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Physics

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Tuesday 16 June

High Energy Physics (Phenomenology)

The next-to-leading order of the differential cross-section of the subprocess of Compton scattering of quark-gluon of prompt photon production in proton-proton collisions at NICA energies

Mohsun Rasim Alizada and Azar Inshalla Ahmadov

In the presented article, the next-to-the-leading-order calculation of the differential cross-section of the Compton scattering subprocess $qg \rightarrow q\gamma$ for prompt photon production in proton-proton collisions at NICA energies has been carried out, both without and taking into account the longitudinal polarization of colliding protons. It is shown that the contribution of the next-to-leading order to the differential cross-section is significant at high energies of colliding protons and constitutes around $15\%$ of the leading-order calculation. The influence of the polarization of colliding protons on the next-to-leading-order calculation is more significant than on the leading-order calculation.
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Materials Science

Chemical Vapor Deposition of Ni-doped Iron Germanium Telluride Nanosheets

Matthew Metcalf, Jesse Martinez, Armella Mushfique et al. (+4 more)

Iron germanium telluride (FGT; FemGenTe2) compounds have attracted significant interest due to their layered van der Waals structure, relatively high Curie temperature, and tunable magnetic properties. Chemical vapor deposition (CVD) is a particularly promising synthesis route owing to its simplicity, low cost, potential for scalability, and widespread adoption in the semiconductor industry, yet it has not been used previously to synthesize FGT with dopants. Here, we report CVD synthesis of both undoped and Ni-doped FGT nanosheets on SiO2/Si substrates. By adjusting precursor molar ratios, we synthesized Ni-doped FGT with multiple Fe concentrations and a 4% Ni-to-Fe ratio. X-ray photoelectron spectroscopy depth profiling further demonstrates that Ni is present in the bulk of the crystals. This straightforward, low-cost, and CMOS-compatible approach demonstrates a route to Ni-doped FGT nanosheets, establishing a foundation for future characterization of Ni-doped FGT and its potential integration into spintronic devices.
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All authors Matthew Metcalf, Jesse Martinez, Armella Mushfique, Alexander Riou, Lutfun Nahar, Bamidele Onipede, Hui Cai

Mathematical Physics

Elastic Surface Instability as a Topological Phase Transition

Yu-Xin Xie

The macroscopic instability of soft materials undergoing extreme deformations is traditionally viewed as a pure structural or mechanical failure. Driven by the quest to uncover universal principles across disparate physical systems, we bridge two vibrant yet seemingly disconnected research frontiers: macroscopic finite-strain solid mechanics and quantum-like topological physics. Here, we demonstrate that the classical elastic surface instability of a deformed hyperelastic manifold is not merely a mechanical bifurcation, but fundamentally a topological phase transition. By incorporating Lie group metric evolution into a generalized Stroh formalism, we map the highly nonlinear geometric frustration onto an algebraic surface impedance matrix $\mathbf{H}$. For a semi-infinite hyperelastic half-space under finite compression, we analytically map the system to a one-dimensional Dirac Hamiltonian, where the macroscopic mechanical stretch acts as a tunable knob for the Dirac mass. We reveal that the onset of surface wrinkles marks a topological transition from a trivial to a non-trivial phase characterized by a quantized step in the winding number, naturally giving rise to a robust, macroscopically localized zero-energy edge state. This fundamental linkage unifies macroscopic symmetry breaking with the topological paradigm, opening a new theoretical pathway for programmable smart soft matter.
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Quantum Physics

Ground- and excited-state energies extraction via Trotterization on IBM quantum computers

Fernando Espinoza-Ortiz, Chungwei Lin and Chih-Chun Chien

We implement the Hadamard test with Trotterized time-evolution operators on IBM quantum computers to simultaneously extract ground- and excited-state energies of the transverse field Ising model (TFIM) and transverse longitudinal field Ising model (TLFIM). The Trotterization circuits for the TFIM admit constant-depth circuits (CDCs) for arbitrary time, allowing us to locate a large number of eigen-energies above the background noise for up to six spins. Via circuit synthesis we show that the three-spin TLFIM has constant-depth structure although it does not meet the known CDC criteria. The CDCs enable the extraction of the ground and first-excited state energies of the three-site TLFIM via its dynamics. We also address complications from the noisy background and discrete Fourier transform to enhance the reliability of the extraction process and compare the results from different generations of IBM hardware to highlight the improvement.
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Strongly Correlated Electrons

Tunable Chaos in the Finite Mean SYK Model

Arkaprava Mukherjee, Sumilan Banerjee, Sandip P. Trivedi et al. (+1 more)

The complex Sachdev-Ye-Kitaev (SYK) model, featuring fermions with all-to-all interactions, serves as a dual paradigm for understanding non-Fermi liquid behavior and the holographic nature of charged black holes. Two defining characteristics of the standard SYK model are its maximal chaos (Lyapunov exponent $\lambda_{\mathrm{L}}=2\pi T$ at temperature $T$), and its finite zero-temperature residual entropy. While previous studies have largely focused on couplings drawn from a zero-mean Gaussian distribution, we investigate a generalized model with a finite mean-to-standard-deviation ratio, $g\equiv J_{0}/\delta J$ of the coupling distribution in order to get deeper insight into the evolution of chaos. We find that increasing $g$ yields the following effects: (i) The system remains a fast scrambler with $\lambda_{\mathrm{L}}=A~T$, but with a suppressed coefficient $A<2\pi$. (ii) In the limit $g\to \infty$, out-of-time-ordered correlators (OTOCs) no longer exhibit exponential growth with $\lambda_{\mathrm{L}}\simeq 0$. (iii) The spectral correlations indicative of late-time chaos maintain Wigner-Dyson level spacing statistics for all values of $g$. (iv) The system preserves a finite residual entropy, albeit with reduced magnitude, for all $g$ values. We conclude that in this generalized SYK model, there is a chaotic to non-chaotic crossover. Moreover different measures of chaos decouple, demonstrating that the presence of finite residual entropy does not strictly imply maximal chaos.
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All authors Arkaprava Mukherjee, Sumilan Banerjee, Sandip P. Trivedi, Nandini Trivedi

