Papers

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Physics

Wednesday 1 July

Atomic Physics

Correct Asymptotic Wavefunctions for Calculating Photoelectron Angular Distributions of O2- and NO-

Wenru Jie, Rui Zhang, Jiayi Chen et al. (+2 more)

The ab initio calculation of photoelectron angular distributions (PADs) for negative ions remains a significant theoretical challenge. In this work, we report a joint experimental and theoretical investigation of PADs for a series of molecular anions with varying polarities, including the nonpolar O2-, the weakly polar NO-, and the strongly polar AsO- and SbO-. To accurately describe the long-range electronic wavefunctions – where photodetachment contributes most strongly – we modified the standard Gaussian-type orbitals (GTOs) by augmenting them with a correct exponential Slater-tail basis set (~e^(-{\xi}r)). This simple yet effective approach significantly improves the agreement between the experimental and theoretical PADs for O2- and NO-. However, notable discrepancies persist for NO- for transitions to the v = 0 and v = 1 vibrational levels of neutral NO even after this correction. Given that our methodology successfully reproduced PADs for strongly polar anions (e.g., AsO- and SbO-), these residual discrepancies are unlikely to stem from "exit-channel scattering" induced by long-range dipole fields. Instead, we tentatively attribute the failure for NO- to the breakdown of the Born-Oppenheimer approximation or the frozen orbital approximation, arising from the extremely weak binding of the excess electron.

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All authors Wenru Jie, Rui Zhang, Jiayi Chen, Qihan Liu, Chuangang Ning

Astrophysics of Galaxies

Direct VLBI evidence for a buried AGN in the triple-merger LIRG UGC 2369S

Wancheng Xu, Sándor Frey, Lang Cui et al. (+1 more)

UGC 2369S is a luminous infrared galaxy (LIRG) undergoing a late-stage merger in a triple system, where the heavily obscured northern core is suspected to host an active galactic nucleus (AGN). However, severe dust and gas obscuration makes definitive confirmation challenging. We aim to provide direct observational evidence for the buried AGN through high-resolution radio imaging, while investigating the AGN accretion and feedback properties within this merger-driven gas-rich environment. We analyzed archival European VLBI Network (1.6 GHz) and Very Long Baseline Array (1.7 and 5 GHz) data of UGC 2369S. Through high-resolution imaging and visibility-domain Gaussian modeling, we characterized the morphology and intensity of its milliarcsecond-scale radio emission. A compact radio component is detected at the northern core, exhibiting high brightness temperature ($T_{\rm b}>10^7$ K) and flat radio spectrum ($\alpha \approx -0.45$), which confirms the presence of an obscured AGN. The sub-Eddington accretion rate ($\lambda_{\rm Edd} \approx 2.7 \times 10^{-4}$) indicates that it falls within the radiatively inefficient accretion flow (RIAF) state. We provide direct imaging evidence for an AGN in the northern core of UGC 2369S, revealing a deeply buried, jet-emitting low-luminosity AGN (LLAGN) enshrouded by a Compton-thick gas cocoon. This demonstrates that VLBI is a uniquely effective tool for disentangling nuclear accretion and feedback processes within the heavily obscured environments of multiple-merger systems.

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All authors Wancheng Xu, Sándor Frey, Lang Cui, Krisztina Éva Gabányi

High Energy Physics (Theory)

Leggett-Garg inequality in the massive scalar vacuum: No violation under spacelike-separated measurements

Yang Xiang

We overcome the long-standing noninvasive measurability (NIM) challenge in Leggett-Garg tests by exploiting the causal structure of quantum field theory (QFT). Our protocol uses three independent ensembles of the vacuum state, each measured by a different pair of observers at spacelike-separated events, yielding the three two-time correlators. By placing these events at positions $(0,0)$, $(\tau,L)$, and $(2\tau,2L)$ with $L>\tau+2\tau_0$, we rigorously ensure that no measurement can influence another. We investigate the vacuum state of a free massive scalar field in 1+1 dimensions, employing the dichotomic observable $Q(f)=\operatorname{sign}(\phi(f))$ where $\phi(f)$ is the smeared field. In the Heisenberg picture, the time evolution is absorbed into a translation of the time-window function, allowing us to derive the two-time correlation function $C(\tau,L)$ and the Leggett-Garg parameter $K_3=2C(\tau,L)-C(2\tau,2L)$. For non-overlapping time windows, we find that the correlation function decays exponentially with $\tau$ for a massive field. For overlapping windows, our numerical computation for a rectangular time window yields $K_3<1$ across the entire mass range, firmly establishing that the vacuum does not violate the LGI. Thus, under strict noninvasive conditions, the vacuum shows no violation of macrorealism, in stark contrast to its well-known violation of spatial Bell inequalities. Our spacelike-separated protocol provides the first LGI test in QFT with rigorously satisfied NIM, setting a methodological benchmark for future studies and highlighting the fundamental distinction between spacelike entanglement and temporal macrorealism in relativistic quantum fields.

