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Physics

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Monday 28 September

Nuclear Theory

Modelling fission with microscopic input: excitation-energy-dependent fission paths for neutron-induced reactions

Adrián Sánchez-Fernández, Wouter Ryssens and Stéphane Goriely

To calculate transmission coefficients, current Hauser-Feshbach reaction codes assume a one-dimensional fission path that is both independent of excitation energy and universal across different fission channels. In contrast, microscopic fission studies typically explore multiple collective variables. Predicting observable fission quantities such as cross sections based on microscopic input thus requires a way to reduce the dimensionality of the latter. For spontaneous fission, the least action path (LAP) – which minimizes the semiclassical action and maximizes the transmission coefficient – is the solution. We demonstrate that the LAP does not generalize to other fission modes such as neutron-induced or $\beta$-delayed fission: at finite excitation energy, the LAP generally does not maximize the transmission. A microscopic PES can have multiple coexisting stationary-action paths. We show that these (i) can switch their action ordering as a function of excitation energy and (ii) yield different neutron-induced fission cross sections predictions, yet match known spontaneous fission lifetimes equally well. For the BSkG3 Skyrme-type energy density functional model, the transition from the axially symmetric LAP at zero excitation energy to a path exploiting the triaxial degree of freedom occurs at an excitation energy that is smaller than the neutron separation energy for essentially all actinides and the majority of unknown exotic nuclei.
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Physics and Society

Measuring the impact of hits

Matúš Medo and Liudmila Rozanova

Many real systems can be represented as growing networks where new nodes and links gradually emerge. The Barabási-Albert model for growing networks, and many models inspired by it, are based on the idea that nodes compete for links. However, the strength and the very presence of this competition have not been tested. We propose a robust statistical approach to quantify how strongly nodes compete for links, and apply it to data from various real systems—commenting on online news and cinema attendance data. We find a range of possible behaviors, from the perfectly elastic case, where new entrants shape network growth in a way that leaves the rest of the system unaffected, to an intermediate case where new entrants measurably affect the rest. Perfect competition is never observed. These findings have direct implications for complex systems modeling and e-commerce applications.
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Quantum Physics

From Simple Sources to Quantum Advantage: Homomorphic Polynomial Transduction via Relative Decoding

Zhong-Xia Shang and Daniel Stilck França

Decoded quantum interferometry (DQI) and its Hamiltonian extension (HDQI) prepare states whose amplitudes are low-degree polynomials of an objective, using Fourier transforms and coherent decoding. We recast this approach as quantum state transduction through algebra homomorphisms. We transfer an efficiently preparable operator state of a degree-$D$ polynomial in a source Hamiltonian $H_A$ to the corresponding polynomial state of a target Hamiltonian $H_B=\pi(H_A)$, where $\pi$ is a unital $*$-homomorphism between the finite-dimensional source and target $C^*$-algebras. The transduction uses operator Fourier transforms and relative decoding to recover source operators rather than individual term-selection labels. The relative distance $d_{\mathrm{rel}}$ is the first degree at which source and target traces disagree. We prove that $2D<d_{\mathrm{rel}}$ is equivalent to preserving all inner products between degree-$D$ polynomials. Moreover, $d_{\mathrm{rel}}\ge d_{\mathrm{ord}}$, where $d_{\mathrm{ord}}$ is the ordinary distance used in (H)DQI, and we give families with $d_{\mathrm{ord}}=O(1)$ but $d_{\mathrm{rel}}=\Theta(n)$ and efficient decoders. Our framework replaces the complicated pilot state preparation by the more modular task of preparing a source polynomial state. DQI and HDQI arise as relation-free special cases. The framework accommodates nonuniform coefficients and noncommuting interactions and extends to fermionic, qudit, and bosonic systems, with applications to approximate optimization and Gibbs sampling. As evidence of advantages, for a nonlinear pairwise variant of optimal polynomial intersection where constant $d_{\mathrm{ord}}$ limits DQI-style preparations, relative decoding yields an ideal quantum score of 0.643 versus 0.606 for the best tested classical heuristic, a gap exceeding 3 percentage points.
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Solar and Stellar Astrophysics

A First Global Full-Vector Coronal Magnetic Field Inference Using MLSO CoMP and UCoMP Observations

Alin Razvan Paraschiv, Zihao Yang, Daniela Adriana Lacatus et al. (+1 more)

Building on recent advances in coronal spectropolarimetry, seismology, and magnetic-field inferences of Z. Yang et al. (2024) and A. R. Paraschiv (2026), we present the first application of the CLEDB IQUD inversion methodology to Mauna Loa Solar Observatory CoMP and UCoMP observations. Using spectropolarimetric IQU measurements together with coronal seismology derived magnetic field BPOS constraints, we recover vector magnetic field solutions across the off-limb solar corona accessible to the observations, demonstrating the feasibility of routine large-scale coronal vector magnetometry without the need for Stokes V observations.
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All authors Alin Razvan Paraschiv, Zihao Yang, Daniela Adriana Lacatus, Momchil Molnar

