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Physics Physics

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Friday 28 August

Computational Physics

Accelerated S-NFC for Million-Chaff RCS Computation Using Low-Rank Compression of Concatenated Block Rows

Dong-Yeop Na, Somyeong Lee and Chung Hyun Lee

Sparsification via neglecting far-field coupling (S-NFC) enables fast full-wave radar-cross-section analysis of large-scale chaff clouds by retaining only significant local electromagnetic interactions. This letter further accelerates S-NFC by concatenating the retained off-diagonal interaction blocks associated with each receiving chaff element and applying a joint low-rank factorization with a shared receiving-side basis. Exact self interactions are preserved, while repeated chaff templates reuse precomputed lower–upper factorizations of the self-interaction blocks. The compressed formulation reduces retained-coupling storage and matrix–vector multiplication cost and also decreases the number of iterations required by the generalized conjugate residual solver. Numerical tests with 100,000 chaff elements demonstrate sub-$1\%$ complex-far-field error for low-rank approximations in sparse regimes and identify a practical self-only limit at sufficiently large mean spacing. For a one-million-chaff plume, the proposed compressed S-NFC achieves a $6.92\times$ end-to-end speedup over uncompressed S-NFC while storing only $6.60\%$ of the retained coupling, with a complex-far-field error of $0.253\%$.
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Computational Physics

Higher-Order Topological Phase in the Two-Dimensional Type-IV Magnet MgCr$_2$O$_4$

Xiaorong Zou, Hyeon Suk Shin, Yanmei Zang et al. (+4 more)

Type-IV two-dimensional (2D) magnetism-a newly classified collinear magnetic phase featuring nonrelativistic spin degeneracy and spin-orbit-coupling-induced momentum-dependent spin splitting-extends the symmetry classification of collinear magnets, opening new opportunities for unconventional topological quantum states. Here, we reveal that the recently proposed two-dimensional type-IV 2D magnet MgCr$_2$O$_4$ hosts an intrinsic higher-order topological insulating phase, featuring $\mathcal{C}_{3z}$-protected corner states and a nontrivial rotational topological invariant of $\chi^{(3)}$ = $\{-2,4\}$ with a quantized fractional corner charge of $4e/3$. Spin-orbit coupling breaks the spin-degeneracy-enforcing symmetry $[C_{2}||M_z]$ while preserving the crystalline $\mathcal{C}_{3z}$ rotational symmetry that protects the higher-order topological phase, thereby enabling spin splitting to coexist with the nontrivial topology. Furthermore, the higher-order topological phase remains intact throughout a wide range of biaxial strains without band-gap closing and topological phase transition, demonstrating the robustness of the symmetry-protected topological state against external perturbations. Our work establishes a direct connection between type-IV magnetic system and higher-order topology, providing a new route for symmetry-engineered magnetic topological quantum states.
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All authors Xiaorong Zou, Hyeon Suk Shin, Yanmei Zang, Ying Dai, Chengwang Niu, Chang-Jong Kang, Chang Woo Myung

Chemical Physics · Cross-listed from cond-mat.mtrl-sci

Ionization Energies, Electron Affinities, Bandgaps, Exciton Binding Energies, and Polarization Energies of Orientation-Controlled Picene, [6]-Phenacene, and [7]-Phenacene Thin Films

Rintaro Makino, Mihiro Kubo, Keiichirou Yonezawa et al. (+2 more)

Phenacenes, in which benzene rings are fused in a zigzag manner, are chemically robust $\pi$-conjugated hydrocarbons of interest for organic electronic applications and superconductivity. However, quantitative electronic parameters of phenacene thin films remain limited compared with those of acenes. Here, we determine the ionization energies (IEs), electron affinities (EAs), band gaps, exciton binding energies, and polarization energies of orientation-controlled thin films of picene, [6]-phenacene, and [7]-phenacene using ultraviolet photoelectron spectroscopy and low-energy inverse photoelectron spectroscopy. The energy parameters depend only weakly on molecular size. In contrast, both IE and EA exhibit large orientation-dependent shifts of approximately 1 eV: lying films show IEs of 6.41-6.43 eV and EAs of 2.16-2.42 eV, whereas standing films show IEs of 5.44-5.67 eV and EAs of 1.36-1.53 eV. Nevertheless, the band gaps of approximately 4 eV and exciton binding energies of approximately 1 eV remain nearly independent of molecular size and orientation. Analysis of polarization energies shows that the induction term is nearly orientation independent, whereas the electrostatic term strongly depends on orientation and originates primarily from molecular quadrupole moments. These results identify molecular orientation as a key factor governing frontier energy levels in phenacene thin films.
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All authors Rintaro Makino, Mihiro Kubo, Keiichirou Yonezawa, Hiroyuki Yoshida, Satoshi Kera

Computational Physics · Cross-listed from cs.LG

Beyond Pairwise Graphs in Science: Hypergraph Adaptive Wavelet Operators for Parametric PDEs

