Instrumentation and Methods for Astrophysics
Assessing the Predictability of $\delta$ Scuti Variable Stars for Spacecraft Navigation
Ahmed Khan, Linyi Hou and Siegfried Eggl
Previous studies have shown that $\delta$ Scuti
stars can be used for determining spacecraft position and time similar to X-ray
pulsar navigation, but open questions remain regarding the light-curve stability, and, therefore, the
navigation accuracy that can be derived from $\delta$ Scuti variable
stars. Here, we develop a computational framework to identify $\delta$ Scuti variable
stars with light curves that are suitable for spacecraft
navigation purposes. Our approach emphasizes quantifying timing uncertainty through developing metrics and evaluating such metrics in the context of spacecraft
navigation. We analyze over 110 $\delta$ Scuti variable
stars from the Kepler space
telescope and 10 additional
stars from the K2 mission. For each
star, we produce a simple model of its normalized flux as a function of time, along with several metrics used to assess its suitability for
navigation. Model quality was further assessed through comparing predictions with observations from the Transiting
Exoplanet Survey Satellite (TESS). Out of the 120 $\delta$ Scuti variable
stars we investigated in this study, 32
stars were identified as candidates predictable enough to enable spacecraft
navigation.
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Quantum Physics
A Coherence Law for Trainability in Noisy Equivariant Quantum Neural Networks
Hassan Ugail and Newton Howard
Symmetry provides a
quantum neural network structure, but on its own it does not keep the network trainable once noise is present. We ask which physical quantity decides whether the gradients of an equivariant
circuit survive decoherence, and we answer with a compact training law. Working with U(1)-equivariant brickwork
circuits that conserve a charge, we find that two distinct effects govern a trainable gradient. Causality fixes where the gradient can live, confining it to the backward light cone of the readout inside the active charge sector. Coherence then determines how fast it decays through the contraction of the off-diagonal sector modes that the projected readout can actually observe. We prove a light-cone reduction that pins the noiseless gradient to the sector-restricted cone with a lower bound independent of the total
qubit number, and we define a readout-visible aligned coherence rate as a Rayleigh quotient of the noise generator along the gradient-carrying mode. A perturbative open-system analysis turns this rate into a leading-order training law. Density-
matrix simulations then confirm that the finite-noise degradation follows a single accumulated variable built from noise depth and coherence contraction, with a coefficient of determination of 0.979. The sharpest test comes from a correlated-dephasing channel that has a large worst-case rate but a near-zero aligned rate. The law predicts no gradient loss for this channel, and none is seen. Sector coherence outperforms every standard channel diagnostic we compare it against, and the analysis identifies readout-visible sector coherence as the quantity that links equivariant architecture, open-system dynamics and noisy trainability.
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Chemical Physics
Unsupervised Thermodynamics of Molecular Diffusion Models: Action-Operator Semantics and Auditable Free-Energy Readout
Wenjie Xi
Diffusion models are increasingly utilized for modeling molecular structures and conformational ensembles, yet the thermodynamic meaning of their learned representations and scores remains elusive. To resolve this ambiguity, we introduce a mathematically consistent action-operator framework natively compatible with
diffusion models. By defining a fixed molecular environment as a base action $S_0(x)$ and an alchemical perturbation as an operator $O(x)$, standard
diffusion noising induces effective noised actions and operators whose gradients and alchemical derivatives are directly represented by the model's learned fields. This rigorous self-consistency enables a “noisy operator bridge” capable of reading out free-energy differences ($\Delta F$) from endpoint ensembles and per-frame evaluations. In controlled experiments on alanine dipeptide systems, we show that incorporating physical inductive biases enables partial recovery of the base action and perturbation operator. When applied to a challenging C6-H to C6-F ligand-pocket nonbonded perturbation (185L/IND) with negligible phase-space overlap, our supervised bridge estimates the alchemical $\Delta F$ within approximately $1\ k_\mathrm{B}T$ of a stable 19-state MBAR reference. Finally, we demonstrate that endpoint coordinates and binary labels alone are sufficient to partially recover the operator shape and a centered free-energy scale without any force or action supervision. This work provides a rigorous path toward transforming generative molecular
diffusion models from black-box coordinate samplers into auditable thermodynamic
estimators.
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Physics and Society · Cross-listed from econ.GN
Cascading Impacts of the USA–China Trade War on Global Oilseed Supply Chain
Diksha Gupta, Ritwick Mishra, Achla Marathe et al. (+2 more)
Global supply chains are highly interconnected, making them vulnerable to cascading disruptions induced by trade policy shocks. Understanding how such disruptions propagate through production networks, and how mitigation mechanisms such as trade reallocation and production adjustment can alleviate their impacts, remains a central challenge. In this work, we develop a linear programming formulation of an Input-Output (IO) system that captures cascading supply-chain disruptions together with trade reallocation and production expansion. Our formulation yields a system-level
equilibrium characterization that enables the joint analysis of disruption propagation and mitigation within a unified framework. We propose an efficient
algorithm for computing approximate
equilibrium solutions by minimizing total unmet demand in large IO systems. We apply our approach to tariff-induced disruptions in the global oilseeds supply chain arising from the U.S.-China trade war. Our results show that a localized 70% disruption to flows from the U.S. oilseeds sector to China leads to a 3.27% loss in global output, with China experiencing a disproportionate loss of 14.02%. As a counterfactual mitigation strategy, allowing a 20% reallocation from Brazil's oilseed sector to China significantly reduces global output losses to 1.36%, although pressure remains high on final-demand flows. We further investigate production expansion as an additional mitigation mechanism and show that it introduces tradeoffs between reducing global final-demand losses and protecting Brazil's domestic flows. Domestic reallocation disproportionately shifts losses toward smaller economies, while globally sourced expansion redistributes losses more broadly across the network.