Computational Physics · Cross-listed from cs.LG

E3J: An Efficient and Open-Source Backend for Euclidean Equivariant Operations on GPU and TPU

Olivier Peltre, Armand Picard, Adrien Pichard et al. (+6 more)

We present e3j, a fast Euclid-equivariance backend for geometric deep learning applications with JAX bindings for GPU and TPU. Leveraging both optimized CUDA and Pallas kernels and algorithmic improvements, the library achieves state-of-the-art throughput and runtime on both forward and backward paths. On a machine learning interatomic potential (MLIP) use case, it outperforms established backends, measuring up to 34% speed-up over cuEquivariance on water box NPT simulation using MACE, while remaining fully open source. E3j achieves over 80% efficiency over the H100 maximum memory bandwidth on tensor product operations, and in many cases more than doubles throughput of message passing convolutions forward compared to previously available backends. In addition, with the release of dedicated Pallas TPU kernel, e3j opens the possibility of large scale equivariant deep learning workloads on TPU architectures, which has so far been difficult to achieve. Our benchmarks show that e3j also achieves over 80% of a TPUv6e memory bandwidth, up to one order of magnitude more than e3nn-jax. The library is available on GitHub, PyPI and is released under an open source Apache 2.0 license.
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All authors Olivier Peltre, Armand Picard, Adrien Pichard, Miguel Bragança, Luca Giacomoni, Valentin Heyraud, Zachary Weller-Davies, Christoph Brunken, Jules Tilly

Space Physics

Spectral Properties of Solar Wind Charge Exchange from Earth's Magnetospheric Boundaries: MHD and Test Particle Simulations

A. Ramachandran, R. T. Desai, H. L. Norman et al. (+6 more)

The Solar Wind Charge Exchange (SWCX) mechanism, where X-rays can be generated through interactions between heavy, highly charged solar wind ions and neutral atoms, offers an opportunity to observe the large-scale transfers of energy and momentum through the Sun-Earth system. In this study, we simulate SWCX signatures from Earth's outer boundaries using Gorgon global magnetohydrodynamic (MHD) simulations combined with kinetic particle-based simulations which we call the X-ray Imaging of the Magnetosphere (XIM) framework. The XIM-predicted emissivities agree with the predictions of the MHD model, producing enhanced emissions from the magnetosheath and cusp regions, but several differences are apparent. Compared with MHD, XIM shows enhanced structuring in the magnetosheath and notable enhanced emissions along the magnetopause associated with betatron acceleration. The results also evidence species-specific spatial variations, which are shown to vary compared to anticipated relative abundances in the solar wind and ion-specific properties. These simulations provide new insights into the underlying dynamics of SWCX at the Earth's outer boundaries, which can be used to understand what might be observed using X-ray observatories in space, such as the recently launched SMILE mission.
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All authors A. Ramachandran, R. T. Desai, H. L. Norman, Y. Tong, D. Bewicke, S. Nitti, J. A. Carter, J. P. Eastwood, J. P. Chittenden

High Energy Astrophysical Phenomena

Investigating signatures of extinct PeVatron activity in supernova remnants IC 443 and W51 C

Silvia Celli and Giovanni Morlino

Context. Supernova remnants (SNRs) are renewed sources of non-thermal particles and the main contributors of Galactic cosmic rays (CRs). Recent ultra-high energy (UHE) gamma-ray data from middle-aged SNRs, such as IC 443 and W51 C, highlight the key role of these systems for particle acceleration. Understanding SNR contribution to PeV CRs requires a detailed modelling about how accelerated particles escape their shocks and are released inside the Galaxy. Aims. We aim at critically assessing the SNR paradigm for the origin of Galactic CRs by investigating the expected secondary radiation produced by hadronic collisions of confined and escaping protons in SNRs, and compare these to recent UHE observations. Methods. Through a time-dependent analytical model describing particle acceleration at the SNR forward shock, we investigate particle escape from the shock expanding into uniform environment and diffusing inside and outside the SNR. Results. Our results support the interpretation that the gamma-ray emission from W51 C and IC 443 is due to hadronic emission from both confined and escaping protons, allowing us to derive robust constraints on the particle maximum energy, the magnetic field amplification process, and the CR acceleration efficiency in these systems. Conclusions. We find that the acceleration efficiency is in the range 1 - 10% (2 - 12%) when the spectrum of accelerated particles is proportional to p^-4 (p^-4.3) and the in-situ diffusion coefficient is suppressed by a factor of 3-10 compared to the average Galactic value. On the other hand, the particle maximum energy ever achieved falls, by a factor of a few, below the PeV energy required to explain the CR knee in the context of SNRs only.
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Superconductivity

Low-Temperature Stabilization of $\delta$-NbN Superconducting Thin Films through Energy-Selective Ion Beam Sputtering

Yifan Liu, Junwoo Lee, Mingyu Xu et al. (+3 more)