Applied Physics

Piezoelectric resonators in thin-film barium titanate from room temperature to millikelvin

Hao Tian, Shu-Yuan Chang, Nuha Akhtar et al. (+2 more)

Ferroelectric materials, with their strong nonlinearities, underpin key technologies across radio-frequency (RF) signal processing, optical communications, and emerging quantum systems. Barium titanate (BTO) is a notable example, combining strong piezoelectric and electro-optic responses. While bulk BTO has been studied for decades, the piezoelectric properties of its recently available thin films, and their behavior at the millikelvin temperatures relevant to quantum hardware, remain largely unexplored. Here, we fabricate and characterize surface acoustic wave (SAW) resonators on thin-film BTO. The measured devices exhibit high electromechanical coupling (k2eff 0.14 at 5.2 GHz) and operate up to 7.8 GHz. From these measurements, combined with finite-element modeling of the multi-domain microstructure, we extract an effective piezoelectric coefficient d33eff of 53 pC/N, comparable to bulk BTO. Exploiting the intrinsic ferroelectricity, we further demonstrate low-voltage switching with a fast (100 ns) response, attractive for reconfigurable RF front-ends and parametric amplifiers. Extending these measurements to millikelvin temperatures, we find that the piezoelectric response persists, with d33eff 19 pC/N, pointing to the potential of BTO for piezoelectric coupling in superconducting quantum circuits. These results position thin-film BTO as a promising piezoelectric platform for both classical and quantum information technologies.
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All authors Hao Tian, Shu-Yuan Chang, Nuha Akhtar, Kasra Sardashti, Mohammad Mirhosseini

High Energy Physics (Experiment)

Electromagnetic Shower Reconstruction and Identification in FASER's Emulsion Detector for LHC Forward Neutrino Measurements

FASER Collaboration: Roshan Mammen Abraham, Xiaocong Ai, Saul Alonso Monsalve et al. (+131 more)

We present methods for electromagnetic shower reconstruction and identification in the FASERnu emulsion detector using 100 GeV and 200 GeV electron test-beam data from the CERN SPS H4 beamline. The reconstruction employs a clustering-based algorithm without energy-dependent tuning to determine shower axes. A multi-level identification chain comprising track pre-selection, a cut-based selection, and a BDT classifier achieves combined background rejection rates of 99.99% (100 GeV) and 99.94% (200 GeV). The method reaches total reconstruction and identification efficiencies of 58.9% (100 GeV) and 70.8% (200 GeV) evaluated from simulated samples. Energy reconstruction using the total number of reconstructed segments as the calorimetric estimator yields relative biases of +0.6% (100 GeV) and -0.8% (200 GeV), with resolutions of 25.4% and 22.6%, respectively. Systematic uncertainties on the energy reconstruction are dominated by variations in emulsion film detection efficiency, with totals of (+10.9%/-8.2%) at 100 GeV and (+10.3%/-6.9%) at 200 GeV. The methodology provides a validated framework for electron neutrino identification with the FASERnu detector at the LHC.
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All authors FASER Collaboration: Roshan Mammen Abraham, Xiaocong Ai, Saul Alonso Monsalve, John Anders, Emma Kate Anderson, Akitaka Ariga, Tomoko Ariga, Jeremy Atkinson, Florian U. Bernlochner, Jianming Bian, Tobias Boeckh, Eliot Bornand, Jamie Boyd, Lydia Brenner, Angela Burger, Franck Cadoux, Roberto Cardella, David W. Casper, Charlotte Cavanagh, Shiyang Chen, Xin Chen, Xing Cheng, Dhruv Chouhan, Andrea Coccaro, Fabio Cufino, Stephane Débieux, Ansh Desai, Sergey Dmitrievsky, Radu Dobre, Monica D'Onofrio, Sinead Eley, Yannick Favre, Jonathan L. Feng, Carlo Alberto Fenoglio, Didier Ferrere, Max Fieg, Wissal Filali, Elena Firu, Haruhi Fujimori, Edward Galantay, Stephen Gibson, Sergio Gonzalez-Sevilla, Yuri Gornushkin, Yotam Granov, Jinjing Gu, Carl Gwilliam, Elie Hammou, Daiki Hayakawa, Michael Holzbock, Shih-Chieh Hsu, Zhen Hu, Giuseppe Iacobucci, Tomohiro Inada, Luca Iodice, Sune Jakobsen, Cesar Jesus-Valls, Arash Jofrehei, Hans Joos, Enrique Kajomovitz, Alex Keyken, Felix Kling, Daniela Köck, Pantelis Kontaxakis, Jelle Koorn, Umut Kose, Peter Krack, Susanne Kuehn, Thanushan Kugathasan, Sebastian Laudage, Lorne Levinson, Botao Li, Jiaxi Liu, Jinfeng Liu, Yi Liu, Margaret S. Lutz, Joern Mahlstedt, Toni Mäkelä, Yasuhiro Maruya, Anna Mascellani, Lawson McCoy, Josh McFayden, Andrea Pizarro Medina, Hiroaki Menjo, Théo Moretti, Toshiyuki Nakano, Laurie Nevay, Yuma Ohara, Ken Ohashi, Hidetoshi Otono, Lorenzo Paolozzi, Annabelle Parry, Pawan Pawan, Brian Petersen, Titi Preda, Markus Prim, Junkai Qin, Michaela Queitsch-Maitland, Juan Rojo, Hiroki Rokujo, André Rubbia, Osamu Sato, Paola Scampoli, Kristof Schmieden, Matthias Schott, Cristiano Sebastiani, Anna Sfyrla, Davide Sgalaberna, Mansoora Shamim, Yosuke Takubo, Kakeru Tanaka, Noshin Tarannum, Simon Thor, Eric Torrence, Serhan Tufanli, Oscar Ivan Valdes Martinez, Svetlana Vasina, Emanuele Villa, Benedikt Vormwald, Chi Wang, Yuxiao Wang, Eli Welch, Aaron White, Monika Wielers, Benjamin James Wilson, Zhongyi Wu, Yue Xu, Heng Yang, Lekai Yao, Daichi Yoshikawa, Stefano Zambito, Shunliang Zhang, Yuxuan Zhang, Xingyu Zhao, Zijian Zhao

