Solar and Stellar Astrophysics
Explosive Molecular Outflows
Luis A. Zapata
About fifteen years ago a new type of extreme (with kinetic energies of $\mathrm{E}_k \sim 10^{47-49}\, \mathrm{erg}$) molecular
outflows associated with very luminous ($\geq 10^5\, \mathrm{L}_\odot$) and massive (10$^3$ M$_\odot$) young clusters was confirmed, the Explosive Molecular
Outflows. This new class of
outflows is largely different from the classical bipolar protostellar flows, with spatial distributions made of numerous narrow straight filament- or streamer-like ejections in an almost isotropic arrangement and with clear Hubble–Lemaître-like expansion motions. Straight filaments point directly to the center of expanding molecular or ionized shells, which exhibit expansion velocities of about 10–50 km s$^{-1}$. However, no young massive
stars are clearly located there, probably because they moved to other places. These physical characteristics suggest that explosive
outflows are short-lived in nature and possibly generated by an energetic single and brief disrupting event. The most up-to-date theoretical model for explaining their nature involves the disruption of non-hierarchical massive protostellar systems, where members may either form a close binary (with separations of a few au) or merge into a single massive
star, as recently proposed for the nearest high-mass
star-forming region, Orion BN/KL.
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Geophysics
VORA: Rapid Association of Earthquake Phases from Local to Global
Junhao Song, Weiqiang Zhu, Haoyu Wang et al. (+3 more)
Earthquake phase association, which groups seismic phase arrivals into common origins, is a key step towards more complete and reliable seismicity catalogs. It has become a challenging task because of the massive phase
datasets produced from dense seismic networks and advanced phase picking methods. Here we present VORA (Voronoi tessellation- and Origin-time-based Rapid Associator), an efficient and scalable earthquake phase associator that treats association as an unsupervised spatio-temporal clustering problem. Specifically, VORA depends on two primary constraints: the estimated earthquake origin time (temporal) and seismic station adjacency (spatial). Recent advances in deep learning models have enabled detection of S- and P-phases with similar effectiveness, making it straightforward to estimate corresponding earthquake origin times from candidate phase pairs given a prescribed range of velocity ratios or directly from raw waveforms. We then leverage the Voronoi diagram to define each station's neighbors, cluster the origin times across neighboring stations, and apply an optional sub-clustering step to separate overlapping events.
Benchmarks on synthetic and real
datasets show that VORA achieves the fastest runtime and maintains robust performance (high recall and precision) even under intense seismicity. Applying it to a two-week global-scale pick
dataset covering the 2019 Ridgecrest earthquake sequence further demonstrates that the same framework scales from local networks to a global station set. VORA requires no training and generalizes across local-to-global regions, varying velocity models, and evolving network geometries, helping to meet the growing demands of expanding seismic networks and the increasing volume of automated phase picks.
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All authors Junhao Song, Weiqiang Zhu, Haoyu Wang, Utpal Kumar, Taka'aki Taira, Richard M Allen
High Energy Physics (Theory)
D-branes in $AdS_2 \times H^2 \times H^2$ under the non-Abelian T-duality
Ali Eghbali
We proceed to construct a non-Abelian dual pair for the $AdS_2 \times H^2 \times H^2$ background by applying the non-Abelian T-duality (here as Poisson-Lie T-duality on a semi-Abelian double). By using a certain parameterization of the $6$-dimensional Lie group ${A}_2 \otimes {A}_2 \otimes A_2$ we construct the original $\sigma$-model including the $AdS_2 \times H^2 \times H^2$ metric in the absence of $B$-field. It is shown that the dual background constructed by means of the Poisson-Lie T-duality is supported by a $B$-field and a metric whose contains a physical singularity. By studying the behavior of the dual spacetime at small $(r , y, u)$ coordinates, we show that the dual metric with a zero field strength and a non-trivial dilaton field make up a solution for the vanishing of the one-loop beta-function equations. Furthermore, at large $(r , y, u)$, it is shown that the $AdS_2 \times H^2 \times H^2$ solution is preserved under the non-Abelian T-duality. Finally, using the duality map obtained from the canonical transformation description of the Poisson-Lie T-duality for the gluing
matrix which locally defines the properties of the D-brane, we find seven different cases of the gluing
matrices for the $AdS_2 \times H^2 \times H^2$ $\sigma$-model and its dual pair. In this way, it is found a symmetric duality action on the branes linking together in a duality chain.
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Soft Condensed Matter
Growing, Buckling, and Swirling: motility from polymerization
Naveen Kumar D, Michael J. Shelley and Brato Chakrabarti
Locomotion in low-Reynolds-number environments is achieved through a remarkable diversity of strategies, from flagellar rotation and ciliary beating to large-scale body deformations. A distinct and biologically important class of propulsion arises when surface-anchored filaments grow and collectively reorient - as seen in the cellulose-extruding bacterium Acetobacter xylinum and in recent experiments on actin-propelled synthetic colloids inspired by the motility of Listeria monocytogenes - suggesting that polymerization itself is a generic route to self-propulsion. Developing a theoretical framework for this class of problems requires simultaneously resolving filament kinetics, their orientational dynamics, and fluid-structure interactions - all self-consistently coupled to the resulting locomotion. To address this, we formulate a continuum framework in which the active forces driving locomotion emerge self-consistently from filament nucleation, growth, catastrophe, and hydrodynamic interactions. We show analytically that polymerization-induced compressive forces drive a long-wavelength buckling instability, leading to spontaneous
symmetry breaking of the filament carpet and large-scale flows. In coupling this framework to a force- and torque-free motile spheroidal particle, a wide variety of behaviors emerge - this includes spontaneous spinning, directed motility, and
chiral swimming - whose selection is governed by the spatial patterning of polymerizing filaments. These results establish a general theoretical foundation for motility, driven by collective dynamics of polymerizing filaments and point towards new design principles for synthetic micron-scale swimmers.