Achieving high-quality superconducting thin films at low temperatures is a central challenge for scalable quantum device integration and Complementary Metal-Oxide-Semiconductor (CMOS)-compatible fabrication. Here, we demonstrate a room-temperature magnetron sputtering approach for synthesizing niobium nitride (NbN) thin films using a novel energy-selective ion source that enables independent control of ion energy and ion flux. This capability provides a powerful route to precisely tailor surface kinetics and crystallization pathways, overcoming longstanding limitations in stabilizing high-quality NbN at reduced temperatures. The resulting films were characterized by superconducting transport measurements, X-ray diffraction, X-ray photoelectron spectroscopy, and transmission electron microscopy. Compared with conventional reactive sputtering, ion beam-assisted growth yields a substantial narrowing of the transition width at the superconducting temperature, indicating improved phase purity and electronic homogeneity. Furthermore, this work introduces energy-selective ion control as a general, non-equilibrium route to stabilize metastable superconducting phases at low temperatures, offering a new design paradigm for thin-film quantum materials.
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All authors Yifan Liu, Junwoo Lee, Mingyu Xu, Weiwei Xie, Robert J. Cava, Qi Hua Fan

Soft Condensed Matter

Quorum sensing with density-enhanced motility and size regulation

Itay Azizi

Motivated by biological systems and my previous studies of quorum sensing with density-enhanced motility, I study a model of density-enhanced size and motility, in which both particle size and motility increase when the local density (over a distance larger than particle diameter) exceeds the global density. The emergent structures along different size ratios are spots, holes, bands and labyrinths controlled by several distinct observations. First, the characteristic pattern length scale is controlled by the sensing radius and remains approximately independent of the size ratio. Second, the total area occupied by the particles decreases with increasing size ratio. Third, the active fraction barely depends on the size ratio. These results demonstrate how both particle size and motility can couple microscopic regulation to large-scale pattern formation. I conclude by discussing possible extensions of the model.
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Materials Science

First Principles Magnetic Initialisation Made Simple

Kit D. Brown and Robert A. Lawrence

A fundamental issue with first principles electronic structure calculation is the requirement for magnetic initialisations, which are usually derived from experimental results. In this paper, we present a new and computationally inexpensive method to predict magnetic structures from first principles, based upon symmetry analysis and a non-magnetic band structure only. We demonstrate that this method of creating initialisations successfully reproduces the known magnetic ground state for a wide class of magnetic materials, including ferromagnetic BCC Fe, antiferromagnetic L1$_0$ PtMn, and frustrated antiferromagnetic L1$_2$ IrMn$_3$, while also predicting non-magnetic materials to remain non-magnetic.
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Quantum Physics

Classical Bound on the Fisher Information Rate of a Dephasing-Enhanced Quantum Neuron

Peng Wang, Yu-Xuan Zhang, Hai-Tao Ding et al. (+1 more)

Dephasing can sharpen the activation of a dissipative quantum neuron, but a stationary response does not determine how much input information its output delivers per unit time. For a single qubit with partial-reset updates at rate $\nu$, we derive the threshold response bandwidth and the exact local Fisher information rate of the complete record from repeated projective readouts, including their backaction. Near the activation threshold, the rate obeys $\mathcal R\leq\nu(1-s)(1+s)^2/2\leq16\nu/27$, where $s$ is the retained amplitude of each update. For every fixed finite Markovian dephasing rate, optimization over the readout interval and $s$ gives the same supremum, approached at $s=1/3$ with arbitrarily rapid ideal readout. A finite measurement dead time instead selects a finite optimal interval, which we obtain by a dimensionless two-parameter optimization. The ideal bound is saturated by a classical two-state jump process: quantum coherence changes finite-cadence performance but cannot raise the optimized bound. These results separate noise-enhanced activation from the operational information throughput of a quantum neuron and provide a hardware-aware benchmark for finite-time quantum neural processing.
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All authors Peng Wang, Yu-Xuan Zhang, Hai-Tao Ding, Leong-Chuan Kwek

High Energy Physics (Theory) · Cross-listed from math.DG

Derived deformation theory of heterotic $G_2$ systems near the standard embedding

Bram Brongers

We study heterotic $G_2$ structures near a torsion-free standard embedding, to first order in $\alpha'$ and to all orders in formal deformations. The tangent connection is the Hull connection determined by the metric and flux. We construct a locally invertible family of differential operators relating the supersymmetry and instanton $BPS$ equations to the Euler-Lagrange equations of the heterotic superpotential. Using this comparison and the physical gauge symmetries, we construct a homological vector field locally formally conjugate to the Hamiltonian vector field of the superpotential. On a closed manifold in the fixed gerbe sector, the torsion equation implies vanishing of the leading flux. We prove ellipticity of the linearized deformation complex with mixed differential-order weights and construct a finite-dimensional cyclic $L_\infty$ model with a formal effective potential.
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Soft Condensed Matter

Electrolyte density, diffusivity and conductivity in graphene nanoconfinement predicted by separating interfacial from genuine confinement effects

Haoyuan Quan, Hanne S. Antila, Maximilian R. Becker et al. (+2 more)