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Mathematical Physics · Cross-listed from math.PR

Thermal Concentration and Poisson-Dirichlet Edge Statistics for Random-Lattice Gibbs Ensembles

Masahiro Kaminaga

We study Gibbs measures on high-dimensional Haar-random unimodular lattices, where the energy of a lattice vector is its squared Euclidean norm. The random lattice is viewed as quenched geometric disorder, and $c>0$ denotes the scaled inverse temperature. We first analyze the edge window of vectors whose length is within the factor $e^{a/n}$ of the shortest length, with fixed $a$ as $n\to\infty$. For the full sign-class Gibbs ensemble, we prove a Poisson point process limit theorem for the Gibbs mass of this window. The mass vanishes in probability for $0<c\le1$, while for $c>1$ it has a nontrivial Poisson limit, and the ranked Gibbs weights converge to the Poisson-Dirichlet distribution with parameter $1/c$. We then pass to a primitive-direction Gibbs ensemble and consider a fixed approximation factor $\gamma>1$. For this modified ensemble, we prove a weighted moment formula and a quenched thermal concentration result in the high-temperature range $0<c<1$. This yields the primitive fixed-factor visibility curve $c=\gamma^{-2}$ for approximate shortest directions. More precisely, the primitive Gibbs mass of the fixed-factor window tends to zero for $c<\gamma^{-2}$, to one for $\gamma^{-2}<c<1$, and to $1/2$ at the critical boundary $c=\gamma^{-2}$. Thus the fixed-factor theorem is a visibility statement for an idealized primitive target measure, not for the original full lattice Gibbs measure. The results provide a random-lattice thermodynamic reference model for Gibbs targets related to approximate shortest vectors, without implying an efficient algorithm for the shortest vector problem.

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Quantum Physics

Quantum advantage prediction in turbulent free-space quantum illumination

Yu Tang, Beining Xia, Qianqian Liu et al. (+3 more)

Quantum illumination offers a significant theoretical advantage for target detection in high background noise environments. However, its practical deployment in free-space channels is hindered by atmospheric turbulence. Stochastic fluctuations in atmospheric turbulence inevitably degrade the quantum signature, rendering the real-time evaluation of quantum advantage under such dynamic conditions a critical yet unresolved challenge. To circumvent the reliance on costly direct turbulence measurements, we propose a physics-driven framework that integrates Kolmogorov-Arnold networks directly bridge macroscopic meteorological observations with microscopic quantum channel dynamics. Trained on 105,120 samples from 12 climatically diverse sites and validated on 26,280 unseen samples from three extreme boundary conditions (arid continental, tropical maritime, high-altitude plateau), our approach establishes a physically consistent mapping from standard meteorological variables to the temporal evolution of the quantum advantage. This end-to-end system dynamically quantifies the degradation of quantum advantage across diverse turbulence conditions. Our results provide a rigorous theoretical and data-driven pathway for environmental adaptation, facilitating the transition of quantum radar networks from proof-of-principle demonstrations to all-weather operational systems.

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All authors Yu Tang, Beining Xia, Qianqian Liu, Cuihong Wen, Heng Fan, Jieci Wang

Quantum Physics

Coupling effect of nearest-neighbor interacting qubit chains to a single qubit system

Manuel Allan L. Orongan, Lemuel John F. Sese and Rayda P. Gammag

This study establishes a theorem that provides sufficient criteria for identifying terms in any time-independent Hamiltonian that have no influence on local dynamics, local observables, or any local phenomena, without any approximation. The usefulness of this theorem is demonstrated by predicting the behavior of three systems. The first system consists of multiple qubit chains with Ising interactions. The second system is formed by a single qubit chain, differentiated by the substitution of Dzyalonshinskii-Moriya (DM) interaction for the last Ising interaction. The predictions were verified by analytically deriving the reduced dynamics of both systems. A third system was also considered, namely, a short qubit chain with a transverse magnetic field on the intermediary environment qubit. This transverse magnetic field signals that the commutation relation required by our theorem no longer holds. The third system's local dynamics were also derived analytically, demonstrating that all Hamiltonian constituents contributed to the reduced dynamics. The physical consequences of our theorem's inapplicability were also explored using this third system by analyzing the entanglement dynamics between the qubits that do not directly interact. The results showed that the entanglement is caused by an emergent coupling between the two non-directly interacting subsystems. This emergent coupling arises from the non-commutativity of the intermediate interactions connecting the two subsystems. When searching for these emergent couplings, our theorem can eliminate intermediate interactions that will not produce them.

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Quantum Physics

Scattering, bound states, and resonances in the one-dimensional Dirac equation via supersymmetric quantum mechanics

Camila C. Soares, Luis B. Castro and Antonio S. de Castro

We develop a unified treatment of scattering and discrete spectra for the one-dimensional Dirac equation with scalar and vector interactions. Under the spin-symmetry condition, the coupled first-order Dirac system maps exactly onto an effective Sturm–Liouville (Schrö\-din\-ger-like) problem for a single spinor component. This mapping provides a convenient framework for analyzing transmission, reflection, and analytic continuation. As an explicit application, we consider effective interactions of hyperbolic Pöschl–Teller type and exploit supersymmetric quantum mechanics and shape invariance to obtain a closed-form expression for the transmission probability. The bound-state spectrum is then recovered from the poles of the analytically continued transmission amplitude, reproducing known results and offering a unified description of scattering and bound states. For the barrier configuration, we briefly comment on the resulting pole pattern in the complex momentum plane and its connection with resonance and quasi-normal-mode behavior. Moreover, we use the chiral transformation to relate the spin- and pseudospin-symmetry sectors and translate results between them without repeating the full derivation.