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All authors Diksha Gupta, Ritwick Mishra, Achla Marathe, Krista Danielle Yu, Anil Vullikanti
High Energy Astrophysical Phenomena
Pulsed Infrared Emission from Magnetar 4U 0142+61 Detected by JWST
Jeremy Hare, George G. Pavlov, Bettina Posselt et al. (+3 more)
We report on a JWST observation of the magnetar 4U 0142+61 on 2024 August 18 with the Near-Infrared Camera (NIRCam). NIRCam observed the magnetar for 33~min in timing mode, providing a time resolution of 2.5~s. In the F410M filter (pivot wavelength 4.08 $\mu$m), we measured the flux density $f_\nu = 22.9\pm0.6$ $\mu$Jy and detected pulsations at a frequency of $115.059\pm0.035$ mHz, in agreement with the magnetar's
spin period at the epoch of the JWST observation. The observed pulse profile has one peak per period (although this may be due to the poor time resolution), with a lower limit on the pulsed fraction of about 10%. We compare the IR pulse profile to the NICER and NuSTAR X-ray pulse profiles and find that the IR peak overlaps with the hard X-ray peak, suggesting a magnetospheric origin for the pulsed IR emission.
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All authors Jeremy Hare, George G. Pavlov, Bettina Posselt, George Younes, Oleg Kargaltsev, Alex van Kooten
Quantum Physics
Hybrid Quantum Neighborhood Selection: NISQ-Compatible Combinatorial Optimization via Stochastic Frontier Decomposition
Nicolas Mendes de Araujo and Lester de Abreu Faria
Large-scale combinatorial optimization is a challenge for near-term
quantum computing because dense Quadratic Unconstrained Binary Optimization (QUBO) formulations yield interaction graphs that exceed the limits of NISQ processors. This work introduces Hybrid
Quantum Neighborhood Selection (HQNS), a hybrid framework mitigating this via
stochastic frontier decomposition. Instead of encoding all N variables into a monolithic
circuit, HQNS selects a compact frontier of F << N active variables per stage, freezing the rest into reduced QUBO coefficients. A multi-stage crawling procedure rotates these frontiers, letting local
quantum subproblems refine a global solution. We evaluate HQNS on the Maximum Diversity Subset Selection Problem (MDSSP) across six scales, N up to 1000.
Circuit burden is reduced from the dense QAOA requirement of O(N^2) two-
qubit terms per layer to O(F^2) per stage, with total complexity governed by the number of stages and classical overhead.
Benchmarks show that HQNS achieves competitive solution quality relative to parallel simulated annealing (SA) while maintaining bounded
circuit width and stable QPU time. In the N=1000
benchmark over ten executions, HQNS preserves 99.9908% of the mean diversity score of an 11-restart parallel SA baseline, while reducing wall-clock time by 65.03%, peak CPU usage by 55.97%, and peak
memory by 35.21%. Ablation shows performance depends on frontier size, warm-starts, CVaR filtering, and
stochastic rotation. These results demonstrate that structured frontier decomposition makes variational optimization executable for dense QUBO instances unsuitable for direct QAOA on present hardware.
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Space Physics · Cross-listed from cs.LG
t-STEP: An interpretable model for Total Electron Content predictions and irregularities estimations
Stephen Tete, Carl Shneider, Maxime Cordy et al. (+3 more)
Earth system infrastructures relying on satellite-based technologies, such as Global Positioning System (GPS) communications, are affected by ionospheric Total Electron Content (TEC) gradients. Modeling these gradients under physical constraints remains challenging due to their dynamic and transient nature. While existing machine learning (ML) models can predict hourly TEC variations, it remains unclear whether their temporal resolution is sufficient to preserve small-scale TEC irregularities within predicted signals. To address this gap, we introduce an interpretable ML-based model, t-STEP, designed to predict TEC at a 30-second resolution and estimate irregularity signatures from the modeled signals. This high cadence enables the derivation of Rate of TEC changes (ROT) and the ROT Index (ROTI) as diagnostic indicators of ionospheric variability. The model is developed using GPS observations from
solar cycle 24 at a station located at 5.49{\deg}S, 47.49{\deg}W. A multi-metric evaluation framework, including dynamic time warping, is used for robustness assessment, while SHAP (SHapley Additive exPlanations) provides insight into feature contributions. The 30-second TEC predictions achieve 91% accuracy with a mean absolute error (MAE) of 4.38 TECU during high
solar activity (2015). Compared with the International Reference Ionosphere (IRI-2020), the hourly model improves accuracy by 35%, reduces absolute errors by 57%, and increases prediction skill by 54%. More importantly, the 30-second model captures TEC irregularity dynamics and morphologies during geomagnetic storms of different intensities, outperforming an
attention-based Long Short-Term
Memory model under the same experimental conditions. This study demonstrates the potential of a single TEC prediction framework for scalable irregularity monitoring without requiring separate models for individual transient events.