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Earth and Planetary Astrophysics
The dynamical surface of Phobos: a morphodynamic atlas
Isabel Herreros and Sébastien Charnoz
Phobos evolves in a highly dynamical environment where surface-material motion is controlled by the combined effects of self-
gravity, time-dependent Martian tides, and inertial forces. In such a low-
gravity regime, the displacement of loose material, cannot be inferred from topographic slope alone, making a dynamical approach essential for interpreting Phobos' surface morphology and for supporting the Martian Moons eXploration (MMX) mission led by JAXA. Here, using our RAVEL code, we apply a dynamical model that combines the surface acceleration field with friction on a digital terrain model of Phobos to compute surface regolith trajectories. The model does not aim to predict the triggering of slope failure. Instead, it addresses where material would preferentially move once motion is initiated. This reveals large scale coherent dynamical regions and a sparse network of preferred regolith transport routes, termed here Regolith Migration Pathways (RMPs). The final positions of the RMPs correlate with smooth, low-relief terrains and spectrally neutral units, consistent with depositional mantles formed by long-term regolith infill, whereas rough, high-standing areas with abundant small craters and blue spectral slopes tend to correspond to dynamically active or denuded source regions. In contrast, spectrally red terrains are generally associated with dynamically quiet, morphologically rough surfaces where our model predicts negligible regolith motion, suggesting older, less frequently reworked units. Taken together, these patterns indicate that much of Phobos' surface morphology and spectral heterogeneity can be explained by long-term regolith redistribution driven by the surface acceleration field along RMPs. We provide a 3D morphodynamic atlas of RMPs across Phobos' surface, which will be useful for constraining the geographical provenance of samples to be collected by the MMX spacecraft.
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Materials Science
Connecting Diffuse Scattering to Atomic-Site-Resolved Occupancy and Displacement Fields through Fourier Filtering
Maksim Eremenko, Victor Krayzman, Matthew G. Tucker et al. (+1 more)
Local structural correlations are encoded in diffuse scattering, but identifying atomic motifs that produce specific diffuse features can be challenging. We introduce MOSAIC, a computational framework for this task when an atomistic configuration is available and a phase-bearing scattering amplitude can be calculated. Our approach relies on applying the
Fourier filter to this amplitude over the reciprocal-space regions encompassing the scattering features of interest to obtain maps of atomic displacements and site occupancies responsible for those features. The method is effective in interrogating the nature and spatial distributions of interatomic correlations in large-scale structural models, such as obtained using Reverse Monte Carlo refinements from experimental data, molecular dynamics, or Monte Carlo simulations, or 2D structural projections derived from atomic-resolution electron microscopy images.
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All authors Maksim Eremenko, Victor Krayzman, Matthew G. Tucker, Igor Levin
Nuclear Theory
Emulating Density Functional Theory Calculations via Empirical Interpolation
Daniel Lay, Pablo Giuliani and Kyle Godbey
Nuclear density functional theory (DFT) is a suitable tool for predicting
nuclear ground-state and fission properties. Statistical uncertainty quantification is desirable to make those predictions reliable, especially for
nuclei far from stability. However, the computational cost associated with describing deformed
nuclei in DFT makes such uncertainty quantification a challenge. In many solvers, the main computational bottleneck is the transformation of the wavefunction-dependent operators from coordinate to configuration space. We explore the use of the empirical interpolation method (EIM) to speed up the coordinate-configuration transformations, effectively constructing DFT emulators for ground-state and fission properties. To train and test the emulator we vary the model parameters across their realistic posterior distribution. We consider both a simplified one-dimensional model, and realistic axially-deformed
nuclei at the Hartree-Fock-Boguliubov (HFB) level. For realistic calculations, we consider sample
nuclei from across the chart, from $A=60$ up to $A=254$, as well as a highly-deformed fission isomer. We construct one emulator for each case, and study the binding energy, quadrupole deformation, and excitation energy of the fission isomer. In all
nuclei, for all observables considered, the EIM emulator agrees with the DFT value to the precision of the original DFT calculations, using as few as 100 HFB calculations to build the emulator. For a given
nuclear ground state or isomer, the emulator is able to predict all observables simultaneously. The emulator provides an order-of-magnitude speedup over the original solver, making EIM a suitable emulation scheme for DFT, especially when high precision is desired as in model calibration and fission. Thus, the EIM helps make statistical uncertainty feasible, improving the reliability of future predictions.
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Chaotic Dynamics · Cross-listed from q-bio.NC
Emergent Generalization by Representation Learning in Artificial Neural Networks
Hardik Rajpal and Dan Goodman
Dimensionality reduction has proven powerful for identifying neural
manifolds, which are low-dimensional structures underlying high-dimensional neural activity. These low-dimensional representations have improved the interpretability of population-level coding. Yet whether such low-dimensional representations are biologically relevant and confer functional advantages in learning systems, or merely reflect
neuron-level activity, remains contested in neuroscience. We show that an explicit information bottleneck forcing a recurrent neural network to learn a low-dimensional representation is necessary for rotational and out-of-distribution generalisation in a time-series prediction task. Using information-theoretic measures of causal emergence, we characterise the dynamics of this representation across the memorisation-to-generalisation transition, finding a non-monotonic trajectory which shows an initial decrease, a minimum, and a subsequent rise to a maximum, even as prediction loss falls monotonically. This trajectory scales with task complexity, and the magnitude of emergent structure reliably predicts generalisation performance. Analysis of hippocampal CA1 and medial prefrontal activity in rats learning an alternating maze task reveals analogous non-monotonic emergence dynamics that track behavioural performance. Together, these findings indicate that the ability of neural networks to learn compact, distributed and emergent representations confers a functional advantage for generalisation, supporting a causal role for learned representations in cognition.