Confined aqueous electrolytes exhibit strong deviations from bulk behaviour, but it remains unclear which changes arise from genuine confinement-induced modification and which merely reflect the influence of interfaces. Here, we introduce an interfacial deficit-length framework, capable of decomposing density, diffusivity, and conductivity of confined electrolyte solutions into interfacial and confinement contributions. By applying the framework to molecular dynamics simulations of aqueous alkali halides in planar graphene nanoslits coupled to bulk reservoirs at variable electrolyte concentration, we show that genuine confinement effects emerge only for slit heights $H \lesssim 1$ nm; for larger H, deviations from bulk behaviour are quantitatively captured by interfacial deficit lengths. These deficit lengths are strongly ion-specific and generally positive for water and salt densities as well as for conductivities, meaning that graphene interfaces reduce the values of these observables, while diffusivity deficit lengths tend to be negative, corresponding to larger slit self-diffusivities relative to the corresponding bulk reference. Our deficit-length framework is applicable to any observable from experiments or simulations on nanoconfined electrolytes and predicts confined electrolyte properties for variable slit height H and reservoir electrolyte concentrations.
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All authors Haoyuan Quan, Hanne S. Antila, Maximilian R. Becker, Philip R. Loche, Roland R. Netz

Instrumentation and Methods for Astrophysics

I2C@2024: an interferometric imaging contest in 2024

Florentin Millour, Mathis Houllé, Jeremy Perdigon et al. (+6 more)

Images in optical long-baseline interferometry have seen a boost in the recent years thanks to new techniques and recipes invented by the community. These images are more and more used for science interpretation and not only illustration, and their fidelity has improved significantly, thanks mainly to the increase in the number of telescopes used in interferometers. The focus today is to improve their reliability and dynamic range. With this contest, we follow up the quest introduced in 2004 of comparing the state of the art image reconstruction software for long-baseline interferometry. This is done in a festive way in the form of an imaging contest, where the organizers propose simulated datasets of targets, whose brightness distributions are meant to be blindly retrieved using various algorithms by the contestants. A prize is offered to the winner of the contest. This year is not different from previous ones and we proposed to the contestants tools to compare their reconstructed images with original images. These tools are now distributed, together with example datasets and images, enabling further tests at home of any image reconstruction tool.
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All authors Florentin Millour, Mathis Houllé, Jeremy Perdigon, Julien Drevon, Ryan Norris, Rebecca Proni, Alexis Matter, Ferreol Soulez, Eric Thiebaut

Cosmology and Nongalactic Astrophysics

MATISSE in the era of GRAVITY+

Florentin Millour, Anthony Soulain, Stéphane Lagarde et al. (+28 more)

MATISSE, the mid-infrared spectro-interferometric imager of the Very Large Telescope Interferometer (VLTI), has been feeding on the light corrected by the GRAVITY+ Adaptive Optics (GPAO) systems since the retirement of MACAO on the four Unit Telescopes in 2024. We report the assessment of the new MATISSE performance with GPAO, based on commissioning observations obtained in 2024 and 2025 and compared with archival MACAO observations of the same stellar sources. The instrumental visibility transfer function is more stable in the L band, while its typical value in the L and N bands is unchanged; the visibility signal-to-noise ratio is consistent with, or better than, the values reported at the initial MATISSE commissioning. The correlated flux increases by 20–30% in GRA4MAT mode thanks to a better fringe tracking performance, and the total flux injected into the instrument increases by a factor of 1.3 to 1.4 (up to 1.7) in the L band at low spectral resolution, with no measurable loss in the N band. Combined with the new K-band fringe-tracking limits enabled by GPAO, this translates into a sensitivity gain of a factor 2 to 6 in the L and M bands, a confirmation of the N-band limits similar to the MACAO era. We then report the performances of MATISSE with the GPAO's laser guide stars in November and December 2025. The updated noise figures follow the exposure time calculator predictions in LM LOW and MED and come out better than them in N LOW, the L-band transfer function is stable at the few percent level between observing blocks an hour apart, and correlated fluxes, differential phases and closure phases are recovered down to a 10\,mJy target. Embedded young stellar objects and AGN are now within reach, thanks to the better performances on red targets brought by the lasers. We finally discuss the science cases opened by this gain and the case for a future upgrade of the instrument.
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All authors Florentin Millour, Anthony Soulain, Stéphane Lagarde, Alexis Matter, Valentin Fleury, Farin Drewes, Mathis Houllé, Jules Scigliuto, Bruno Lopez, Anthony Meilland, G. Petrov Romain, Philippe Berio, Anthony Berdeu, Guillaume Bourdarot, Sylvestre Lacour, Mathias Nowak, Jean-Baptiste Le Bouquin, Antoine Mérand, Frank Eisenhauer, Julien Woillez, Miguel Montargès, Diogo Ribeiro, Taro Shimizu, Jens Kammerer, Xavier Haubois, Stefan Gillessen, Pierre Cruzalèbes, Frédéric Gonté, Walter Jaffe, James Leftley, Nicole Nesvadba

Fluid Dynamics

Handling geometric singularities efficiently with the immersed-boundary method: application to riblets

Stefano Cipelli, Alessandro Chiarini, Maurizio Quadrio et al. (+2 more)

