phase-shifter platform useful for a wide range of smart-
antenna experiments. The shape is recovered from low-rate surface measurements, independently of RF conditions and without feedback, making the approach a general sensing modality applicable beyond the beam correction demonstrated here.
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Fluid Dynamics
Tracking the boundary between absolute/convective instability using adjoint equations
Yue Xiao, Hui Li and Zijing Ding
Determining absolute/convective instability boundaries conventionally requires repeated saddle searches in the complex-wavenumber plane and a subsequent scan of the physical parameter space to locate zero absolute growth. Such nested calculations become costly and sensitive to modal branch association for large non-normal
eigenvalue problems. This work develops a direct continuation method for neutral stationary-saddle boundaries of frequency-affine generalised
eigenvalue problems. The zero-group-velocity condition is expressed as an adjoint solvability residual and solved together with the direct and adjoint eigenproblems, complex gauge constraints and the neutral-growth condition. The resulting one-dimensional solution
manifold in the combined state–parameter space is tracked by scaled pseudo-arclength continuation, allowing parameter folds to be crossed without switching the physical continuation variable. The formulation recovers the analytical Ginzburg–Landau boundary and, for a Gaussian-wake Orr–Sommerfeld problem, agrees with separately formulated finite-difference saddle corrections to approximately $10^{-8}$ in relative critical Reynolds number. Compared with nested complex-wavenumber and parameter-plane saddle scanning, the tested scans require $8.1$–$52.2$ times the wall time of the direct adjoint continuation. Extrapolation of the measured cost–accuracy trend to a boundary error of $E_H\sim10^{-6}$ suggests an estimated cost ratio of approximately $1.8\times10^{4}$ in favour of the direct continuation. Application to a coupled Oldroyd–B free-surface film reveals genuine folds of the neutral-saddle
manifold and a re-entrant CI–AI–CI boundary geometry for the selected saddle family.
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Optics · Cross-listed from cond-mat.mes-hall
Anomalous Reflection of Caustic Spin-Wave Beams in a Magnonic Waveguide
Franz Vilsmeier and Christian Back
Reflection of waves at interfaces is conventionally governed by Snell's law, which follows from conservation of momentum parallel to the interface. Here we show experimentally that caustic
spin-wave beams in anisotropic media obey a fundamentally different reflection mechanism. Applying time-resolved Kerr microscopy to a yttrium iron garnet waveguide, we observe that reflected beams are selected by transitions between caustic points on the anisotropic iso-frequency contour rather than by momentum conservation. As a consequence, the reflected carrier wave vector and wavefront orientation exhibit trends opposite to those predicted by Snell's law. By tuning the magnitude and orientation of an external
magnetic field, we continuously control the resulting reflection process and beam routing. Our results establish caustic-point transitions as a distinct reflection law for anisotropic wave beams and provide a route towards reconfigurable magnonic beam steering.
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Plasma Physics
Sensitivity of a low-shear heliotron configuration to localised ferrite-steel perturbations
A. Matsuyama, F. Tanji, Y. Nakamura et al. (+10 more)
The influence of ferritic steel on low-shear stellarator/heliotron
magnetic configurations is investigated for the Heliotron J device using a point dipole magnetisation model. By numerically evaluating ferritic steel plates assumed at several locations inside the Heliotron J
vacuum vessel, the changes in the rotational transform and
magnetic island width are shown to be sensitive to the installation location. This location sensitivity arises from the toroidal variation of poloidal mode coupling between the background nonaxisymmetric field and ferritic-steel perturbation, rather than being determined solely by the perturbation amplitude. The resulting mode coupling can enhance the resonant
vacuum magnetic perturbation at specific locations. Ferritic steel plates placed on the outer side of a straight section produce the most significant changes in the
magnetic topology and exhibit the highest sensitivity to violations of the $M=4$ toroidal periodicity. Additionally, we show that appropriate arrangements of passive
magnetic dipoles can reduce the effective helical ripple while preserving the
vacuum magnetic well depth in Heliotron J, and can induce a stellarator-asymmetric boundary perturbation in low-field experiments.