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Materials Science · Cross-listed from cs.CE
Data-efficient continuous conditional denoising diffusion model for microstructure generation
Tarakram Ramgopal, Gowtham Nimmal Haribabu, Hussein Farahani et al. (+2 more)
Traditional computational models, such as cellular automata and phase-field methods, are effective for simulating microstructural
evolution but often face computational bottlenecks, limiting their application in high-throughput and on-demand process optimization. Generative machine learning approaches, such as denoising
diffusion models, have emerged as powerful tools for surrogate modeling of process-structure maps, specifically producing representative microstructures conditioned on process parameters. However, they often require large amounts of data for training, particularly when process conditions are continuous rather than discrete categorical variables. To address this, we present a continuous conditional denoising
diffusion model for generating microstructures conditioned on processing parameters. Trained on a compact
dataset of process-microstructure pairs, this framework first adds noise to microstructure images and then trains a neural network to progressively remove the noise, learning the underlying statistical patterns of the microstructure. To address data inefficiencies associated with continuously valued process conditions, we propose a vicinal-loss training strategy that associates process conditions in data-sparse regions with nearby conditions in the
dataset. Combined with classifier-free guidance and denoising
diffusion implicit sampling, this approach enables data-efficient continuous conditional generation of microstructures compared to classical denoising
diffusion models. The model successfully generates representative microstructures for low-carbon steel conditioned on manganese composition, matching key physical features such as phase and grain morphology, grain size distribution, phase fraction, and interfacial area distribution. More generally, this approach opens avenues for efficient process design and optimization of materials and their microstructures.
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All authors Tarakram Ramgopal, Gowtham Nimmal Haribabu, Hussein Farahani, Cornelis Bos, Siddhant Kumar
Astrophysics of Galaxies
Diffhalos: A Generative Model of Cosmological Lightcones of Dark Matter Halos
Georgios Zacharegkas, Andrew P. Hearin, Alan Pearl et al. (+3 more)
We present a generative model of cosmological lightcones of dark matter
halos, Diffhalos. In our model, we draw Monte Carlo samples of the
halo mass function in a lightcone with a JAX-based implementation of the
halo model, Halox, and we generate samples of subhalos by drawing from a model for the conditional subhalo mass function. We generate mass assembly histories (MAHs) using a normalizing flow trained on merger trees in cosmological N-body simulations. We show that Diffhalos can generate samples of
halos, subhalos, and their MAHs with a statistical distribution that accurately approximates populations in simulated lightcones. As an example application, we use Diffhalos to calculate gradients of the
halo and subhalo mass functions with respect to cosmological parameters. We conclude with a discussion of ongoing work using Diffhalos together with models of the
galaxy–
halo connection to make theoretical predictions for cosmological populations of
galaxies, and to generate mock
galaxy catalogs.
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All authors Georgios Zacharegkas, Andrew P. Hearin, Alan Pearl, Matthew R. Becker, Florian Kéruzoré, Sara Ortega-Martinez
High Energy Physics (Phenomenology)
Matter Profile Mismodeling as the Origin of the CP CPT Degeneracy in Long-Baseline Neutrino Oscillation
Bipin Singh Koranga and Vivek Kumar Nautiyal
We demonstrate that approximating the Earth's density profile with a single path averaged value instead of the spatially resolved Preliminary Reference Earth Model PREM generates a joint parameter degeneracy in the $(\delta_{\text{CP}}, \Delta_{\text{CPT}}, \theta_{\text{CPT}})$ space. At long baselines ($L \geq 5000\text{ km}$), this
geometric artifact becomes entirely indistinguishable from genuine Beyond the Standard Model (BSM) physics. While previous studies established individual channel biases separately, this work provides the first analytic proof that these biases form an extended two dimensional valley within the full three-parameter space. Furthermore, we rigorously demonstrate that multi channel combinations alone are insufficient to resolve this degeneracy. A Poisson loglikelihood chi square analysis confirms that DUNE like exposures utilizing a constant density approximation would erroneously report this artifact as a $\pm3\sigma$ BSM discovery. Specifically, at $L = 7000\text{ km}$, the constant-density assumption shifts the recovered $\delta_{\text{CP}}$ by $17.8^\circ$ and fabricates a spurious CPT violation at $\Delta_{\text{CPT}} = 4.1 \times 10^{-4}\text{ eV}^2$. Consequently, full spatially resolved PREM propagation is established as a strict mathematical requirement rather than an optional refinement for the correct physical interpretation of data from next-generation long baseline experiments, including DUNE, HyperKamiokande, and P2O.
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Optics
Phase-controlled transport of Floquet-driven compact chiral photonic states
Gabriel Caceres-Aravena, Paloma Vildoso, Helena Drüeke et al. (+1 more)
The Aharonov-Bohm (AB) effect remains a cornerstone of fundamental and applied physics. In this work, we utilize the AB caging effect originated from an effective
magnetic field induced by multiorbital interactions, creating an all flat band (FB)
lattice system. Normally, FB states are known for being compact in space and having a zero tail; therefore, their mobility in a linear environment is generally understood as impossible. We propose a Floquet driving protocol in an all-FB photonic system to fully control the dynamics of localized photonic states. The modulation of the
Hamiltonian along the propagation coordinate allows the translation of compact states in the direction of constructive interference, resulting in an effective stroboscopic
quantum walk-like effect. We find that the traveling states exist in
chiral pairs. We experimentally implement the Floquet driven protocol using femtosecond
laser written photonic waveguides and demonstrate directional control of the propagation, determined by the relative phase of the input condition.