We present an enhancement of classical immersed boundary methods for the direct numerical simulation of the incompressible Navier-Stokes equations, designed to efficiently cope with geometrical singularities. The method, while general, is described here in the context of the flow over a plane wall covered by small longitudinal riblets. The enhancement consists in prescribing that the solution near the boundary matches the steady Stokes solution. In this way, sharp corners, where velocity gradients are strongest and viscous effects dominate, become tractable with grids comparable to those necessary for a smooth wall. The method requires the availability of a local Stokes solution, that can be obtained either analytically or numerically. Two test cases are discussed: the laminar flow over one riblet, which allows to measure protrusion heights, and a fully turbulent channel flow with ribbed walls. In both cases, the method reproduces reference results at a substantially lower computational cost.
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All authors Stefano Cipelli, Alessandro Chiarini, Maurizio Quadrio, Davide Gatti, Paolo Luchini

Instrumentation and Methods for Astrophysics

The best of all worlds: gravitational-wave transient detection with multiple pipelines

Nikolas Moustakidis, Theofilos Moustakidis, Deep Chatterjee et al. (+2 more)

The search for gravitational-wave transients (modeled and unmodeled) as performed by the LIGO-Virgo-KAGRA collaborations and the broader community typically involves multiple detection algorithms, often redundant and sometimes complementary. We here address the problem of combining such detection algorithms in order to maximize the noise vs signal discrimination power of such an astrophysical search that utilizes multiple analysis pipelines. Using a machine learning approach, we construct a neural network-based classifier that utilizes information (or lack thereof) from all participating pipelines in the search for compact binary coalescences in LIGO-Virgo-KAGRA's realtime (and offline) processing of gravitational-wave data. We benchmark the method with simulated (astrophysical) signals and real noise from the instruments and obtain receiver operating characteristic curves to quantify its performance. We show how this leads to an effectively new, combined pipeline that outperforms any single pipeline alone or other logical combinations of them. This is particularly critical for real-time operations of the LIGO-Virgo-KAGRA detectors as such combination of detection methods can lead to increased robustness in identifying astrophysical sources and to reduction of the number of false alerts that may otherwise be sent out as astronomical telegrams. Our method also aims in simplifying the presentation of astrophysical results out of the LIGO-Virgo-KAGRA detectors by combining all participating pipelines in the astrophysical searches as well as optimizing resources by the broader multi-messenger astrophysics community in following up astronomical alerts for gravitational-wave transient events.
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All authors Nikolas Moustakidis, Theofilos Moustakidis, Deep Chatterjee, Anastasios Tefas, Erik Katsavounidis

High Energy Physics (Phenomenology)

Meson photoproduction at Jefferson Lab: from two-meson final states to meson-baryon spin-density matrices

Vincent Mathieu

Recent progress in the understanding of meson photoproduction, obtained from the joint effort of the Joint Physics Analysis Center (JPAC) and the GlueX and CLAS experiments at Jefferson Lab, is reviewed. The photoproduction of the $\eta\pi$ system is now well understood, from the $a_2(1320)$ resonance region to the high-mass region dominated by double Regge exchanges. Since the lightest hybrid meson, the $\pi_1(1600)$, is expected to decay predominantly into $b_1\pi$, reactions with a recoiling $\Delta^{++}$ are promising channels for exotic searches. As a first step towards $\gamma p \to b_1 \pi \Delta^{++}$, the complete angular distribution of $\gamma p \to \rho^-\Delta^{++}$ with a linearly polarized photon beam is derived. It involves 56 double-index spin-density matrix elements, which describe the correlations between the $\rho$ and the $\Delta$ decays. When the production amplitudes factorize, as is the case for the exchange of a single Regge pole, the intensity reduces to the product of the standard $\rho$ and $\Delta$ decay distributions and depends on only 14 parameters.
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High Energy Physics (Theory) · Cross-listed from math.PR

On eigenvectors of the SYK model

Yukun He

We consider the Sachdev-Ye-Kitaev model with $N$ Majorana fermions and interaction order $q$. For even $q\in \{2,4,...,N-2\}$, we give an elementary proof and show that the eigenvectors of the model are completely delocalized in all deterministic directions.

Quantum Physics

Experimental quantum-computing-enhanced sensing using Grover's algorithm

Mathieu Ouellet, Purnendu Sen, Xiangqin Wang et al. (+6 more)

The combination of quantum sensing with quantum computing to provide an enhancement over conventional quantum sensing has recently emerged as a promising potential application of quantum computing that could give advantages without needing large-scale or fault-tolerant hardware. In this work, we report an experimental demonstration of a recent theoretical proposal to repurpose Grover's search algorithm to improve the ability to detect signals with unknown frequency within a large detection bandwidth. Our experiments were based on a system comprising a single superconducting qubit coupled to a single superconducting cavity, highlighting the modest hardware requirements for realizing the protocol. We found that Grover-based sensing was able to outperform the natural non-Grover baseline for our experimental platform for detection bandwidths $>$10~MHz, with an advantage that empirically grew superlinearly with the bandwidth beyond that break-even point. The use of the Grover-based protocol reduced the amount of signal that needed to be sensed to make an accurate detection decision by more than 10$\times$ for choices of larger detection bandwidth and higher desired detection accuracy. Our results provide a proof-of-principle validation that Grover-based quantum computational sensing can be realized in near-term hardware and provide a metrological advantage well beyond break-even in spite of the additional protocol complexity.
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All authors Mathieu Ouellet, Purnendu Sen, Xiangqin Wang, Saswata Roy, Xingrui Song, Vladimir Kremenetski, Sridhar Prabhu, Valla Fatemi, Peter L. McMahon

