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Physics

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Wednesday 7 October

Mathematical Physics · Cross-listed from math.OA

The Differential Structure of Generators of KMS-Symmetric Quantum Markov Semigroups

Matthijs Vernooij and Melchior Wirth

A KMS-symmetric quantum Markov semigroup is completely determined by the quadratic form in induces on the GNS Hilbert space. The quadratic forms that arise in this way are called quantum Dirichlet forms. In this article we give a complete description of bounded quantum Dirichlet forms in terms of derivations. In particular, we exhibit an explicit characterization of the bounded quantum Dirichlet forms on type I factors. We also show that any unbounded quantum Dirichlet form can be represented in terms of derivations. The key technical insight is that the modular group always restricts to a strongly continuous group on the domain of a quantum Dirichlet form such that the square root of the analytic generator is accretive with respect to the form norm.
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High Energy Astrophysical Phenomena

Gamma-rays from black hole coronae: disentangling the leptonic and hadronic contributions

Sébastien Le Bihan, Daniel Grošelj and Martin Lemoine

IceCube detections of TeV neutrinos from nearby Seyfert galaxies imply, if confirmed, that the accompanying gamma rays are substantially reprocessed down to the MeV range by electromagnetic cascades, which places multi-messenger constraints on neutrino emission models. However, gamma rays can also be produced by the primary nonthermal electrons of the X-ray corona, as recent radiative kinetic simulations of magnetized turbulence have shown. To disentangle the leptonic and hadronic contributions, we self-consistently combine results from these simulations with predictions for hadronically induced electromagnetic cascades. Focusing on NGC 4151, we find that the leptonic channel dominates the MeV band, and remains comparable to the hadronic cascade up to $\lesssim$0.1 GeV, when the nonthermal electron tail carries $\gtrsim5\%$ of the electron energy. The leptonic contribution may be detectable in soft gamma rays by the upcoming Compton Spectrometer and Imager (COSI) mission, whereas our predicted hadronic component falls below its sensitivity. We also find that the same nonthermal electron population can account for both the $0.1-1$ MeV excess of the cosmic X-ray background, generally attributed to AGNs, and the MeV tail of Cygnus~X-1 in the hard state, lending observational support to our model. Our results offer a refined view of multi-messenger signals from black-hole coronae, grounded in their nonthermal kinetic physics.
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Plasma Physics

Real-time Tokamak Equilibrium Reconstruction Under Limited Experimental Data via Physics-Grounded Synthetic Pre-training

Mingdong He, Qixian Hu, Tengfei Xu et al. (+2 more)

Real-time equilibrium reconstruction is essential for tokamak plasma control. Data-driven surrogates are usually trained on high-quality labeled experimental data, but producing a large amount of labeled data sufficient for surrogate learning requires many expensive discharge shots, and few exist at the start of a new campaign or the operation of a new device. To reduce this cost, we propose to pre-train on simulated equilibria, generated at low cost by physics-based simulation, then fine-tune on limited real data. We evaluate under three settings with increasing difficulties, i.e., in-distribution, out-of-distribution (shape), and cross-campaign (temporal) splits, which mirror how reconstruction is actually deployed. Experimental results validate that synthetic pre-training is highly effective when few real labels are available: fine-tuning on only 1% of the full available real dataset cuts the per-sample normalized root-mean-square error (nRMSE) of the reconstructed poloidal flux by roughly 58% under out-of-distribution shapes and 64% under cross-campaign extrapolation, compared to a model trained from scratch on the same amount of real data. These realistic evaluations show that synthetic pre-training improves equilibrium reconstruction accuracy in the data-scarce regime that real tokamak campaigns face.
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All authors Mingdong He, Qixian Hu, Tengfei Xu, Tailin Wu, Zheng Xiong

Quantum Physics

Exploring topology via momentum-selective tomography

Sainan Huai, Ling Lin, Kunliang Bu et al. (+8 more)

Identifying and measuring topological invariants remains a fundamental challenge due to the non-local nature of momentum eigenstates in real space. Established approaches based on Bloch oscillations, quantum walks, charge pumping and quench dynamics, typically fail to provide direct momentum-dependent geometric information of each Bloch state. Here, we propose a novel framework for implementing direct band-topology tomography via momentum-selective measurements, and experimentally demonstrate it on a superconducting processor featuring a highly connected coupling architecture. Utilizing a “star-like" geometry in which an auxiliary probe couples to a one-dimensional topological chain with spatially modulated coupling strengths, we selectively address the desired momentum states of the chain. This approach enables the direct and robust extraction of the winding phase that contributes to the associated topological invariant. Leveraging non-local couplers bridged by long tantalum airbridges, we realize an extended Su-Schrieffer-Heeger (SSH) model and map its full topological phase diagram. Through a nested Fourier analysis over time and space, we directly extract the winding phase across Brillouin zone and resolve quantized winding numbers of $\nu=\{0,\pm1,2\}$ characterized by phase winding $\{0, \pm 2\pi,4\pi\}$. Our work establishes a versatile tool for probing topological characteristics and opens a new avenue for robust quantum computing architectures based on topological protection.
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All authors Sainan Huai, Ling Lin, Kunliang Bu, Tianqi Cai, Zhiwen Zong, Xiaopei Yang, Yuan Li, Yulei Ye, Zhenxing Zhang, Shengyu Zhang, Chaohong Lee

Atmospheric and Oceanic Physics · Cross-listed from stat.AP

Statistical Oceanography of Profiling Floats and Surface Drifters

Mikael Kuusela, Sofia C. Olhede and Adam M. Sykulski

The Global Ocean Observing System is key to understanding oceanic variability and climate change. The ocean is vast and often sparsely and irregularly sampled in time and space by various instruments and systems. Statistical models, especially spatio-temporal ones, are useful for enabling inferences, forecasts and decisions from sparse oceanic observations. This article focuses on the statistical treatment of two types of in situ observations in the Global Ocean Observing System: from profiling floats and surface drifters, focusing on the Argo and Global Drifter Programs. We describe the spatio-temporal models that have been developed in recent years for these data, to give a picture of the statistical challenges faced in modern physical oceanography. We will discuss in detail two types of reference frames when modeling such data: Eulerian and Lagrangian, the former of which is more appropriate for profiling floats and the latter for surface drifters.
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Physics and Society · Cross-listed from cs.AI

Shared and structured inputs undermine collective random choice by reasoning AI agents