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All authors Stephen Tete, Carl Shneider, Maxime Cordy, Claudio Cesaroni, Andreas Hein, Vasily Petrov
Quantum Physics
Characterization of Unlearnable Noise with Mid-Circuit-Measurement-Based Cycle Benchmarking
M. H. Cheng, Stefano Mangini, V. Bartsch et al. (+4 more)
Noise characterization of multi-
qubit entangling Clifford operations is a key practical bottleneck for
quantum error mitigation and for the calibration, validation, and optimization of
quantum error-correction protocols, especially in the presence of state preparation and measurement (SPAM) errors. Although cycle benchmarking can isolate some Pauli error components, it cannot resolve the problem of coupled error parameters, which leads to unlearnable degrees of freedom even in simple noisy gates, not to mention general $n$-
qubit Clifford gates. Here we introduce mid-
circuit-measurement-based generalized cycle benchmarking, a framework that makes otherwise unidentifiable Pauli fidelities and non-Markovian noise learnable via repeated measurements and classical post-processing. Applying the deferred feed-forward principle to generalized cycle benchmarking, we show that an insertion of mid-
circuit measurements can reverse Pauli cycles induced by a general Clifford gate. This fact enables us to reveal a Pauli-noise learnability condition for Clifford gates. Assuming sufficient state preparation quality, we numerically demonstrate the feasibility of characterizing the previously unlearnable noise components. We implement the protocol on superconducting
quantum processing units and validate its effectiveness in disambiguating the coupled noise components, benchmarked against conventional
tomography. Finally, we observe consistent measurement-induced bit-flip bias and non-Markovian correlations, which define a range of applicability for the Pauli noise model and the proposed noise-characterization protocol.
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All authors M. H. Cheng, Stefano Mangini, V. Bartsch, A. C. Medina, Sergey N. Filippov, Matteo A. C. Rossi, M. S. Kim
Applied Physics
Sub-Terahertz Channel Performance under Snowfall
Kefeng Huang, Jiabiao Zhao, Yuheng Song et al. (+8 more)
The terahertz (THz) band promises terabit-per-second links but is highly sensitive to snowfall. Natural snowflakes are non-spherical. Yet existing THz studies treat them as spheres under Mie theory, and no ITU-R model covers THz snow attenuation. This work combines line-of-sight measurements at 120, 140, and 160 GHz with physics-based scattering modeling. The measured loss is compared against the ITU-R P.1817-1 optical model, Mie models, and a discrete dipole approximation (DDA) for randomly oriented hexagonal-plate ice
crystals, each with the Scott and Gunn-Marshall size distributions. Over the measured band, ITU-R P.1817-1 overestimates and the Mie models underestimate the loss. The shape-aware DDA-Scott model agrees best, with the lowest RMSE at every frequency. From DDA-Scott, we derive a compact modified ITU-R expression in carrier frequency and
liquid-water-equivalent (LWE) rate. It reproduces the reference to within 2.5 dB/km over 100-500 GHz and 0-3 mm/h. A Rician K-factor analysis shows the channel stays LoS-dominated, so snowfall degrades the link mainly through attenuation, not multipath fading. A QPSK/16-QAM link-budget analysis then quantifies the cost of the spherical assumption. Mie-based margins overestimate the tolerable snowfall rate by 3.4 across 120-160 GHz, rising toward 5.8 in the upper transparency windows by model extrapolation. The model is further mapped into snow-limited range and adaptive-modulation switching boundaries. These results support future ITU-R recommendations for THz channels under snowfall.
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All authors Kefeng Huang, Jiabiao Zhao, Yuheng Song, Yapeng Ge, Jie Yang, Wanzhu Chang, Xiaoxiang Li, Wenbo Liu, Peian Li, Hong Liang, Jianjun Ma
Quantum Physics
Lie Group Diffusion Models for Hardware-Aware Quantum Circuit Synthesis
Jyotirmai Singh
An important task in
quantum computing is
unitary circuit synthesis compatible with physical hardware constraints. This problem has a natural hybrid structure as local single-
qubit gates are continuous variables on the Lie group $SU(2)$ while the entangling
circuit structure is discrete and hardware-dependent. In this work, we use generative models to perform
quantum circuit synthesis incorporating both the natural $SU(2)$
manifold geometry of
quantum gates and hardware constraints that determine the overall
circuit structure. Our model comprises two components: a
circuit skeleton selector that chooses an entangling
circuit and a
diffusion model that generates
quantum gates on the given
circuit template by performing
diffusion on the curved
manifold $\mathrm{SU(2)} \simeq S^3$ itself. We demonstrate this approach with
unitary compilation of physically motivated three-
qubit Hamiltonian simulation targets such as the Transverse Field Ising Model and the Heisenberg-XXZ Model and show that Lie group
diffusion outperforms comparable baselines. The synthesised
circuits can also be customised subject to constraints, which we demonstrate by producing
circuits with large and small gate rotation angles for the same target
unitary evolution. We also investigate the fidelity-complexity frontier of the synthesised gates to demonstrate that the
circuit selector learns to select
circuits that balance fidelity with complexity rather than collapsing onto the most expansive entangling template. These results demonstrate that Lie group
diffusion provides a natural generative framework for hardware-aware
quantum circuit synthesis.