Rajat Sarkar, Venkataramana Runkana and Souvik Chakraborty

Physical systems are often modeled by solution operators that map input fields, parameters, geometries, or past states to steady or future physical states. Learning these maps is difficult, especially for time-dependent systems that must assimilate history and remain stable under autoregressive rollout. Many neural operators work best on regular, structured grids, while realistic simulations often require unstructured meshes or point clouds to resolve complex geometries; in such settings, grid-centric representations can lose accuracy. Graph neural operators handle these domains through message passing or spectral graph filtering, but pairwise edges do not directly capture group-wise couplings among mesh cells, local neighborhoods, or conservation volumes. We introduce the Hypergraph Adaptive waveLet Operator (HALO), which lifts the domain to a hypergraph and learns in its spectral wavelet domain. HALO avoids explicit hypergraph-Laplacian eigendecomposition through Chebyshev polynomial wavelet filters, giving localized spectral kernels at linear sparse-matrix cost. Its trainable dyadic wavelet scales are regularized toward tight-frame coverage, allowing the frequency response to adapt to each PDE while encouraging stable multi-scale spectral coverage. Across 2D and 3D benchmarks on structured and unstructured discretizations, HALO achieves best or near-best accuracy among frequency-, transformer-, DeepONet-, state-space-, and graph-based baselines and sustains stable multi-step rollouts. The same model scales to industrial aerodynamic geometries: on meshes of a few hundred thousand points it is on par with, or better than, the strongest fixed-discretization transformers, while remaining resolution-equivariant.
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Fluid Dynamics · Cross-listed from math.NA

A Massively Parallel Hybridizable Discontinuous Galerkin Solver for Direct Numerical Simulation of Compressible Flows on GPUs

Andrew Welter, Thea Collin, Ngoc Cuong Nguyen et al. (+1 more)

Direct numerical simulation (DNS) of compressible transitional and turbulent flows requires numerical methods that combine high-order accuracy, robustness, and computational efficiency to resolve a broad range of spatial and temporal scales. This paper presents a massively parallel hybridizable discontinuous Galerkin (HDG) solver for DNS of the compressible Navier-Stokes equations on GPU-accelerated high-performance computing systems. The proposed solver combines high-order HDG discretization with robust shock capturing, diagonally implicit Runge-Kutta (DIRK) time integration, and an efficient Newton-GMRES solution strategy accelerated by additive Schwarz preconditioning and reduced-basis approximation. A distributed implementation of these methods based on GPU-aware MPI, Kokkos, and CUDA/HIP libraries enables scalable execution on heterogeneous computing platforms. The solver is demonstrated on three canonical benchmark problems covering a wide range of Mach-number flow regimes: subsonic transitional flow over the Eppler 387 airfoil, the supersonic Taylor-Green vortex, and hypersonic boundary-layer transition. Numerical results are compared with available experimental measurements and published DNS data, showing good agreement across distinct flow regimes. The results demonstrate the ability of the proposed solver to resolve laminar-turbulent transition, strong compressibility effects, shock-associated flow structures, and fully three-dimensional turbulent dynamics.
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All authors Andrew Welter, Thea Collin, Ngoc Cuong Nguyen, Jaime Peraire

Computational Physics

Vectorized Symmetric and Fermionic Tensor Network Implementations for GPU-Accelerated Variational Monte Carlo

Si-Jing Du, Johnnie Gray, Ao Chen et al. (+1 more)

Variational Monte Carlo (VMC) calculations based on tensor networks (TN) have recently achieved competitive accuracy in ground-state calculations of strongly correlated spin and fermionic systems. However, existing tensor network VMC (TN-VMC) algorithms have not been formulated in a manner that can fully utilize GPU acceleration. We tackle the key missing ingredient, namely, the vectorized evaluation of tensor network amplitudes and tensor network operations. This ensures high GPU utilization by batching over computations with identical structure. In particular, we show how to achieve vectorization for the practically relevant case of abelian symmetric tensor networks (which includes fermionic tensor networks) by developing a “flat” tensor network formalism for block-sparse tensor representation and contraction. Using this, we construct a GPU-adapted symmetric TN-VMC workflow with batched tensor network computation. In the two-dimensional Fermi–Hubbard model, we demonstrate a GPU speedup of up to $300 \times$ over single core CPU implementations, for fermionic TN variational wavefunctions.
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All authors Si-Jing Du, Johnnie Gray, Ao Chen, Garnet Kin-Lic Chan

Applied Physics

Extending the operating window of scanning electron microscopy through an integrated electron-optical architecture for high-temperature and near-ambient-pressure environments

Yue Chai, Honglong Zhao, Xinning Tian et al. (+2 more)

Scanning electron microscopy (SEM) under simultaneously high-temperature, near-ambient-pressure (NAP), and reactive-gas environments requires coordinated control of vacuum isolation, electron-beam transmission, signal generation, and thermal management, constraints that have long limited the operating window of environmental scanning electron microscopy (ESEM). Here we establish an integrated electron-optical architecture that combines a multistage differential-pressure pathway, front-stage pressure transition, detector optimization, thermal management, and a gas-focusing sampling architecture into a unified ESEM platform. Pressure distribution and electron-beam transmission are quantitatively validated through computational fluid dynamics (CFD), Monte Carlo electron-gas scattering analysis, and direct beam-current measurements, while detector optimization and thermionic-electron suppression preserve stable imaging under elevated pressure and temperature. The resulting system enables stable SEM imaging at pressures up to 20,000 Pa and high-temperature imaging up to 1,400 degrees C, continuous observation of hydrated biological specimens, and synchronized SEM-QMS operando characterization using local gas sampling. These developments establish a general electron-optical framework for extending ESEM toward realistic operando environments where elevated temperature, reactive gases, structural evolution, and gas-phase chemistry can be investigated simultaneously.
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All authors Yue Chai, Honglong Zhao, Xinning Tian, Chao Ang, Zhu-Jun Wang