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Astrophysics of Galaxies

Probing the Parsec-Scale Dynamical Structure of Ionized Gas in Radio-Quiet AGN with SKA

Yuki Kudoh and Satoko Sawada-Satoh

We systematically organize the radio-emitting components in radio-quiet active galactic nuclei (RQ AGN), including jets, accretion disk coronae, dust, ionized gas outflows, and circumnuclear star formation. We present a diagnostic framework for distinguishing these components using spectral turnovers and spectral indices produced by synchrotron self-absorption (SSA) and free-free absorption (FFA), together with brightness temperature and peak frequency. The central premise is that the observed spectral index and its spatial distribution are not unique source properties unless the observing beam is specified: changing the angular resolution changes the physical scale being sampled and therefore changes the mixture of radio-emitting components. By exploiting this scale dependence with SKA1-MID and SKA-VLBI, spatially resolved spectral-index mapping will reveal which physical processes dominate from circumnuclear star formation on $\sim$100 pc scales to jets, coronal emission, and compact ionized gas on parsec and sub-parsec scales. Through multi-frequency continuum imaging and spectral-index mapping, SKA observations will provide a multi-scale physical view of radio-quiet AGN that links radio emission mechanisms to accretion, obscuration, and feedback.

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Quantum Physics · Cross-listed from cs.LG

Generative Modeling of Quantum Distribution with Functional Flow Matching

Jaehoon Hahm, Tak Hur, Joonseok Lee et al. (+1 more)

The emergence of powerful deep generative models based on diffusion and flow matching has enabled the learning and modeling of complex distributions. Learning quantum distributions, however, remains challenging due to the inherent difficulty of accurately modeling the meaningful physical properties of quantum states. We propose Quantum Flow Matching (QFM), a novel generative model designed to learn quantum distribution by utilizing spin Wigner function and flow matching. By converting density matrix into the spin Wigner function and leveraging functional flow matching to learn distributions in function space, QFM enables accurate and effective learning of multi-qubit quantum distributions. We demonstrate the effectiveness of our method by evaluating physical quantities such as trace, purity, and entanglement entropy of the generated quantum states, accurately capturing the underlying physics of the given quantum distributions.

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All authors Jaehoon Hahm, Tak Hur, Joonseok Lee, Daniel K. Park

Cosmology and Nongalactic Astrophysics

Synchrotron and free-free mapping with simulated REACH observations between 50-170 MHz

Daniel Robins, Dominic Anstey, Harry Bevins et al. (+2 more)

Global 21cm experiments aim to detect the hydrogen 21cm signal by separating it from foreground emission that can be orders of magnitude brighter than the signal. REACH (the Radio Experiment for the Analysis of Cosmic Hydrogen) forward-models the sky by jointly fitting signal and foreground spectral parameters to an existing sky map. The fitted parameters yield spectrally constrained, absolutely calibrated maps of the radio sky across the full 50-170 MHz observing band, among the lowest continuous frequencies yet mapped. We assess REACH's ability to fit the 21cm signal and recover accurate foreground maps, using physically motivated foreground models of increasing complexity (starting from a pure synchrotron power law model, then introducing variable amplitudes, curvature, and a free-free component). We evaluate these models against simulated REACH observations of correspondingly complex foregrounds, based on the Global Sky Model and the Python Sky Model. To recover the 21cm signal, more complex datasets require correspondingly complex models, but this introduces degeneracies which limit accurate recovery of foreground parameters. Fitting a foreground with independent synchrotron and free-free emission enables component-separated sky mapping, which has applications beyond radio cosmology; synchrotron is well-recovered across the sky, but free-free recovery is limited. REACH is therefore capable of probing Galactic physics at uniquely low frequencies, alongside its primary goal of detecting the 21cm signal.

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All authors Daniel Robins, Dominic Anstey, Harry Bevins, Eloy de Lera Acedo, Melis O. Irfan

Instrumentation and Detectors

The Solar Neutrino and Astro-Particle PhYsics (SNAPPY) CubeSat Development

Brian M. Sutin, Edward Bierens, Brian Doty et al. (+14 more)

The SNAPPY CubeSat, which was launched May 3, 2026, will demonstrate and space qualify the nuSol neutrino-detection technology. The nuSol technology detects solar neutrinos using a gallium isotope which decays by emitting two particles spaced apart in time; this allows differentiating neutrino events from cosmic rays. In the NIAC Phase II project review in 2021, concept and science were determined to be feasible; however, two precursor studies were recommended before pursuing a full mission study. These studies were to characterize the true deep-space background for the detector's gallium double-pulse signal and to collect a statistically significant number of double-pulse events demonstrating that fast electronics can reliably select and analyze this signal. To test double-pulse signals in space, a NIAC Phase III funded building a 3U CubeSat carrying a 0.1-kg gallium-aluminum-gadolinium-garnet detector housed within an active veto array and shielding. Because the detector requires deep-space-like conditions, the CubeSat is designed for a polar low-Earth orbit at 450 km or higher altitude, collecting data over the Earth's poles above the Van Allen belts. The detector is highly sensitive, with roughly 7-percent energy resolution, with active veto shielding and passive shielding using a patented tungsten-powder and epoxy mixture that disintegrates upon atmospheric reentry. SNAPPY enables additional science during the extended mission phase of year two operations. These include measurements of solar wind particle density and energy spectra with particle identification of electrons, protons, and alpha particles; detection of very low-energy gamma rays from galactic gamma-ray bursts without directionality.