Takahiro Ezaki, Naoto Imura and Katsuhiro Nishinari

Random selection is widely used in resource allocation and auditing, making reliable implementation essential for AI-agent systems. Behavioural tests across six reasoning models uncovered threshold and divisibility rules used in identifier-based choices. For threshold-following GPT-6 Sol and Gemini 3.8 Flash, single-agent measurements prospectively predicted correlated participation under shared identifiers and biased participation under distinct identifiers with common timestamp bits. Changing dates, formats and identifier labels revealed when these predictions held. Explicit instructions to randomize independently reduced but did not eliminate shared-input correlation. To test implications for oversight, we asked four models to select customer requests randomly for human review. GPT-6 Sol approached the target rate while selecting predictably from identifiers; the others rarely selected requests. All four closely followed supplied random draws. These findings expose collective and audit vulnerabilities that selection rates alone miss, making input-dependent bias, correlation and predictability central targets for agent evaluation.
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Quantum Physics

Geodesic-based optimal control for leakage suppression in superconducting qubits

Adonai Hilário da Silva, Tanmoy Pandit and Francesco Cosco

Superconducting qubits are often based on the first two energy levels of a physical anharmonic LC oscillator. Since the anharmonicity of such systems is usually much lower than the involved energy gaps, population can easily leak to higher energy states. This is what characterizes leakage errors, and it can have multiple sources: from coherent error induced by the control platform to incoherent thermal dissipation. In this work, we adapt an optimal control method based on sub-Riemannian geodesic search in the unitary group for a system consisting of two superconducting qubits with leakage levels. We use the $R_x(\pi/2)$ rotation for single-qubit operation analysis, and the $i$SWAP operation for two-qubit analysis. For the former, we find considerable performance improvement in average gate fidelity as well as in the reduction of leakage errors when comparing the obtained optimal pulses with Gaussian and DRAG pulses, especially for short duration pulses. For the $i$SWAP gate, although leakage error remains roughly the same, we manage to obtain considerably higher fidelities with the cost of requiring a slightly longer time evolution.
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Materials Science

Vanishing Altermagnetism and Emergent Ferromagnetism at the Two-Dimensional Limit of CrSb

Yunlong Liu, Zixuan Wu, Qinxi Liu et al. (+8 more)

Altermagnets offer a promising route to spintronic devices by combining spin-split electronic states with zero net magnetization, but how reduced dimensionality reshapes their magnetic order remains poorly understood. Here, we grow bilayer-thickness CrSb (0001) films directly on SrTiO3(001) substrates by molecular beam epitaxy and uncover an unexpected thickness-dependent magnetic transition. The one-bilayer films exhibit room-temperature ferromagnetism with strong perpendicular magnetic anisotropy, whereas ferromagnetism vanishes in two-bilayer films, contrasting sharply with the altermagnetic ground state of bulk CrSb. Density functional theory calculations reveal that the exposed Cr surface induces orbital rearrangement that strengthens intralayer ferromagnetic exchange while suppressing competing interlayer antiferromagnetic coupling, driving the dimensional crossover from altermagnetism to ferromagnetism. These findings establish dimensionality and surface termination as powerful controls of magnetic order and provide a platform for engineering ultrathin magnetic states for spintronic applications.
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All authors Yunlong Liu, Zixuan Wu, Qinxi Liu, Yupeng Zhi, Mingqiang Ren, Xue Jiang, Canli Song, Ding Zhang, Xucun Ma, Huimin Zhang, Jijun Zhao

Geophysics

Real-world application of deep learning in large-scale seismic interference attenuation: A case study in the Camie field of Angola

Jing Sun and Song Hou

In marine seismic acquisition, seismic interference (SI) occurs when energy from nearby external seismic source(s) is captured. It typically appears as coherent noise with linear or non-linear movement and varying amplitudes across different sail lines. SI is commonly observed and poses a challenge for seismic data processing. We present a case history of a previously proposed deep neural network (DNN)-based workflow applied for SI attenuation across a marine seismic block in the Camie Field of Angola. This field survey covers over 345 km2 and is marked by the challenge of multiple SI types. The employed DNN-based workflow performs SI attenuation in the common shot domain based on a supervised learning framework: a small subset of the SI-contaminated data was first processed by a conventional geophysical algorithm to obtain an estimate of the SI noise, which was then manually blended with the SI-free common shot gathers from the same survey to generate the training pairs. To ensure signal fidelity, several techniques were applied to improve the DNN's performance. A key highlight of this case history is its scale: this represents a real-world, large-scale processing project and we present a comprehensive comparison of the DNN-based workflow with the conventional geophysical algorithm across the entire survey block, focusing on both processing quality and processing time. The results demonstrate the outstanding performance of the employed DNN-based workflow, which achieved higher SI removal accuracy, with less signal leakage and more complete SI removal. The promising results of this application also open up possibilities for integrating deep learning into other seismic denoising tasks. In addition, we discuss the limitations of this case history, aiming to provide insights for future research and applications in the field.
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Statistical Mechanics

Correspondence between Asymptotic Quantum Many-Body Scars in Closed Systems and Diffusive Nambu-Goldstone Modes in Open Systems

Masaya Kunimi, Taiki Haga and Masaya Nakagawa

Hydrodynamic relaxation in open quantum many-body systems can be understood in terms of diffusive Nambu–Goldstone (NG) modes associated with strong-to-weak spontaneous symmetry breaking (SWSSB). Here, we find a common structure underlying weak ergodicity breaking in closed quantum systems and diffusive hydrodynamics in open quantum systems. We establish a spectral correspondence between the parent Hamiltonian of rainbow quantum many-body scar (RQMBS) states in closed systems and the effective Lindbladian of strongly dissipative open systems with strong $U(1)$ symmetry and local charge-dephasing Lindblad operators. For broad classes of spin, fermionic, and bosonic systems, we construct asymptotic RQMBS (ARQMBS) states. Within the enlarged scar subspace, the parent Hamiltonian admits a local Rokhsar–Kivelson-type frustration-free decomposition. A single-mode variational construction gives an $O(k^2)$ upper bound on its lowest excitation energy and yields states satisfying the defining ARQMBS criteria: orthogonality, vanishing energy variance, and characteristic entanglement scaling. Under vectorization, RQMBS states are mapped to maximally mixed infinite-temperature states in fixed-charge sectors, which exhibit long-range SWSSB order under finite-density conditions. Assuming uniformly bounded positive transition rates, the effective Lindbladian has the same local projectors as the parent Hamiltonian but with positive transition-dependent weights, yielding two-sided spectral bounds and the same system-size scaling of their gaps. For uniform rates, the two operators are proportional to each other and their eigenmodes coincide. Therefore, an exact quadratic parent-Hamiltonian branch maps directly to a diffusive NG mode. Our results connect different mechanisms of slow relaxation in closed and open quantum many-body systems.
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Strongly Correlated Electrons

Unified treatment of local dynamical interactions in correlated metals using Eliashberg theory

Jan Berges, Samuel Poncé, Mario Caserta et al. (+2 more)

