Atmospheric and Oceanic Physics
Hard conservation correctors can hide a degrading model when training autoregressive emulators
William E. Chapman, John Schreck and Yingkai Sha
AI weather and
climate emulators increasingly incorporate physical principles into their formulation. One approach is to apply hard correctors that modify network outputs so that global mass, water, or energy budgets close. Prior work introduced such training-time correctors in the CREDIT framework and reported reduced precipitation bias and improved stability. Motivated by those results, we fine-tuned a global atmosphere emulator with a water-budget corrector, using the corrected prediction in the supervised loss and evaluating through post-correction budget closure. By that measure, training appeared successful. Every delivered field closed the moisture budget to machine precision. However, raw precipitation developed a growing global low bias over 18 training epochs, while the required correction increased from about 2% to roughly 24%. The cause is a scale degeneracy. A uniform change in raw precipitation amplitude is offset by a compensating change in the correction factor, leaving the corrected field, and therefore the supervised loss, unchanged. This invariance removes the restoring force on raw precipitation amplitude, allowing other training pressures to drive drift. Two changes recovered stable behavior. We supervised the pre-correction prediction and penalized its raw budget imbalance, while the hard correction remained in place for the delivered field. The required correction returned to less than 1% within the next epoch. A controlled 2x2 ablation showed that the runaway occurred only when corrected-output supervision was combined with no imbalance penalty. Exact post-correction closure therefore says little about whether the raw model has learned the budget. When a corrector removes information from the loss, the raw fields and the applied correction need to be tracked.
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Atomic Physics · Cross-listed from quant-ph
Monolithic printed-circuit board RF-trap for electrons
Zijue Luo, Jae Eu, Tianyi Wang et al. (+1 more)
Qubits encoded in the
spin of trapped electrons have been proposed as a promising novel platform for
quantum information processing. While trapping of electrons has been largely carried out in Penning traps for precision measurement purposes, it is desirable to use linear Paul traps instead, leaning on the successes of trapped ion
quantum processors. Here we present a Paul trap for electrons made of a single printed
circuit board. Our approach requires no assembly and the rigid design minimizes manufacturing intolerances. We characterize the trap performance and observe trapped electron lifetimes of 2.13 ms and secular frequencies of up to 90 MHz.
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All authors Zijue Luo, Jae Eu, Tianyi Wang, Boerge Hemmerling
Instrumentation and Detectors · Cross-listed from astro-ph.CO
GUEST: Gravitational Universe Exploration with Satellite Tracking. A passive satellite laser-ranging mission for the dark gravitational Universe
Diego Blas, Aurélien Hees, F. Javier Atapuerca et al. (+78 more)
GUEST is a space mission concept whose central objective is the detection of gravitational waves (GWs) in the microhertz band – a physics-rich frequency window that no other present or planned detector can reach at a significant level. The concept is simple: two dense, passive spheres, covered with cube-corner retroreflectors, deployed in {highly eccentric} Earth orbits ($e \gtrsim 0.7$, period $P \gtrsim 33$ h), tracked continuously by the global network of satellite
laser-ranging stations over a minimum observation time of 10 years, with an expected total duration of 30 years. The orbits themselves act as resonant detectors of the oscillating gravitational perturbations, with the microhertz sensitivity emerging from the selected orbital parameters. From the same data stream, GUEST delivers a programme of fundamental and applied science that cuts across particle physics, gravitational-wave astronomy, cosmology, astrophysics, and geodesy: the first coherent search for GWs from supermassive black-hole binaries in the $\mu$Hz band, the exploration of
primordial GW backgrounds in the unexplored energy-scale gap between
pulsar-timing arrays and LISA, a dedicated probe of ultra-light dark matter in a parameter region untouched by any other experiment, a new way to search for ultra-light
bosons, order-of-magnitude-improved tests of new gravitational interactions at astronomical ranges, and a step change in the absolute determination of $GM_\oplus$ that underpins the Global Geodetic Observing System and future
navigation and Earth-observation missions. This white paper presents the motivation, scientific reach, and mission concept of GUEST.