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All authors Brian M. Sutin, Edward Bierens, Brian Doty, Atri Dutta, Jonathan Folkerts, Brooks Hartsock, Kyle Messick, Holger Meyer, Daniel Reichart, Nick Solomey, Mark Crystal, Miguel Rodriguez-Otero, Evgeny Kuznetsov, Robert McTaggart, James Cutler, Joel Steinkraus, Jose G. Rivera

Astrophysics of Galaxies

OCCAM X. Neutron Capture Abundances with Keck/HIRES & Magellan/MIKE

Natalie R. Myers, Peter M. Frinchaboy, Henrique Reggiani et al. (+10 more)

The chemistry of stars provides powerful insight into the history of the Milky Way. With multiple large-sky spectroscopic surveys that are currently available, using chemistry as a means to study the evolution and history of the Milky Way has flourished. Open clusters have long been used as landmarks to calibrate different age dating methods (e.g., gyrochronology and asteroseismology). In this work, we utilize the SDSS-IV/APOGEE-based Open Cluster Chemical Abundances and Mapping (OCCAM) survey as our foundation for new optical observations; enabling us to characterize neutron-capture abundances for known cluster members. For 56 stars in 18 open clusters, we collected high-resolution (R > 50,000), high-S/N (>75 at 5500A), spectra from Keck I and Magellan Baade telescopes. With these data, we derive abundances for 23 elements using BACCHUS, including 7 neutron capture abundances not measurable by APOGEE. Finally, we characterize the radial distribution of these neutron-capture elements in the Milky Way. We find that the second-peak s-process and r-process abundances exhibit relatively flat gradients in the Milky Way. Although not as distinct, the first-peak s-process abundances also have slopes which are shallower than the alpha and iron-peak elements. The differences in the neutron-capture gradients from the lighter elements not just indicates the sources producing these elements are fundamentally different, but that the timescales on which they are produced also differ (especially for the r-process). Moreover, a metallicity dependence of the AGB stars responsible for producing the heaviest s-process abundances may be necessary to consider in Galactic evolution models.

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All authors Natalie R. Myers, Peter M. Frinchaboy, Henrique Reggiani, Sarah Loebman, Catherine Manea, Matthew Shetrone, Katia Cunha, Keith Hawkins, Amaya Sinha, Gail Zasowski, John Donor, Jonah M. Otto, Alessa I. Wiggins

Optics

Finite slab first passage statistics of Henyey Greenstein scattering

Robert Cordery and Claude Zeller

A photon entering a plane parallel scattering slab performs a random walk and eventually escapes through one of the two faces or is absorbed. The standard model employs a Henyey Greenstein phase function (HG) and an exponential step length distribution (Exp). Slab reflectance, transmittance, absorptance, and emergent angular distributions can be calculated in terms of random walk statistics. A central result is that the slab calculations factor into the order resolved first passage statistics of a half space combined with the a factor for the slab thickness. Absorptance is derived from order resolved walk statistics using the absorption rate. Two approaches are used. In the Monte Carlo (MC) approach, an extremely long random walk with many steps is efficiently generated without regard to any boundaries. The intersection of this walk with a large collection of target objects creates an ensemble of excursions of the objects. The MC approach relies explicitly on the memoryless property of Exp so that the portion of the first and last steps inside the object follow the same length distribution as the walk steps. The details of each excursion are recorded and any statistics can be extracted from the database of excursions. In particular, first passage statistics are extracted from this ensemble. In this work the objects are slabs with different positions and thicknesses. In the radiative transfer (RT) approach the slab is divided into thin layers with scattering treated to first order in each layer. The RT equations are then directly integrated over the slab to give the desired first passage statistics, reflectance, transmittance, and absorptance. The two methods agree to the Monte Carlo precision over the tested range of random walk parameters.

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Plasma Physics

Improved Particle Confinement with Resonant Magnetic Perturbations in DIII-D Tokamak H-Mode Plasmas

N. C. Logan, Q. Hu, C. Paz-Soldan et al. (+9 more)

Experiments on the DIII-D tokamak have identified a novel regime in which applied resonant magnetic perturbations (RMPs) increase the particle confinement and overall performance. This Letter details a robust range of counter-current rotation over which RMPs cause this density pump-in effect for high confinement (H mode) plasmas. The pump in is shown to be caused by a reduction of the turbulent transport and to be correlated with a change in the sign of the induced neoclassical transport. This novel reversal of the RMP induced transport has the potential to significantly improve reactor relevant, three-dimensional magnetic confinement scenarios.