First-principles studies of materials with strong electronic correlations introduce additional theoretical complexities and computational costs, even more so if lattice degrees of freedom also play a role. To address these challenges, we show how direct and phonon-mediated electron-electron interactions can be treated consistently. The key observation is that the GW and Fan-Migdal self-energies are topologically the same diagram, so that they can be unified using a single effective interaction, which is the sum of the two interactions. The Dyson equation for the electron Green function then yields normal-state Eliashberg equations, which can be viewed as a subset of the Hedin-Baym equations for coupled electrons and phonons [Phys. Rev. X 13, 031026 (2023)]. We solve these dynamical equations in a local approximation to calculate from first principles the temperature-dependent quasiparticle spectrum, with close attention to the low-energy window determining transport. We apply this extended dynamical Hubbard approach to the correlated metal Sr$_2$RuO$_4$, which has long served as a benchmark system for advanced electronic-structure methods. The resulting renormalization of quasiparticle bands is in qualitative agreement with experiments and results from dynamical mean-field theory. However, here the low-energy linewidth and associated resistivity within the Green-Kubo formalism in the bubble approximation are underestimated, suggesting the need for vertex corrections. This work highlights how simple dynamical formulations can provide an extensible framework for studying correlated materials, which treats electronic and vibrational excitations on equal footing.
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All authors Jan Berges, Samuel Poncé, Mario Caserta, Nicola Marzari, Tommaso Chiarotti

Soft Condensed Matter

Resolving the Effects of the Mixing Process on Hierarchical Structures in Polymer Nanocomposites by Bayesian Ultra-Small-Angle X-ray Scattering Analysis

Yui Hayashi, Kazuki Mita, Shigeo Kuwamoto et al. (+1 more)

Bayesian inference was combined with Unified Fit to resolve the effects of the mixing history on polymer nanocomposites whose ultra-small-angle X-ray scattering profiles are nearly indistinguishable by conventional analysis. Bayesian Unified Fit was applied to comparing the aggregate size, internal mass-fractal structure, and surface roughness for three carbon black–filled ethylene propylene diene copolymer rubber samples prepared by different mixing processes. Whereas conventional Unified Fit reported essentially identical carbon-black dispersions, the radius of gyration, mass fractal dimension, and surface fractal dimension for the three samples all followed the same ordering, which coincides with the reported ordering of the tensile strength and elongation at break and suggests that the inferred aggregate hierarchy is physically meaningful for the macroscopic mechanical response. These results identify the aggregate size as a candidate structural descriptor of rubber reinforcement and provide an uncertainty-aware basis for examining processing–structure–property relationships in polymer nanocomposites.
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All authors Yui Hayashi, Kazuki Mita, Shigeo Kuwamoto, Masato Okada

Quantum Physics

Q-PhotoMarket: A Design Space Exploration Framework for Photonic Hybrid Quantum Neural Networks in Financial Market Prediction

Alberto Marchisio, Hanzalah Mohamed Siraj, Muhammad Kashif et al. (+2 more)

Photonic quantum computing has recently emerged as a promising platform for hybrid quantum machine learning due to its native realization of linear-optical circuits and the computational complexity of boson sampling. However, despite growing interest in quantum methods for finance, the influence of photonic circuit design choices on predictive performance remains largely unexplored. Existing studies typically evaluate a single architecture, leaving the broader photonic design space unexamined. In this work, we present Q-PhotoMarket, a systematic design space exploration (DSE) framework for photonic hybrid quantum neural networks (HQNNs) applied to financial market prediction. We explore over 5,000 valid photonic configurations spanning input photon states, circuit architectures, entangling models, and measurement strategies across their compatible computation spaces, for U.S., Indian, and cryptocurrency markets. To improve search efficiency, the exhaustive exploration is complemented with Bayesian optimization. We further incorporate threshold calibration and prediction-collapse diagnostics to enable reliable evaluation under increasingly imbalanced return thresholds. Experimental results show that systematic exploration of more than 5,000 photonic HQNN configurations reveals consistent architectural patterns across financial markets, identifies robust high-performing designs, and demonstrates competitive performance relative to classical machine learning baselines.
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All authors Alberto Marchisio, Hanzalah Mohamed Siraj, Muhammad Kashif, Nouhaila Innan, Muhammad Shafique

Quantum Physics

Quantum anomaly detection in real scarce data

Emanuele Casciaro, Fabio Mascherpa, Alfonso Amendola et al. (+1 more)

Anomaly detection on small and unbalanced datasets remains very challenging in machine learning, although this scenario is common in several domains, including healthcare, cybersecurity, finance, and energy. Data augmentation and generative AI may mitigate training-data scarcity, but they often fall short because anomalies are, by definition, unpredictable, rare, and highly diverse events compared to high-probability normal data. Overfitting to pseudo-anomalies, model collapse, high-dimensional data, uninterpretable black-box models, and validation challenges are typical issues limiting their practical applicability. In this context, quantum machine learning may provide a promising and more sustainable avenue because it can enable more interpretable models with far fewer trainable parameters and smaller datasets, implementable on energy-efficient quantum hardware. Here, we propose a novel two-step hybrid classical–quantum architecture for sequential data and test it on a realistic scenario in the global energy-transition domain, i.e., automated anomaly detection in large-scale photovoltaic plants. The achieved generalization capability and competitive prediction accuracy may pave the way for new hybrid learning models able to exploit the continuously increasing power of cloud-available and more sustainable quantum accelerators integrated with more traditional energy-hungry High Performance Computing resources.
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All authors Emanuele Casciaro, Fabio Mascherpa, Alfonso Amendola, Filippo Caruso

Solar and Stellar Astrophysics

A Novel Approach to Identify Unseen Companions: An In-Depth study of GDR3 220_28

T. B. Cysil, Blesson Mathew, B. Shridharan et al. (+6 more)

Emission lines in the spectrum and the excess seen in the spectral energy distribution (SED) at infrared (IR) wavelengths serve as crucial indicators of accretion activity and the presence of gas and dust in the circumstellar environment of a young star. As accretion ceases over several million years, the H$\alpha$ emission diminishes. However, IR excess combined with negligible H$\alpha$ emission could also extend to indicate certain close binary systems, where a circumbinary disk contributes to the observed excess. Additionally, in unresolved binaries, companion stars can contribute to the photometry, leading to inaccuracies in parameter measurements and skewed positions in the color-magnitude diagram (CMD). We identify a photometrically peculiar object from a survey of the Cepheus star-forming regions (SFRs), Gaia DR3 2205212960562531328, exhibiting a shift from its expected position in the CMD, as indicated by the Gaia optical photometry. This peculiarity drives our research, prompting an investigation through an approach that combines astrometric accuracy, photometric modeling and spectroscopic studies. The Gaia XP spectrum of the source shows a systematic blue excess, indicating an additional hotter unresolved component. Two-component SED modelling yields a companion with $T_{\rm eff}\sim27000$ K and $\log g\ge4.5$, consistent with sdB stars. Further CMD and spectroscopic analyses support a binary system consisting of an A0-type PMS star with an sdB companion. In addition, ZTF photometry shows tentative evidence for a periodicity of 0.498 days. This study paves the way for a systematic search of similar binary systems that would otherwise remain unidentified.
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All authors T. B. Cysil, Blesson Mathew, B. Shridharan, S. Muneer, Pramod Kumar S, S. Nidhi, Sreeja S Kartha, Suman Bhattacharyya, T. Robin