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All authors Diego Blas, Aurélien Hees, F. Javier Atapuerca, Giada Bargiacchi, Massimo Bassan, Joshua N. Benabou, Bruno Bertrand, Adrien Bourgoin, Clare Burrage, Nicolò Burzillà, Alfonso Caldiero, Roberto Campagnola, Andrea Caputo, Ana Caramete, Laurentiu Caramete, Joan Manel Casalta Escuer, Julien Chabé, Gabriel Chiritoi, Marco Cinelli, Florin-Ioan Constantin, Neil J. Cornish, Clément Courde, Simone Dell'Agnello, Alessandro Di Marco, Sebastian Ellis, Malcolm Fairbairn, Ariadna Farrés, Joshua W. Foster, Silvia Gasparotto, Marta Goli, Yann Gouttenoire, Michael Häfner, Antonio J. Iovino, Maria-Catalina Isfan, Justin Janquart, Alexander C. Jenkins, Jean-Paul Kneib, Sébastien Le Maistre, David Lucchesi, Marco Lucente, Angus Macdonald, Jorge Martín Camalich, Rosa Martínez Rubiella, Josep J. Masdemont, Ilia Musco, Toshimichi Otsubo, Cristóbal Padilla, Fco. Rogelio Palomo Pinto, Alice Paun, Alice Perego, Roberto Peron, Florentina-Crenguta Pislan, Florin Adrian Popescu, Luca Porcelli, Nanda Rea, Rafael Rebolo, Marco Reyes, Ignasi Ribas, José C. Rodríguez, Pascal Rosenblatt, Albert Roura, Soumen Roy, Mariano Sánchez Nogales, Francesco Santoli, Feliciana Sapio, Anja Schlicht, Ulrich Schreiber, Angela Serrano, Daniel Serrano Lombillo, Alberto Sesana, Carlos F. Sopuerta, Krzysztof Sośnica, Nicola Tamanini, Elisa Todarello, Sokratis Trifinopoulos, Miguel Vanvlasselaer, Dario Vetrano, Massimo Visco, Hanxi Wang, Xiao Xue, Miguel Zumalacárregui
Atomic Physics · Cross-listed from quant-ph
Remote entanglement need not be the bottleneck for modular trapped-ion quantum computing
Felix W. Knollmann, David P. Nadlinger, John Blue et al. (+7 more)
Modularity underpins classical computing; as
quantum processors encounter limits on fabrication yield, reliability, and size, they will also need it acutely. The bottleneck to linking modules is producing shared
entanglement at sufficient rate, density, and fidelity. Trapped ions hold the best demonstrated photonic links, yet they rely on bulky collection optics that cap how densely links can be packed, and remote
entanglement operations trail local gates by two orders of magnitude in rate and fidelity. We synthesize several enabling results $\unicode{x2014}$ single-
photon heralding, coherent
recoil correction, projective
distillation, and trap-integrated photonics $\unicode{x2014}$ into one comprehensive architecture that substantially narrows this gap. Single-
photon heralding leads to linear scaling of success probability with detection efficiency, allowing compact integrated photonics to saturate the
entanglement rate at a local-operation limit in dense, easy-to-parallelize channels. Addressing its inherent error mechanisms at their source, we project a Bell-pair fidelity of 99.9% at rates and densities compatible with fault-tolerant operations. Remote
entanglement then need not remain the bottleneck for modular trapped-ion computing; the limit shifts to the local operations that must improve regardless.
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All authors Felix W. Knollmann, David P. Nadlinger, John Blue, Sabrina M. Corsetti, Sam J. Bishop, Adam R. Martinez, Jelena Notaros, Colin D. Bruzewicz, Robert McConnell, Isaac L. Chuang
History and Philosophy of Physics · Cross-listed from quant-ph
Adlam's Frame: comment on "Wigner's Frame"
Andrea Di Biagio and Anne-Catherine de la Hamette
Recent no-go
theorems based on extended Wigner's Friend scenarios (EWFS) reveal a deep tension between the universal validity of
quantum theory and local friendliness (LF), the conjunction of three natural assumptions: the absoluteness of observed events, locality, and no-superdeterminism. In a recent work, Adlam argues that this tension can be dissolved by appealing to
quantum reference frames (QRFs). We present and critically assess her proposal. We show that her proposed resolution does not arise from QRFs, but instead relies on three independent modifications: certain degrees of freedom are always definite, observers can flip upon measuring
spins, and the outcomes the superobservers record and use to test the inequalities are not their friends' observed results. The proposal and the arguments for the plausibility of these modifications rest on several misconceptions about QRFs and EWFS, which we rectify. We conclude that, within standard
quantum theory,
quantum reference frames do not evade the EWFS no-go
theorems.
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Instrumentation and Detectors · Cross-listed from astro-ph.CO
Probing large mass-splitting inelastic Dark Matter with RES-NOVA
D. Alloni, G. Benato, P. Carniti et al. (+46 more)
Probing inelastic dark matter at large mass splittings requires heavy target
nuclei, an extended
recoil-energy range, and the high-velocity tail of the dark-matter distribution. We exploit these features with the RES-NOVA prototype detector, featuring a PbWO4 cryogenic calorimeter, produced from archaeological Pb and operated at the deep-underground laboratory of Gran Sasso of INFN (Italy), analyzing a 32.4 g day exposure over 2.5 keV - 1 MeV under both the Standard
Halo Model (SHM) and a Large Magellanic Cloud (LMC)-motivated velocity distribution. We extend direct-detection constraints beyond the 330 keV reach of established technologies (e.g. Xe-based TPCs), probing splittings up to 510 (780) keV in the SHM (LMC)
benchmark, while future exposures will probe new regions of the parameter space.
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All authors D. Alloni, G. Benato, P. Carniti, M. Cataldo, L. Chen, M. Clemenza, M. Consonni, G. Croci, I. Dafinei, F.A. Danevich, C. de Vecchi, D. Di Martino, R. Elleboro, N. Ferreiro Iachellini, F. Ferroni, F. Filippini, S. Ghislandi, A. Giachero, L. Gironi, P. Gorla, C. Gotti, D.L. Helis, D.V. Kasperovych, V.V. Kobychev, G. Marcucci, A. Melchiorre, A. Menegolli, S. Nisi, M. Musa, L. Pagnanini, L. Pattavina, G. Pessina, S. Pirro, S. Pozzi, M.C. Prata, A. Puiu, S. Quitadamo, M.P. Riccardi, M. Rossella, R. Rossini, E. Sala, F. Saliu, A. Salvini, V.I. Tretyak, L. Trombetta, D. Trotta, H. Yuan, J. Luengas, H. Ramani
Physics and Society
Citation Pathways in the AI Era: Interpretive Knowledge Nodes, Citation Compression Layers, and the Measurement Boundary of Scholarly Impact
Li Li and Yu Cao
This article identifies "citation pathway" as a long-neglected analytical dimension in scientometrics. Traditional evaluation metrics focus on measuring citation counts while paying insufficient
attention to the intermediate nodes through which knowledge flows from its original source to the citing author. Building on an analysis of the normative structure of current reference systems, this article introduces two new concepts: Interpretive Knowledge Nodes (IKN) - academic papers that provide structured reorganizations of classic works - and Citation Compression Layers (CCL) - the intermediate layers that emerge when such knowledge products acquire stable publication identities and enter formal citation networks at scale. The central proposition is that AI has not changed citation rules themselves but has transformed the cost structure of producing citable knowledge intermediaries. Under conditions of full compliance, the network position effects of citation pathways may become a salient variable affecting the validity of impact measurement. Through a thought experiment involving a hypothetical journal R and a parsimonious "Citation
Gravity conceptual model," this article substantiates this proposition and discusses the measurement boundaries of scholarly impact indicators, as well as the institutional risk of incentive misalignment under extreme scenarios.