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All authors N. C. Logan, Q. Hu, C. Paz-Soldan, R. Nazikian, T. Rhodes, T. Wilks, S. Munaretto, A. Bortolon, F. Laggner, F. Scotti, R. Hong, H. Wang

Adaptation and Self-Organizing Systems · Cross-listed from cs.NE

Self-Organized Learning in Oscillatory Neural Networks with Memristive Signed Couplings

Riley Acker, Aman Desai, Garrett Kenyon et al. (+1 more)

Oscillatory neural networks (ONNs) have emerged as a promising neuromorphic architecture, leveraging coupled dynamical systems to perform computation and represent information through phase relationships. Their interactions can be designed to support intrinsic energy-minimizing dynamics, enabling tasks such as associative memory and optimization, and positioning them as a candidate architecture for continuous learning and inference. We present a neuromorphic primitive implemented using memristive edges with inhibitory couplings as a potential design for autonomous learning, and provide circuit simulation validation that the system is capable of denoising noisy inputs on an auto-associative task. While numerical Hopfield/Ising models routinely assume signed weights, neuromorphic implementations of ONNs often fail to realize negative weights due to device and circuit constraints. A practically implementable route to inhibitory (negative) weights is particularly valuable: it expands the class of attractor structures accessible to oscillator networks beyond purely synchronous couplings, and supports phase-coded memories where anti-phase constraints are not merely transiently enforced during training but can persist autonomously after release. We provide circuit simulations and theoretical analyses demonstrating that signed effective weights are necessary for anti-phase attractors to persist autonomously.

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All authors Riley Acker, Aman Desai, Garrett Kenyon, Frank Barrows

Optics

X-ray Coherent Attosecond Pulse Pair Spectroscopy

Zain Abhari, Thomas M. Linker, Thomas Kroll et al. (+14 more)

X-ray free electron laser (XFEL) experiments using self-amplified spontaneous emission (SASE) pulses typically achieve temporal resolutions of order several femtoseconds, as the pulse duration puts a practical limit to pump-probe or probe-probe schemes. Even with the emerging capabilities to generate pulses with attosecond durations with new single-spike SASE schemes, direct access to attosecond electron dynamics remains an experimental challenge. Here we show how X-ray coherent attosecond pulse-pair spectroscopy (X-CAPPS) provides a powerful new approach to access the ultrashort time-delay window. Coherent attosecond pulse pairs with time delays varying from ~500 as to ~5 fs are generated with Cu K$\alpha_1$ stimulated X-ray emission from a gain medium pumped by intense SASE XFEL pulses. These pulse pairs are analyzed with two subsequent Bragg crystal spectrometers, and the resulting interference spectrum is captured on two sequential 2D image detectors encoding their time separation, relative amplitudes, and phases with high precision. X-CAPPS requires no split-and-delay X-ray optics, nor XFEL pulse modifications, making it broadly implementable across existing facilities. This technique enables the investigation of attosecond processes with $\mathring{A}$ngström resolution, providing a new tool for probing ultrafast dynamics across a wide range of atomic, molecular, and solid systems.

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All authors Zain Abhari, Thomas M. Linker, Thomas Kroll, Yurina Michine, Gota Yamaguchi, Yuichi Inubushi, Taito Osaka, Jumpei Yamada, Ichiro Inoue, Makina Yabashi, Aliaksei Halavanau, Andrei Benediktovitch, Nina Rohringer, Matthias F. Kling, Claudio Pelligrini, Hitoki Yoneda, Uwe Bergmann

Quantum Physics

Active Learning for Calibrating Entangling Gates via Surrogate-Based Optimization

Caleb Walton, Patricia García-Caspueñas, Filippo Zacchei et al. (+3 more)

The fidelity of a quantum gate is sensitive to small deviations in the physical control parameters. Unfortunately, it is generally difficult to exactly model the implemented Hamiltonian for a set of user-defined parameters, necessitating on-device calibration. Here, we present an active learning framework based on Bayesian optimization with a Gaussian Process surrogate to find the optimal parameter set. We validate the technique through numerical calibration of the laser amplitude and frequencies that implement the trapped-ion Mølmer Sørensen gate. We show that a Gaussian process can model the Hamiltonian dynamics. The addition of active learning accelerates the discovery of the optimal parameter set with speed and final fidelity dependent on the quantum projection noise of the data. These results establish the utility of active learning and surrogate models for quantum calibration and control.

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All authors Caleb Walton, Patricia García-Caspueñas, Filippo Zacchei, Ana Larrañaga, Steven L. Brunton, Sara Mouradian

Tuesday 30 June

General Physics

Hyperfine transitions in atoms and rotational transitions in molecules of the early Universe as a possible source of CMB distortions

M. N. Golubev, P. A. Kislitsyn and A. V. Ivanchik

In the near future, measurements are expected to detect the influence of the hyperfine transition in the ground state of the hydrogen atom on the cosmic microwave background (CMB) spectrum. This raises the question of what other substances could produce similar distortions and to what extent. This work presents a systematic analysis of the potential for the most abundant atoms, molecules, and their ions to distort the CMB spectrum. In addition, the wavelength ranges for all the transitions considered in which such distortions might be observed have been calculated. As a result, we conclude that the distortions caused by the most abundant elements are orders of magnitude smaller than those produced by hydrogen.