Astrophysics of Galaxies

Registering Gaia positions on VLBI images: constraining opacity-driven core shift in B 1038+528 / B 1038+529

M. H. Xu and Y. Y. Kovalev

Because of the complex and time-variable radio structure of active galactic nuclei (AGNs), absolute astrometric positions cannot generally be registered unambiguously with specific features in VLBI images. We aim to register Gaia optical centroids on VLBI images with about 0.1 mas accuracy and to locate the optical emission relative to the radio core in the quasar pair B 1038+528 and B 1038+529, in which the opacity-driven core shift was first discovered. We combine the relative position of the pair from phase-referenced VLBI at four epochs between 1981 and 1995, their Gaia optical positions, and the nearly orthogonal radio-jet directions. Assuming that each Gaia–core displacement lies along the local jet axis, we register the Gaia centroids relative to the radio cores with about 0.1 mas accuracy without using absolute VLBI positions. The Gaia centroids lie upstream of the 8.4-GHz radio cores, by 293 {\pm} 93 {\mu}as in B 1038+529 and 169 {\pm} 96 {\mu}as in B 1038+528. The latter agrees with the 260 {\mu}as 8.4-GHz core shift implied by the 2.3–8.4 GHz shift measured for this quasar four decades ago. The absolute astrometric position of B 1038+528 with VLBI lies about 0.6 mas downstream of the core, and its geodetic position time series drifts along the jet by more than 1 mas, showing that the 0.8–1.6 mas Gaia–VLBI offsets of the pair are dominated by source structure rather than by core shift. Gaia positions can be registered on VLBI images with an accuracy set by the astrometry uncertainties. If the Gaia centroids mark the jet base, the measured separations are absolute 8.4-GHz core shifts, corresponding to projected distances of about 1.2 pc and about 2.5 pc from the jet base; a contribution from an optical jet emission would make them lower limits. The method is applicable to AGNs with Gaia detection and phase-referenced VLBI astrometry.
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High Energy Physics (Experiment)

Observation of the electromagnetic Dalitz transition $J/\psi\to e^+ e^- \eta_c$

BESIII Collaboration: M. Ablikim, M. N. Achasov, P. Adlarson et al. (+766 more)