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Medical Physics
A Mapping Sheath with Thermally Drawn Multi-Electrode Basket for Cardiac Electrophysiological Recording and Ablation Catheter Delivery
Qindong Zheng, Anil Demircali, Jinshi Zhao et al. (+14 more)
Cardiac arrhythmias, particularly atrial fibrillation, represent a major cardiovascular health burden and underscore the need for efficient and integrated strategies for electrical mapping and targeted therapy. Cardiac electrophysiology procedures depend on accurate identification of arrhythmogenic substrates followed by timely catheter ablation, but conventional diagnostic and therapeutic devices remain separate, often requiring repeated catheter exchanges and multiple access routes. Here, we report an adaptable strategy for functionalizing hollow-core sheaths with EP mapping capabilities, integrating multielectrode recording and ablation catheter delivery within a single compact platform. The device leverages thermal drawing to enable complex
geometric fabrication, miniaturization, rapid prototyping, and scalable manufacturing of ultrathin electrode splines arranged circumferentially at the distal end to form an adjustable basket. The mapping sheath exhibited mechanical and electrophysiological properties suitable for intracardiac
navigation and electrogram recording in bench-top evaluations, an in vitro left atrial phantom study, and ex vivo Langendorff-perfused porcine heart testing. In vivo porcine studies further demonstrated translational feasibility through vascular introduction, fluoroscopic visualization, intracardiac deployment, tissue contact, electrogram acquisition, and reconstruction of voltage and activation maps. These results support the development of intracardiac platforms with an adapted manufacturing approach, potentially guiding advances in agile cardiac mapping and ablation.
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All authors Qindong Zheng, Anil Demircali, Jinshi Zhao, Xiaotong Guo, Libaihe Tian, Oliver Jones, Jamie Kay, Shengzhe Li, Alex Ranne, Elaine Lim, Huiyi Wu, Simos Koutsoftidis, Mohamed Abdelaziz, Emmanuel Drakakis, Prapa Kanagaratnam, Nick Linton, Burak Temelkuran
Quantum Physics
Squeezing as a catalyst for non-Gaussian advantage in characterization of nonlinear media
Manju, Samaneh Hesabi, Siting Tang et al. (+2 more)
We address the precise characterization of coupling strength of nonlinear media in continuous-variable (CV)
quantum systems using coherent and squeezed
vacuum states as Gaussian probes, together with their
photon-added and
photon-subtracted counterparts as non-Gaussian probes. We consider three main classes of nonlinear
Hamiltonians, namely quadrature nonlinearities, generalized squeezing and Kerr-type interactions. By analytically evaluating the
quantum Fisher information (QFI), we compare the performance of Gaussian and non-Gaussian probes and assess the optimal probe based on the probe parameters, energy resource and non-Gaussianity. Our results are twofold as follows: first, for coherent-state family, the improvement provided by
photon addition at fixed coherent amplitude originates mainly from the extra energy carried by the probe and does not provide a genuine metrological resource, since the same precision can be achieved by a Gaussian coherent-state signal of a larger energy, which can be more easily produced. Second, in contrast,
photon addition and subtraction become effective resources when applied to already nonclassical states such as squeezed
vacuum states. In this case, they lead to a significant enhancement of the QFI, particularly for higher-order interactions. Although Gaussian squeezed states remain optimal at equal energy constraint,
photon-added and
photon-subtracted squeezed states achieve comparable sensitives with significantly lower squeezing requirements. Since large squeezing level remains experimentally challenging, these non-Gaussian probes offer a practical route towards enhanced estimation of the nonlinear coupling strength within currently accessible squeezing regimes.
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All authors Manju, Samaneh Hesabi, Siting Tang, Peter van Loock, Matteo G. A. Paris
Fluid Dynamics
Kriging and Neural Network models for pressure losses across perforated plates
Shuai Li
In this paper, two novel data-driven models based on Kriging and neural networks (NN) are proposed to predict pressure losses across perforated plates with circular perforations in turbulent flows. The models are developed using two sets of experimental data available in the literature. The predictive performance of the proposed models is assessed and compared against widely used empirical formulae. It is found that the proposed models consistently outperform existing empirical models for most perforated plate configurations contained in the experimental
datasets. Besides, the predicted pressure losses generally show good agreement with experimental measurements, demonstrating that data-driven approaches based on Kriging and NN provide a feasible framework for modelling pressure losses across perforated plates. Overall, both approaches are promising, despite being trained on a relatively limited amount of experimental data, owing to the scarcity of measurements reported in the literature. To demonstrate the applicability of the proposed models in numerical simulations, two-dimensional channel flows are simulated using the Reynolds-averaged Navier-Stokes (RANS) equations, in which the new pressure-loss models are implemented as a source term in the momentum equations. The RANS predictions are insensitive to mesh resolution and the number of
cells used to represent the perforated plate, and they agree well with the model predictions, confirming the applicability of the proposed approaches to practical computational fluid dynamics (CFD) simulations.
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High Energy Physics (Phenomenology)
Neutrino oscillation in a minimal length spacetime
Luísa Nadal Camargo, Thiago Oliveira Ferreira, Dimiter Hadjimichef et al. (+1 more)
We investigate how
neutrino oscillations are modified in a non-commutative spacetime characterized by a minimal length scale, described by the Quesne-Tkachuk
algebra. By incorporating the
algebra's deformation parameter $\beta$ into the effective
neutrino mass, we derive the 2-
flavor oscillation probability in this non-commutative setting. The resulting probability depends not only on the usual mass-squared difference but also on a fourth-order mass difference scaled by $\beta$. A comparison between the standard and non-commutative oscillation probabilities reveals a beat pattern arising from the additional non-commutative phase, which induces a small shift in the oscillation profiles. Finally, we extend our analysis to include the effects of a
magnetic field on
neutrino propagation.
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All authors Luísa Nadal Camargo, Thiago Oliveira Ferreira, Dimiter Hadjimichef, César A. Z. Vasconcellos
High Energy Physics (Theory)
Metric-like Cubic Vertices for Massless Bosonic Higher-Spin Fields in AdS$_3$
Freddie King, Taylor Pomfret and Karapet Mkrtchyan
We derive parity-even transverse-traceless metric-like cubic vertices for massless bosonic higher-
spin fields in AdS$_3$. Starting from the known two- and three-derivative vertices in three-dimensional flat space, we construct their AdS$_3$ extensions by imposing gauge invariance and accounting for dimension-dependent identities. The result is shown to be consistent with minimal coupling to
gravity.