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Atomic Physics · Cross-listed from hep-ph
Correlated comagnetometry for precision measurements
Yossi Rosenzweig, Yevgeny Kats, Eli Sarid et al. (+3 more)
Magnetometers are among the most widely used probes in science and technology. Comagnetometers increase sensitivity by self-cancellation of
magnetic noise, but only at low frequencies. We suggest a correlated measurement of two alkali species in one
cell to cancel the
magnetic background also at high frequencies. The inter-species phase difference of the light-matter interaction response function is found to be calibration free and insensitive to common-mode intensity noise. Utilizing a dark-matter signal as a testcase, the method achieves a thirtyfold background suppression, raising the signal-to-noise ratio by an order of magnitude or more, depending on the coupling to the different subatomic particles. We show that the method also provides model differentiation. The higher sensitivity and model differentiation open a path to novel probes for precision measurements in general and exotic fields in particular.
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All authors Yossi Rosenzweig, Yevgeny Kats, Eli Sarid, Menachem Givon, Yonathan Japha, Ron Folman
Classical Physics · Cross-listed from cond-mat.mes-hall
Non-Abelian Gauge Field Mechanics
Ivan Velkovsky, Carlos Camacho, Tomoki Ozawa et al. (+2 more)
Non-Abelian gauge fields play a key role in describing the behavior of particles whose motion is coupled to internal degrees of freedom, such as their
spin. Here, we experimentally realize a tuneable non-Abelian gauge field in an active mechanical
lattice by using pairs of oscillators to encode a local pseudo-
spin for each site, with inter-site
spin-dependent couplings engineered via real-time measurement and feedback. We experimentally extract Wilson-loop observables in our set-up and hence demonstrate that we can create a genuinely non-Abelian gauge field. We then exploit the controllability of our mechanical
lattice to engineer non-reciprocal hoppings to explore non-Hermitian non-Abelian gauge potentials. For a two-dimensional (2D)
lattice, we demonstrate that the non-Hermiticity can manifest in direction-dependent Wilson loops for a single plaquette, while for a one-dimensional (1D) system, we show that a non-Abelian gauge potential can switch the localization of non-Hermitian skin modes between opposite ends of a chain. Our work establishes active mechanical
lattices as a flexible and programmable platform for probing non-Abelian gauge fields and exploring their interplay with non-Hermitian dynamics.
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All authors Ivan Velkovsky, Carlos Camacho, Tomoki Ozawa, Hannah Price, Bryce Gadway
Plasma Physics
Equilibrium of a Rapidly Rotating Axisymmetric Magnetic Mirror Machine
Richard Fitzpatrick
A recent paper [Hazeltine, et al., Phys.
Plasmas 33, 072501 (2026)] has questioned whether the standard result, (ultimately) due to Ferraro, that the
plasma angular velocity is approximately constant along individual
equilibrium magnetic field-lines in a rotating axisymmetric
magnetic mirror machine, continues to hold when the rotation becomes sonic or supersonic. In order to resolve this issue, the
equilibrium of a rapidly rotating mirror is investigated, starting from first principles, using an ideal two-fluid model with anisotropic pressure. It is found that, as long as the ion gyro-radius is much less than the machine size, and the angular velocity of the
plasma is much less than the ion gyro-frequency, the Ferraro result holds good.
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Computational Physics
anyakrakusuma: A Python Library for Entropic Schrödinger Bridges on Idealized Geometries
Dasapta Erwin Irawan, Sandy Hardian Susanto Herho, Agus Wahyu Jatmiko et al. (+7 more)
We present anyakrakusuma, an open-source Python library that solves the discrete static Schrödinger bridge problem, the entropically regularized counterpart of optimal transport, through a log-domain Sinkhorn–Knopp iteration and reconstructs the entropic interpolation between two empirical point clouds. The solver is paired with a diagnostic pipeline that characterizes the optimal coupling and the intermediate distributions through information-theoretic and
geometric measures. We exercise the library on four idealized planar cases spanning a circle-to-circle dilation, a spiral-to-mixture fragmentation, a rigid reorientation of two moons, and a Lissajous-to-trefoil deformation. The log-domain formulation is necessary rather than merely convenient at the parameters studied, where the cost-to-regularization ratio reaches four hundred and the Gibbs kernel underflows double precision across most of its range; the iteration nonetheless attains a marginal residual of $10^{-9}$ and unit marginal fidelity in every case. Residual histories decay geometrically over approximately eight decades at per-iteration contraction factors between $0.966$ and $0.976$, which are local rates near the fixed point that lie many orders of magnitude below the worst-case
Hilbert-metric bound. The covariance analysis recovers an imposed ninety-degree reorientation to within $0.07^\circ$, roughly forty times smaller than its uncertainty, across a masked interval of near-isotropy on which the principal axis is unobservable. The diagnostics are reported with explicit
attention to the regimes in which each is well defined, including the differential
entropy, which is meaningful only on the open interpolation interval. The presented cases are constructed rather than measured; quantitative application to empirical point clouds requires further study.