Soft Condensed Matter

Ergodicity, ergodicity breaking, and temporal evolution of probability density in non-equilibrium: new perspectives by multispeckle DLS

Hans Joachim Schöpe

Testing the ergodicity hypothesis through experimentation in real systems is of crucial importance as it challenges a fundamental assumption underlying a wide range of theoretical models of physical and complex systems. High-calibre experiments can demonstrate whether, when and how a real system explores all of its possible states, and serve as a crucial conduit between abstract theoretical frameworks and tangible real-world applications. This approach is intended to guarantee that our descriptions of complex systems remain both physically meaningful and technologically relevant, thereby facilitating a more nuanced and comprehensive understanding. The development of a novel light scattering experiment has enabled us the direct measurement of the full distribution of fluctuations in the particle concentration in colloidal model systems and thus the direct determination of the probability distribution. This, in turn, facilitates the experimental verification of the ergodic hypothesis and the quantification of ergodicity breaking as a function of metastability.
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Quantum Physics

Enantiomer-specific pumping of chiral molecules in high-$J$ rotational states

Fen Zou, Yan Gao and Peng Zhang

Enantiomer-specific state transfer (ESST) based on electric-dipole transitions has attracted considerable interest in the studies of manipulating molecules with electromagnetic fields. It also holds promise as a powerful tool for enantiomer detection and separation. To date, experimental demonstrations of ESST have focused mainly on molecules in the lowest rotational angular-momentum states, namely, $J=0$ and $J=1$. Realistic molecular samples, however, may contain appreciable populations in higher-$J$ rotational states, making it desirable to develop ESST schemes applicable to such states. Nevertheless, one cannot derive such schemes via a simple and straightforward extension of existing low-$J$ schemes, because higher-$J$ manifolds contain more magnetic sub-levels and involve more complicated networks of electric-dipole transitions. Here, we propose an ESST scheme for chiral molecules involving the $J=1$ and $J=2$ rotational states. Specifically, our scheme is based on enantiomer-specific pumping driven by three linearly polarized microwave fields and one laser beam. Under this scheme, one enantiomer is pumped into an enantiomer-specific dark state within a sub manifold with $J=1,2$, whereas the other enantiomer is dissipatively pumped out of this manifold. Our strategy can be extended to systems involving rotational states with even higher angular momenta.
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Mathematical Physics

GR-FM: Geometrically Regularized Flow Matching for SDF-Based Medical Image Segmentation

Yuxin Ai, Zhichang Guo, Fanghui Song et al. (+1 more)

Medical image segmentation remains challenging in terms of accurate boundary localization and complex-structure preservation, as target regions often exhibit weak boundaries, fine-grained structures, and irregular shapes, while high-quality images and precise annotations are usually limited. Existing generative segmentation approaches based on Flow Matching mainly learn velocity fields in the state space but lack explicit constraints on the spatial regularity and distance-field properties of the recovered representation. This limitation may lead to spatial oscillations, boundary displacement, and discontinuities in fine structures. To address these issues, we propose an image-conditioned Geometrically Regularized Flow Matching framework, termed GR-FM, which formulates segmentation as a continuous probability transport process from an initial distribution to a target implicit representation distribution. Instead of directly modeling binary masks, GR-FM adopts the SDF to describe the target structure, where each pixel is represented by its signed distance to the object boundary, resulting in a continuous geometric field. Flow Matching and ordinary differential equations are then employed to achieve deterministic and efficient distribution transport. The training objective further incorporates a biharmonic regularization term and an Eikonal constraint to enhance the spatial smoothness, structural consistency, and distance-field characteristics of the recovered representation. Moreover, we analyze the continuous transport process under geometric constraints and investigate the evolution of the zero level set. Experiments conducted on the MoNuSeg, GlaS, and DRIVE datasets demonstrate that GR-FM achieves competitive performance in both region overlap and boundary accuracy, reduces performance variation, and maintains stable segmentation results with only a small number of integration steps.
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All authors Yuxin Ai, Zhichang Guo, Fanghui Song, Dazhi Zhang

Superconductivity

Unconventional superconductivity in locally non-centrosymmetric CeNi$_2$As$_2$

Félix Morineau, Jan Knapp, Javier Landaeta et al. (+12 more)