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Quantum Physics
Bright-mode parity synthesis for bosonic state transfer through a single ancilla
Pradip Laha and Peter van Loock
Bosonic modes provide hardware-efficient
quantum memories and logical registers, including highly non-Gaussian encoded states, but transferring finite-dimensional bosonic states through a restricted ancilla interface requires identifying which collective mode is actually controlled. We study a restricted setting in which two oscillators couple with opposite signs to a single two-level ancilla. In the normal-mode basis, the symmetric mode is dark, while transfer between the physical modes is equivalent to synthesizing parity on the antisymmetric bright mode. This reduction gives exact finite-sum transfer formulas for Fock states, Fock-state
qubits, and finite Fock superpositions, and explains why resonant single-ancilla transfer is recurrence-limited beyond the single-
photon sector. We then show that detuned Jaynes–Cummings
evolution provides a native two-parameter route to high-fidelity finite-cutoff parity synthesis, with residual ancilla excitation, calibration sensitivity, and a minimal Markovian noise estimate quantified separately. Bosonic-code examples illustrate how transfer sensitivity is governed by
photon-number support and residual bright-mode phase errors. The result provides a practical
benchmark and organizing principle for constrained ancilla-mediated bosonic transfer when direct exchange is unavailable or undesirable.
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Adaptation and Self-Organizing Systems · Cross-listed from stat.ML
Bidirectional Autoregressive Latent Diffusion for Forward and Inverse Magnetohydrodynamics
Alexander Scheinker
This work presents a new bidirectional autoregressive latent
diffusion approach for predicting the
evolution of multiple fields (mass density, pressure, velocity, and
magnetic field components) for magnetohydrodynamics. We show that this bidirectional flow can be used as a self-supervised consistency metric for uncertainty and error estimation, which enables the model to estimate test-time uncertainty and error without access to ground truth, by comparing how closely flowing forwards and backwards in time returns to the same predicted fields. We also demonstrate this methods's potential to serve as a non-invasive
plasma diagnostic, and show how adaptive feedback can be used to make the model more robust based on sparse diagnostics or limited views/measurements.
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Fluid Dynamics
Monolithic kinetic algorithm for heterogeneous porous media systems using a continuous one-domain approach
Nikita O. Gusev and Ilya V. Karlin
We propose a
lattice Boltzmann model (LBM) on standard
lattices for simulating multi-dimensional, weakly compressible, isothermal flows within and around isotropic heterogeneous porous media. The model incorporates Darcy-Forchheimer drag and a Brinkman-like effective viscous stress tensor. In the hydrodynamic limit, it recovers a generalized volume-averaged formulation valid in both free-fluid and porous-medium regions. By relying on a single kinetic equation and a monolithic LBM
algorithm, the formulation provides a one-domain solver for free-fluid/porous-medium interactions. Unlike previous LBM formulations for porous media, the proposed model recovers the correct porosity scaling of both the pressure and convective terms, while preserving the isotropy, and hence the Galilean invariance, of the viscous stress tensor. Linear and nonlinear drag, variable-porosity corrections, and additional body forces are incorporated through a consistent generalized forcing scheme. The model allows the speed of sound to be specified independently thereby improving computational efficiency. In addition, it includes a freely tunable effective bulk viscosity that can be used to enhance numerical stability. Model performance was evaluated using 2D
benchmark flow problems. The ability of the proposed LBM model to simulate transport between free-fluid and heterogeneous porous regions within a one-domain framework enables a broad range of applications, particularly in early-stage, device-scale design studies of engineered porous structures with spatially varying porosity.
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Quantum Physics
Dynamics of quantum entanglement in two time-dependent coupled harmonic oscillators
Ayoub Ghaba, Radouan Hab-arrih, Elhoussine Atmani et al. (+1 more)
We investigate the
quantum entanglement dynamics of two coupled harmonic oscillators with a time-dependent interaction. Using the Lewis-Riesenfeld invariant method, we derive the exact analytical wave functions without any perturbative or adiabatic approximations and combine this with a phase-space analysis using the Wigner function to provide a complete description of the system's
quantum state
evolution. We obtain general expression form for the purity and the linear
entropy $S_L=1-\mathcal{P}$ for arbitrary excitation numbers $(n,m)$, allows a systematic study of
entanglement for a large class of
quantum states. We show that the
entanglement dynamics is very sensitive to the interplay between the detuning parameters $\theta$ and $\vartheta_2$, the frequency parameter $\beta_0$ and the coupling strength $\epsilon$: the increase of detuning takes the system from slow irregular oscillations to fast and regular periodic behavior, and the stronger coupling systematically enhances both the amplitude and the average value of the linear
entropy. Most importantly, for the resonance case $\omega_1=\omega_2=1$ and strong couplings $\epsilon \approx 0.99$, the system shows robust undamped synchronized periodic oscillations of the linear
entropy for all
quantum states considered, indicating preserved
quantum coherence without saturation. Our findings demonstrate that linear
entropy is a sensitive and practical
entanglement witness, and we establish explicit analytical relations between the coupling parameters of the system and its
entanglement properties, which are directly relevant to
quantum information processing and the control of
quantum correlations in continuous-variable systems.