Quantum Physics

Exponentially many initializations to avoid barren plateaus

Ankit Kulshrestha, Ricard Puig, Diego García-Martín et al. (+4 more)

Barren plateaus are stated as an average-case phenomenon: pick an ansatz, initialize it naively, and concentration follows. This has led to the common view that a potential cure for barren plateaus is simply to initialize the parameters more carefully. Here we show that the situation is subtler. We introduce a first-moment framework that gives a simple operator-level diagnostic for when an initialization may escape the fully concentrated barren-plateau fixed point, and for comparing the biases induced by different initialization strategies. Our framework recovers several known initialization schemes such as identity and Gaussian initialization, but also shows that barren-plateau avoidance is highly non-unique. Indeed, many shifted, biased, and non-symmetric parameter distributions can avoid concentration, and these choices need not be equivalent. In fact, our results show that one can generate exponentially many families of inequivalent initialization strategies. Then, our numerics indicate that different first-moment-distinct initializations can lead to different attained minima, suggesting that avoiding barren plateaus via smart initializations can trade the exponential concentration problem for the challenge of selecting the right trainable pocket amongst many options.
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All authors Ankit Kulshrestha, Ricard Puig, Diego García-Martín, Lukasz Cincio, Ilya Safro, Zoë Holmes, M. Cerezo

Mesoscale and Nanoscale Physics

Magnon-dislon hybridization in magnetic insulators

Carlos Saji, Nicolas Vidal-Silva and Roberto E. Troncoso

Spin dynamics in ordered magnets with topological lattice defects is investigated. Using fracton–elasticity duality, we develop an effective field theory of magnons coupled to quantized lattice dislocations (dislons) in magnetic insulators. Within this framework, an elastic gauge field mediates a nonlocal interaction between dislocations and magnetization gradients. The resulting magnetoelastic coupling gives rise to coherent magnon-dislon hybridization whose properties are dictated by dislocation topology. Screw dislocations exhibit helicity-selective hybridization and symmetry-protected dark dislon sectors, while edge dislocations generate anisotropic hybrid excitations with finite spin-precession ellipticity through the glide constraint. Our results establish dislocations as dynamical topological defects with directly observable polarization fingerprints in magnon spectra, and reveal magnon-dislon hybridization as a new route to control spin dynamics.
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High Energy Physics (Phenomenology)

$\pi^0$-$\gamma$ mixing in the presence of a strong magnetic field

D. Gomez Dumm, S. Noguera and N.N. Scoccola

We analyze the mixing between the $\pi^0$ meson and the photon in the presence of a strong uniform magnetic field, in the context of a two-flavor Nambu-Jona-Lasinio model. It is shown that only one specific photon polarization state can get mixed with the $\pi^0$ state, a fact that can be understood on general grounds. For magnetic fields with values up to 1 GeV$^2$/e, it is found that the effect of the mixing on the pion mass and pion-quark couplings is relatively small (below a level of 15%), which is at variance with previous results reported in the literature.
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Fluid Dynamics

Solution of the Newtonian plane Couette flow with dynamic wall slip using machine-learning methods

Georgia Foutsitzi, Nikolaos Antoniadis and Georgios C. Georgiou

This study presents a comparative investigation of Physics-Informed Neural Networks (PINNs) and data-driven Deep Operator Networks (DeepONets) for predicting the evolution of plane Newtonian Couette flow with dynamic wall slip. While traditional numerical methods, such as the Crank-Nicolson scheme, offer high accuracy, their computational demand poses challenges in real-time applications. To address this, we first implement a PINN framework to solve the governing equations for specific physical parameters. Subsequently, we develop a data-driven DeepONet, trained on high-fidelity numerical data, to learn the continuous solution operator across a broad range of slip boundary conditions and upper wall velocities. Our results indicate that while the PINN achieved superior point-wise precision with a relative L_2 error of 0.083%, it remains constrained by the requirement for instance-specific retraining. In contrast, the DeepONet demonstrates robust generalization on unseen and out-of-distribution signals with a mean relative error of 0.36% and 0.88%, respectively. Most notably, it provides near-instantaneous inference, achieving a speedup factor of approximately 540X over the numerical solver and 30.5% over the PINN. This work demonstrates the synergy between physics-based and data-driven architectures and establishes DeepONet as a highly efficient surrogate model for rapid parametric exploration and real-time fluid dynamics forecasting.
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Chemical Physics