Using $(10.087\pm0.044)\times10^9$ $J/\psi$ events collected with the BESIII detector at the $e^+e^-$ BEPCII collider, we present the first observation of the electromagnetic Dalitz decay $J/\psi\to e^+ e^- \eta_c$. The relative branching fraction $R \equiv \frac{\Gamma(J/\psi\to e^+e^-\eta_c)}{\Gamma(J/\psi\to \gamma\eta_c)}$ is determined to be $(0.65\pm0.02_{\rm stat.}\pm0.07_{\rm sys.})\%$, where the first uncertainty is statistical and the second systematic. The $q^2$-dependent form factors are also extracted, and no significant deviation from the theoretical prediction is seen.
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All authors BESIII Collaboration: M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, C. S. Akondi, R. Aliberti, A. Amoroso, Q. An, Y. H. An, M. S. Anderson, Y. Bai, O. Bakina, H. R. Bao, X. L. Bao, M. Barbagiovanni, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. B. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann, D. Cabiati, H. Cai, M. H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, X. Y. Chai, J. F. Chang, T. T. Chang, G. R. Che, Y. Z. Che, C. H. Chen, Chao Chen, G. Chen, H. S. Chen, H. Y. Chen, M. L. Chen, S. J. Chen, S. M. Chen, T. Chen, W. Chen, X. R. Chen, X. T. Chen, X. Y. Chen, Y. B. Chen, Y. Q. Chen, Z. K. Chen, J. Cheng, L. N. Cheng, S. K. Choi, X. Chu, G. Cibinetto, F. Cossio, J. Cottee-Meldrum, H. L. Dai, J. P. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, C. Q. Deng, Z. Y. Deng, A. Denig, I. Denisenko, M. Destefanis, F. De Mori, E. Di Fiore, X. X. Ding, Y. Ding, Y. X. Ding, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, Z. J. Dong, M. C. Du, S. X. Du, Shaoxu Du, X. L. Du, Y. Q. Du, Y. Y. Duan, Z. H. Duan, P. Egorov, G. F. Fan, J. J. Fan, Y. H. Fan, J. Fang, Jin Fang, S. S. Fang, W. X. Fang, Y. Q. Fang, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, Q. X. Feng, Y. T. Feng, M. Fritsch, C. D. Fu, J. L. Fu, Y. W. Fu, H. Gao, Xu Gao, Y. Gao, Y. N. Gao, Y. Y. Gao, Yunong Gao, Z. Gao, S. Garbolino, I. Garzia, L. Ge, P. T. Ge, Z. W. Ge, C. Geng, A. Gilman, K. Goetzen, J. Gollub, J. B. Gong, J. D. Gong, L. Gong, W. X. Gong, W. Gradl, M. Greco, M. D. Gu, M. H. Gu, C. Y. Guan, A. Q. Guo, H. Guo, J. N. Guo, L. B. Guo, M. J. Guo, R. P. Guo, X. Guo, Y. P. Guo, Z. Guo, A. Guskov, J. Gutierrez, J. Y. Han, T. T. Han, X. Han, F. Hanisch, K. D. Hao, X. Q. Hao, F. A. Harris, C. Z. He, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, P. C. Hong, G. Y. Hou, X. T. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, Q. P. Hu, S. L. Hu, T. Hu, Y. Hu, Y. X. Hu, Z. M. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, P. Huang, X. T. Huang, Y. P. Huang, Y. S. Huang, T. Hussain, N. Hüsken, N. in der Wiesche, J. Jackson, Q. Ji, Q. P. Ji, W. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, L. K. Jia, X. Q. Jia, D. Jiang, S. J. Jiang, X. S. Jiang, Y. Jiang, J. B. Jiao, J. K. Jiao, Z. Jiao, L. C. L. Jin, S. Jin, Y. Jin, M. Q. Jing, X. M. Jing, T. Johansson, S. Kabana, X. L. Kang, X. S. Kang, B. C. Ke, V. Khachatryan, A. Khoukaz, O. B. Kolcu, B. Kopf, L. Kröger, L. Krümmel, Y. Y. Kuang, X. Kui, N. Kumar, A. Kupsc, W. Kühn, Q. Lan, W. N. Lan, T. T. Lei, M. Lellmann, T. Lenz, C. Li, C. H. Li, C. K. Li, Chunkai Li, Cong Li, D. M. Li, F. Li, G. Li, H. B. Li, H. J. Li, H. L. Li, H. N. Li, H. P. Li, Hui Li, J. N. Li, J. S. Li, J. W. Li, K. Li, K. L. Li, L. J. Li, L. K. Li, Lei Li, M. H. Li, M. R. Li, M. T. Li, P. L. Li, P. R. Li, Q. M. Li, Q. X. Li, R. Li, S. Li, S. X. Li, S. Y. Li, Shanshan Li, T. Li, T. Y. Li, W. D. Li, W. G. Li, X. Li, X. H. Li, X. K. Li, X. L. Li, X. Y. Li, X. Z. Li, Y. Li, Y. H. Li, Y. B. Li, Y. C. Li, Y. G. Li, Y. P. Li, Z. H. Li, Z. J. Li, Z. L. Li, Z. X. Li, Z. Y. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, Z. Z. Liang, G. R. Liao, L. B. Liao, M. H. Liao, Y. P. Liao, J. Libby, A. Limphirat, C. C. Lin, C. X. Lin, D. X. Lin, T. Lin, B. J. Liu, B. X. Liu, C. Liu, C. X. Liu, F. Liu, F. H. Liu, Feng Liu, G. M. Liu, H. Liu, H. B. Liu, H. M. Liu, Huihui Liu, J. B. Liu, J. J. Liu, K. Liu, K. Y. Liu, Ke Liu, Kun Liu, L. Liu, L. C. Liu, Lu Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. M. Liu, W. T. Liu, X. Liu, X. K. Liu, X. L. Liu, X. P. Liu, X. T. Liu, X. Y. Liu, Y. Liu, Y. B. Liu, Yi Liu, Z. A. Liu, Z. D. Liu, Z. L. Liu, Z. Q. Liu, Z. X. Liu, Z. Y. Liu, X. C. Lou, H. J. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. H. Lu, Y. P. Lu, Z. H. Lu, C. L. Luo, J. R. Luo, J. S. Luo, M. X. Luo, T. Luo, X. L. Luo, Z. Y. Lv, X. R. Lyu, Y. F. Lyu, Y. H. Lyu, F. C. Ma, H. L. Ma, Heng Ma, J. L. Ma, L. L. Ma, L. R. Ma, Q. M. Ma, R. Q. Ma, R. Y. Ma, T. Ma, X. T. Ma, X. Y. Ma, F. E. Maas, I. MacKay, M. Maggiora, S. Maity, S. Malde, L. M. Mansur, Y. J. Mao, Z. P. Mao, S. Marcello, A. Marshall, F. M. Melendi, Y. H. Meng, Z. X. Meng, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, B. Moses, N. Yu. Muchnoi, J. Muskalla, Y. Nefedov, F. Nerling, H. Neuwirth, Z. Ning, S. Nisar, Q. L. Niu, W. D. Niu, Y. Niu, C. Normand, S. L. Olsen, Q. Ouyang, I. V. Ovtin, S. Pacetti, Y. Pan, A. Pathak, Y. P. Pei, M. Pelizaeus, G. L. Peng, H. P. Peng, X. J. Peng, Y. Y. Peng, K. Peters, K. Petridis, J. L. Ping, R. G. Ping, S. Plura, V. Prasad, L. Pöpping, F. Z. Qi, H. R. Qi, S. Qian, W. B. Qian, C. F. Qiao, J. H. Qiao, J. J. Qin, J. L. Qin, L. Q. Qin, L. Y. Qin, P. B. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, Z. H. Qu, J. Rademacker, K. Ravindran, C. F. Redmer, A. Rivetti, M. Rolo, G. Rong, S. S. Rong, F. Rosini, Ch. Rosner, M. Q. Ruan, W. R. Ruangyoo, N. Salone, A. Sarantsev, Y. Schelhaas, M. Schernau, K. Schoenning, M. Scodeggio, W. Shan, X. Y. Shan, Z. J. Shang, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, W. H. Shen, X. Y. Shen, B. A. Shi, Ch. Y. Shi, H. Shi, J. L. Shi, J. Y. Shi, M. H. Shi, S. Y. Shi, X. Shi, H. L. Song, J. J. Song, M. H. Song, T. Z. Song, W. M. Song, Y. X. Song, Zirong Song, S. Sosio, S. Spataro, S. Stansilaus, F. Stieler, M. Stolte, S. S Su, G. B. Sun, G. X. Sun, H. Sun, H. K. Sun, J. F. Sun, K. Sun, L. Sun, R. Sun, S. S. Sun, T. Sun, W. Y. Sun, Y. C. Sun, Y. H. Sun, Y. J. Sun, Y. Z. Sun, Z. Q. Sun, Z. T. Sun, H. Tabaharizato, N. T. Tagsinsit, C. J. Tang, G. Y. Tang, J. Tang, J. J. Tang, L. F. Tang, Y. A. Tang, Z. H. Tang, L. Y. Tao, M. Tat, J. X. Teng, J. Y. Tian, W. H. Tian, Y. Tian, Z. F. Tian, K. Yu. Todyshev, I. Uman, E. van der Smagt, B. Wang, Bin Wang, Bo Wang, C. Wang, Chao Wang, Cong Wang, D. Y. Wang, F. K. Wang, H. J. Wang, H. R. Wang, J. Wang, J. J. Wang, J. P. Wang, K. Wang, L. L. Wang, L. W. Wang, M. Wang, Mi Wang, N. Y. Wang, P. Wang, S. Wang, Shun Wang, T. Wang, W. Wang, W. P. Wang, X. F. Wang, X. L. Wang, X. N. Wang, Xin Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. H. Wang, Y. J. Wang, Y. L. Wang, Y. N. Wang, Yanning Wang, Yaqian Wang, Yi Wang, Yuan Wang, Z. Wang, Z. L. Wang, Z. Q. Wang, Z. Y. Wang, Zhi Wang, Ziyi Wang, D. Wei, D. H. Wei, D. J. Wei, H. R. Wei, F. Weidner, H. R. Wen, S. P. Wen, U. Wiedner, G. Wilkinson, M. Wolke, J. F. Wu, L. H. Wu, L. J. Wu, Lianjie Wu, S. G. Wu, S. M. Wu, X. W. Wu, Z. Wu, H. L. Xia, L. Xia, B. H. Xiang, D. Xiao, G. Y. Xiao, H. Xiao, Y. L. Xiao, Z. J. Xiao, C. Xie, K. J. Xie, Y. Xie, Y. G. Xie, Y. H. Xie, Z. P. Xie, T. Y. Xing, D. B. Xiong, G. F. Xu, H. Y. Xu, Q. J. Xu, Q. N. Xu, T. D. Xu, X. P. Xu, Y. Xu, Y. C. Xu, Z. S. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, W. H. Yan, W. P. Yan, X. Q. Yan, Y. Y. Yan, H. J. Yang, H. L. Yang, H. X. Yang, J. H. Yang, R. J. Yang, X. Y. Yang, Y. Yang, Y. G. Yang, Y. H. Yang, Y. M. Yang, Y. Q. Yang, Y. Z. Yang, Youhua Yang, Z. Y. Yang, W. J. Yao, Z. P. Yao, M. Ye, M. H. Ye, Z. J. Ye, K. Yi, Junhao Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, L. W. Yu, T. Yu, X. D. Yu, Y. C. Yu, Yongchao Yu, C. Z. Yuan, H. Yuan, J. Yuan, Jie Yuan, L. Yuan, M. K. Yuan, S. H. Yuan, Y. Yuan, C. X. Yue, Ying Yue, A. A. Zafar, F. R. Zeng, S. H. Zeng, X. Zeng, Y. J. Zeng, Yujie Zeng, Y. C. Zhai, Y. H. Zhan, B. L. Zhang, B. X. Zhang, D. H. Zhang, G. Y. Zhang, Gengyuan Zhang, H. Zhang, H. C. Zhang, H. H. Zhang, H. Q. Zhang, H. R. Zhang, H. Y. Zhang, Han Zhang, J. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. S. Zhang, J. W. Zhang, J. X. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jin Zhang, Jiyuan Zhang, L. M. Zhang, Lei Zhang, N. Zhang, P. Zhang, Q. Zhang, Q. Y. Zhang, Q. Z. Zhang, R. Y. Zhang, S. H. Zhang, S. N. Zhang, Shulei Zhang, X. M. Zhang, X. Y. Zhang, Y. T. Zhang, Y. H. Zhang, Y. P. Zhang, Yao Zhang, Yu Zhang, Yu Zhang, Z. Zhang, Z. D. Zhang, Z. H. Zhang, Z. L. Zhang, Z. X. Zhang, Z. Y. Zhang, Zh. Zh. Zhang, Zhilong Zhang, Ziyang Zhang, Ziyu Zhang, G. Zhao, J.-P. Zhao, J. Y. Zhao, J. Z. Zhao, L. Zhao, Lei Zhao, M. G. Zhao, R. P. Zhao, S. J. Zhao, Y. B. Zhao, Y. L. Zhao, Y. P. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, B. M. Zheng, J. P. Zheng, W. J. Zheng, W. Q. Zheng, X. R. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, X. Zhong, H. Zhou, J. Q. Zhou, S. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, Y. X. Zhou, Y. Z. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, K. S. Zhu, L. X. Zhu, Lin Zhu, S. H. Zhu, T. J. Zhu, W. D. Zhu, W. J. Zhu, W. Z. Zhu, Y. C. Zhu, Z. A. Zhu, X. Y. Zhuang, M. Zhuge, J. H. Zou, J. Zu