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All authors Gabriel Caceres-Aravena, Paloma Vildoso, Helena Drüeke, Rodrigo A. Vicencio
Quantum Physics
Optimal Average Success Probabilities of Binary $(n,n-1)$ and $(n,n-2)$ Quantum Random Access Codes
Shuo Tan and Syed A. Jafar
A binary $(n,m)$
quantum random access code (QRAC) compresses an $n$-bit classical string into an $m$-
qubit quantum state, from which a decoder attempts to recover a randomly selected target bit. Of particular interest is the optimal average probability of success, $P^{Q,\mathrm{avg},\mathrm{opt}}_{n,m}$, which was numerically conjectured to satisfy the bound $P^{Q,\mathrm{avg},\mathrm{opt}}_{n,m}\leq \frac{1}{2}+\frac{1}{2}\sqrt{\frac{m}{n}}$. Recent constructions of $(n,n-1)$ QRACs by Suzuki and $(n,n-2)$ QRACs by Akibue et al. meet this bound exactly, raising the question of their strict optimality. In this work, we settle this question by proving the conjectured upper bound for $m\in\{n-1,n-2\}$, thereby precisely determining $P^{Q,\mathrm{avg},\mathrm{opt}}_{n,n-1}$ and $P^{Q,\mathrm{avg},\mathrm{opt}}_{n,n-2}$. The proof utilizes a translation recently studied by Lin and de Wolf from local to global reconstruction via pretty good measurement, along with dimensional and positive-semidefinite constraints on an induced channel.
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High Energy Astrophysical Phenomena
Fermi-Large Area Telescope Detection of Very High Energy (>100 GeV) Emission from Compton-Dominated Blazars
P N Naseef Mohammed, Vaidehi S. Paliya and C D Ravikumar
The observation of broad emission lines in the optical spectra of flat-spectrum
radio quasars (FSRQs) suggests radiatively efficient
accretion powering these objects. In such broad emission line blazars, the intense broad-line region (BLR) radiation can provide seed
photons for inverse Compton scattering, leading to a Compton-dominated spectral energy distribution. Interestingly, the same BLR
photon field can also absorb very high-energy (VHE; E>100 GeV) $\gamma$-ray radiation, thus explaining the paucity of VHE-detected FSRQs. Here we report the results of a systematic search to identify VHE-emitting sources in a sample of 626 Compton-dominated blazars (Compton dominance > 1), using $\sim$17.5 years of
Fermi-Large Area
Telescope observations. We identified 14 blazars at greater than 4$\sigma$ confidence level, including 4 sources detected in the VHE band at high significance (> 5$\sigma$) for the first time. We also found 21 objects from which at least one VHE
photon was detected, thus substantially expanding the known VHE FSRQ population. Investigating the temporal coincidence of the VHE
photons with the $\gamma$-ray activity, we noticed the VHE emission to be detected during flaring as well as low jet activity epochs. By estimating the optical depth for the $\gamma$$\gamma$ absorption due to the BLR
photon field, we constrained the VHE-emitting region to be located outside BLR (>1.1-1.4$\times$ BLR radius). We conclude that multi-wavelength followup observations of these enigmatic VHE-detected broad line blazars will permit us to constrain the radiative processes responsible for the GeV-TeV emission, and will set the
benchmark for their observations with the upcoming Cherenkov
Telescope Array Observatory.
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High Energy Physics (Phenomenology)
Lorentz-Violating Photon Decay into Neutrinos and Constraints from PeV Photon Stability
Zurab Kepuladze
We study the
vacuum decay of a Lorentz-violating
photon into a
neutrino-antineutrino pair. Lorentz-violating corrections to the
photon dispersion relation are parametrized through an effective invariant mass $m_{\mathrm{eff}}^{2}=k_{\alpha}k^{\alpha}$. This makes the otherwise forbidden decay $\gamma\to\nu\bar{\nu}$ kinematically allowed. The process proceeds through the Standard Model one-loop
neutrino electromagnetic vertex and is therefore strongly suppressed. Using the low-$q^{2}$ anapole form factor, we derive the decay rate and apply it to TeV and PeV
photons. We find that below the electron-positron threshold the
neutrino channel is open but generally too slow to provide stronger constraints than existing bounds. Above the threshold, $\gamma\to e^{+}e^{-}$ dominates unless the relative
photon-electron LIV parameter closes this channel. In that case, the
neutrino decay gives an independent constraint on
photon-
neutrino relative LIV parameters.
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Earth and Planetary Astrophysics
The muon Moonshot: Moon subsurface tomography with upward-going muons
Zimo Hu, Leyun Gao, Zhengyun You et al. (+6 more)
We propose a novel
muon Moonshot concept for lunar subsurface
tomography based on upward-going
muons originated from the lunar regolith. Unlike the Earth, the Moon lacks an atmosphere, leaving a dense regolith below and a near-
vacuum environment above. Consequently, while most downward-going
hadrons are absorbed before decaying, upward-going
hadrons escaping the regolith can decay in flight, producing a significant source of lunar
muons. These
muons are detectable by instruments on the lunar surface or in near-lunar orbit. We perform Monte Carlo simulations to investigate their energy spectra, angular distributions, and integrated fluxes under various theoretical and detector configurations. The results indicate that the lunar
muon flux is sensitive to detector altitude under a flat-terrain assumption, demonstrating its potential as a novel non-invasive probe of shallow subsurface voids. We also present case studies on the detection of underground cavities and water resources, with cavity-induced flux variations observable in less than two minutes and weaker water signals distinguishable after about 36 minutes of data collection with a $1~\mathrm{m^2}$ detector, and discuss potential implementations in future lunar missions.