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All authors Ayoub Ghaba, Radouan Hab-arrih, Elhoussine Atmani, Abdallah Slaoui
Quantum Physics
Gaussian Quantum Metrology with Realistic Linear Sensors
Jacques Ding, James W. Gardner, Tuvia Gefen et al. (+1 more)
Quantum sensing promises enhanced precision, but the usual
quantum Cramer Rao bound can be too optimistic for realistic linear sensors, where squeezing, filtering, and loss reshape
quantum noise. We derive the tight Holevo Cramer Rao bound and show that realistic degradation yields a hierarchy with the usual bound and homodyne readout. This hierarchy already exists in gravitational-wave detectors. We propose a hardware-efficient readout that reaches the Holevo bound without extra signal loss, increasing compact-binary detection rates by up to 25% over the present LIGO homodyne readout.
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All authors Jacques Ding, James W. Gardner, Tuvia Gefen, Yanbei Chen
High Energy Physics (Theory)
Landau's Leviathans
Vsevolod Chestnov, Giulio Crisanti and Mathieu Giroux
We present a new method together with a proof-of-concept implementation for determining the Landau singularities of Feynman integrals, read off directly from where the Euler characteristic of the associated integral drops. Working over finite fields makes the requisite elimination tractable for multi-scale integrals at the multi-loop frontier. The
algorithm returns the genuine and complete set of singularities, subject to a set of conditions which are practically testable. We apply these methods to classes of Feynman integrals beyond the reach of current methods, including non-planar six-point diagrams at two loops, as well as a fully massive three-loop envelope graph. Several of the newly found singularities, both in $d$- and 4-dimensional external kinematics, are of unexpected complexity when compared to previously known singularities for these examples.
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Quantum Physics
Physics-Informed Neural Quantum Control for Rovibrational Photoassociation in a Morse Molecular System
Murilo D. Forlevesi, Emanuel Fernandes de Lima and Edson Denis Leonel
We present a Physics-Informed Neural
Quantum Control (PINQC) framework for rovibrational photoassociation in a Morse molecular system. The proposed method combines neural-network-based
laser-field generation with differentiable
quantum propagation, allowing optimized
laser pulses to be obtained directly from the underlying
quantum dynamics without requiring external training data. The optimized control fields efficiently transfer an initially continuum-like Gaussian wave packet into the vibrational ground-state level, promoting continuum-to-bound population transfer through coherent rovibrational dynamics. The resulting photoassociation process involves both vibrational stabilization and rotational redistribution arising naturally from dipole-induced couplings between neighboring rotational channels. A central result of the present work is the successful application of the PINQC framework to extended rovibrational models containing larger rotational levels than those previously accessible in our conventional photoassociation calculations. The optimization remains numerically stable despite the increased complexity of the molecular system, demonstrating that differentiable optimization provides an effective strategy for treating rovibrational models of increased dimensionality. These results establish the PINQC framework as a promising computational tool for molecular photoassociation and motivate future investigations of increasingly complex rovibrational
quantum-control problems.
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Astrophysics of Galaxies
The Lockman-SpReSO Project: A Deep X-ray Spectral View of a FIR-selected AGN Population
Mauricio Elías-Chávez, Takamitsu Miyaji, Martín Herrera-Endoqui et al. (+21 more)
We present a detailed X-ray spectral analysis of the active
galactic nucleus (AGN) population in the Lockman-SpReSO project, a multiwavelength campaign of FIR sources in the Lockman Hole field. Using deep XMM-Newton observations cross-matched with FIR-selected
galaxies, we characterize 94 AGNs based on their X-ray spectral properties. The sample is distributed over a large
redshift range of $z = 0.07-5$, and reaches a flux limit of $5 \times 10^{-16}\, \mathrm{erg\, s^{-1}\, cm^{-2}}$ in the $0.3-10\, \mathrm{keV}$ band. We model the X-ray spectra using absorbed power-law, reflection, and soft excess components to estimate intrinsic column densities ($N_{\mathrm{H}}$), rest-frame $2-10\, \mathrm{keV}$ luminosities, and iron line equivalent widths $(EW)$. Additionally, we included an advanced model fitting for Compton-thick AGNs (CT-AGNs) using the XCLUMPY model. Our results show an increase in the fraction of obscured AGNs toward higher
redshifts, including the identification of one strong and two borderline CT-AGN candidates with $N_{\mathrm{H}} \gtrsim 10^{24}\, \mathrm{cm^{-2}}$. Soft excess emission is detected in 10 AGNs, with an average blackbody temperature of $0.12 \pm 0.02\, \mathrm{keV}$. We also detect the X-ray Baldwin effect in both obscured and unobscured populations, and we found a strong correlation between the
torus angular width $(\sigma_\mathrm{tor})$,
dust covering factor $(f_{\mathrm{cov}})$, and X-ray luminosity, described by $f_{\mathrm{cov}} = (-0.1 \pm 0.01) \times \log(L_{2-10\, \mathrm{keV}}/(10^{44}\, \mathrm{erg\, s^{-1}})) + (0.65 \pm 0.01)$, supporting the receding
torus scenario. While consistent with deep X-ray surveys, the FIR selection favours the identification of dusty
star-forming host
galaxies and heavily obscured AGNs.