Bayesian Sampling of Structural Ensembles: The Role of Ensemble-Counting Measures

Ivan Gilardoni and Giovanni Bussi

Structural ensemble refinement is widely used to integrate molecular simulations with experimental measurements. While most applications focus on the maximum-a-posteriori (MAP) ensemble, Bayesian sampling of the posterior distribution can provide uncertainty estimates and posterior averages for arbitrary observables. A notable step in this direction was introduced by the Bayesian Energy Landscape Tilting (BELT) framework, where sampling is performed on a family of maximum-entropy ensembles parametrized by Lagrange multipliers. Here, we show that Bayesian sampling in this setting requires an explicit choice of ensemble-counting measure. In particular, the flat measure in Lagrange-multiplier space used in the original BELT formulation leads to a posterior distribution that is formally non-normalizable for finite reference trajectories. We propose the Jeffreys measure as an invariant ensemble-counting prescription, restoring normalizability in the finite-sample situations considered here, and providing a consistent definition of posterior averages. Using both an analytically tractable Gaussian model and maximum-entropy refinement of RNA oligomer simulations, we compare different ensemble-counting measures and show that they can significantly affect Bayesian estimates. The resulting methodology has been implemented in the MDRefine software package.
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Quantum Physics

Towards an Optimally Distributed Quantum Fourier Transform Circuit

Zachary Vernec, Michael Silver and Hans-Arno Jacobsen

A promising avenue for scaling quantum computing is to connect quantum processing units (QPUs) by generating entanglement between them. This requires circuit partitioning: partially rewriting quantum circuits to run on a distributed quantum system using quantum teleportation protocols, while preserving the unitary operation implemented by the circuit. The key metric to minimize when partitioning is the e-bit count, defined as the number of maximally entangled qubit pairs that must be generated between QPUs. We focus on partitioning the quantum Fourier transform (QFT) circuit, which is widely used as a subroutine in quantum algorithms such as quantum phase estimation and arithmetic circuits. Specifically, we present an optimal gate-packing-based partitioning scheme under bounded communication ancilla constraints, as well as a novel detached-gate-based partitioning scheme that achieves optimal e-bit consumption when ancilla availability is unrestricted. We compare these schemes against prior analytical partitioning approaches for the QFT and evaluate them against partitions produced by general-purpose circuit partitioning algorithms. We further validate our approach by implementing the bounded-ancilla circuits on quantum hardware.
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Other Condensed Matter

Dynamical axion quasiparticles: an open quantum system

Daniel Boyanovsky

We study the non-equilibrium dynamics of emergent dynamical axion quasiparticles (DAQ) coupled to a photon bath in equilibrium via a Chern-Simons term as a quantum open system. A quantum master equation (QME) is derived up to second order in this coupling implementing only a partial Markov approximation, allowing time dependent rates in the Lindblad (QME). These are determined by the equilibrium correlation functions of the Chern-Simons density, and their time dependence allows us to explore transient dynamics in coherences and population: the formation of the quasiparticle on short time scales and its decay, and the build-up of population with an effective time dependent rate. Early time evolution features quantum anti Zeno dynamics with enhanced quasiparticle decay and population growth. These phenomena describe transient violations of Fermi's Golden rule and of detailed balance, and are distinct non-Markovian effects directly related to the spectral density of the Chern-Simons correlators. We obtain the equation of motion of coherent (DAQ) condensates both with the (QME) and with quantum many body linear response establishing a direct bridge between both methods. As a corollary we obtain the expectation value of the Chern-Simons density induced by a (DAQ) condensate in linear response, the topological susceptibility is shown to be proportional to the (DAQ) many body self-energy. We provide a Feynman diagram-based interpretation of approximations invoked in the (QME) and corrections from system-bath correlations in higher order.
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Cosmology and Nongalactic Astrophysics

The Coherence Principle: A Falsifiable Prior for Model Selection from the Grammar of Theories

Raul Jimenez, Carlos Peña Garay, Fergus Simpson et al. (+1 more)

Bayesian model selection in cosmology and particle physics is often performed where posterior odds inherit a strong, often unacknowledged dependence on the prior assigned to competing models. Standard responses – reference priors, hierarchical priors, or appeals to naturalness – ignore relevant theoretical knowledge or rely on criteria hard to define operationally. We propose the Coherence Principle: a reproducible prescription for assigning model priors according to compatibility with the validated structure of an existing theory. This structure, or grammar, includes symmetries, conservation laws, locality, Lorentz invariance, and universality patterns. Unmotivated violations of these rules incur a coherence cost, converted into a prior weight through a maximum-entropy exponential form controlled by one calibratable parameter $\alpha$. The resulting prior is distinct from both the Bayesian Occam factor and naturalness: it penalizes not parameter volume or fine tuning, but departures from validated theoretical grammar. We illustrate the principle with examples from cosmology and fundamental physics: neutrino mass mechanisms, dark energy and modified gravity, inflation, beyond-Standard-Model sectors, and hierarchical astrophysical inference. We test it also on four historical cases – general relativity, Pauli's neutrino, parity violation, and special relativity – where evidential and theoretical contexts can be reconstructed. These examples show that it favors the historically successful choice when the proper grammar is defined in the correct domain and time. The Coherence Principle makes explicit a common but usually tacit part of physical reasoning: trust in validated structural rules. It turns this judgment into a transparent, testable, and overrulable component of Bayesian inference, leaving empirical likelihoods free to dominate when data are sufficiently constraining.
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All authors Raul Jimenez, Carlos Peña Garay, Fergus Simpson, Licia Verde