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All authors Zimo Hu, Leyun Gao, Zhengyun You, Qite Li, Qiang Li, Yuhong Yu, Liangwen Chen, Xueheng Zhang, Zhiyu Sun
Atomic Physics
On the measurability of Wigner time delays at shape resonances in photodetachment of polyatomic anions
Jan Dvořák, Jakub Benda, Thomas N. Rescigno et al. (+3 more)
The energy dependence of the complex phases of electron continuum wave functions carries information about electron dynamics. Streaking and attosecond interference experiments (called RABBIT) seek to measure this energy dependence, and therefore, the time delays of ionization. The long-range Coulomb interaction dominates in those experiments, and can obscure the low-energy features of the Wigner time delays that are the object of the measurement. Photodetachment of electrons from negative ions has no long-range Coulomb interaction, and RABBIT and streaking measurements of photodetachment delays have the potential to reveal time delays of up to one femtosecond in low-energy features. We predict the results of such experiments on a particularly interesting polyatomic example, the nitrate anion (NO$_3^-$), for both valence and core electron detachment. We simulate the experiments in these cases and analyze the underlying physics of measurements on polyatomic anions where many electron partial waves contribute and find that the angular dependence of the measured delays generally differs from the Wigner delays. However, we demonstrate that measurements performed for ejection directions close to the polarization of the light sources can directly access the Wigner delays that give a time-dependent window on electron-molecule interactions. A promising experiment involving core photodetachment of NO$_3^-$ with X-rays is proposed.
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All authors Jan Dvořák, Jakub Benda, Thomas N. Rescigno, Cynthia S. Trevisan, Robert R. Lucchese, C. William McCurdy
High Energy Astrophysical Phenomena
Strongly interacting matter with criticality induced by modified excluded volume in core-collapse supernova simulations
Anil Kumar, Noshad Khosravi Largani, Stefan Typel et al. (+3 more)
This article reviews critically the core-collapse
supernova explosion mechanism associated with a sufficiently strong first-order phase transition from normal
nuclear, in general hadronic matter to deconfined
quark matter, which commonly assumes Gibbs conditions for the coexistence of phases and a phase transition construction accordingly. To this end, a novel class of multi-purpose equation of state (EOS) is developed, based on the modified excluded volume (MEV) approach employing a medium-dependent excluded-volume functional within the relativistic mean field framework with density-dependent
meson-nucleon couplings. The chosen MEV parametrisation features the change in the number of degrees of freedom, mimicking the EOS softening in excess of
nuclear saturation density, featuring a first-order phase transition with van der Waals like behaviour and the presence of a critical point at high temperatures. Simulations of core-collapse
supernovae are performed, based on general relativistic
neutrino radiation hydrodynamics in spherical
symmetry, in order to explore the previously reported
supernova explosion scenario within this class of phenomenological modified microscopic hadronic EOS. A burst-like
neutrino signature is released, substantially longer than previously reported based on common
hadron-
quark hybrid model EOS with two-phase approach and Gibbs phase-transition construction, as observable signal, which is complemented by a gravitational wave mode analysis.
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All authors Anil Kumar, Noshad Khosravi Largani, Stefan Typel, Pablo Cerdá-Durán, Alejandro Torres-Forné, Tobias Fischer
Materials Science
The evolution of AI from image interpretation toward scientific inference in nanoparticle electron microscopy
Evropi Toulkeridou, Jiafei Li, Leonardo Lari et al. (+1 more)
Artificial intelligence (AI) is transforming electron microscopy by enabling quantitative analysis of increasingly large and complex
datasets for nanoparticle characterization. Recent advances in machine learning (ML) and deep learning (DL) have expanded microscopy from a descriptive imaging technique into a data-driven platform for structural interpretation, dynamic analysis, and scientific inference. This review examines AI methodologies for nanoparticle electron microscopy, focusing on transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), scanning transmission electron microscopy (STEM), and in situ TEM. The discussion is organized around the principal challenges in nanoparticle characterization, including particle detection,
segmentation, morphology quantification, atomic-resolution restoration, defect identification, two-dimensional-to-three-dimensional structural inference, and analysis of dynamic processes in situ. We review computational approaches from conventional ML and convolutional neural networks to
transformer architectures, self-supervised learning, foundation models,
multimodal AI, and physics-informed learning. We further discuss integrating microscopy data with simulations, metadata, and autonomous experimentation to relate nanoparticle structure, dynamics, synthesis conditions, and functional properties. The advantages, limitations, benchmarking, and data requirements of current methodologies are critically assessed. Finally, emerging opportunities for foundation models, AI-guided microscopy, closed-loop experimentation, and autonomous materials discovery are discussed. By integrating advances across computer
vision, materials informatics, and electron microscopy, this review highlights the role of AI in next-generation nanoparticle characterization and accelerated materials discovery.
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All authors Evropi Toulkeridou, Jiafei Li, Leonardo Lari, Panagiotis Grammatikopoulos
Statistical Mechanics
Revisiting the non-equilibrium phase transitions of the continuous-trait Axelrod model
Sandro M. Reia, Paulo R. A. Campos and José F. Fontanari
We investigate the non-
equilibrium phase transitions of the continuous-trait Axelrod model, an
agent-based framework where individual culture is represented by a vector of $F$ continuous features confined to the interval $(0,1)$. Local interactions are governed by a metric similarity threshold $d$, which acts as a continuous control parameter of social tolerance. The dynamics inevitably freeze into one of two absorbing configuration classes: an ordered, homogeneous monocultural state at high tolerance, or a highly fragmented, disordered state at low tolerance. While previous studies characterized the transition as hybrid based on the continuous behavior of the domain density $\mu$ alongside a discontinuous jump in the largest domain fraction $\rho$, we show that this apparent continuity is an artifact of severe finite-size masking effects. By shifting the methodological focus to the scaling of the median $\tilde{\mu}$ and analyzing the full probability distributions $P(\mu)$, we unveil a clear bimodal structure with disjoint maxima across independent simulation runs. Our results reveal that for $F=2$, the system undergoes a genuinely hybrid transition in the contemporary sense, featuring a tiny but finite latent jump ($\mu_c \approx 0.089$) at the critical threshold $d_c \approx 0.0784$ while scaling toward it from below via a non-analytical power law with a mean-field exponent $\beta \approx 1/2$. Conversely, for $F=3$, the higher trait-space dimensionality suppresses local fluctuations, yielding a traditional, non-hybrid first-order transition. We apply this framework to the alternative discrete Poisson variant of the model, successfully confirming its known continuous transition for $F=2$ and discontinuous, non-hybrid transition for $F=3$, thereby establishing a unified characterization of phase transitions in Axelrod-like systems.