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All authors Mauricio Elías-Chávez, Takamitsu Miyaji, Martín Herrera-Endoqui, Irene Cruz-González, Yair Krongold, Héctor Hernández-Toledo, Mirjana Povic, Bereket Assefa, Mauro González-Otero, Castalia Alenka Negrete, Miguel Cerviño, J. Antonio de Diego, Miguel Sánchez-Portal, Erika Benítez, Jordi Cepa, José Antonio Vázquez Mata, Monica I. Rodriguez, Emilio J. Alfaro, J. Jesús González, Carmen P. Padilla-Torres, J. Ignacio González-Serrano, Vladimir Ávila-Reese, Ángel Bongiovanni, A. M. Perez Garcia
High Energy Astrophysical Phenomena
General Relativistic Shock Wave Solutions with Black Hole Formation: The Singular Isothermal Sphere Case
Chien-Ting J. Chen, Michael J. Cai and Fabio Pacucci
The rapid emergence at $z\gtrsim 6$ of ubiquitous populations of supermassive black holes (SMBHs) revealed by JWST and of
quasars with estimated masses $M_\bullet > 10^{10} M_\odot$ demands efficient pathways for early growth. The smooth collapse of a singular isothermal sphere (SIS) has been solved analytically in full general relativity, but the shock waves that inevitably accompany such collapse have not. Here, we derive general-relativistic self-similar shock-wave solutions for the collapse of an SIS to a black hole, extending the framework of Cai & Shu (2005) to discontinuous flows. We obtain the general relativistic jump conditions for an isothermal fluid and show that they connect interior collapse solutions to exterior envelopes that may be static, expanding, or collapsing, yielding a rich family of shocks propagating at up to $\sim$40% the speed of light; the available exterior types narrow with increasing sound speed. A coordinate-matching technique that uses the zero-velocity surface uniquely bridges the Schwarzschild and comoving self-similar descriptions, completing the characterization of the growing black hole. The central
accretion rate is set by the interior collapse alone and is suppressed by a factor of $\sim$5–7 relative to the smooth expansion-wave solution, while the energy released at the shock reaches $\sim$10% of the enclosed rest mass – nearly twice the 5.7% radiative efficiency of Schwarzschild
accretion. These results provide an analytical energy budget for direct-collapse black hole formation, with implications for SMBH seed assembly, the dense cocoons around nascent high-
redshift black holes, the recently discovered JWST's Little Red Dots, and relativistic transients such as gamma-ray bursts.
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Lattice Field Theory
Complete Access to Leading-Twist $\Lambda$-Baryon Light-Cone Distribution Amplitudes from Lattice QCD
Mu-Hua Zhang, Haoyang Bai, Min-Huan Chu et al. (+11 more)
We report the first complete
lattice-QCD determination of the leading-twist light-cone distribution amplitudes (LCDAs) of the $\Lambda$
baryon, obtained as full two-dimensional functions of the valence-
quark momentum fractions. The calculation employs large-momentum effective theory to relate the light-cone amplitudes to equal-time nonlocal three-
quark matrix elements of boosted $\Lambda$
baryons. Controlled physical extrapolations to the continuum, physical pion mass, and infinite momentum, together with hybrid renormalization, large-$\lambda$ extrapolation, and perturbative matching, yield the three leading-twist LCDAs $V$, $A$, and $T$. Using the
lattice-determined LCDAs in place of the asymptotic form, we find an $\mathcal{O}(10\%)$ shift in the $\Lambda$ electromagnetic form factor at perturbative scales, demonstrating that the full two-dimensional LCDAs, rather than only their asymptotic shapes or lowest moments, are required for precision baryonic phenomenology. This work, together with the companion paper [1] detailing the
baryon-LaMET framework, provides the first complete multi-dimensional $x$-dependent
baryon LCDAs from first principles and establishes a
benchmark for
lattice access to multi-dimensional
baryon structure.
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All authors Mu-Hua Zhang, Haoyang Bai, Min-Huan Chu, Jun Hua, Xiangdong Ji, Xiangyu Jiang, Jian Liang, Cai-Dian Lü, Andreas Schäfer, Wei Wang, Yi-Bo Yang, Jian-Hui Zhang, Jia-Lu Zhang, Qi-An Zhang
Solar and Stellar Astrophysics
Radio Wave Propagation as a Probe of the Solar Corona and Solar Wind
K. Sasikumar Raja, Prasad Subramanian, Susanta Kumar Bisoi et al. (+3 more)
Radio waves propagating through an inhomogeneous, turbulent medium such as the
solar corona and
solar wind become distorted, causing the initially plane wavefronts becomes corrugated and acquire an RMS phase deviation across the wavefront. This leads to observable effects such as angular broadening of
radio sources or intensity scintillation. Such waves can be used to probe the
solar wind through various techniques, including angular broadening and interplanetary scintillation observations. Such observations enable the study of several key properties, such as the phase structure function, amplitude of
turbulence, density modulation index,
solar wind heating rates,
magnetic field
topology, and dissipation scales. These phenomena provide critical insights into the physical processes governing the
solar corona and
solar wind and its interaction with
radio waves, offering valuable constraints on both coronal and
solar wind
turbulence and coronal
magnetic field configurations. Currently, the limited number of
radio sources near the ecliptic restricts our observations. However, the SKA-Low and SKA-Mid are expected to detect a significantly larger number of
radio sources, thereby providing deeper insights into the
solar corona,
solar wind, and heliosphere. Long-term observations will be crucial to understanding how the above-mentioned parameters vary with heliocentric distance and over the
solar cycle.