Solar and Stellar Astrophysics

ISOSCELES Project: II. Modelling galactic B-type stars for fast and $\delta-$slow wind regimes

N. Machuca, M. Curé, I. Araya et al. (+5 more)

Radiation-driven winds in B-type stars play a key role in their evolution, yet their hydrodynamical structure remains uncertain, particularly in evolved objects. While the classical fast solution of the modified CAK theory is widely adopted, it does not always reproduce the optical wind diagnostics of B-type giants and supergiants. We investigate the applicability of the classical fast and $\delta$-slow hydrodynamical solutions to B-type stellar winds through a homogeneous spectroscopic analysis based on optical diagnostics. We analysed 50 Galactic B-type stars spanning luminosity classes I to V using mid- and high-resolution optical spectra from the IACOB, ESO-UVES, and CASLEO datasets. Synthetic spectra were taken from the ISOSCELES grid, which combines hydrodynamical wind models computed with Hydwind and NLTE radiative transfer with Fastwind. Stellar and wind parameters were derived through a multi-line $\chi^2$ fitting procedure using hydrogen, helium, and silicon lines. We find evidence for different preferred hydrodynamical regimes across luminosity classes. Most supergiants ($\sim$96%) and giants ($\sim$88%) are better reproduced by $\delta$-slow models, characterised by higher ionisation parameters, slower terminal velocities ($v_\infty \lesssim 300$,km,s$^{-1}$, and denser outflows. In contrast, most dwarfs and subgiants ($\sim$88%) are more consistent with the classical fast solution, showing higher $v_\infty$ and lower $\dot{M}$. These trends suggest a dichotomy between luminosity classes. Our results indicate that the $\delta$-slow solution provides a viable framework for modelling the optical spectra of evolved B-type stars, whereas fast solutions remain adequate for less evolved objects. The ISOSCELES grid provides a physically motivated basis for interpreting optical wind diagnostics and motivates future multi-wavelength studies of B-type stellar winds.
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All authors N. Machuca, M. Curé, I. Araya, R. O. J. Venero, L. S. Cidale, C. Arcos, S. Simón-Díaz, A. Lobel

Superconductivity

Magnetic field induced transition from nodeless to nodal superconductivity in $\beta$-PdBi$_{2}$

Emmanouil K. Kokkinis, Joseph J. Betouras and Andrey V. Chubukov

Recent tunneling measurements on $\beta$-PdBi$_2$ reported a magnetic field induced phase transition from a fully gapped to a nodal superconducting state. We develop a microscopic theory of superconductivity in this multi-band material, taking into account spin-orbit coupling and Zeeman splitting. We show that there are two attractive pairing channels in this system: an s-wave and a p-wave. At zero magnetic field, s-wave superconductivity wins. At a finite field, this channel becomes less favorable because Fermi surfaces split, and the gap symmetry changes to p-wave. We show that at a higher field, the excitation spectrum of a p-wave multi-band superconductor becomes gapless, with nodal points located in between the split Fermi surfaces. We argue that this behavior accounts for the experimentally observed field-induced nodal superconductivity in $\beta$-PdBi$_2$.
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Materials Science

Hydration-controlled twist forms a moiré glass in charge-frustrated layered silicates

Juhyeok Lee, Piotr Zarzycki, Colin Ophus et al. (+5 more)

Twisting layered materials produces moiré superlattices, but prescribed twist angles are usually obtained by demanding assembly procedures. Here we show that montmorillonite, an abundant swelling clay, forms tunable moiré superlattices naturally. Focal-series high-resolution transmission electron microscopy, geometric phase analysis, and molecular dynamics simulation reveal that its apparent rotational disorder is biased toward low-angle misorientations inherited from discrete hydration states. Multilayer stacks preferentially adopt twists near 1-2{\deg}, 4{\deg}, and 10{\deg}, producing long-wavelength moirés without long-range rotational order. We define this kinetically trapped state as a moiré glass, distinct from featureless turbostratic stacking. Simulations indicate that lattice-charge disorder stabilizes the angular preferences, whereas charge ordering promotes random stacking. Hydration screens interlayer interactions and lubricates twist, while dehydration arrests the resulting configurations in discrete steps. These results establish dynamic hydration as a macroscopic handle for programming twist in layered matter.
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All authors Juhyeok Lee, Piotr Zarzycki, Colin Ophus, Jim Ciston, Benjamin Gilbert, Jillian F. Banfield, Mary C. Scott, Michael L. Whittaker

Quantum Physics

Exact propagating Dirac wave packets in an attractive Coulomb-like potential

Siddhant Das

We construct exact, positive-energy, normalizable wave-packet solutions of the Dirac equation in the axisymmetric potential $V=-\,v_0/\rho$ – to our knowledge, the first such solutions in any external potential. Remarkably, one family comprises only elementary functions whose longitudinal profiles reproduce the free-Schrödinger Hermite–Gauss wave packets in the nonrelativistic limit. All packets share two striking features: (i) a probability density that is pointwise decoupled from spin orientation – despite the inherent spin-orbit coupling of the Dirac equation – and (ii) a complete freezing of their time evolution at the critical coupling $v_0\to\hbar c/2$. We also present a simple scheme that maps solutions of the 2D Helmholtz equation to further exact Dirac wave packets.
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High Energy Astrophysical Phenomena