Cosmology and Nongalactic Astrophysics

LazyTB: Extended LTB-solutions with Multiple Interacting Fluids

Kimmo Kainulainen, Enrico D. Schiappacasse, Linda Tenhu et al. (+1 more)

We present a low entry barrier numerical code LazyTB that solves the Einstein equations in the ADM-formulation for a general spherically symmetric problem with an arbitrary number of fluids with user defined equations of state and optional interactions between the fluids mediated by drag-vectors. We present the ADM equations in terms of carefully chosen dimensionless variables that avoid some numerical instabilities by analytic cancellation of potentially diverging terms. We demonstrate the code by applying it to a number of examples including the standard LTB model, a model with radiation and dark matter, a polytropic dark energy model with a non-vanishing sound speed and a model with coupled interacting dark matter and dark energy. We also implement a suite of diagnostic tools, including ray-tracing algorithms, that allow extracting physical observables such as luminosity distances for observers at arbitrary locations from the simulations. The code is built to be easy to extend also beyond the late-universe applications considered in the examples of this paper. LazyTB is available at https://github.com/ollijvaisanen/LazyTB.
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All authors Kimmo Kainulainen, Enrico D. Schiappacasse, Linda Tenhu, Olli Väisänen

Quantum Physics

Divide et Impera quantum neural networks for modular hybrid computing architectures

Emanuele Casciaro, Fabio Mascherpa, Alfonso Amendola et al. (+1 more)

Quantum machine learning is rapidly emerging as a promising and potentially more sustainable approach that can complement traditional, energy-hungry HPC, AI, and GPU resources-particularly for the demanding global challenges the world urgently needs to address. In recent years, the first prototypes of quantum processors have reached the market, are sometimes available via the cloud, and distributed quantum computing is beginning to move from a largely theoretical concept to a demonstrated reality. However, these devices are still noisy and qubit-limited. Therefore, it is desirable to design quantum machine learning models with a reduced quantum register and a limited number of quantum gates, avoiding overly deep and wide quantum circuits. Here, we explore this idea by proposing a novel divide-et-impera-based training protocol that splits quantum neural networks into smaller components and better governs their optimization. We benchmark our approach on real data and real-world prediction tasks in intertwined energy and environmental domains, such as the status of charging stations for electric vehicles and the global air quality index. Our results suggest a design principle for quantum machine learning algorithms across a wide range of applications, which can be more feasibly tested on state-of-the-art quantum processors or within modular quantum architectures being developed for future hybrid infrastructures interconnected via high-speed communication links.
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All authors Emanuele Casciaro, Fabio Mascherpa, Alfonso Amendola, Filippo Caruso

Disordered Systems and Neural Networks

Predicting activation-barrier and plasticity-onset statistics in a model of glasses

Makoto Suda, Edan Lerner and Eran Bouchbinder

A recently introduced anharmonic mean-field model unifiedly reproduced a broad range of low-temperature glass phenomena — including harmonic nonphononic spectral properties, linear micromechanics and strongly driven elasto-plastic dynamics — indicating that its underlying energy landscape is intrinsically glassy. Here, we apply a nonlinear modes framework to the model and derive analytic predictions for the asymptotic distributions of activation barriers $p(\Delta{U})\!\sim\!(\Delta{U})^{1/4}$ and the external force needed for the onset of plasticity $p(f_{\rm c})\sim f_{\rm c}^{2/3}$, for their extreme-value scaling and for $\langle\Delta{U}\rangle$ beyond the asymptotic regime. These predictions are expected to equally apply to the mean-field model and to finite-dimensional glasses. We develop efficient algorithms for sampling minima and saddles of the model's glassy potential energy landscape, and quantitatively confirm the theoretical predictions. This progress is enabled by identifying a subset of collective degrees of freedom that are physically relevant for activated glassy dynamics, which like the theoretical predictions should apply to realistic glasses.
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Quantum Physics

Sample-based quantum simulation of vibrational structure of polyyne chains

Sarah Mostame, Tanvi P. Gujarati, Alberto Baiardi et al. (+3 more)