Recent years have seen intense research on heavy fermion superconductivity, inspired by the discovery of multiple superconducting phases in UTe$_\text{2}$ and CeRh$_\text{2}$As$_\text{2}$. In the latter material, two superconducting phases observed under applied magnetic field oriented along the crystallographic $\textit{c}$ direction are associated with local inversion symmetry breaking. To advance understanding of these phenomena, it is highly desirable to find further examples of heavy fermion superconductivity in materials with locally non-centrosymmetric structure. We have succeeded in this quest, by growing single crystals of the CaBe$_\text{2}$Ge$_\text{2}$ isomorph of CeNi$_\text{2}$As$_\text{2}$. The resulting superconductivity brings more than we had foreseen. In addition to providing the opportunity to compare and contrast with that of CeRh$_\text{2}$As$_\text{2}$, the condensation occurs from an incoherent normal state quantitatively similar to that of UBe$_\text{13}$. Our findings therefore raise profound questions not just about superconductivity in the locally non-centrosymmetric structures, but about unconventional superconductivity itself.
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All authors Félix Morineau, Jan Knapp, Javier Landaeta, Thomas Lühmann, Lea Richter, Petra Knappova, Soumen Ash, Sushma Lakshmi Ravi Sankar, Konstantin Semeniuk, Elena Hassinger, Christoph Geibel, Manuel Brando, Daniel F. Agterberg, Andrew P. Mackenzie, Seunghyun Khim

Solar and Stellar Astrophysics

First results from PADRE/MeDDEA: X-rays from a flare and its CME

Muriel Zoë Stiefel, Säm Krucker, Olivier Limousin et al. (+22 more)

The MeDDEA hard X-ray spectrometer onboard NASAs PADRE CubeSat operates four flight-spare detectors from the Solar Orbiter/STIX instrument. This paper aims to evaluate the accuracy of the MeDDEA calibration and to demonstrate that MeDDEA data are ready for scientific exploitation. Using the first joint observations between MeDDEA and STIX, we investigate faint HXR emission associated with an escaping CME relative to the emission from the full flare. The first large flare observed by MeDDEA is analyzed, and the MeDDEA spectrum is compared with simultaneous observations from Fermi/GBM and ASO-S/HXI. From the Solar Orbiter viewpoint, the flare is highly limb-occulted allowing STIX to isolate high coronal emission associated with the CME while MeDDEA observed the full flare. We combined spectral fitting with HXR/EUV imaging from STIX, HXI, and AIA to investigate the locations and energetics of the flare- and CME-associated HXR sources. The MeDDEA spectral observations are in agreement with FERMI/GBM and ASO-S/HXI within 10 percent in the energy range of 18-30 keV. The CME-associated photon flux observed by STIX in the nonthermal range is faint at about 1 percent of the flare photon flux. The energy content of the thermal component associated with the CME, on the other hand, is found to be of the same order of magnitude as the thermal energy of the flare loop, at least for a filling factor of unity. Imaging information from STIX in combination with AIA reveals that the emission measured by STIX is located within the associated CME. We report that MeDDEA provides scientifically reliable spectral observations and is ready for scientific use.
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All authors Muriel Zoë Stiefel, Säm Krucker, Olivier Limousin, Niharika Godbole, Gwendoline Marc, Amir Caspi, Kyle Gregory, Ace Stratton, Diana Renaud, Aline Meuris, Laura A. Hayes, André Csillaghy, Pascal Saint-Hilaire, Juan Camilo Buitrago Casas, Christopher Smith, Savannah Sky Perez-Piel, Anton Tremsin, Elizabeth Warren, Bradley Pafchek, Eliad Peretz, Carlos Urdiales, Reynaldo Gonzalez, Chris M. Moeckel, Juan Carlos Martinez Oliveros, Steven Christe

Fluid Dynamics

A generalized, quasi-universal subgrid model for macroscopic moving contact line flows

Vyankatesh Manoj Mundhada and Manoj Kumar Tripathi

Predictions of moving contact line flows are challenging due to the stress singularity associated with the no-slip boundary condition on solid surfaces and the inherently multiscale nature of the phenomenon. Resolving the microscopic length scale renders the numerical simulations intractable for macroscopic flows due to extremely high computational costs. Affordable and predictive numerical solutions for macroscopic flows require a subgrid model, free of case-specific calibration, that mitigates the grid-dependence observed otherwise. We demonstrate a coupling between Cox's matched asymptotic relation and the empirical contact angle models to obtain a quasi-universal subgrid model. The coupling requires a one-time knowledge of the observation length scale or resolution of the experiments used to formulate the empirical models. The present model eliminates the need for prescribing phenomenological parameters such as the microscopic slip length and wall contact angle, allowing for the predictive simulations of such flows. We demonstrate the reduction in error due to grid-dependence by conducting axisymmetric simulations of droplet spreading for a wide range of Reynolds and Weber numbers for three different contact angle models in the advancing and receding contact line motion scenarios.
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Quantum Physics

Cyclotomic Cosets: Hidden Subgroup and Quantum Sieving Algorithm for Prime-Power Moduli