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Applied Physics

Non-reciprocal heat transfer advances flexible thermoelectric devices

Jinwen Yang, Wenmei Luo, Hongbin Xu et al. (+5 more)

Complex heat dissipation assemblies, inferior performance, and limited flexibility are the primary constraints impeding the wide application and commercialization of conventional flexible thermoelectric devices in wearable electronics and other high-end cooling scenarios. In this work, we report a non-conventional design for flexible thermoelectric devices which can reduce the temperature to -7.03 at room temperature without external heat sink, achieving a cooling temperature drop of 29.25. The design is based on non-reciprocal heat transfer, integrated with thermally conductive composites and screen-printing technologies. This approach takes advantage of directional heat flow, thereby eliminating the need for complex heat sink networks, which extend the applications of flexible thermoelectric devices from personal thermal management to more broader fields such as home healthcare and emergency first aid.

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All authors Jinwen Yang, Wenmei Luo, Hongbin Xu, Fuqing Duan, Yafei Ding, Jie Chen, Guimei Zhu, Baowen Li

Biological Physics

Reaction-Coordinate-Dependent Non-Markovian Friction Governs Protein-Folding Dynamics

Lucas Tepper, Benjamin J. A. Héry, Cihan Ayaz et al. (+4 more)

It is common to project the full atomic-resolution representation of a protein onto a one-dimensionalreaction coordinate (RC) to capture the protein-folding kinetics. As a direct consequence ofthis dimensionality reduction, non-Markovian friction emerges in the framework of the general-ized Langevin equation (GLE). All previous applications of GLEs to protein folding employed anRC-independent friction memory function and therefore did not account for the different frictionin the folded and unfolded states. Using a recently derived GLE with RC-dependent mass andfriction memory function, we introduce a novel method to extract memory functions from timeseries data via a conditional Volterra equation. When applied to molecular dynamics (MD) data ofsix fast-folding proteins, we find strongly RC-dependent memory friction in line with the intuitiveexpectation that friction is higher in the folded than in the unfolded state due to internal proteinfriction. Our numerically efficient method to simulate the GLE confirms the accuracy of the GLEparameter extraction by comparison with the MD data. We show that RC-dependent memoryfriction not only adds physical insight into the folding process but also significantly improves thedescription of protein folding kinetics using low-dimensional RCs.

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All authors Lucas Tepper, Benjamin J. A. Héry, Cihan Ayaz, Florian N. Brünig, Benjamin Dalton, Anton Klimek, Roland R. Netz

Chemical Physics

Position: The Inevitable Transition to Machine Learning in Quantum Chemistry

Karen Sargsyan and Chao-Ping Hsu

Finding exact solutions to the quantum many-body problem is computationally intractable (QMA-hard). Traditional approximations for electrons in an atom or molecule – density functional theory and wavefunction methods – have been indispensable, but their development shows signs of saturation: DFT functionals have proliferated without converging toward the exact functional, and strong correlation remains largely unsolved after decades of effort. This position paper argues that machine learning represents the most promising path forward – not as a proof of logical necessity, but as a decision-theoretic argument: ML succeeds whether the underlying problems are truly hard or merely lack simple analytical solutions. We reframe recent traditional method development as “hand-crafted machine learning” that has exhausted the hypothesis space accessible to human intuition. Significant challenges remain, but these have clear research paths forward, unlike the fundamental barriers facing traditional approaches. ML-based approaches merit strategic priority in quantum chemistry's next phase.

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Atmospheric and Oceanic Physics

GraphCast Skill and Systematic Biases in Indian Summer Monsoon Forecasts: Evaluation Against ERA5 and IMERG

Somnath Luitel, Parthasarathi Mukhopadhyay, Manmeet Singh et al. (+2 more)

The Indian Summer Monsoon (ISM) is one of the most dynamically complex phenomena in the global climate system, yet its accurate prediction remains challenging for both physics-based and data-driven models. This study presents a systematic climatological evaluation of Google's GraphCast, a machine-learning global weather prediction system, against ERA-5 reanalysis and IMERG satellite precipitation for the boreal summer season (June-September, JJAS) over 2021-2024. We analyze deterministic GraphCast forecasts initialized at 00 UTC across 6-hourly steps to assess +24h, +48h, and +72h performance over the full ISM domain. The evaluation covers the climatological mean state (spatial rainfall, surface temperature, low-level winds), rainfall intensity distributions, thermodynamic drivers (tropospheric temperature gradient, DTT; apparent heat source and moisture sink, Q1 and Q2), monsoon dynamics (vertical wind shear, meridional structure), and variability across intraseasonal, synoptic, and spectral scales. GraphCast reproduces the spatial pattern and annual cycle of monsoon rainfall with high fidelity at short leads, showing a near-zero domain-averaged rainfall bias over the core monsoon zone (-0.7 to -1.2 mm/day) and high daily temporal correlation with IMERG (0.89-0.92). However, temporal variance is moderately suppressed across timescales (power-spectrum variance ratio ~0.63), and the intensity distribution systematically underrepresents extreme events and the 95th percentile. GraphCast closely captures the vertical structure and seasonal evolution of Q1 and Q2, but degrades in northward-propagating intraseasonal variability. Overall, GraphCast shows a moderate underrepresentation of rainfall intensity and variance rather than a wet bias or variance collapse, providing benchmark diagnostics for AI weather models.