Predicting anharmonic vibrational spectra is a complex computational task, which becomes quickly infeasible as molecular size and the number of vibrational basis functions increase, leading to an exponential growth of the underlying Hilbert space. Here, we employ a sample-based quantum diagonalization (SQD) framework to compute anharmonic vibrational energies and spectra. The approach combines quantum state preparation and sampling with configuration recovery, diagonalization of the Hamiltonian projected in a subspace of basis configurations, and calculation of transition-dipole moments to obtain both vibrational energies and infrared spectra. We investigate two approaches for sampling, namely, vib-LUCJ and vib-SqDRIFT and apply the method to study the polyyne molecules C$_2$H$_2$ and C$_4$H$_2$, reaching representations requiring up to 104 qubits. Beyond energies, transition-dipole calculations reveal that infrared intensities and excited-state composition continue to evolve with basis size through anharmonic mixing and intensity redistribution, even when low-energy eigenvalues appear converged. These results show that sample-based quantum subspace methods can capture spectroscopic information in vibrational spaces far beyond the regime of full diagonalization. Moreover, our simulation identify multi-state recovery and scalable projected-space treatment as central challenges for further scaling sample-based approaches.
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All authors Sarah Mostame, Tanvi P. Gujarati, Alberto Baiardi, Abhijit Mitra, Dimitar Trenev, Sumathy Raman

High Energy Physics (Phenomenology)

A Double-Dilaton Holographic Model of QCD: Running Coupling and Meson Phenomenology

Hector Cancio and Pere Masjuan

We present a holographic model of QCD to study the strong coupling constant $\alpha_s$ from the low-energy region to the high-energy regime. The approach uses a double-dilaton background, which breaks conformal and chiral symmetries, while large-$N_c$ corrections are incorporated to connect the holographic description with perturbative QCD. The model leads to an infrared fixed point and provides a smooth transition to the pQCD running. The resulting background also produces linear Regge trajectories for scalar, vector, and tensor states in reasonable agreement with experimental data.
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High Energy Astrophysical Phenomena

Remnant-wide mapping of heterogeneous presupernova burning histories in the O-rich ejecta of Cassiopeia A

Yui Kuboike, Toshiki Sato and Kai Matsunaga

Late-stage shell interactions, including shell mergers, can mix material across adjacent burning shells and imprint chemically inhomogeneous structures in the hydrostatic O-rich layers before core collapse. Whether such inhomogeneities survive the explosion and remain observable in the resulting supernova remnant is not well understood. We investigate the spatial and compositional structure of the O-rich ejecta in Cassiopeia A using deep Chandra X-ray observations. Principal component analysis of narrow-band images reveals O-rich ejecta spanning a compositional sequence from Ne-rich through NeSi-rich to O/Si-rich material. Spatially resolved spectroscopy of 20 representative regions confirms systematic depletion of Ne and Mg toward the O/Si-rich component. Notably, the composition of the O/Si-rich ejecta over a broad elemental range from O to Ca is simultaneously well reproduced by O-layer material in 17-20 $M_\odot$ one-dimensional presupernova models that experienced strong shell-merger-induced burning and mixing. In contrast, the Ne-rich ejecta retain substantially higher Ne and Mg abundances and resemble less strongly processed O-shell material. These chemically distinct components are spatially segregated on remnant-wide scales, with Ne-rich ejecta preferentially concentrated toward the north and O/Si-rich ejecta more prominent in the southeast. Our results suggest that late-stage shell burning and mixing in the progenitor of Cassiopeia A were spatially heterogeneous. The remnant-wide distribution of ejecta with different burning histories further indicates that part of this asymmetric presupernova structure may have survived the explosion and remains imprinted in the present-day remnant.
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General Relativity and Quantum Cosmology

Black holes with conical infinity in gravitational caloric theory

S. X. Tian and Zong-Hong Zhu

Whether gravitational caloric theory admits spherical black-hole solutions beyond Schwarzschild remains open. A well-defined black-hole solution requires both a regular horizon and a nonsingular exterior extending to infinity. To investigate this question, we cast the vacuum equations for a purely radial caloric field in a general static spherically symmetric metric into a three-dimensional autonomous system, which facilitates the global classification of solutions. We show that the regular asymptotic geometry can be Minkowski or conical, with the latter requiring a specific relation between the model parameters. Within this parameter slice, Schwarzschild is the only asymptotically flat black hole, whereas non-Schwarzschild black holes with conical infinity exist. These black holes can remain arbitrarily close to Schwarzschild from the near-horizon region to the conventional weak-field region (e.g., Solar System scales), yet retain an order-unity solid-angle deficit or excess at infinity. The asymptotic solid angle depends on a single model parameter and is independent of the caloric field amplitude. At fixed locally inferred mass, the caloric amplitude sets the conical transition scale, with weaker fields shifting the transition outward. We derive the local metric corrections and use the resulting periapsis shift to formulate an orbital test of the transition scale.
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Mathematical Physics · Cross-listed from math.SP

Graph transformations and eigenvectors of the Laplacian, signless Laplacian and Adjacency matrices

Jean-Guy Caputo, Leonardo de Lima and Arnaud Knippel

We study graph transformations and their effects on the eigenvectors of three fundamental graph matrices: the adjacency matrix $A$, the signless Laplacian $Q$, and the Laplacian $L$. We extend the Laplacian eigenvector edge and matching principles introduced by Merris to $Q$ and $A$. We also extend some of the known $L$ graph transformations to $Q$ and $A$ and prove that graphs admitting a common eigenvector $\mathbf{x}$ for $A, L$ and $Q$ are such that vertices corresponding to nonzero components of $\mathbf{x}$ have same degree. Following our previous work for $L$, we investigate bivalent graphs for $A$ and $Q$, that is graphs admitting an eigenvector with all components in $\{-1, 1\}$. In particular, for trees, we characterize $Q$-bivalence and establish that $A$-bivalence forces all vertex degrees to be odd.
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Soft Condensed Matter

Multiscale Decoupling in Peptide-Membrane Interactions: From Elastic Softening to Domain-Mediated Stiffening

Veerendra K. Sharma, Shuo Qian, Gergely Nagy et al. (+2 more)