Plasma Physics

Counter-rotating density and current structures in a partially magnetized $\mathbf{E}\times\mathbf{B}$ plasma

Pengze Xiao, Ya Zhang, Hongyu Wang et al. (+2 more)

The first 3D kinetic simulation of a magnetron discharge reproduces the measured rotating spoke and reveals that density and current rotate in opposite directions: the $m=1$ spoke turns in the $\mathbf{E}\times\mathbf{B}$ direction at 90~kHz while $m\simeq16$ electron-cyclotron-drift-type filaments turn at 1.0~MHz, with no net propagation along $\mathbf{B}$. Magnetic drifts exchange far more energy than they deposit, yet their spoke-front heating sustains the ionization. Following helical paths, the anode-directed current is relayed by de-trapping turbulence at the sheath edge (50%) and by the spoke channel in the bulk (97%).
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All authors Pengze Xiao, Ya Zhang, Hongyu Wang, Wei Jiang, Jean-Pierre Boeuf

Chemical Physics

Mode-Specific Dynamics of $\text{CO}_2$ Hydrogenation on Copper: The Hidden Role of Molecular Rotation

Junfan Xia, Zhikai Jiang, Yaolong Zhang et al. (+3 more)

Catalytic hydrogenation of $\text{CO}_2$ to formate on copper is a key elementary step for $\text{CO}_2$ utilization. Previous experimental and theoretical studies suggested an Eley-Rideal mechanism for this reaction, promoted by bending vibrational excitation, yet direct state resolved evidence remains lacking. Here, we present first-principles dynamical predictions for $\text{CO}_2$ hydrogenation on Cu(111) based on an accurate full-dimensional neural network potential energy surface. Our calculations near-quantitatively reproduce the measured reaction probabilities, including their nozzle-temperature and incidence-energy dependence. Our state-resolved results indicate that while vibrational excitation of the bending mode enhances reactivity, it alone cannot account for the observed reactivity increase with nozzle temperature. Instead, rotational excitation plays a dominant role, mainly attributable to the significant change in anisotropy of the molecular polar orientation as $\text{CO}_2$ accesses the transition state. This mode-specific insight reinforces the hidden role of rotation in surface reactivity, opening new avenues for state-selective control of $\text{CO}_2$ hydrogenation on heterogenous catalysts.
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All authors Junfan Xia, Zhikai Jiang, Yaolong Zhang, Bo Peng, Hua Guo, Bin Jiang

Plasma Physics

Reinforcement-learning control of turbulence transition in the modified Hasegawa-Wakatani system

Luning Sun, Ben Zhu, Xin-Yang Liu et al. (+2 more)

Control of plasma turbulence remains a long-standing challenge in magnetically confined fusion research. Here, we explore a reinforcement-learning (RL) approach for bidirectional control of the turbulence-zonal-flow transition in the modified Hasegawa-Wakatani system, a minimal model of electrostatic drift-wave turbulence. Within our model, a weak zonal drag damps the otherwise long-lived zonal structures, giving them a finite lifetime and restoring the drive-damping balance required for repeatable transitions within finite control episodes; meanwhile, actuation is applied through a spatially distributed Gaussian source field under a time-weighted budget constraint on actuation costs. The plasma model is then coupled to CNN-based soft actor-critic and twin-delayed deterministic policy-gradient agents through a GPU-native JAX solver that is highly optimized for fast online training. In the turbulence-suppression task, the learned budget-aware schedule achieves the lowest time-integrated turbulent flux for a given consumed budget, outperforming both constant and linearly decreasing baselines across all tested unseen initial conditions. In the inverse zonal-break task, the agent discovers an up-down antisymmetric actuation pattern that induces radial $E\times B$ convection, disrupts the zonal structure, and sustains the turbulent state. A physics-informed warm-buffer initialization facilitates this discovery, as random exploration alone struggles to locate the narrow optimal manifold within the vast action space. These results demonstrate reinforcement learning as a practical trajectory optimizer for nonlinear plasma dynamics, such as turbulence control, and highlight the importance of physics guidance in such applications.
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All authors Luning Sun, Ben Zhu, Xin-Yang Liu, Deepak Akhare, Jian-Xun Wang

Biological Physics

RNA-like Polyelectrolyte in a Viral Capsid: Molecular Dynamics with Explicit Electrostatic Interactions