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All authors Somnath Luitel, Parthasarathi Mukhopadhyay, Manmeet Singh, Sandeep Juneja, Saptarishi Dhanuka

Chemical Physics

Quantum Thermodynamics of Electron Transport along Chains of Redox Centers

Fabrizio Cleri, Ralf Blossey and Stefano Giordano

Intramolecular electron transport in biological systems is typically described as a diffusive hopping process, according to the semi-classical rate theories of Marcus and Hopfield combined with classical Pauli-type master equations. However, the possibility that non-trivial quantum mechanical effects could play a functional role in the transport dynamics in certain biomolecular processes has attracted increasing attention. Here, we extend the quantum mechanical model of open system dynamics by the Lindblad equation to a key biological component, the long chains of redox centers based on iron-sulfur clusters or heme groups that are widespread in many biological organisms, where they realize the cellular respiration. This approach allows to explore a wide range of physical parameters, showing key features of electron transport in these multi-domain protein structures. We pay particular attention to heat and entropy transfer between the electrons and the protein bath, which constitutes a benchmark of physical realism for the models. Electron currents, average transfer times and relative efficiency of the transport process are also explicitly characterized.

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Physics and Society

Edge-based mean-field approximation of dynamics on networks via approximate lumping of Markov chains

Gábor Timár, Jonathan A. Ward and Péter L. Simon

Mean-field approximations for dynamical processes on networks are widely used, but existing derivations often rely either on moment closures or on idealised assumptions about network structure, leaving the nature of the underlying averaging unclear. Here we present a mathematically principled framework for deriving edge-based mean-field approximations for a broad class of Markov processes on networks using approximate lumping. We consider models in which each vertex is in one of a finite number of vertex states and transitions depend on the number of neighbours in each state. Our approach partitions the full Markov chain state space according to the number of vertices and edges in each possible state, and averages transition rates between partitions. This yields density-dependent population processes that, in the limit of large system size, reduce to a low-dimensional system of ordinary differential equations. We demonstrate the method on single graphs and graph ensembles, such as Erdős-Rényi random networks, and show that well-known edge-based mean-field approximations arise as special cases of our approach. Our approximate lumping framework clarifies the nature of the averaging underlying mean-field approximations, providing a basis for future work on assessing their accuracy.

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General Relativity and Quantum Cosmology

Inflation from Covariant Signature Change: A Geometric Mechanism

Raghvendra Singh and Sergey Bondarenko

We present a covariant mechanism in which a smooth change of metric signature, from a Euclidean to a Lorentzian regime, drives a finite interval of accelerated expansion. The transition, encoded by a scalar interpolator along a timelike congruence, occurs on a codimension-one hypersurface where the continued metric is degenerate but curvature invariants remain finite, so the surface is curvature-regular. Using this covariant continuation, we rewrite the Einstein tensor of the continued metric as a localized, interpolator-dependent effective source for the post-transition Lorentzian branch, yielding a purely geometric stress tensor supported near the crossing. In the Lorentzian regime, we derive a model-independent, local criterion for acceleration: inflation persists while the interpolator's slope exceeds a critical value fixed by the extrinsic curvature and the spatial Ricci curvature on the initial hypersurface, and ends when this inequality is first saturated. Standard smooth profiles (tanh, generalized logistic, and power-law/arctan) admit closed-form expressions for the proper-time duration of the accelerated epoch, showing that, for fixed geometric data, the profile shape controls this duration. The construction provides a non-singular, inflaton-free route from a regular Euclidean origin to an early Lorentzian phase of accelerated expansion, in a manner compatible with no–boundary–type boundary conditions.

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Other Condensed Matter

Valley-dependent electron optics using quantum dots in bilayer graphene

Fereshte Ildarabadi and Stephen R. Power

Electrostatically defined quantum dots (QDs) with layer-antisymmetric gating in Bernal-stacked bilayer graphene (BLG) open a local gap and generate a mass-like term with opposite sign in the two valleys, producing strongly valley-dependent scattering without magnetic fields, strain, or spin-orbit coupling. Building on this mechanism, we propose a tunable platform based on such QDs for valley-dependent electron optics in BLG. Using a four-band continuum model and a generalized multiple-scattering formalism, we analyze scattering of Gaussian electron beams from single- and multi-dot architectures and compute valley-resolved currents and angular profiles. A single dot produces distinct valley-dependent deflection, while multi-dot configurations enable enhanced control: identical-dot arrays act as valley splitters, whereas oppositely gated pairs function as valley filters. Combining these elements yields tunable generation, steering, and filtering of highly valley-polarized currents with strong suppression of forward transmission. The required energy scales, gate asymmetries, and device dimensions are within experimentally accessible regimes for dual-gated BLG, establishing quantum-dot arrays as a realistic platform for controllable valley-resolved electron optics.