Membrane composition plays a central role in determining how antimicrobial peptides (AMPs) interact with and alter the physical properties of lipid membranes. Here, we investigate the composition-dependent mechanical and structural response of lipid membranes to the AMP aurein using neutron spin-echo (NSE) spectroscopy, neutron membrane diffraction (NMD), and pressure (P)-area (A) isotherms, complemented by previously reported quasielastic neutron scattering (QENS) measurements. In a zwitterionic DMPC membrane, aurein induces progressive softening, manifested by a concentration-dependent decrease in both the bending rigidity and area compressibility modulus. NMD reveals a slight bilayer thinning but no prominent peptide-associated contribution within the deuterated hydrocarbon region, indicating that the progressive mechanical softening is not accompanied by increasingly deep peptide penetration into the hydrophobic core. In contrast, anionic phosphatidylglycerol (PG)-containing DMPC/DMPG membranes exhibit a non-monotonic response, with initial softening followed by pronounced stiffening at higher peptide concentrations. Complementary P-A isotherm measurements independently reproduce these contrasting mechanical responses, showing progressive softening of DMPC but stiffening of DMPC/DMPG. Most importantly, the combined NSE and QENS results reveal a striking multiscale decoupling: aurein suppresses molecular-scale lipid lateral diffusion while simultaneously reducing collective membrane stiffness at the mesoscopic scale, demonstrating that molecular lipid dynamics and collective membrane mechanics can evolve in opposite directions under the same peptide perturbation.Together, these results show that membrane composition governs the collective mechanical response to aurein, while molecular lipid dynamics can respond independently at shorter length and time scales.
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All authors Veerendra K. Sharma, Shuo Qian, Gergely Nagy, Sonam Raghav, Sajal K. Ghosh

High Energy Physics (Phenomenology)

Boson-Fermion Atomic Dark Matter

Natsumi Nagata and Tsutomu T. Yanagida

We propose a simple scenario of boson-fermion atomic dark matter, in which the dark matter abundance originates from a primordial particle-antiparticle asymmetry. The dark sector consists of a complex scalar and a Dirac fermion carrying opposite charges under an unbroken U(1)$_D$ gauge symmetry. Their asymmetries are generated non-thermally through the CP-violating decays of heavy Majorana fermions produced by inflaton decay, in close analogy with non-thermal leptogenesis in the visible sector. The symmetric components efficiently annihilate into massless dark photons, while the surviving scalar and fermion populations cannot annihilate with each other and instead recombine into neutral boson-fermion dark atoms. Remarkably, the same interactions responsible for generating the primordial asymmetry induce atom-antiatom oscillations after recombination, so that the present-day dark matter can be approximately symmetric despite its asymmetric origin. Residual ionized components or sufficiently extended dark atoms can also give rise to appreciable dark-matter self-interactions, potentially leaving observable imprints on the formation and structure of dark matter halos and offering complementary cosmological and astrophysical probes of the dark sector. The massless dark photon survives as dark radiation, yielding a characteristic contribution $\Delta N_{\rm eff}\simeq0.05-0.07$ for the thermal history considered here. This prediction lies within the reach of future precision CMB observations, providing a direct cosmological test of the scenario.
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Nuclear Experiment

Event-by-event net-charge fluctuations in pp, OO, Ne-Ne, and Pb-Pb collisions with ALICE at the LHC

Nida Malik

Investigations involving the event-by-event fluctuations of conserved quantities, like net charge, net baryon number, and strangeness in heavy-ion collisions, provide insights into the properties of quark-gluon plasma (QGP) and the phase diagram of strongly interacting matter. Event-by-event fluctuations of net electric charge in pp collisions at $\sqrt{s} = 13$ and $13.6$ TeV and for OO, Ne-Ne, and Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.36$ TeV are studied by analysing the data collected by the ALICE detector at CERN Large Hadron Collider. The analysis is carried out in terms of the variable $\nu_{\mathrm{dyn}}[+,-]$, chosen for its robustness against detector efficiency losses. The observed dependence of $\nu_{\mathrm{dyn}}[+,-]$ on the charged-particle density shows a smooth, energy-independent decrease in the magnitude of $\nu_{\mathrm{dyn}}[+,-]$ from smaller to larger collision systems. The negative values of $\nu_{\mathrm{dyn}}[+,-]$ indicate a dominance of correlations between oppositely charged particle pairs compared with those arising from like-sign charge pairs. Since $\nu_{\mathrm{dyn}}[+,-]$ is known to have an intrinsic dependence on multiplicity, an appropriate scaling is applied. The variable is therefore scaled with the mean multiplicities, $\frac{1}{\frac{1}{\langle N_+ \rangle} + \frac{1}{\langle N_- \rangle}}$. The dependence of the scaled values of $\nu_{\mathrm{dyn}}[+,-]$ on charged particle density is also looked into. The results are compared with model calculations from PYTHIA, EPOS4, AMPT and HIJING.
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Quantum Physics

Quantum Approximation Complexity of Classical Optimization Problems

Stuart Hadfield

Classical approximation complexity asks what solution quality can be guaranteed with polynomial-time computation. The classes APX, PTAS, and FPTAS distinguish a fixed approximation ratio, approximation to any fixed accuracy, and approximation schemes whose running time is also polynomial in inverse accuracy. Their randomized counterparts are R-APX, R-PTAS, and R-FPTAS. We define bounded-error quantum counterparts BQ-APX, BQ-PTAS, and BQ-FPTAS. Membership requires a uniform quantum algorithm that, on every input, returns a feasible classical solution achieving at least the claimed approximation ratio with probability at least 2/3. Scores (objective values) must be efficiently classically computable. Running time includes parameter selection, preparation, measurement, decoding, and repetition. Many quantum optimization methods are used heuristically, and high benchmark scores alone do not establish these guarantees. We further establish a conditional hierarchy for logarithmic, polynomial, and exponential approximation factors. Assuming NP $\nsubseteq$ BQP, the quantum classes form a strict hierarchy. Problems based on prime factorization and discrete logarithms give conditional quantum-classical separations. Certified Maximum Order has an exact quantum algorithm, while any randomized polynomial-time algorithm guaranteeing at least an inverse-polynomial approximation ratio on every input would yield efficient factoring. Discrete-Logarithm Fitting has an exact quantum algorithm and a deterministic one-half approximation, but any fixed improvement over one half would give a randomized polynomial-time algorithm for the safe-prime discrete logarithm problem. Our results show, under explicit complexity assumptions, that quantum computation can improve worst-case approximation guarantees. A quantum-classical gap for common problems such as MaxCut or MaxSAT remains open.
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Mathematical Physics

Absence of Absolutely Continuous Spectrum for One-Dimensional Capacitance Operators with Critical Long-Range Interactions

Habib Ammari and Jiayu Qiu

In this paper, we establish the absence of absolutely continuous spectrum for scalar one-dimensional Laurent operators with multiplicative disorder and critical long-range hoppings. In particular, the requirement of at least quartic off-diagonal decay rate in the existing theory is bypassed by exploiting the finite-difference bound of the convolution kernel, which is available even when the interaction decays only as $|n|^{-1}\log^{-\beta}|n|$ with $\beta>1$. We then apply the abstract main result to a concrete physical model, the capacitance operator in subwavelength physics. For a chain of three-dimensional resonators with one resonator per period, we verify the required decay and finite-difference estimates and conclude the absence of absolutely continuous spectrum. These results leave open the distinction between pure point and singular continuous spectrum, but constitute a key step in proving Anderson localization in wave systems with critical long-range interactions.
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