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All authors Dasapta Erwin Irawan, Sandy Hardian Susanto Herho, Agus Wahyu Jatmiko, Sito Fossy Biosa, Candrasa Surya Dharma, Edi Riawan, Astyka Pamumpuni, Rendy Dwi Kartiko, Rusmawan Suwarman, Deny Juanda Puradimaja
Chemical Physics
BCover: An Electronic Structure-Based Scoring Suite for Reaction-Aware Covalent Docking
Emil Zak and Michał Szczepanik
Covalent virtual screening requires ranking compounds according to both noncovalent recognition and their ability to adopt a reaction-competent geometry with an appropriately reactive warhead. Here, we introduce BCover, a reaction-aware scoring suite that combines pre-reactive docking with
quantum-chemistry-derived ligand reactivity descriptors, the electrostatic properties of the
protein pocket.
Quantum-chemical descriptors are aggregated using a nonlinear tree-based scoring model. BCover was evaluated retrospectively on the COValid
benchmark, comprising nine targets and ten reactive sites, and compared with AutoDock, DOCK6, DOCKovalent, AlphaFold3 with Rosetta rescoring, and AlphaFold3 confidence-based ranking. BCover achieved an average adjusted LogAUC of 31% (57% max), an average ROC-AUC of 0.88 (0.96 max), an average EF1 of 18 (33 max). Its average LogAUC exceeded those of the classical docking methods and AlphaFold3-Rosetta, although AlphaFold3-mPAE provided the strongest overall enrichment. At an average runtime of about 10~s per ligand, BCover was approximately 25-fold faster than the evaluated AlphaFold3 workflows and achieved the highest average time-adjusted virtual-screening productivity index. Redocking experiments further showed that the method recovered near-native ligand conformations. These results demonstrate that combining docking-derived geometry with ligand local electronic reactivity and pocket electrostatics provides an efficient and interpretable strategy for covalent ligand prioritization. BCover is intended as a high-throughput screening method that complements more computationally demanding QM/MM and free-energy calculations during subsequent lead optimization.
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Fluid Dynamics · Cross-listed from astro-ph.IM
Per Astronomix ad Astra: High-Order Differentiable (Magneto)hydrodynamics with Energy-Conserving Self-Gravity
Leonard Storcks, Nils Thuerey and Tobias Buck
We present astronomix, a performant differentiable (magneto)hydrodynamics simulator written in Python/JAX. We demonstrate how automatic differentiation, validated against hand-derived analytical functional derivatives and finite differences, enables inverse modeling over millions of parameters and allows for sensitivity and stability analysis as well as correct eigenmode initialization. The differentiability of astronomix furthermore enables training machine-learning models inside the simulator. On a single GPU at a given resolution, astronomix has runtimes of the same order of magnitude as the GPU-optimized code AthenaPK but reaches far lower errors on smooth problems due to its higher order. astronomix scales to multiple GPUs ($\sim 6.5$ strong scaling speedup on $8$ GPUs) and multiple nodes ($\sim 76\%$ weak scaling efficiency on $16$ GPUs over $4$ nodes). We also present a novel fourth-order self-
gravity scheme which complements the fifth-order finite difference constrained transport magnetohydrodynamics scheme implemented in astronomix. To maximize performance, we created an agentic skill that generates and validates custom Pallas GPU kernels from our JAX reference code and test suite. The simulator is available at https://github.com/leo1200/astronomix.
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Popular Physics
The Physics Behind Ham Production
Sergey Parnovsky and Andrey Varlamov
We analyze the physical mechanisms underlying the production of dry-cured hams, including prosciutto and jamón. Key processes such as osmosis and
diffusion govern water removal and salt penetration, while enzymatic activity during long-term air curing develops
flavor and texture without heat. The study quantifies
diffusion depths, evaporation rates, and the effects of airflow and humidity on preventing defects like case hardening. By highlighting the physics behind salting and curing, the work provides a deeper understanding of how traditional techniques achieve safe, tender, and flavorful hams.
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General Physics
Non-injective field redefinitions and quantum inequivalence in scalar theories
Bin Zhu
We study scalar theories obtained by pulling a free massive multiplet back through a
polynomial field redefinition with constant unit Jacobian. Our main example uses the three-variable noninjective map recently announced by Alpöge. After a linear normalization, it defines a three-scalar sigma model with a flat, unit-volume field-space metric and three isolated
vacua. Each
vacuum is locally described by three free modes of mass m, and the exact equations of motion reduce locally on each sheet to free Klein–Gordon equations. The global theory is nevertheless not a single free theory: the field-space metric is incomplete, the number of real preimages changes across target space, and the commuting position operators have nonconstant joint spectral multiplicity. This rules out a global
unitary implementation of the field redefinition and a regular Weyl exponentiation of the formal canonical momenta. We then analyze a four-scalar map with a generic quintic fiber. It exhibits the same mechanism with an additional field that controls the fiber
polynomial. The two examples separate perturbative equivalence on a chosen local sheet from global
quantum equivalence of the full field space.