Xintong Jiang, Colin Denniston and Gonca Erdemci-Tandogan

The organization of RNA genomes within viral capsids is primarily controlled by electrostatic interactions between the negatively charged genome and positively charged N-terminal domains of coat proteins. In theoretical approaches, these interactions are commonly captured by mean-field models that smooth capsid charge over the inner surface and treat ionic screening as a continuum. However, charges are localized at discrete N-terminal binding sites and ionic screening arises from correlated ion distributions. Here we use molecular dynamics simulations with explicit ions, explicit water, and full Coulomb electrostatics to simulate a linear polyelectrolyte confined within a model capsid bearing discrete N-terminal-like charge sites. We first validate our approach by simulating a polyelectrolyte in bulk solution and demonstrating that persistence length decreases with increasing salt, matching experimental measurements for single-stranded RNA. When confined within a capsid, radial density profiles shift systematically inward from the capsid wall with increasing salt concentration, in agreement with mean-field predictions. By independently varying charge magnitude, binding-site density, and N-terminal protrusion length, we show that total electrostatic coupling governs global organization while geometric details modulate local genome-wall contact and angular genome organization near N-terminals (within the T=3 architecture, linear genome topology, and monovalent salt range studied here). Across all simulations, equilibration times increase sevenfold with salt, revealing kinetic effects inaccessible to equilibrium theory. These results validate continuum approximations for radial organization while revealing deviations arising from discrete molecular details and establishing a framework for future investigations of genome secondary structure, capsid geometry, and assembly kinetics.
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Optics · Cross-listed from cond-mat.mes-hall

Subcritical bifurcation and on-off bistability in ballistic polariton condensates

Oleg I. Utesov, Soohong Choi, Pavel Kozhevin et al. (+11 more)

Dynamics of exciton-polariton condensates under continuous-wave incoherent Gaussian optical pumping is considered. It is shown that the conventional supercritical Stuart-Landau picture is invalid in a certain domain of the parameter space. For strong polariton repulsion from the reservoir and relatively small pump spots, the dynamics is adequately described by the quintic Stuart-Landau equation. The corresponding subcritical pitchfork bifurcation leads to condensate formation, accompanied by bistability between the trivial and nontrivial states over a finite pump-power range and a one-bit memory. Further increase of the repulsion parameter or decrease of the spot size breaks down the perturbative approach and leads to a peculiar self-trapping regime with complex dynamics. Experimental evidence of the emergence of the proposed behavior is provided. Our findings can be used to design polaritonic setups that exploit the predicted memory effect.
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All authors Oleg I. Utesov, Soohong Choi, Pavel Kozhevin, Min Park, Daegwang Choi, Hyungdo Lee, Alexey N. Osipov, Alexey V. Yulin, Se Kwon Kim, Yong-Hoon Cho, Igor S. Aranson, Hyoungsoon Choi, Anton V. Nalitov, Sergei V. Koniakhin

Chemical Physics

Resolving Spin-Phonon Relaxation Pathways in Molecular Qubits via Regularized Regression

Sayan Banerjee

Designing molecular qubits requires controlling the spin-lattice relaxation pathways that fundamentally limit the coherence time. For spin-1/2 molecular qubits, significant discrepancies remain between theoretical predictions and experimental measurements of spin-phonon relaxation pathways, with theory often overestimating the role of low-frequency vibrational modes. Here, we present an alternative first-principles approach augmented with regularized regression that identifies spin-phonon relaxation pathways in an automated fashion without ad hoc mode selection. Applied to Cu porphyrins spin-1/2 molecular qubits, the method successfully reproduces experimental trends in relaxation times and predicts the curvature in the relaxation-vs-temperature profile. The g-tensor time series reveal distinct system-specific autocorrelation functions and spectral-density profiles despite the qubits' structural similarity. Further, regression between g-tensor time series and mode-projected vibrational-amplitude time series obtained from molecular dynamics yields linear and bilinear mode coupling contributions to each g-tensor component. Because the method is based on atomic displacements sampled directly from molecular dynamics, it naturally incorporates anharmonic effects and does not require the harmonic approximation. This framework puts forward a regression-driven, mode-resolved, and coupling-order-separated spin-phonon analysis as a general strategy for predicting and engineering longer-lived molecular qubits.
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Instrumentation and Detectors

Migration of Belle II TOP Feature Extraction from the Zynq Processing System to PCIe40 Readout PCs

Harsh Purwar, Shahab Kohani, Vasily Shebalin et al. (+11 more)

The Belle II Time-of-Propagation (TOP) detector is a key system for charged-particle identification (PID). Although TOP operated successfully during initial Belle II data taking, increasing luminosity and beam-induced background led to more frequent single-event upsets (SEUs) in the radiation-exposed Zynq systems-on-chip (SoCs). Resulting lockups of the embedded processing systems (PSs) interrupted data acquisition. To mitigate this limitation, waveform feature extraction, a critical task of the on-detector Zynq PS, was migrated to the off-detector PCIe40 readout PCs (ROPCs). The new architecture bypasses the PS in the event data path and performs feature extraction outside the detector radiation environment. This change removed SEU-induced PS lockups from the event data path and enabled stable operation of the TOP front-end electronics and the Belle II data-acquisition system under increased luminosity and background conditions. The typical TOP deadtime decreased from about 1% to a level consistent with zero after the final firmware patch, and stable operation was demonstrated at a Level-1 (L1) trigger rate of 30 kHz with a microchannel-plate photomultiplier-tube (MCP-PMT) hit rate of approximately 5 MHz per PMT. This paper describes the migrated architecture, its deployment and validation, and its operational and PID performance.
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All authors Harsh Purwar, Shahab Kohani, Vasily Shebalin, Martin Bessner, Matt Andrew, Thomas Browder, Tommy Lam, Kurtis Nishimura, Sourav Patra, Vladimir Savinov, Marko Staric, Gary Varner, Satoru Yamada, Keisuke Yoshihara