Short-Duration Gamma-ray Burst and Afterglow Rates in the Rubin and Roman Era

Tzvetelina Dimitrova and Nathaniel Butler

Short-duration gamma-ray burst (sGRB) afterglows that follow BNS-gravitational wave (GW) events are essential for understanding the tension between the observed sGRB rate and BNS merger rate, heightened by the recent conclusion of aLIGO O4 with no new confirmed BNS detections. Using a probabilistic sGRB world model derived from a source BNS merger population, we simulate afterglow emission with AfterglowPy to investigate detection prospects of afterglows in the new era of optical surveys, and probe their multi-messenger implications. The predicted sGRB/BNS association is strongly dependent on sGRB beaming, which may be constrained by orphan afterglows (OA) - that arise from events with no prompt $\gamma$-ray detection. We conclude that the Vera C. Rubin Observatory's Large Synoptic Survey Telescope (LSST) may detect an afterglow sample sufficient in constraining sGRB jetting, with an estimated $5.3^{+1.7}_{-1.2}$ on-axis afterglow and $11^{+5}_{-3}$ OA detections per year; while the deep sensitivity of the Roman Space Telescope appears promising for probing the faint end of afterglow events in targeted follow-up strategies. The detection of afterglows in upcoming LIGO runs is possible but challenging, as we predict fewer than $\approx 1.4$ LSST or Roman discoverable events per year within the projected aLIGO O5 BNS range across all considered jet models and observing scenarios. We update previous sGRB-BNS rate predictions, finding that continued non-detection of a BNS in O5 would require revisiting key assumptions underlying sGRB-BNS models.
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Instrumentation and Methods for Astrophysics

Modeling Doppler Shifts in Radial-Velocity Data with Deep Learning toward Earth-mass Exoplanet Detection

Isidro Gómez-Vargas, Xavier Dumusque, Yinan Zhao et al. (+2 more)

Detecting the tiny Doppler shifts induced by Earth-mass planets in stellar radial-velocity measurements remains extremely challenging due to stellar activity. Many deep-learning methods performing well on simulated data remain difficult to apply reliably on real stellar spectra. The aim of this work is to develop a deep-learning framework that generalizes to real, unseen spectra and improves the detectability of Earth-mass planets in radial-velocity data. We train artificial neural networks on HARPS-N solar spectra with injected planetary signals, using physics-motivated spectral representations based on flux and line-formation temperature, together with their velocity gradients. Two training strategies are explored: hold-out testing and cross-validation. Model robustness is enhanced through genetic-algorithm-based hyperparameter optimization, and predictive uncertainty is quantified using Monte Carlo dropout. Our most precise neural network model reliably retrieves, under the cross-validation strategy, the amplitudes, phases, and orbital periods of planetary signals with amplitudes greater than or equal to 25 cm/s and periods between 10 and 550 days. In addition, in all cases tested here, the successfully recovered signals correspond to the most significant peaks in the periodograms of the Doppler-shift predictions. Temperature-based spectral-shell representations consistently outperform flux-based shells. We also release doppleriann, a Python package implementing the proposed framework. Our results demonstrate that combining physically motivated spectral representations with deep learning provides a promising pathway toward the detection of Earth-mass planets in radial-velocity data from real observations, supported by a modeling framework that is both physically grounded and statistically rigorous, incorporating uncertainty quantification and optimized training strategies.
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All authors Isidro Gómez-Vargas, Xavier Dumusque, Yinan Zhao, Khaled Al Moulla, Michael Cretignier

Mesoscale and Nanoscale Physics

Persistent current and orbital magnetization along a valley-contrasting junction in bilayer graphene in a magnetic field

K. Shizuya

In a magnetic field bilayer graphene hosts an octet of pseudo-zero-mode electron levels nearly degenerate in orbitals $n=(0,1)$, valleys and spins. They split in valleys by electrostatic gating. In gated bilayer graphene, in which the interlayer bias is set up to flip sign across a line, one has a line junction that traps a portion of pseudo-zero-mode electrons inside the insulating bulk band gap, giving rise to electron states localized along the junction, known as kink states. A close look is made into the spectra and electromagnetic response of such kink states. There are two species of valley current associated with them, a drift current driven by the bias gradient and a circulating current coming from cyclotron motion. It turns out that they both flow in essentially the same direction, with the circulating current exhibiting a magnetic character distinct from those of other higher levels. In equilibrium they spatially circulate within the kink states, creating a quasi-one-dimensional channel of orbital magnetization. The electric control of the orbital magnetization and valley currents via a network of gated junctions will find useful applications in valley electronics.
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High Energy Physics (Experiment)

ParticleTransformer is all you need for reconstructing hadronic tau leptons

Nalong-Norman Seeba, Laurits Tani, Torben Lange et al. (+1 more)

The large number of $Z \rightarrow \tau\tau$ events expected during the TeraZ program at FCC-ee will allow for precision measurements and searches for physics beyond the Standard Model, requiring accurate reconstruction of hadronically decaying tau leptons. This reconstruction is particularly challenging due to the presence of undetected neutrinos and the diverse topology of hadronic tau decays, making the design of robust heuristic reconstruction algorithms challenging. In this work, we present the first fully machine learned hadronic tau reconstruction approach tuned for FCC-ee studies. The reconstruction is formulated as a set of complementary tasks, including tau identification, decay mode classification, charge reconstruction, and full four-momentum regression. The algorithms are evaluated on fully simulated electron-positron collision samples with realistic detector effects using the CLD detector setup. We compare dedicated task-specific models with a unified multi-task model and quantify their performance in a granular manner across all reconstruction tasks. Both approaches achieve per-mille-level tau mis-identification rates at high signal efficiency, decay mode classification F1 scores of up to 0.95 for the dominant channels, and sub-per-mille charge mis-identification rates, outperforming a conventional jet-charge estimator by up to two orders of magnitude. For the full kinematic reconstruction, the models achieve per-mille-level angular resolution and percent-level visible transverse momentum resolution, exceeding the performance of reconstruction-level jet observables. The resulting models provide a realistic high-performance solution for hadronic tau reconstruction at FCC-ee, offering identification, charge discrimination, decay mode analysis and full kinematic reconstruction.
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All authors Nalong-Norman Seeba, Laurits Tani, Torben Lange, Joosep Pata