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Materials Science
Why Do Thick MOCVD-Grown beta-Ga2O3 Epilayers on (001) Substrates Crack: Crystallographic Origin
Martin Frentrup, Indraneel Sanyal, Dan Lamb et al. (+5 more)
Thick, defect free epitaxial layers grown using industry standard techniques are a fundamental requirement for the widespread adoption of fully vertical power devices based on ultra wide bandgap gallium
oxide (Ga2O3). However, metal-organic chemical vapour deposition (MOCVD) of such layers on native beta-Ga2O3 substrates with the largest diameter (001) orientation remains relatively unexplored, and the origins of the reported surface roughening and cracking with increasing thickness are not yet fully understood. To address this, we report a systematic study of MOCVD grown beta-Ga2O3 epilayers deposited at growth rates of ~3.5 um/h, with thicknesses from 0.3 to 3.5 um. The epilayers exhibit a relatively smooth but striated surface morphology, with progressively increasing nanometre-scale roughness beyond coalescence and crack formation observed from ~1.8 um thickness. High resolution X ray diffraction reveals that, despite growth on (001) substrates, the epilayers adopt a predominantly (-401)-oriented structure from the earliest stages of growth. Rocking curve analysis further indicates a higher degree of in-plane twist than tilt, both decreasing with increasing epilayer thickness. While the epilayer and substrate are
lattice-matched along the [010] in plane direction, the epitaxial
alignment in the orthogonal epilayer [104] in plane direction imposes, in theory, a maximum tensile in-plane strain of approximately +4.1% arising from the underlying
lattice mismatch, thereby driving crack formation perpendicular to this direction. Our results suggest that this epitaxial relationship is likely associated with faceted reconstruction of the (001) substrate surface during annealing, driven by the minimisation of surface energy under oxygen-rich MOCVD growth conditions.
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All authors Martin Frentrup, Indraneel Sanyal, Dan Lamb, Ciaran P. Llewelyn, Jonathan Evans, Owen J. Guy, Mike Jennings, Saptarsi Ghosh
Soft Condensed Matter
Numerical analysis of capillarity-driven thinning rheometry for polydisperse polymer solutions
Isaac Pincus, Vincenzo Calabrese, Simon J. Haward et al. (+1 more)
Liquid bridges of
polymer solutions that are self-thinning due to the action of capillarity undergo a transition from Newtonian-like linear thinning to exponential elastocapillary (EC) thinning when the
polymer chains are stretched by the elongational flow and the resulting elastic contribution to the stress exceeds the viscous stress. As the Oldroyd-B model predicts that the EC thinning rate is set by the relaxation time ($\tau$) of the
polymer, the characteristic thinning timescale extracted from the exponential decay ($\tau_{EC}$) is commonly interpreted as a direct measure of $\tau$. Here we show that for real polydisperse
polymer solutions, $\tau_{EC}$ reflects only a subset of the molecular weight (MW) distribution – those chains actively stretched by the flow. We demonstrate this using a multi-mode FENE-PM model that explicitly incorporates the molecular weight distribution, validated against the filament thinning experiments of Calabrese et al. [Phys. Rev. X 15, 021025 (2025)] on bidisperse blends of narrowly-distributed low-MW and high-MW polystyrene solutions. The model predicts that only chains with effective Weissenberg number $Wi = \dot{\varepsilon} \tau > 1/2 $ are extended by the flow and contribute elastic stress; this threshold naturally favors high molecular weight species, whose longer relaxation times allow them to remain stretched throughout the elastocapillary regime. The measured $\tau_{EC}$ is therefore set by this stress-contributing sub-ensemble rather than the full distribution. Further, our model predicts that $\tau_{EC}$ depends on both the molecular weight distribution and total
polymer concentration, as well as experimental parameters including pre-stretch and initial filament diameter, confirming that it is best understood as an experiment-specific quantity rather than an intrinsic fluid property.
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All authors Isaac Pincus, Vincenzo Calabrese, Simon J. Haward, Gareth H. McKinley
Quantum Physics · Cross-listed from cs.SE
Model-Driven Digital Twin Framework for Quantum Networks
Amal Elsokary, Hayato Ishida, Ran Wei et al. (+2 more)
Quantum networks are advancing towards larger and more operational infrastructures, yet their evaluation remains fragmented across heterogeneous physical platforms, simulators, protocols, and architectural abstractions. Current digital-twin studies for
quantum networks mainly realise isolated capabilities or application-specific solutions rather than reusable system-level twins. This paper argues that Model-Driven Engineering (MDE) can provide a systematic basis for integrating and evolving these heterogeneous artefacts. It derives requirements for design-time evaluation and runtime synchronisation, and proposes a progression of architectures from code-driven and domain-model-driven solutions to point-to-point and hub-and-spoke integration. A conceptual implementation case study illustrates this using SysML v2, QKD kit, an EMF-based controller, and SeQUeNCe. The work provides a foundation for adaptable and interoperable digital twins for
quantum networks.