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Fluid Dynamics
A Low-Storage Implicit Dual-Time Finite-Volume Framework for Radio-Frequency Capacitively Coupled Plasma Fluid Simulations
Yuze Zhu, Hangkong Wu, Junzhe Cao et al. (+2 more)
Radio-frequency (RF) capacitively coupled
plasmas (CCPs) are widely utilized in
semiconductor manufacturing. Efficiently and accurately solving the underlying fluid governing equations to resolve the complex multi-physics fields is crucial for optimizing
plasma reactor designs and process control. To overcome the severe numerical stiffness and prohibitive time-step constraints inherent in low-temperature
plasma modeling, we present a robust, low-storage implicit dual-time finite-volume framework for RF CCP simulations, establishing a highly efficient and
memory-friendly pathway for the predictive modeling of multi-dimensional low-temperature
plasmas. In this approach, the physical time advancement is strictly decoupled from explicit stability limits through a backward-difference formula (BDF), while the resulting nonlinear system is efficiently solved using pseudo-time iterations. A localized block-implicit relaxation method is employed to handle the stiff transport and chemical source terms at the
cell level, effectively circumventing the massive
memory overhead typical of conventional fully implicit solvers. Concurrently, a semi-implicit treatment of Poisson's equation is integrated to accelerate the electrostatic coupling. The framework is first verified against a standard one-dimensional argon discharge
benchmark, demonstrating that a highly accurate periodic state can be achieved with satisfactory computational efficiency through the optimal selection of the physical time step, pseudo-CFL number, and inner iteration step. To further demonstrate the multidimensional applicability of the proposed method, the solver is extended to genuine two-dimensional configurations. The numerical results show the multi-dimensional distortion of the electrostatic potential and localized electron heating zones induced by the transverse boundaries.
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All authors Yuze Zhu, Hangkong Wu, Junzhe Cao, Yufeng Wei, Kun Xu
Atomic Physics
Orbit-resolved spin holography: role of Coulomb focusing in target-dependent polarization
Tao Chen, Yang Li, Fang Liu et al. (+3 more)
Strong-field photoelectron holography encodes ultrafast electron dynamics through momentum-space interference. However, the orbit-resolved origin of spider-like
spin fringes and the mechanism underlying their target dependence remain unclear. Here, we resolve both issues by analyzing photoelectron
spin textures generated during tunneling ionization. We use the Coulomb
quantum-orbit strong-field approximation, benchmarked against time-dependent Schrödinger equation simulations for $\mathrm{He^+}$ and Xe, to separate orbital-channel and
quantum-orbit contributions. Spider-like fringes arise from interference between $p$-orbital ionization channels with different
magnetic quantum numbers within an individual orbit class and therefore do not require interorbit interference. The observable polarization along these fringes, however, depends on the balance among orbit-class contributions. The decomposition associates the opposite first-leg polarizations of $\mathrm{He^+}$ and Xe with different relative weights of
laser-deflected and forward-scattered trajectories, consistent with target-dependent Coulomb focusing. Photoelectron
spin textures thus complement momentum distributions as probes of Coulomb-driven strong-field dynamics.
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All authors Tao Chen, Yang Li, Fang Liu, Pei-Lun He, Carla Figueira de Morisson Faria, Feng He
Plasma Physics
An Implicit Time-Domain Harmonic Balance Method for Radio-Frequency Capacitively Coupled Plasma Simulations
Yuze Zhu, Yufeng Wei, Yue Zhang et al. (+1 more)
Fast and accurate fluid simulation of
radio-frequency capacitively coupled
plasmas (RF CCPs) is of great importance for the iterative design and parameter optimization of modern
plasma reactors. This study presents the first successful extension of the time-domain harmonic balance (HB) method to a fully coupled drift-
diffusion-Poisson system with complete electron-energy transport for RF
plasma simulations. To resolve the severe numerical stiffness arising from highly nonlinear energy-dependent kinetics and dense phase-coupling, a highly efficient spatiotemporal operator-splitting strategy is employed. By sequentially executing a spatial implicit relaxation and a
cell-local temporal inversion, this strategy entirely avoids the
memory-intensive assembly of global Jacobians while preserving robust numerical stability. The proposed method is rigorously validated against a standard parallel-plate argon CCP
benchmark. Evaluated across all discrete temporal collocation points, the HB solution demonstrates that retaining eight harmonics perfectly resolves both the quasi-steady bulk
plasma and the highly nonlinear transient sheath dynamics, yielding macroscopic relative errors strictly below 0.3% compared to conventional dual-time stepping (DTS) solutions. Beyond its high physical fidelity, the time-domain HB method completely bypasses the prohibitive physical transients required by conventional time-marching methods. Evaluated on a purely sequential single-core execution, the HB method delivers a greater than 10-fold speedup over fully converged DTS baselines and remains over 5 times faster than the coarsest time-marching configurations. These results establish the time-domain HB framework as a physically rigorous,
memory-efficient, and highly accelerated paradigm for practical RF
plasma simulations.
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All authors Yuze Zhu, Yufeng Wei, Yue Zhang, Kun Xu
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
DFT+U+V is equivalent to DFT+U with density-dependent hybridized projectors
Edward Linscott, Alberto Carta and Nicola Marzari
Hubbard-corrected density-functional theory (DFT+$U$) is a popular tool for first-principles modeling of materials with localized $d$ or $f$ electrons, but its on-site corrections tend to over-localize charge and break covalent bonds. Inter-site $+V$ corrections were introduced to counter this and are now widely used, but a formal justification has been lacking. Here we show that – to first order in $V/U$ – inter-site corrections are exactly equivalent to on-site DFT+$U$ evaluated on a density-
matrix-dependent redefinition of the Hubbard projectors, hybridized with those of neighboring sites, providing insight into the explicit mechanism by which $V$ affects covalency. If the projectors are held frozen, as is common practice, the equivalence partially breaks down. Beyond reinterpreting the formalism, these results sharpen the questions of how $V$ should be computed and what the Hubbard subspaces fundamentally are.