Mathematical Physics · Cross-listed from math.PR

Stable size-biasing and the positive scale-mixture order of generalized Gaussian laws

Domingos S. P. Salazar

Let $X_r\sim N_r(0,1)$ be the centered unit-scale generalized Gaussian random variable with density proportional to $\exp(-|x|^r/2)$. We prove that, for $p,q>0$, there exists a strictly positive random variable $V$, independent of $X_q$, such that $X_p\stackrel{d}{=}VX_q$ if and only if $p\le q$. Moreover, the law of $V$ is unique. For $p<q$, put $a=1/p$, $b=1/q$, and $\alpha=b/a=p/q$. If $S_\alpha$ is a positive $\alpha$-stable random variable with Laplace transform $\mathbb{E}\exp(-uS_\alpha)=\exp(-u^\alpha)$, set $W_0=S_\alpha^{-b}$, let $W$ be the $W_0$-size-biased version of $W_0$, and define $V_{p,q}=2^{a-b}W$. Then $X_p\stackrel{d}{=}V_{p,q}X_q$. For $p>q$, the required Mellin quotient, viewed as the candidate characteristic function of $\log V$, is unbounded by Stirling's formula, and hence cannot be a characteristic function. The factor laws form a multiplicative cocycle, $V_{p,r}\stackrel{d}{=}V_{p,q}V_{q,r}$, for $p\le q\le r$, where the factors on the right-hand side are independent copies. Thus the Mellin quotient isolated by Dytso, Bustin, Poor and Shamai is realized constructively throughout the $p<q$ branch. In particular, $\Phi_{p,q}$ is positive definite exactly in the range $p\le q$, and the inverse Fourier–Mellin candidate density in the remaining $p<q$ branch is a genuine nonnegative probability density. The known Gaussian-base and bounded-parameter product cases are recovered as parts of a single positive scale-mixture classification.
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Cosmology and Nongalactic Astrophysics

CMBComp: A Simple and Accurate Compressed CMB Likelihood for Dark Energy, Curvature, and Massive Neutrinos

Amogh Srivastav, Prakhar Bansal and Dragan Huterer

We present CMBComp, a compact and accurate compressed cosmic microwave background (CMB) likelihood that captures the dominant geometric information of the full CMB likelihood derived from the combined SPT-3G D1 + ACT DR6 + Planck PR3 primary CMB anisotropy + Planck PR4/NPIPE CMB-lensing dataset, which we collectively refer to as SPA. The compression is fast to evaluate and trivial to implement in standard inference pipelines. We construct and validate it in five model spaces: the spatially flat cosmological-constant model ($\Lambda$CDM), and its dynamical-dark-energy ($w_0w_a$CDM), massive-neutrino ($\nu\Lambda$CDM), non-flat ($o\Lambda$CDM), and joint massive-neutrino–dynamical-dark-energy ($\nu w_0 w_a$CDM) extensions. Five compressed likelihoods are introduced, corresponding to two three-parameter compressions for the dark-energy sector (CMB-3 for $\Lambda$CDM and CMB-3w for $w_0w_a$CDM), two four-parameter compressions for the neutrino sector (CMB-4$\nu$ for $\nu\Lambda$CDM and CMB-4$\nu$w for $\nu w_0 w_a$CDM), and a four-parameter curvature compression (CMB-4k for $o\Lambda$CDM). Combining each compressed likelihood with the DESI DR2 baryon acoustic oscillation (BAO) data, we demonstrate that the resulting posteriors agree to high precision with those obtained from the corresponding full-CMB chains. CMBComp is therefore particularly well suited to cosmological inference for models that modify the late-time expansion history, enabling accurate CMB constraints to be incorporated into new analyses with minimal computational overhead and without reliance on a full Boltzmann-solver-based inference pipeline. The compressed likelihood files and example notebooks accompanying CMBComp are made publicly available at https://github.com/Amoghsriv/CMBComp.
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High Energy Physics (Theory)

Tropical WKB asymptotics of NRS coordinates for opers in $SU(2)$, $N_f=4$ theory

Vasilii Iugov

We study the semiclassical limit of SL_2-opers on the four-punctured sphere in Nekrasov-Rosly-Shatashvili Darboux coordinates. Using exact Wentzel-Kramers-Brillouin (WKB) connection formulae, we express the trace coordinates of the corresponding SL_2(C) character variety as finite Laurent sums of Voros exponentials. Tropicalizing these formulae and the NRS relations gives a chamberwise integer affine linear system for the leading logarithms of the NRS coordinates. In chambers where this system is unimodular and the selected cycles form a primitive symplectic pair, the leading asymptotics agree, up to flavor-period shifts, with Seiberg-Witten periods of the N=2 SU(2) theory with N_f=4 fundamental hypermultiplets. We verify this mechanism in a sample chamber and in the weak-coupling degeneration. No global coordinate-independent recovery theorem is claimed; non-unimodular or degenerate chambers are treated as limitations of the chosen NRS chart. In the weak-coupling degeneration, we show that the NRS chart can be chosen compatibly with the plumbing limit so that the resulting chamber is unimodular and non-degenerate away from tropical walls.
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Fluid Dynamics · Cross-listed from math.AP