Accelerator Physics · Cross-listed from hep-ph

Future of Artificial Intelligence for Science in Japan 2024 Community Report

Yoshitaka Itow, Jia Liu, Hirokazu Maesaka et al. (+16 more)

This white paper summarizes scientific challenges and AI/ML research opportunities identified through the FAIRS Japan 2024 unconference process. The discussion focuses on three major physics domains: accelerator physics, cosmology and astrophysics, and neutrino physics. Although each domain has distinct scientific goals and experimental constraints, several common technical themes emerge: high-dimensional reconstruction, fast and accurate simulation, uncertainty propagation, simulation-to-data mismatch, anomaly detection, real-time decision-making, and shared infrastructure.
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All authors Yoshitaka Itow, Jia Liu, Hirokazu Maesaka, Vinicius Mikuni, Nhat-Minh Nguyen, Hironao Miyatake, Atsushi J. Nishizawa, Patrick de Perio, Daniel Ratner, Kazuhiro Terao, Leander Thiele, Omar Alterkait, Francois Drielsma, Rocio Garcia, Masako Iwasaki, Ahsani Hafizhu Shali, Federica Tarsitano, Takahiro Terada, Junjie Xia

Chemical Physics

OrbGNN: A Wave function-based Machine Learning Interelectronic Representation

Brody Quebedeaux, Shahzad Akram, Markus Reiher et al. (+1 more)

Machine learning interatomic potentials (MLIPs) have become emerging tools in molecular modeling and computational chemistry. By learning high-dimensional potential energy surfaces from quantum chemical data, MLIPs enable accurate and efficient predictions of structural, thermodynamic, and dynamical properties. However, such models have limitations in predictions of electronic properties and the effects of static electron correlation due to their lack of electronic structure information. This work presents OrbGNN, an electronic structure graph architecture analogous to molecular graph and MLIP frameworks, where pair-orbital interactions constitute the graph representation, while orbital entanglement encodes the connectivity between them. By embedding information derived from orbital correlation metrics directly into the graph topology, OrbGNN provides a compact representation of a molecule s orbital landscape and electron correlation patterns. Analysis of the behavior of the feature space in an orbital graph are shown to demonstrate model robustness. The model is evaluated for the dissociation of nitrogen and for a larger dataset of diatomic molecules. Finally, the OrbGNN model is applied to a set of octahedral iron(II) complexes to predict spin-state energy gaps.
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All authors Brody Quebedeaux, Shahzad Akram, Markus Reiher, Konstantinos D. Vogiatzis

Thursday 27 August

Instrumentation and Detectors

The efficiency of moderating neutron detector: Monte Carlo simulation, experimental validation, and angular dependence

Carl R. Brune

This paper describes the Monte Carlo simulation and experimental validation of the neutron detection efficiency in a 4pi polyethylene moderating detector. The experimental validation was performed using several sources providing neutron energies from 10s of keV up to 14 MeV. The Monte Carlo simulations employed the MCNP6 code are believed to be accurate within 3% for neutron energies below 6 MeV. A new method for parametrizing the dependence of the efficiency on the neutron angular distribution for in-beam experiments is also presented. This approach utilizes a Legendre decomposition of the efficiency and allows all of the needed information to be extracted from a single simulation.
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Medical Physics · Cross-listed from cs.AI

PEEL: Physics-Enabled Evidential Learning for Identifiable Uncertainty in CT Imaging

Ge Wang

Normal-inverse-gamma (NIG) regression is not uniquely identifiable from its marginal Student-t likelihood: the likelihood determines three combinations of four NIG parameters and is constant along a one-dimensional fiber. We identify that fiber using independent physical measurement. As an initial embodiment, a reconstruction network receives one noisy filtered-backprojection (FBP) image and is first trained only by Student-t negative log-likelihood to estimate the three identifiable coordinates (gamma, alpha, c). The network is then frozen; repeated physical-noise realizations propagated through its reconstruction output form a Monte Carlo (MC) teacher label for output-domain aleatoric variance. An aleatoric head attached to frozen features learns this label, after which (beta, nu) are recovered algebraically. On 30 held-out simulated objects at five photon levels, one-image predictions achieved pooled Spearman correlations of 0.832-0.951 against independent 400-repeat references, median within-image correlations were 0.834-0.947, and 98.81-99.55% of evaluated pixels satisfied the algebraic admissibility condition. The method needs no KL term, reference prior, evidence regularizer, or cross-loss weight.
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Instrumentation and Detectors · Cross-listed from eess.SP