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All authors Amal Elsokary, Hayato Ishida, Ran Wei, Michael J. de C. Henshaw, Siyuan Ji
Applied Physics · Cross-listed from eess.SP
Non-Reciprocal Dynamic Metasurface Antenna: Practical Multiport-Network Modeling and Optimization for Multi-User Interference Resilience
Shuai S. A. Yuan, Jean Tapie, Bahman Amrahi et al. (+2 more)
Channel reciprocity fundamentally limits full-duplex (FD) base stations due to multi-user co-channel interference. We examine the potential of deploying a non-reciprocal dynamic metasurface
antenna (NR-DMA) at the base station to overcome this limitation. Our NR-DMA architecture connects a single circulator to three feed ports of a multi-feed DMA with strong mutual coupling (MC) between its seven feeds and 96 1-bit-programmable meta-elements. We model our system with multiport network theory, using experimentally estimated proxy parameters of a fabricated 19-GHz DMA and the measured circulator response. Our NR-DMA's reconfigurability is captured by a diagonal tunable scattering
matrix, showing that non-reciprocal DMAs and RISs need not require a "beyond-diagonal" tunable scattering
matrix. We jointly optimize the DMA state, analog feed weights, circulator-port assignment, and circulation direction. Our optimized NR-DMA realizes distinct forward and reverse channel responses. In our interference-limited high-SNR case study, the NR-DMA improves the FD sum rate by about 60% over a reciprocal DMA
benchmark. Comparisons with proxy objectives and MC-unaware optimization show that end-to-end FD optimization and MC-aware modeling are both essential.
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All authors Shuai S. A. Yuan, Jean Tapie, Bahman Amrahi, Viktar Asadchy, Philipp del Hougne
Materials Science
Anomalous Compressibility and Electronic Robustness of Metallic Delafossite PdCoO$_2$ under Pressure
Cheng Peng, Pahuni Jain, Tyler Harper et al. (+2 more)
The layered delafossite PdCoO$_2$ is an exceptional
oxide metal whose ultrahigh conductivity arises from a Pd-derived nearly-free-electron band. Here, high-pressure single-
crystal X-ray diffraction combined with first-principles calculations is used to investigate its structural, bonding, and electronic
evolution up to 10 GPa. PdCoO$_2$ retains the rhombohedral R-3m structure throughout the investigated pressure range, with no structural phase transition. The
lattice exhibits an unusual anisotropic compression, with the in-plane a-axis contracting more strongly than the stacking c-axis, opposite to the behavior of most layered materials. Despite this anomalous compressibility, only minor changes are observed in the local Pd-O and Co-O coordination environments, indicating a remarkably rigid bonding framework.
Crystal orbital Hamilton population analysis reveals only subtle strengthening of the existing bonding interactions, without the emergence of destabilizing Pd-related antibonding states. Consistent with these findings, the Pd-derived metallic band and quasi-two-dimensional
Fermi surface remain essentially unchanged under compression. Boltzmann transport calculations further show that the in-plane conductivity is nearly pressure-independent, whereas the out-of-plane conductivity decreases modestly, resulting in a slight increase in transport anisotropy. These results demonstrate that the anomalous compressibility of PdCoO$_2$ originates from its robust chemical bonding network, which preserves both the
crystal structure and the highly conductive Pd-derived metallic state under pressure.
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All authors Cheng Peng, Pahuni Jain, Tyler Harper, Chris Leighton, Weiwei Xie
Quantum Physics
Gram-Certified Resource Continuation for Structured Quantum Representation Audits
Azadeh Alavi, Fatemeh Kouchmeshki, Hossein Akhoundi et al. (+1 more)
Dense representation of an $n$-
qubit pure state requires $2^n$ complex amplitudes, precluding dense classical materialization at large $n$. We develop Gram-certified resource continuation for structured
quantum-representation workloads and ask when a solution obtained under a lower-cost resource model remains a justified initialization for a richer one. For coarse and fine state ensembles connected by a declared isometry, fine, coarse, and cross complex amplitude overlaps form a positive-semidefinite block Gram
matrix. A signed operator of dimension at most twice the sample count has the nonzero signed spectrum of the fine density minus the lifted coarse density, yielding trace- and operator-norm diagnostics without constructing either density operator. We prove that a coarse weighted spectral flag with objective suboptimality $\delta_c$ has fine-level suboptimality at most $\delta_c+2\varepsilon$, where $\varepsilon$ is the empirical trace distance; the factor two is attainable. We distinguish encoder change from exact feasible-family prolongation, give a gap-dependent subspace-stability test, and show that continuation cannot overcome a final Schmidt-rank ceiling. In deterministic synthetic controls over an 8-to-40-
qubit ladder, exact ancilla lifts agree to numerical precision. Transferred initialization reduces final-rung block updates from 30 to 20, but the complete cascade costs $4.80$–$5.43$ times a direct final-rung solve, without material objective improvement. Reordering eight Bell pairs reduces the maximum
matrix-product-state bond from 256 to 2. Thus continuation is justified only when cross-rung mismatch, feasible-family inclusion,
topology, and total work jointly satisfy prespecified audits. These noise-free classical results neither establish generic 40-
qubit simulability nor claim hardware performance or
quantum advantage.