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All authors K. Sasikumar Raja, Prasad Subramanian, Susanta Kumar Bisoi, Janardhan Padmanabhan, Eduard Kontar, Anshu Kumari
Materials Science · Cross-listed from cs.LG
STEMGym: Benchmarking Sequential Decision-Making under Dose Budgets in Autonomous Electron Microscopy
Can Polat, Erchin Serpedin, Mustafa Kurban et al. (+1 more)
A central premise of autonomous scientific imaging is that smarter
navigation, whether
Bayesian, RL-based, or otherwise adaptive, is the principal lever for sample-efficient acquisition. We present evidence to the contrary in scanning transmission electron microscopy (STEM), an atomic-resolution imaging modality whose every measurement deposits damaging electron dose. We introduce STEMGym, an open-source Gymnasium
benchmark of 15 physics-simulated STEM worlds spanning five materials, three difficulty levels, and four characterisation tasks, scored by the Dose-Efficiency Curve area (DEC-AUC), a single scalar capturing the information-vs-dose Pareto frontier. Across 33
agent configurations under realistic dose budgets, the dominant determinant of dose efficiency is the analyst (perception) pipeline, not the navigator: pairing a trained CNN analyst with naïve raster scanning raises DEC-AUC by 5.5x over a CNN-free raster baseline (0.287 vs.\ 0.052), while substituting
Bayesian or adaptive finite-state-machine
navigation for raster yields no statistically significant further gain. Production-tier
vision-
language models further underperform task-specific CNNs by {\sim}13x on crystallographic defect analysis. By decoupling perception,
navigation, and planning under a unified dose budget, STEMGym reframes where ML effort should be invested in autonomous electron microscopy and provides the measurement infrastructure to test it.
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All authors Can Polat, Erchin Serpedin, Mustafa Kurban, Hasan Kurban
General Relativity and Quantum Cosmology
Saturation Equations of State in Critical Gravitational Collapse: The Primordial Black Hole Threshold
Benaoumeur Bakhti
The threshold and scaling laws of gravitational critical collapse depend sensitively on the matter equation of state. We investigate how these quantities are modified by a generic feature of dense matter that is absent from the radiation fluid commonly assumed in
primordial black hole (PBH) studies: pressure stiffening as a maximum density is approached. As an analytically tractable proxy, we adopt the closed-form equation of state of a single-occupancy
lattice gas, \(p=-T\ln(1-\rho)\), which exhibits a density-dependent sound speed and a saturation density. Using general-relativistic simulations of spherically symmetric collapse, we show that this nonlinear pressure feedback increases the PBH formation threshold by \(0.50\pm0.02\%\) relative to the radiation equation of state within the causal regime of the model. At the same time, the critical mass-scaling exponent remains \(\gamma=0.357\pm0.001\), consistent with the radiation-fluid value to within our numerical precision. This agreement reflects the fact that the
lattice equation of state approaches the radiation fluid at low density and remains only a mild perturbation over the near-critical regime, rather than indicating a universal critical exponent. Our results provide a proof of principle that saturation-induced stiffening can stabilize gravitational collapse and shift the PBH threshold, while introducing a linear-response framework for assessing the impact of more realistic equations of state on
primordial black hole formation.
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Applied Physics · Cross-listed from cs.SD
EchoHawk: A Reproducible Acoustic Pipeline for Drone Detection, Classification, and Direction-Finding, with a Cautionary Study of Session-Level Data Leakage
David Shulman
Passive acoustic sensing is an attractive modality for counter-unmanned aerial system (counter-UAS) defence: it is covert, low-cost, and effective against drones with small radar cross-sections or minimal
radio emissions. We present EchoHawk, an open and fully reproducible reference pipeline that detects a drone from its rotor harmonics, estimates its blade-passing frequency, and localises it with a microphone array via classical wideband beamforming (delay-and-sum, MVDR, MUSIC) and time-delay processing (GCC-PHAT, SRP-PHAT), followed by temporal tracking. We evaluate the system on a physically transparent synthetic
benchmark that pits drones against hard low-frequency harmonic confusers, such as ground vehicles, and on real recorded audio. Our central methodological contribution is a documented case of session-level data leakage in a widely used public
dataset: because its recordings are pre-segmented into short clips, naive clip-level splits place adjacent slices of the same continuous recording in both training and test sets, inflating reported performance. Enforcing recording-session-grouped cross-validation reduces, for example, a random-forest baseline's detection probability at a 1% false-alarm rate from 0.796 to 0.745, yielding honest numbers. All code, figures, and a synthetic data generator are released so that every result runs without any download.
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Nuclear Theory
Nuclear equation-of-state at high density and multi-messenger astronomy: contribution of heavy-ion collisions
A. Le Fèvre
In the past decades, heavy-ion collisions (HIC) at intermediate energies have allowed to probe the
nuclear equation-of-state (EoS) of both symmetric and asymmetric
nuclear matter over a broad range of densities. In particular, flow has proven to be a powerful observable. Combining the
symmetry energy and the symmetric
nuclear matter constraints of the EoS from HIC allowed to predict a density dependence of the pressure in a
neutron star, up to about 2.5 times saturation density ($n_{sat}$), which agrees with recent astronomical measurements deduced from gravitational waves and
pulsar observations. So far, the accuracy from HIC expectations is comparable to the latter up to 1.5 $n_{sat}$. In these studies, a fundamental aspect is the determination of the profile of densities that are probed by experimental observables used to constrain the EoS. In the near future, new experiments like ASY-EOS performed at higher incident energy and with better accuracy will push further the frontier of the knowledge of the
symmetry energy at higher density. These efforts cannot be conclusive without a reliable uncertainty determination, which is related to the reliability of transport model dependencies. Improvements and breakthroughs in transport model simulations and
nuclear theory are therefore expected in a joint effort towards HIC contributions to the field of
neutron-
star physics, including the contribution of strangeness and of the QCD phase transition.
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