Mathias Boucher, Pierre-Alain Fouque and Yixin Shen

The Learning With Errors (LWE) problem is a fundamental assumption in post-quantum cryptography. Regev established a quantum reduction from LWE to the Dihedral Coset Problem (DCP). Later, Brakerski et al. introduced the Extrapolated Dihedral Coset Problem (EDCP), proving its equivalence to LWE. However, unlike DCP, EDCP no longer admits a coset structure. This limits the direct application of techniques for hidden subgroup problems. In this work, we introduce the Cyclotomic Coset Problem (CCP), a cyclotomic generalization of DCP that preserves an exact hidden-subgroup structure. Let $\zeta_p$ be a primitive $p$-th root of unity, let $\pi=\zeta_p-1$, and write $q=p^t$ and $L=t(p-1)$. We work over $R_q=\mathbb Z_q[\zeta_p] \cong \mathbb Z[\zeta_p]/(\pi^L)$, where the isomorphism follows from the total ramification identity $(p)=(\pi)^{p-1}$. We exploit the resulting $\pi$-adic ideal chain to construct a quantum sieve that successively reduces phase states modulo $\pi^{L},\pi^{L-1},\ldots,\pi$. For every fixed prime $p$ and modulus $q=p^t$, our algorithm solves the CCP in time and sample complexity $2^{O_p(\log n\log q)}$, using polynomial quantum space. The sieve also applies to uniform EDCP and Gaussian S|LWE>, yielding quasi-polynomial time algorithms for all the above problems when $q=\text{poly}(n)$. This extends the power-of-two EDCP sieve of Bai et al. (CRYPTO 2025) to a cyclotomic setting. However, we emphasize that our result does not, by itself, yield a quasi-polynomial-time algorithm for standard LWE, because the currently known reduction produces only a limited number of approximate CCP states.
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Quantum Physics

Simulation-Based Quantum System Inference with Neural Posterior Estimation

Hang Zou, Anton Frisk Kockum, Martin Rahm et al. (+1 more)

Models of quantum systems faithfully map system parameters to observations, but the inverse problem of parameter inference from measurement data presents a fundamental challenge: computationally intractable likelihoods due to an exponentially large Hilbert space. Here, we introduce simulation-based quantum system inference, a unified, likelihood-free framework that learns parameter posteriors directly from classical simulation data. The central idea is to pair polynomial-cost classical simulators, such as Pauli propagation and tensor networks, with normalizing flows or other neural density estimators for accurate, reusable inference. A single model, trained once, maps any new measurement record to its posterior in one forward pass—turning per-experiment inference into a fixed, up-front cost. We numerically demonstrate the framework's versatility across Pauli noise learning, quantum error mitigation, quantum state tomography, and Hamiltonian learning, with examples involving 81-qubit shallow circuits and 735-parameter inference. In each case, the approach yields accurate estimates of identifiable parameters, while posterior uncertainty provides additional diagnostics of non-identifiability and indicates where further characterization is needed. Our framework reduces data-acquisition requirements in quantum experiments and accelerates parameter inference, providing a practical route to characterizing and improving large-scale quantum systems.
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All authors Hang Zou, Anton Frisk Kockum, Martin Rahm, Simon Olsson

Cosmology and Nongalactic Astrophysics

Localized Enhancements of the Primordial Power Spectrum and the Abundance of Early Bright Galaxies

Shaghayegh Yavari, Hamed Kameli and Shant Baghram

Recent observations of bright galaxies at high redshifts by the James Webb Space Telescope have motivated renewed interest in cosmological mechanisms that can enhance the abundance of early massive dark matter halos. We study a phenomenological modification of the primordial curvature power spectrum in the form of a localized Gaussian enhancement. The modified spectrum is propagated to the linear matter power spectrum, the smoothed density variance, and the Sheth-Tormen halo mass function. We show that a bump centered at small scales can selectively enhance the abundance of rare high-redshift halos and, through a fixed semi-analytic mapping between halo mass and ultraviolet luminosity, shift the bright end of the UV luminosity function toward JWST measurements. The enhancement becomes more pronounced at higher redshift due to the exponential sensitivity of the rare-halo tail to the variance. We emphasize that the effect is limited by small-scale power-spectrum constraints, particularly Lyman-$\alpha$ forest data, and should be interpreted as a partial cosmological contribution rather than a complete solution to the JWST galaxy tension.
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Nuclear Experiment

Toward FAIR and AI-Ready Data: An Assessment of the GlueX Experiment's Data Ecosystem at Jefferson Lab

Anil Panta, Brad Sawatzky, Casey Morean et al. (+2 more)

Department of Energy programs increasingly require that experimental data be not only preserved but usable by artificial intelligence (AI) systems, yet no accepted standard defines when a dataset is AI-ready. We argue that data must be FAIR (Findable, Accessible, Interoperable, Reusable) before they can be AI-ready, and that AI readiness is a distinct property requiring its own assessment. Using the GlueX experiment in Hall D at Jefferson Lab as a pilot, we map the data ecosystem, assess it against FAIR, and define an AI-readiness framework whose criteria are backed by deterministic metrics. We also evaluate existing validation software to separate what can be assessed with off-the-shelf tools from what requires domain-specific development. The assessment yields a set of findings, each paired with a recommendation, some of which are already in production or prototyped and others planned as next steps.
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All authors Anil Panta, Brad Sawatzky, Casey Morean, Dmitry Romanov, Douglas Higinbotham