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All authors A. Matsuyama, F. Tanji, Y. Nakamura, S. Inagaki, Yusuke Yamashita, Akihisa Yamamoto, S. Kobayashi, F. Kin, S. Kado, S. I. Inagaki, S. Konoshima, T. Mizuuchi, K. Nagasaki
Physics and Society
Temporal Boundaries of Newell's Car-Following Model: Insights from Lane-Free Traffic
Suhaib Nazir, Hillel Bar Gera and Bhargava Rama Chilukuri
Newell's simplified car-following model offers behavioral interpretability with minimal parameters, yet the temporal limits within which it holds during actual car-following interactions, particularly in lane-free traffic, remain poorly understood. This has direct consequences for Newell parameter estimation. This study evaluates the model using high-resolution
UAV trajectories from a lane-free highway corridor in Chennai, applying two independent estimation approaches: linear regression of the speed-spacing relationship (aggregate and pair specific), and a shifting optimization method that recovers parameters by minimizing spacing variance. A boundary-corrected variant of the shifting method is then introduced to isolate transitional regimes at interaction endpoints while preserving the original Newell formulation. Pair-specific regression substantially outperforms the aggregate specification ($R^2$ = 0.84 vs. 0.54), underscoring pronounced driver heterogeneity. Parameters recovered via trajectory shifting are statistically equivalent to regression estimates, providing independent support for the trajectory translation principle underlying Newell's model. Boundary correction markedly improves model fit, increasing the mean $\bar{R^2}$ from 0.66 to 0.95, and is preferred for 81% of pairs according to the
Bayesian Information Criterion (BIC). The results indicate that interaction boundary effects, rather than failures of the core behavioral assumptions, are the principal source of estimation error in this setting. Correcting for these effects improves parameter recovery without compromising model parsimony. Boundary correction is therefore a necessary step in trajectory-based calibration of Newell-type models, with implications for traffic state estimation and microscopic traffic simulation.
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Optics
Ion-Implanted Silicon Nanoregions Enable Ultra-Low-Loss Trimming of Cladded Photonic Integrated Circuits
Zhongyu Tang, Shabnam Taheriniya, Seongmin Jo et al. (+8 more)
Photonic integrated
circuits (PICs) have emerged as a key platform for information processing, including optical communication and computing. As PIC complexity increases, fabrication-induced response deviations accumulate, making post-fabrication trimming critical for unlocking their full potential. Here, we demonstrate that silicon ion implantation enables scalable, ultra-low-loss trimming of cladded PICs by locally forming a high-index silicon-rich region. Structural characterization confirms that the silicon-implanted nanoregion is confined to the cladding without observable damage to the underlying waveguide. The implantation-induced excess loss is below 0.001 dB per {\pi} phase shift, while the optical response remains stable over a four-month observation period. Automated trimming is demonstrated on a photonic crossbar array, reducing the average channel output variation from 78.5% to 5.9%. These results establish a practical route towards automated, ultra-low-loss post-fabrication trimming for large-scale cladded PICs.
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All authors Zhongyu Tang, Shabnam Taheriniya, Seongmin Jo, Xinyu Ma, Akhil Varri, Anna P. Ovvyan, Vincent Spreter, Liam McRae, Xiansong Meng, Wolfram H. P. Pernice, Rongyang Xu
Computational Physics · Cross-listed from nucl-th
Full-Spectrum Quantum Simulation for the Nuclear Shell Model
B. Maheshwari, P. Stevenson and P. Van Isacker
The
nuclear shell model is a general way of expressing the many-body
nuclear Hamiltonian and deciphering the underlying
nuclear structure. In today's era of modern and high-power computation, the primary limitation of the
nuclear shell model is the enormous dimensionality of its
Hilbert space, which far exceeds available storage capacity and prevents the diagonalization of the full
Hamiltonian matrix in that space.
Quantum computing offers a scalable solution to bypass this curse of dimensionality. In this work, we introduce a single-run
quantum simulation capable of obtaining multiple shell-model eigenstates simultaneously. The
nuclear Hamiltonian is transformed from a bit to a
qubit basis using the Jordan-Wigner transformation, explicitly preserving fermionic anti-commutation. We employ a Subspace Search Variational
Quantum Eigensolver (SSVQE) along with an Adaptive Derivative-Assembled Pseudo-Trotter (ADAPT) ansatz to construct the
quantum circuit required to solve the shell-model problem. The ADAPT-SSVQE
algorithm uses a
symmetry-preserving single and double-excitation operator pool and optimizes a weighted energy sum to obtain the simultaneous convergence of all eigenstates within a targeted MJ subspace, eliminating the need for post-processing efforts to extract excited spectra. We
benchmark this approach by solving the problem for two and three identical nucleons in a j = 9/2 orbital, successfully extracting five and ten mutually orthogonal states, respectively, within a 10-
qubit active space. The
algorithm achieves spectroscopic accuracy, in simulation, relative to exact diagonalization and intrinsically restores total angular momentum (\hat{J}^2)
symmetry.
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