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Instrumentation and Detectors

Computer vision-based neural networks for radioisotope identification in urban environments

Masen Bachleda, Alea Minar, Ayush Panigrahy et al. (+1 more)

Algorithm development for radioisotope identification in mobile urban search scenarios face significant challenges from non-uniform backgrounds, momentary source encounters, and severe class imbalance between rare threat signatures and background measurements. We present a machine learning-based approach to this problem that converts list-mode gamma-ray data into two-dimensional waterfall spectrograms and applies computer vision architectures to the resulting images. Rather than treating waterfalls as conventional images, we employ a representation where consecutive time spectra can form input channels, similar to RGB channels in color images. This representation encodes both spectral and temporal information, enabling neural networks to more effectively learn patterns that distinguish source signatures from background fluctuations. We evaluate three architectures, a multilayer perceptron (MLP), convolutional neural network (CNN), and vision transformer (ViT), on the Radiological Anomaly Detection and Identification (RADAI) benchmark dataset. At a false positive rate of less than one false alarm per hour, our CNN outperforms the previous-best non-negative matrix factorization (NMF) method across all global metrics, achieving true detection, classification, and identification rates of 0.4334, 0.3965, and 0.2950 respectively, compared to 0.4151, 0.3611, and 0.2625 for NMF. At lower false positive rate constraints, the neural network approaches show comparable but ultimately lower performance than NMF, indicating opportunities for further research.

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All authors Masen Bachleda, Alea Minar, Ayush Panigrahy, Peter Lalor

Instrumentation and Methods for Astrophysics

Nautilus Space Observatory: Unveiling the Diversity and Origin of Sub-Neptunes with the Nautilus Space Observatory

Luis Welbanks, Kylie E. Hall, Julien de Wit et al. (+10 more)

Sub-Neptunes are the most common class of planets in the Galaxy, yet they have no Solar System analog and remain poorly understood as a population. JWST observations have revealed atmospheres spanning a wide range of metallicities, compositions, and cloud properties, driving active debates over whether warm sub-Neptunes harbor liquid water oceans beneath H2-rich envelopes, maintain stratified H2/H2O interiors, or have well-mixed, metal-rich envelopes. Open questions also remain over what physical processes drive transitions between hazy and clear atmospheres. These are intrinsically population-level questions that single-target observations, however deep, cannot resolve. Here we argue that a sub-Neptune population survey with the Nautilus Space Observatory, a proposed constellation of large-diameter space telescopes, would deliver the first statistical map of sub-Neptune atmospheric diversity, test competing classification schemes, identify habitable candidates, and serve as a pathfinder population for the eventual habitable-worlds search. These goals are achievable across the proposed mission classes for the constellation, and this architecture is uniquely well-matched to this science case since population-level questions demand sample size and a uniform observing strategy.

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All authors Luis Welbanks, Kylie E. Hall, Julien de Wit, Ana Glidden, Noah Tuchow, Ilaria Pascucci, Dániel Apai, Robin Wordsworth, Benjamin V. Rackham, Chia-Lung Lin, Raymond Pierrehumbert, Mercedes López-Morales, A. D. Feinstein

Quantum Physics

Quantum-advantage resource of a two-mode Gaussian state: Analytical theory of convex optimization and a Galois no-go for the closed-form solution

Kunwar Kalra and V. V. Kocharovsky

We study the problem of extracting a quantum complexity resource from a mixed Gaussian state of the multimode light. We present the first complete, certificate-checked solution to this problem in a genuinely coupled sector. We carry this out for the two-mode case, the smallest case in which modes are genuinely coupled. Even in this case the solution is highly nontrivial, and we rigorously prove that it cannot be given in a closed form.

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Instrumentation and Methods for Astrophysics

The Simons Observatory: Overview of the Cryogenic Half-wave Plate Polarization Modulators

Junna Sugiyama, Kyohei Yamada, Bryce Bixler et al. (+5 more)

The Simons Observatory (SO) is a ground-based Cosmic Microwave Background (CMB) experiment that is located in the Atacama plateau. The Small Aperture Telescopes (SATs) of SO are optimized for polarimetry on the degree scale. Atmospheric $1/f$ contamination of the CMB signal poses a significant challenge for observations at this angular scale. In order to control the $1/f$ noise, the SATs utilize a Cryogenic Half-Wave Plate (CHWP) in their optics. The CHWP modulates the polarization signal to a higher frequency to separate it from the unpolarized atmospheric noise. Precision measurements of the CHWP rotation angle are required to successfully recover the target polarized signals. We present a method to reconstruct the CHWP rotation angle that achieves a noise level of 0.16 $\mu\mathrm{rad\sqrt{s}}$, meeting our requirement.

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All authors Junna Sugiyama, Kyohei Yamada, Bryce Bixler, Daichi Sasaki, Yuki Sakurai, Kam Arnold, Nicholas Galitzki, Akito Kusaka