A Nonuniform-Sampling Theory for Static Multi-Threshold Sampling

Ao Qiu and Qingguo Xie

Multi-Threshold (MT) sampling fixes voltage levels and records when a waveform crosses them. The resulting signal-generated event stream is governed not by a prescribed clock but by the nonuniform geometry of the realized crossing set. Within classical nonuniform sampling, we develop a retained-event MT theory for static, uniformly spaced thresholds. For a realized retained MT time set, Beurling's weak-limit theorem gives the exact necessary-and-sufficient condition for stable sampling of $PW_\Omega$. For a fixed signal class, the same principle gives the a priori criterion: uniform stable MT sampling is equivalent to Bernstein uniqueness for every set in the class weak-limit hull. This criterion reduces to computable forms under structured priors. Periodic templates give finite fiber/rank tests, periodic-gap streams give a Shannon-type complete-interpolation boundary and a stable-sampling density rule, and finite-state gap priors reduce noncritical certification to a maximum-cycle-mean condition. Kadec-type local certificates, retained-density bounds, and finite-matrix tests provide practical sufficient conditions for finite active records, while conditional perturbation bounds quantify how jitter, front-end noise, and threshold error consume a clean sampling margin under event correspondence. The theory also identifies the unavoidable boundary of this model: unrestricted finite-energy retained MT records have zero full-line lower Beurling density and therefore cannot provide a universal prior-free sampling theorem for $PW_\Omega$. Within retained-event point sampling, the MT recovery question is resolved precisely: exact recovery is governed by event-set geometry, computable guarantees require structural priors or finite-dimensional/tail assumptions, and the unrestricted static finite-energy problem is impossible.
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Chemical Physics

Molecular Transferability of a Noble-Gas Coordinate for Electronegativity Equalization

Megan Simons, Jonathan Washburn and Elshad Allahyarov

Charge-equilibration models predict how electrons redistribute over a molecule more cheaply than quantum chemistry, and each begins from a table of atomic electronegativities and hardnesses. A recent table replaces ionization energies and electron affinities with one geometric quantity: each main-group atom's fractional distance to the noble gas closing its row. Holding geometries, electrostatic damping and the molecule list fixed, we compare it with spectroscopic values, with its own kernel refitted, and with a quadratic control, over a primary set of fifty-two molecules and ions at the B3LYP/def2-TZVP level. Two structural consequences follow from the table construction rather than the equalization solver. Atoms at equal fractional distance receive identical electronegativities, so the dipole moments of chlorine monofluoride, iodine monobromide and sulfur dioxide vanish exactly, and the measured $0.72$ debye $\mathrm{HF}/\mathrm{HCl}$ gap is lost. Because the first period is excluded, hydrogen retains its spectroscopic electronegativity above every geometric value, reversing $\mathrm{O{-}H}$, $\mathrm{N{-}H}$ and hydrogen-halide polarity. Fitted alike, geometric and quadratic kernels agree to $0.0022$ electron per atom, so predictions are set by the fitted energy scales, not the kernel shape. Resolving the electronegativity scale period by period restores correct polarity in all five polyatomic heavy-atom-hydrogen tests.
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Chemical Physics

Scaling Neural Network Quantum States for Ab Initio Quantum Chemistry

Chenxi Yu, Hanlin Kong, Jianan Wei et al. (+4 more)

Neural-network quantum states (NNQSs) can represent many-electron wave functions without explicitly enumerating the determinant space, but their accuracy depends jointly on model size and variational-optimization effort. Here we characterize this dependence for a physics-conditioned autoregressive NNQS trained separately on two six-molecule source benchmarks. Across eight model sizes and five optimization milestones, we find that model size and optimization steps jointly shape the energy error. The capacity advantage of larger models becomes more apparent with sufficient optimization, while the returns from additional optimization vary with model size. We capture this coupling using an interaction scaling law and quantify the cumulative compute of each evaluated configuration. The resulting error-compute Pareto frontiers provide a practical decision rule for jointly selecting model size and optimization steps under a given compute budget within the evaluated range. Furthermore, we find that this beneficial scaling trend persists during fine-tuning on held-out N$_2$. Pretrained models show decreasing error with increasing model size, with a steeper reduction following pretraining on the Hard benchmark. Together, these results place autoregressive neural quantum states within the broader landscape of empirical neural scaling and open a quantitative route toward the systematic scaling of neural quantum solvers for ab initio quantum chemistry.
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All authors Chenxi Yu, Hanlin Kong, Jianan Wei, Lizhong Fu, Honghui Shang, Wenguan Wang, Jinlong Yang

General Physics

Exploring thermodynamic and photonic properties of new black hole solutions in F(R) gravity theory

Mohsen Dehghani

We investigate black hole solutions in F(R) gravity within a four-dimensional spacetime, separately treating the cases of vanishing and nonvanishing energy momentum tensors. We demonstrate that in the absence of an energy momentum tensor, the number of independent equations is sufficient to obtain the Ricci flat solutions without the need for a prescribed F(R) function. In the same case, also the solutions with variable Ricci scalar can obtained too. Furthermore, for a nonvanishing energy momentum tensor, we derive exact solutions for both constant and variable Ricci scalars, thereby introducing new charged black holes. Utilizing this new method, we not only recover the general relativistic and previously known F(R) gravity solutions but also introduce four new classes of F(R) black holes. We calculate their thermodynamic quantities and confirm the validity of the first law of black hole thermodynamics. The thermal stability of these new black holes is analyzed using both thermodynamic and geometrical approaches. Finally, the photon spheres and black hole shadows are studied within the F(R) gravity framework.
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Physics and Society

Save 2050: A Planetary-Scale Collective Prediction System for the Singularity Crisis