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All authors Azadeh Alavi, Fatemeh Kouchmeshki, Hossein Akhoundi, Abdolrahman Alavi
Astrophysics of Galaxies
Magnetically Arrested Discs Powering Jets in a Large Sample of Low-Accretion FR I Radio Galaxies
Huibo Fei, Han He, Bei You et al. (+4 more)
We study a sample of 289 Fanaroff-Riley type I (FR I)
radio galaxies selected from the LOFAR Two-Metre Sky Survey (LoTSS) DR1, identified by their edge-darkened
radio morphologies. Using Sloan Digital Sky Survey (SDSS) DR17 optical photometry and spectroscopy, we derive Eddington-scaled
accretion rates spanning -6.84 < log $\dot{m}$ < -0.87 (median $\approx$ -2.84). The vast majority of sources lie below $\dot{m}$ = 0.01, indicating that their central engines are well described by advection-dominated
accretion flows (ADAFs). However, even for a rapidly spinning black hole with a = 0.95, the maximum jet power predicted by the Blandford-Znajek mechanism in the standard ADAF regime is lower than the observed jet power (estimated from 151 MHz
radio luminosity) for approximately 70% of the sample. We demonstrate that the magnetically arrested disc (MAD) scenario, in which large-scale poloidal
magnetic flux accumulates near the event horizon, can fully account for the powerful jets observed in these low-
accretion systems. Within the MAD framework, the data are consistent with slow-spinning black holes with $a < 0.5$. This large, uniformly selected LoTSS sample extends the MAD requirement previously established for the bright 3CR FR I population, indicating that magnetically arrested discs are common in FR I
radio galaxies across a wide range of luminosities.
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All authors Huibo Fei, Han He, Bei You, MinFeng Gu, Liang Chen, Xuheng Ding, Leyi Wang
Mesoscale and Nanoscale Physics
Staggered orbital magnetization from itinerant electrons: orbital antiferro- and ferrimagnetic phases
Lucas L. Lage, Kevin J. U. Vidarte, Tarik P. Cysne et al. (+3 more)
Because electronic orbital angular momentum in solids is inherently non-local, its contribution to magnetism is usually cast in terms of a net orbital magnetization. Here, we show that itinerant electrons can generate orbital
magnetic phases with
ferromagnetic,
antiferromagnetic, or ferrimagnetic orders. We demonstrate this possibility in a honeycomb
lattice, using both the standard and a modified Haldane model. Employing real-space formulations, we decompose the itinerant orbital magnetization into sublattice contributions, $M_A$ and $M_B$. Their net ($M_z=M_A+M_B$) and staggered ($M_z^s=M_A-M_B$) combinations are then used to identify the orbital order. By varying the sublattice potential and the
Fermi energy, we find distinct regimes: a (PT)-symmetric orbital antiferromagnet in the modified Haldane model, an orbital ferromagnet in the standard Haldane model, ferrimagnetic metallic states where net and staggered orbital magnetizations coexist, and insulating regimes in which the ferro- and
antiferromagnetic orbital characters can be interchanged. These findings are explained by a low-energy theory in terms of two distinct valley mechanisms: valley-dependent Dirac masses in the standard Haldane model and valley-dependent energy shifts in its modified version.
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All authors Lucas L. Lage, Kevin J. U. Vidarte, Tarik P. Cysne, Tatiana G. Rappoport, A. Latgé, R. B. Muniz
Astrophysics of Galaxies
Spectral Energy Distributions of Globular Clusters in VV191a
Ashton Cardona, Timothy Carleton, Jessica Berkheimer et al. (+9 more)
We investigate globular cluster (GC) candidates associated with the elliptical
galaxy VV191a using JWST NIRCam and archival HST imaging. Beginning with an initial catalog of over 500 candidate sources, we apply morphological filtering, photometric
redshift selection, and spectral energy distribution (SED) fitting using BAGPIPES to isolate a refined sample of 61 probable GCs, including a high-confidence subset of 20 objects. The derived age distribution is concentrated between ~ 6-10 Gyr, with a peak near ~ 8 Gyr, while
metallicities are predominantly near and super-
solar. Unlike many GC systems in elliptical
galaxies, the VV191a sample does not exhibit a clear bimodal
metallicity distribution. Derived
stellar masses span a broad range and suggest significant degeneracies related to
dust attenuation and foreground contamination from the overlapping spiral
galaxy VV191b. These results support the presence of an evolved GC population in VV191a while highlighting limitations imposed by broadband SED fitting and foreground contamination
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All authors Ashton Cardona, Timothy Carleton, Jessica Berkheimer, Rogier A. Windhorst, Seth Cohen, Rolf Jansen, Anton M. Koekemoer, Gibson Bowling, Patrick Kamieneski, Jakob Perivolotis, Tyler Hinrichs, Christopher Willmer
Optics
Train-Resolved Statistical Recovery of Weak SAXS Signals in Liquids at the European XFEL
Carles Serrat, Asier García, Biel Serrat et al. (+11 more)
We present a train-resolved SAXS methodology for recovering weak scattering signals from high-repetition-rate XFEL
datasets and apply it to aqueous L-cysteine solutions measured at the European XFEL. Independent scale-plus-offset fitting was performed for matched cysteine and water train pairs, followed by subtraction of transmission-matched water–water controls. The 0.5 M
dataset reveals a reproducible sign-changing residual SAXS signal that increases with incident XFEL transmission and remains after removal of detector-wide scaling, additive offsets, and matched water–water control residuals. Convergence and block-averaging analyses show that the residual emerges progressively as independent train pairs are accumulated and exhibits uncertainty scaling close to the expected inverse square-root dependence on N. These results establish a statistically robust transmission-dependent residual SAXS contribution whose microscopic origin remains unresolved, while demonstrating that train-resolved observables combined with matched controls can substantially improve sensitivity to weak scattering signals in high-repetition-rate XFEL experiments.
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All authors Carles Serrat, Asier García, Biel Serrat, Angelo Beratto-Ramos, Johan Bielecki, Huijong Han, Sara Hernández, Tokushi Sato, Joana Valerio, Mohammad Vakili, Egor Sobolev, Katerina Doerner, Chan Kim, Majed Chergui