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Optics
Programmable photonics enabled by ferroionic two-dimensional materials
Ghada Dushaq, Srinivasa R Tamalampudiand, Solomon Serunjogi et al. (+1 more)
Artificial intelligence (AI) models are scaling rapidly, exposing fundamental limitations in conventional computing architectures, where the physical separation of
memory and computation imposes substantial energy and latency overheads. Optical neural networks offer a viable solution by enabling high-throughput, low-latency computation through the intrinsic parallelism of light. However, the scalability of photonic computing is constrained by the lack of materials that can provide low-loss, energy-efficient, and nonvolatile control of optical phase. Here, we discuss the emerging role of ferroionic two-dimensional materials as a platform for programmable photonics. Unlike conventional ferroelectrics, where polarization arises from bounded
lattice distortions, ferroionic systems enable field-driven ionic redistribution, providing access to a continuum of stable and reconfigurable states. We outline how these material dynamics can be exploited to realize multi-level photonic states and nonvolatile phase control. Furthermore, we highlight a back-end integration strategy that introduces multifunctionality, including tunable optical nonlinearities into pre-fabricated photonic
circuits without compromising optical performance. By bridging material-level dynamics with device- and system-level functionality, ferroionic materials provide a pathway toward reconfigurable, low-loss, and energy-efficient photonic computing architectures, opening new opportunities for neuromorphic and adaptive photonic systems.
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All authors Ghada Dushaq, Srinivasa R Tamalampudiand, Solomon Serunjogi, Mahmoud Rasras
Instrumentation and Detectors · Cross-listed from cond-mat.mtrl-sci
Foundry CMOS platform for multimodal quantum materials characterization
Sharad Kumar Yadav, Luca Nessi, Ondrej Dyck et al. (+13 more)
Quantum materials experiments increasingly rely on microwave, electrical, thermal, optical, and structural probes, but these capabilities are typically assembled from custom hardware that limits reproducibility and scalability. Here we show that a commercial 65-nm CMOS process can be repurposed as a passive, foundry-manufacturable characterization platform by functionally partitioning its metal stack into microwave, thermal, and electrical subsystems within a 1 mm2 footprint. The integrated RF architecture enables cryogenic
magnetic susceptibility measurements of Fe3GeTe2
heterostructures at 1.75 K without sample-specific fabrication. We further demonstrate NV-center optically detected
magnetic resonance (ODMR) with >20% contrast at 4-9 dBm microwave power, reducing power requirements by 20-25 dB relative to conventional
antenna-based approaches while maintaining sensitivities of 2-3 uT/sqrt(Hz). We additionally confirm compatibility with in-situ electron-beam imaging, showing no measurable degradation in image quality upon device operation. These results establish a scalable, foundry-manufacturable platform for
multimodal quantum sensing and materials characterization.
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All authors Sharad Kumar Yadav, Luca Nessi, Ondrej Dyck, Jinchen Wang, Bogdan Dryzhakov, Alex Melendez, Huan Zhao, Qian Song, Doha Amer, Cole Brabec, Saleh Alqazlan, Ruonan Han, Riccardo Comin, Stephen Jesse, Dirk Englund, Jawaher Almutlaq
Fluid Dynamics
A machine-learned probability distribution in the phase space of turbulent channel flow for synthetic turbulence and flow reconstruction
Frederik Aerts, Dirk Nuyens and Johan Meyers
Although a complete characterisation of the probability distribution in the phase space of turbulent flows remains elusive, accurately sampling this distribution is essential for both synthetic
turbulence generation and turbulent flow reconstruction. Motivated by these applications, we examine to what extent a machine-learned distribution can approximate the physical invariant distribution of turbulent channel flow at $\mathrm{Re}_\tau=180$. We assess three important properties of the approximation: physical ensemble statistics, consistent conditional sampling, and dynamical invariance. To this end, a flow-based generative model is trained on a minimal conditional flow unit, which we define as the smallest domain outside which conditional fields, given a single observation at the domain centre, are indistinguishable from unconditional fields in terms of mean-square discrepancy to other conditional fields. We also introduce a consistent procedure for sampling from the conditional learned distribution. Comparisons with direct numerical simulation show that synthetic turbulent fields reproduce key statistical and dynamical features of
turbulence, including intermittency and nonlinear energy transfer. The consistency of conditional sampling is demonstrated in a flow reconstruction problem, and subsequently used to generate synthetic turbulent velocity fields on a large domain. When adopted as initial conditions in direct numerical simulations, these fields yield physical and statistically stationary ensemble statistics, indicating that the learned distribution provides a good approximation to the natural distribution of the turbulent dynamical system.
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Optics
Fiber-Optic Communication and Torsion Sensing via a BB84-Inspired Polarization Scheme
Vinícius Piaia, Rodrigo Cosme, Paulo Robalinho et al. (+3 more)
Polarization-encoded optical-fiber links provide a useful platform for investigating the coexistence of communication and sensing functions in a shared optical channel. In this work, a classical analog of the BB84 polarization-encoding scheme was implemented over a bend-insensitive fiber link to evaluate how temperature, axial strain, and torsion affect the transmitted state of polarization and the recovery of a binary key. Temperature variations from 24 {\deg}C to 35 {\deg}C and axial strain up to 2 m{\epsilon} produced only minor polarization-state variations and did not affect key recovery. In contrast, fiber torsion induced a pronounced retarder-like
evolution of the state of polarization, reducing the detector-intensity contrast used for bit discrimination and degrading key recovery. For intermediate torsion angles, the erasure rate reached 50%. The polarization state tended to recover for rotations close to {\Delta}{\theta} = 180{\deg}, consistent with the oscillatory response observed on the Poincaré sphere. These results identify torsion as the dominant impairment in the tested polarization-encoded fiber link and demonstrate its potential use as a sensing mechanism in integrated communication-and-sensing architectures.