Jiang Zhang, Bing Yuan and Qian Zhang

The Anthropocene mode of development is driving civilization toward a "singularity crisis": artificial intelligence (AI) is rapidly approaching general intelligence (AGI) with escalating risks of losing control, while unrestrained economic growth generates super-exponential growth of entropy production that pushes the Earth system toward its tipping points. This paper proposes the "Save 2050" initiative: a distributed planetary-scale collective prediction system that aggregates judgments about the future from humans and AI through open registration, crowdsourcing, and incentive mechanisms, and integrates them via large-scale simulation into inspectable "predicted worlds," enabling humanity to systematically see the future for the first time. We argue for the initiative's feasibility along four dimensions—the maturation of AI forecasting, human collective intelligence and the institutional environment, supporting progress in related fields, and societal demand. We then identify three key enabling technologies: long-horizon automated resolution, simulation-based prediction aggregation, and reflexivity governance. We analyze potential risks—including reflexivity, cognitive monoculture, narrative capture, and regulatory and ethical concerns—together with mitigation strategies, and we outline a phased roadmap with open problems. The initiative's primary goal is not to intervene in the future, but to make the future visible, discussable, and co-writable.
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Instrumentation and Detectors

Frequency Synchronization Circuit Model for Analog Vector-Matrix Multiplication in the Frequency Domain

Taeju Lee, Scott T. Habermehl, Timothy W. Caplice et al. (+3 more)

This work introduces a frequency synchronization circuit model for analog vector-matrix multiplication in the frequency domain. The frequency synchronization is implemented by coupling oscillators through all-to-all connections. Each oscillator is implemented using complementary cross-coupled transconductance pairs and RC high-pass filters. In this work, the frequency synchronization is achieved not only using oscillators alone but also through a configuration in which oscillators and resonator models (i.e., MEMS/NEMS resonators) are combined. While addressing the frequency synchronization of all the coupled oscillators, a partial synchronization is also discussed by controlling the coupling strength of a selected subset of oscillators. This frequency synchronization analysis focuses on the small-signal analysis using analog circuit and resonator models, thereby enabling an understanding of the synchronized frequency defined by the parameters of the analog circuit and resonator models.
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All authors Taeju Lee, Scott T. Habermehl, Timothy W. Caplice, Michael L. Roukes, Philip X.-L. Feng, Kenneth L. Shepard

Biological Physics

Noise-robust navigation from an adaptive run-and-tumble policy

Aniruddha Datta and Shiladitya Banerjee

How do organisms navigate when the signals guiding them are noisy? Variance adaptation, the rescaling of sensitivity to noise, is common in sensory systems, but its role in navigation is unexplored. We introduce a minimal active Brownian particle whose run-and-tumble policy follows from an optimality principle. Variance adaptation emerges as part of this policy. Adaptation keeps chemotactic drift finite as noise grows, while a non-adaptive particle's collapses exponentially. Adaptation also carries a cost, degrading performance in quiet environments and requiring a tuned adaptation sensitivity.
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Physics and Society

Don't look now: paying for documented need punishes discovery in US lead-pipe funding

Gustavo Pedro Ricou and Kristin C. Epstein

The United States allots USD 15 billion for lead service line replacement in proportion to documented lead, the largest of a growing class of environmental-indicator transfers. Reconstructed exactly, the rule prices looking below zero. Resolving an unknown pipe lowers a state's expected allotment in three of the eight jurisdictions we can measure above the statutory floor, and raises it in none. Below it the allotment cannot move. Systems filing nothing are scored lead-free. We prove no fixed formula on self-reported inventories can pay for need without punishing its measurement, so we made an audited one. The unique additive repair credits unknowns at a rate no filing can move, and is strategy-proof. Discovery is repriced from a median loss of USD 48.63 per line per year to zero. Allocation swings fall from 16.5% of the pool to 0.8%, for an audit costing 1.23% of annual funds. The formula's tilt toward vulnerable systems survives.
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2608.27736 · 27 Aug · 23 pages, 5 figures, 1 table. Supplementary information (34 pages). v2 corrects two v1 errors: the abstract gave the audit cost as 1.36% where the body gave 1.23% (the body is right), and the supplement's allocator equation summed allotments to a price per line, not to the pool. Audit design also revised; point estimates unchanged. Data/code: doi:10.5281/zenodo.22552146

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Optics

Deterministic control over launching efficiency of higher-order hyperbolic phonon polaritons

Thiago S. Arnaud, John E. Buchner, Ryan W. Spangler et al. (+3 more)

Hyperbolic materials, which exhibit an extreme form of birefringence enabling the volume confinement and frequency-dependent propagation of deeply sub-diffractional optical modes, offer the opportunity for extreme confinement via the stimulation polaritonic modes, with substantially higher confinement obtained through the efficient excitation of of the higher-order (shorter wavelength) hyperbolic polaritonic modes, which they can support. However, while these higher-order hyperbolic polaritons (HO-HPhPs) form high-momentum ray-like propagation within the bulk, efficient excitation of these modes, especially in contrast to the long-wavelength lower-momentum surface polariton propagating modes, has remained a challenge. Critically, the large momentum mismatch between these modes and free-space light, alongside the spatial mismatch between the sub-diffractional scatterer and the distinct modal distribution of HO-HPhPs, lead to a suppressed launching efficiency of these higher-order modes, limiting their use in nanophotonic applications. Here, we report the experimental observation of a 10-fold enhancement in the excitation efficiency of HO-HPhPs through the use of subsurface scatterers over traditional surface scattering (e.g. a flake edge or gold launcher) within single-crystalline {\alpha}-MoO3 slabs. We employ full-wave numerical simulations to investigate the role of the spatial overlap between HO-HPhP modal distributions and the scatterer placement upon excitation efficiency. Furthermore, we develop a generalized process using transfer matrix method to selectively design modal HO-HPhP excitation, which advances the capabilities of HPhP multiplexing for on-chip applications.
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All authors Thiago S. Arnaud, John E. Buchner, Ryan W. Spangler, Maximilian Obst, Jon-Paul Maria, Joshua D. Caldwell