Flow kinematics for equatorial coupled surface and internal waves

David Henry, Rossen Ivanov and Gabriele Villari

We study the propagation of coupled surface and internal equatorial internal waves. A model of two vertically stratified fluid layers with different constant densities is employed. Taking Coriolis forces into account, we derive explicit solutions to the linearized governing equations which assumes irrotational fluid motion in both layers separately, and further obtain the dispersion relation which determines the phase speeds of propagating surface and internal waves. We prove a result on solutions to the dispersion relations which greatly simplifies our subsequent analysis of the nonlinear dynamical systems which describe the motion of the fluid in the upper layer. Phase portraits for all possible streamlines in both fluid layers are presented, while furthermore a Lagrangian description of the fluid flow is obtained, and the particle trajectories of the fluid particles are determined.
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Materials Science

Magnetotransport Measurements on Isolated Polycrystalline Grains of Type-II Silicon Clathrate

Sam Saiter, Joseph P. Briggs, Yinan Liu et al. (+5 more)

The first low-temperature electronic transport characterization of individual polycrystalline grains of type-II silicon clathrate (Na$_x$Si$_{136}$, $x \ll 1$), isolated using microfabrication techniques, is reported. Structural characterization via Raman spectroscopy confirms that the isolated grains are largely devoid of amorphous silicon (a-Si). Temperature-dependent resistivity reveals multiple conduction regimes, including thermally activated freeze-out behavior and a transition to low-activation-energy transport at cryogenic temperatures, consistent with hopping conduction mechanisms. Hall measurements from 290 K to 3.5 K yield carrier concentration and mobility trends that correlate with the extracted activation energies, verifying $n$-type conduction. Additionally, gate-dependent conductivity measurements demonstrate electrostatic tunability at room temperature. Collectively, these results establish the magnetotransport parameters of single, isolated grains of type-II silicon clathrate and demonstrate the potential of this material for future quantum and optoelectronic devices.
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All authors Sam Saiter, Joseph P. Briggs, Yinan Liu, Audrey Faricy, Gavin Sher, Carolyn A. Koh, Reuben T. Collins, Meenakshi Singh

Applied Physics

Epitaxial Growth of Ultra-smooth ${\delta}$-NbN Thin Films on TiN-Buffered Sapphire by Room-Temperature Sputtering

Swagata Bhunia, Aakash Shandilya, Sounak Samanta et al. (+7 more)

The ${\delta}$ phase of Niobium Nitride (NbN) is a promising superconducting material, which is chemically stable and shares lattice compatibility with conventional III-Nitride semiconductors. Due to a high critical temperature (T$_{c}$) and a high critical (magnetic) field (H$_{c}$), NbN is much-coveted for a diverse set of applications spanning from single photon detectors, and hot-electron bolometers to quantum computing architectures using superconducting circuits. However, synthesizing high-quality epitaxial films of phase pure and stoichiometric ${\delta}$-NbN in a cost-effective manner, is challenging. In this study, we investigate the epitaxial growth of single crystalline ${\delta}$-NbN on TiN-buffered c-sapphire (Al$_{2}$O$_{3}$) substrates by sputtering at room temperature. For these films, we demonstrate a surface-roughness in picometer-scale, the lowest reported till date. The critical temperature (T$_{c}$) of the epitaxial ${\delta}$-NbN films was observed to decrease with the insertion of the TiN buffer layer, tentatively attributable to the leakage of Cooper pairs, due to the proximity effect. TiN and NbN layer behave as a bilayer system, wherein Cooper-pair leakage is facilitated by the absence of any oxide interlayer. Consequently, T$_{c}$ reduces with increasing thickness of the TiN layer.
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All authors Swagata Bhunia, Aakash Shandilya, Sounak Samanta, Bikash C Barik, Soumyadip Chatterjee, Parushottam Majhi, Siddarth Rastogi, Kantimay Das Gupta, Suddhasatta Mahapatra, Apurba Laha

Cosmology and Nongalactic Astrophysics

Covariance shrinkage for cosmological inference with Sellentin-Heavens-type likelihoods

Mattera Raffaele

Covariance matrices used in astronomical and cosmological parameter inference are often estimated from a finite number of simulations, so covariance uncertainty can affect posterior calibration and parameter constraints. We study covariance regularisation from the perspective of likelihood-based inference with simulation-estimated covariance matrices. First, we analyse scalar covariance scaling under the Gaussian plug-in likelihood and the covariance-marginalised Sellentin–Heavens likelihood. Using an expected negative log-likelihood loss, we show that Hartlap covariance-side scaling is recovered as the optimum under the Gaussian plug-in likelihood, whereas the unscaled sample covariance is optimal under the Sellentin–Heavens likelihood. This shows that scalar covariance corrections are likelihood-dependent and that an additional Hartlap-type global scaling is not favoured once covariance uncertainty is marginalised through the Sellentin–Heavens likelihood. We then introduce a shrinkage formulation in which the sample covariance is regularised towards a spherical target and the shrinkage intensity is treated as an auxiliary inferential quantity. A prior is assigned to the shrinkage intensity, the likelihood induces its posterior distribution, and the final parameter posterior is obtained by marginalising over it. Monte Carlo experiments show that shrinkage substantially improves covariance conditioning, while marginalisation over the shrinkage intensity propagates uncertainty about the amount of regularisation into posterior inference. The proposed approach provides a simple way to combine covariance-marginalised likelihood inference with structural regularisation of noisy simulation-estimated covariance matrices.
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