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All authors Vinícius Piaia, Rodrigo Cosme, Paulo Robalinho, Susana Silva, Henrique M. Salgado, Orlando Frazão
Computational Physics
Modeling rare-earth and energy materials supply chains under theoretical China-outer-Mongolia political reunification scenarios
Xi Liu and Wenxi Fang
Critical rare earth elements, lithium, copper, and coal underpin global clean energy transitions and advanced manufacturing, yet China faces persistent supply
volatility and resource security risks amid fragmented cross-border mineral trade with Outer Mongolia. This paper constructs a dynamic partial
equilibrium Stackelberg supply chain model spanning ten years, integrating three geographic nodes: Outer Mongolia's mineral extraction sector, Baotou's rare earth processing hub in Inner Mongolia, and residual demand from the Rest of the World (RoW). The model endogenizes core mechanisms including mineral supply curves constrained by infrastructure stock, lagged capital accumulation, Leontief processing production functions, profit-driven investment, and optimal export tax policy maximizing China's discounted social welfare. Three comparative scenarios are calibrated and simulated: a baseline status-quo trade framework, deep Sino-Mongolian resource integration, and a delayed cross-border infrastructure counterfactual.
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Optics
Physics-Informed Neural Networks for Optimal Beam Shaping in Flat Optics
Rafael de la Fuente Herrezuelo
We introduce a physics-informed neural network (PINN) approach for designing phase profiles in flat optics that reshape an incident beam into a prescribed target intensity distribution. The method solves Monge–Ampère beam-shaping equations associated with energy-conserving ray mappings generated by a phase-only optical element. We treat both finite-distance and far-field targets using a generalized-Snell-law formulation. The learned phase profiles are validated by scalar diffraction simulations and compared with conventional phase-
retrieval methods such as Gerchberg–Saxton. To our knowledge, this is the first time a PINN has been used for beam shaping problems in flat optics.
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Physics and Society
A principled closure framework for higher-order SIS epidemic models on networks
Kevin Teo, Peter L Simon and István Zoltán Kiss
Susceptible-infected-susceptible (SIS) epidemic models on networks are governed by hierarchical moment equations where the dynamics of smaller subsystems depend on the state of larger ones. Moment closure approximations, which truncate this hierarchy by expressing higher-order state probabilities in terms of lower-order ones, are essential for obtaining tractable reduced systems. Higher-order networks, which extend the pairwise structure to include group interactions, introduce a combinatorial explosion of closure configurations, making systematic derivation harder. Consequently, existing higher-order SIS models are derived heuristically, where structural and dynamical assumptions underpinning their closures are not always apparent from the formulation alone. We develop a bottom-up derivation of higher-order SIS dynamics, building systematically from node-level equations to pairs, triplets, and three-body interactions. Central to our approach is a network-dependent closure operator that generates topologically appropriate approximations from local pairwise and triadic structure. Using this framework, we recover three existing higher-order SIS models–Burgio et al.'s maximal clique, Malizia et al.'s pair-based and inter-order models–as special cases, each arising under specific topological and dynamical assumptions. Our derivation reveals assumptions that are invisible from heuristic approaches: for instance, Malizia et al.'s inter-order overlap parameter is insufficient alone to express the model within our framework despite performing well against simulations, with the original derivation implicitly invoking additional structural assumptions. Our framework offers both a foundation for higher-order epidemic modeling and a constructive pathway for understanding the assumptions implicit in heuristically derived mean-field closures and provides a principled method of generating new models.
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Chemical Physics
RuNNer 2.0: A Software Suite for High-Dimensional Neural Network Potentials
Alexander L. M. Knoll, Moritz R. Schäfer, K. Nikolas Lausch et al. (+11 more)
We present RuNNer 2.0, the "Ruhr University Neural Network energy representation", a highly optimized software suite for training and evaluating high-dimensional neural network potentials (HDNNPs) of the second, third, and fourth generation. Long-range electrostatics and charge equilibration (QEq) for the description of non-local charge transfer in fourth-generation (4G) HDNNPs are accelerated by quasi-linear-scaling plane-wave methods, reducing QEq computational complexity from $\mathcal{O}(N^3)$ to $\mathcal{O}(N\log^2 N)$ such that linear or quasi-linear scaling is achieved across all HDNNP generations. An optimized
memory management strategy eliminates the training overhead traditionally associated with long-range interactions, allowing 4G-HDNNPs to be trained with the same efficiency as their local counterparts. Developed in modern Fortran (2003/2008 standards), combined with a hybrid MPI/OpenMP parallelization scheme, RuNNer 2.0 has been designed to run efficiently in any CPU environment, from cost-effective local workstations to massive HPC clusters. Its modular library architecture facilitates straightforward binding to external simulation software; native interfaces to LAMMPS and the Atomic Simulation Environment (ASE) provide full access to all its features, including built-in committee-based uncertainty quantification. The high efficiency and scalability of the RuNNer 2.0 ecosystem are demonstrated through detailed
benchmarks.