Optics

Extending Silicon Avalanche Photodetection Beyond $2~\mu$m by Direct GeSn Integration

M. R. M. Atalla, J. Bélec, E. Rahier et al. (+5 more)

Silicon avalanche photodiodes provide a technologically mature platform for sensitive photodetection, but their spectral response is intrinsically limited by the silicon bandgap. Extending their operation into the infrared requires the integration of narrow-bandgap absorbers while preserving efficient avalanche multiplication and compatibility with silicon processing. Here, we propose and demonstrate a monolithic approach that combines direct, buffer-free growth of GeSn on silicon with a lateral thin-junction separate-absorption-multiplication architecture. The GeSn layer, with a Sn composition reaching 6 at.%, extends optical absorption to a wavelength of $2.6~\mu$m, while avalanche multiplication is spatially confined to an ion-implanted silicon lateral junction. This separation enables independent control of infrared absorption and carrier multiplication without the thick Ge virtual substrates conventionally used for GeSn epitaxy. GeSn-on-Si avalanche photodiodes exhibit low pre-breakdown dark current, stable breakdown at 72 V independent of device diameter, and clear infrared photoresponse extending beyond $2~\mu$m. At 78 K, the devices exhibit external quantum efficiency exceeding 100%, reaching 163% at $1.55~\mu$m, providing direct evidence of avalanche multiplication. These results establish direct integration of narrow-bandgap group-IV absorbers with silicon multiplication regions as a scalable strategy for extending the spectral reach of silicon avalanche photodetection, opening a route toward monolithic infrared detectors for sensing, imaging, communications, LiDAR, and quantum photonics
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All authors M. R. M. Atalla, J. Bélec, E. Rahier, S. Koelling, K. Omambac, P. Daoust, S. Assali, O. Moutanabbir

Atomic Physics

Quantified absorption of laser light by silver atoms in a hollow-cathode lamp

Matthew P. Wilde, Richard G. Wolfendale, Mark Bengyel et al. (+2 more)

We present a quantitative study of laser absorption on the $5{^{2}}\mathrm{S}_{1/2} \rightarrow 5{^{2}}\mathrm{P}_{3/2}$ transition of silver in a hollow-cathode lamp. Spectra obtained using a weak probe are measured and compared to a simple theoretical model. We fit our results to extract an effective temperature and number density associated with the silver in the lamp and confirm that the spectra are dominated by Doppler broadening. We consider the broadening effect of collisions between silver and the neon buffer gas in the lamp, and establish that these effects are small but modify the optimum effective parameters for the model. Our work results in a simple, quantitative, and predictive model for laser absorption in the lamp.
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All authors Matthew P. Wilde, Richard G. Wolfendale, Mark Bengyel, Ifan G. Hughes, Philip D. Gregory

Space Physics · Cross-listed from astro-ph.HE

Magnetospheric birefringence breaks the rotating-vector model and depolarises X-ray pulsars

Alexander A. Mushtukov, Sergey S. Tsygankov, Silvia Zane et al. (+4 more)

Accreting X-ray pulsars have long been expected to show large linear polarisation below the cyclotron resonance. In the standard picture, this follows from two facts: radiative opacities in the strongly magnetised neutron star environment depend strongly on polarisation mode, and the emission comes from compact polar regions. The emerging radiation should therefore be locally polarised and add almost coherently, with a polarisation angle tracing the projected magnetic field as in the rotating-vector model. Recent X-ray polarimetric observations, instead, show modest polarisation fractions and position angle swings that often depart from this simple picture. Here we show that propagation through the magnetosphere of an accreting neutron star can naturally produce both effects. Using general-relativistic ray tracing and Stokes-parameter transport, we find that photons emitted from compact polar regions acquire ray-dependent polarisation angle offsets in two ways. First, nearly field-aligned trajectories can cross local non-adiabatic pockets inside the QED birefringent region. Second, photons that intersect the plasma-loaded accretion flow accumulate additional phase shifts between plasma normal modes. Both effects broaden the distribution of polarisation angles across the ray bundle and reduce the hotspot-integrated linear polarisation, while also producing systematic deviations from rotating-vector-model expectations. Magnetospheric propagation should therefore be treated as part of the polarimetric transfer problem in accreting X-ray pulsars, and may help explain the observed low polarisation fractions and anomalous angle swings.
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All authors Alexander A. Mushtukov, Sergey S. Tsygankov, Silvia Zane, Nabil Brice, Ruth M. E. Kelly, Roberto Taverna, Roberto Turolla