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All authors Alexander L. M. Knoll, Moritz R. Schäfer, K. Nikolas Lausch, Moritz Gubler, Henry Wang, Richard Springborn, Redouan El Haouari, Alea Miako Liebetrau, Jonas A. Finkler, Emir Kocer, Marco Eckhoff, Stefan Goedecker, Gunnar Schmitz, Jörg Behler
Medical Physics
Review of oxygen measurement and relevance to the mechanisms of FLASH radiotherapy
Brian W. Pogue, David I. Hunter, Corbin Narita et al. (+3 more)
FLASH radiotherapy (FLASH-RT) is the phenomenon of relative sparing of normal tissue when ultra-high dose rates (UHDR) are used compared with conventional dose rates (CDR) as clinically used. Despite extensive investigation, the underlying mechanisms remain unexplained. Among the proposed hypotheses, tissue oxygen has consistently been a central theme because oxygen is the most dominant factor known to modulate radiation-induced damage. The factors implicated in FLASH sparing include the baseline partial pressure of oxygen (pO2), transient radiolytic oxygen consumption (ROC), and oxygen-dependent changes in the chemistry of reactive oxygen species (ROS) that vary with dose rate. This review synthesizes current evidence on in vivo oxygen measurement techniques, highlighting their capabilities and limitations in capturing the spatial and temporal heterogeneity of tissue oxygenation. Key experimental studies in skin are summarized and interpreted by modulating oxygen levels via changes in inspired oxygen gas and vascular clamping interventions, demonstrating that the FLASH effect occurs only at intermediate baseline pO2 (normoxic or slightly hypoxic) values, but not at hypoxia or hyperoxia. Direct measurement of oxygen consumption during UHDR irradiation is possible, providing one of the first in situ measurements of radiation chemistry in patients. In parallel, recent advances in fast in vitro radiation chemistry assays indicate that UHDR irradiation alters radical yields, favoring increased production of solvated electrons and reduced hydroxyl radical mediated damage. Taken together, the available data suggest that the FLASH sparing effect arises from an interplay among the delivered dose and dose rate, local oxygen availability, and radiation chemistry, with tissue-specific variation in scavenging, leading to altered biological responses across the CDR-to-UHDR shift.
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All authors Brian W. Pogue, David I. Hunter, Corbin Narita, William S. Thomas, Xu Cao, Harold M. Swartz
Optics
Scanless quantum Fourier-transform mid-infrared spectroscopy for rapid high-sensitivity hyperspectral mapping
Paul Gattinger, Bettina Heise, Andreas W. Schell et al. (+3 more)
Fourier-transform infrared (FTIR) spectroscopy is a well-established technique for qualitative and quantitative chemical analysis. Classical FTIR systems rely, however, on direct mid-infrared (mid-IR) scan-based time-domain measurements of coherence functions; thus, the signal-to-noise ratio and measurement speed are constrained by design. In this paper, we demonstrate a scanless
quantum FTIR (sQFTIR) technique that exploits principles of metrology with entangled
photons to circumvent the limitations inherent to classical FTIR systems. The approach exploits the interferometric nature of the sensing paradigm and relies on frequency-domain measurements performed with a static, low-gain nonlinear interferometer. A robust reconstruction
algorithm is used to retrieve time-domain signals and reconstruct respective mid-infrared (mid-IR) spectra (3000$~$cm$^{-1}$ to 2380$~$cm$^{-1}$) from near-IR measurements (approx. 780$~$nm to 820$~$nm). The suggested sQFTIR protocol eliminates the need for optical delay scanning and leverages inherent mapping between the related domains. In the theoretical section, we evaluate the intrinsic signal-to-noise advantage of the proposed method over conventional scan-based time-domain measurements; a difference of 26.8 dB (factor of 21.8) is demonstrated. Building on the enhanced sensitivity of the scheme, we demonstrate rapid sQFTIR-based hyperspectral imaging with a spatial resolution of 12.3$~\mu$m and a spectral resolution down to 8$~$cm$^{-1}$. Hyperspectral mapping of human colon tissue, microplastics, and multilayer
polymer samples composed of polypropylene and ethylene vinyl alcohol yield high-quality single-pixel spectra with acquisition times down to 10$~$ms.
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All authors Paul Gattinger, Bettina Heise, Andreas W. Schell, Kristina Duswald, Markus Brandstetter, Ivan Zorin
Physics and Society
Where onshore wind meets forests: electricity system planning with ecologically graded forests
Muhammad Shahzad Javed, Marianne Zeyringer, Johannes Rahlf et al. (+1 more)
Onshore wind is expected to supply much of the growth in renewables, yet its expansion increasingly extends into forests, where wind generation and forest conservation act as competing
climate strategies for the same land. Net-zero system assessments typically treat forests homogeneously. Here, we grade forest exclusions by ecological value and couple them with a high-resolution net-zero electricity system model, representing onshore wind on forested and non-forested land as two distinct technologies. Applying a set of ecologically graded scenarios to Norway, we quantify how forest protection by its ecological value reshapes system design, the balance of onshore wind within and outside forests, and the robustness of these outcomes to complementary energy policy levers. At equal cost, the system treats forest as its preferred onshore resource, with forest wind comprising 60 to 90 percent of onshore capacity under permissive scenarios. Excluding forest raises system cost by up to 0.5 percent per GW of foregone forest wind, with diminishing returns as ecological criteria for forest exclusions tighten. Directing wind into forests does not compromise system efficiency, with onshore curtailment remaining largely unchanged at 3 to 8 percent. Land-use and technology decisions that appear independent may, in fact, interact, as
solar deployment reshapes the value of each wind resource and determines which is displaced from the generation mix. By quantifying the ecological value forgone per unit of forest onshore wind, this study makes explicit a trade-off that energy system modelling usually leaves implicit, providing a transferable basis for balancing the competing
climate strategies of protecting forests and sustaining wind expansion.
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All authors Muhammad Shahzad Javed, Marianne Zeyringer, Johannes Rahlf, Oliver Moen Snoksrud