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Sunday 4 October

Computational Physics

A Contrast-Source Inversion Scheme Based on Stochastic Optimization and Plug-and-Play Regularization

An electromagnetic inversion scheme that integrates stochastic optimization (STO) and plug-and-play (PNP) regularization into contrast-source inversion (CSI), termed STO-PNP-CSI, is developed. Standard CSI solves for the contrast source vector of every transmitter at each iteration, which is expensive in a multi-transmitter configuration. STO instead solves for only one randomly selected contrast source vector per iteration, which reduces the per-iteration cost and can help the inversion escape poor local minima and saddle points. The resulting loss of information, however, increases the ill-posedness of the inversion. To counter this, the Swin-Conv-UNet (SCUNet) denoiser is plugged into the CSI scheme as an implicit regularizer, supplying a learned prior that is stronger than conventional hand-crafted ones and stabilizes the reconstruction. The proposed STO-PNP-CSI is applied to both synthetic and experimental data. The results show that it yields accurate reconstructions at substantially lower computational cost than CSI, including under strong nonlinearity and measurement noise.
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Computational Physics · Cross-listed from astro-ph.HE

Fast Bayesian Updating of the Neutron-Star Equation of State with Neural Posterior and Evidence Estimation

We present two complementary neural routes for microscopic neutron-star EOS inference: truncated sequential neural posterior estimation with mixture importance sampling (TSNPE+MIS), which targets one observation, and amortized neural posterior estimation with importance sampling (A-NET+IS), which is reused across nuclear inputs and NICER sources. Both are corrected against the original prior and full likelihood, with the effective sample size as a diagnostic. We test nucleonic and hyperonic relativistic mean-field models with nuclear data, NICER, GW170817, and pQCD. For the fiducial analyses, both agree with UltraNest in the parameter posteriors and 90% mass-radius and tidal-deformability bands. TSNPE+MIS band-edge differences are only 0.024-0.033 km and 1.02-1.03%, while A-NET+IS differences are 0.019-0.050 km and 0.86-1.13%. TSNPE+MIS reduces the computing time by factors of 1.6-2.3; after training, A-NET+IS is 15-240 times faster per configuration. The frozen A-NET also analyzes three NICER sources absent from training, including the newly reported high-mass, compact PSR J1614-2230 posterior. For this source, the inferred $R_{1.4}$ agrees with UltraNest within 0.010 km for nucleonic matter and 0.009 km for hyperonic matter. We also introduce a Green-function Evidence Network (EN), a regression-based variant of Evidence Networks and, to our knowledge, the first Evidence Network applied to neutron-star EOS inference. After a one-time cost, its network queries return absolute evidences in about 0.03 s for new nuclear data and 3.5 s for a new NICER source; all 16 differences from UltraNest are below $1\sigma$, and independent importance-sampling evidences agree within the quoted EN uncertainties. Under the adopted likelihood, both evidence calculations favor nucleonic matter by Bayes factors of about 22:1-27:1.
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Instrumentation and Detectors

A Cryogenic Geophone with stable response from Room Temperature to millikelvin

With the development of pulse-tube cryocoolers, the availability and use of low-temperature environments have increased exponentially in recent years. However, replacing liquid helium with a mechanical cooling device has, since its introduction, highlighted the need to attenuate the mechanical vibrations generated by the cryocooler itself. In the case of dilution refrigerators, which are capable of reaching temperatures on the order of few mK, the issue of mechanical vibrations reaching the experimental setup is, in many situations, extremely critical. This has led to the development of several customized experimental approaches aimed at attenuating vibrations. However, the inertial measurement of vibrations at cryogenic and, in particular, ultracryogenic temperatures has relied on customized sensors, since no commercially available, calibrated instruments exist for measurements at these temperatures. Nevertheless, many research groups employ commercial geophones that are recalibrated at low temperatures. This approach, however, is not free from systematic errors and presents significant challenges in quantitatively assessing the absolute response. In this work, we describe the development of cryogenic geophones exhibiting an almost temperature-independent response, from room temperature down to approximately 10 mK.
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Computational Physics · Cross-listed from cond-mat.dis-nn

Ground-state properties of the two-dimensional SWAP spin-glass ensemble

We study the recently introduced SWAP ensemble for Ising spin-glasses, where the spins obtain varying lengths, with length scale $\Delta \in [0, 2]$. The lengths can be exchanged in the spirit of the SWAP algorithm for glassy poly-disperse hard-sphere systems. Using an annealing schedule, if the annealing is slow enough, ground states of the corresponding Ising Hamiltonian, where the spin lengths are incorporated into the bonds, can be obtained with high probability. We prove this statement for two-dimensional systems with sizes of up to $L^2=1024^2$ spins by comparison with exact ground states obtained by using graph matching algorithms. In particular, we analyze the nature of the obtained realizations of the disorder by calculating exact zero-temperature domain-wall energies, from exact ground state calculations using periodic and anti-periodic boundary conditions. For medium or large values of $\Delta$, e.g. $\Delta=1$, the realizations turn ferromagnetic if the annealing is slow enough, i.e., they lose their zero-temperature spin-glass property. If $\Delta$ is small, the realizations remain glassy, but the SWAP annealing does not easily find a true ground state.
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Optics

Deep learning enables large-scale inverse design of free-form metasurfaces

Metasurfaces are ultrathin optical elements that control light through carefully engineered structures smaller than the wavelength of light, enabling compact devices with functionalities that are difficult to achieve with conventional optics. However, exploiting their full design freedom over large areas has been prohibited by the large computational cost of repeated electromagnetic simulations required for inverse design. Here we introduce a physics-tailored deep-learning surrogate model that exploits the locality and symmetries of electromagnetic interactions to generalize from small-scale simulations to metasurfaces orders of magnitude larger. The model captures nonlocal interactions while predicting optical fields more than four orders of magnitude faster than the conventional electromagnetic solver it is trained on, enabling gradient-based topology optimization under arbitrary illumination. We validate the approach through the inverse design and experimental realization of free-form metagratings with diffraction angles up to 75 degrees, as well as a millimeter-scale free-form holographic metasurface more than 1,000 wavelengths across and comprising 1.6 billion degrees of freedom. By decoupling the scale of electromagnetic simulation from the scale of inverse design, our approach enables system-scale free-form photonic devices that retain nanoscale design freedom.
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All authors Viktor A. Lilja, Khosro Zangeneh Kamali, Mikael Käll, Philippe Tassin

Computational Physics · Cross-listed from cs.LG

Physics-Augmented Graph Transformers for Patch-Antenna Forward and Inverse Design

Full-wave electromagnetic (EM) simulation enables accurate patch-antenna analysis but is computationally expensive for large-scale forward prediction and inverse design. We present a mesh-native, physics-augmented graph-learning framework that treats radiation-pattern prediction as signal reconstruction on an irregular surface mesh. For the forward problem, a GPS graph transformer is trained with Physics-Augmented Intermediate Supervision (PAIS), an auxiliary node-level objective that predicts complex surface currents, the physical intermediate linking geometry to radiation. PAIS improves multiple GNN backbones at no inference-time cost, while shuffled-current and non-physical controls show the gain comes from physical correspondence. Direction-conditioned decoding and a differentiable radiation-integral consistency loss further exploit this structure. On an 80,000-sample CST benchmark, GPS+PAIS reaches MSE 0.17 / PSNR 19.67, generalizes to a PCA split, and transfers zero-shot to canonical patches. For inverse design, surrogate-filtered diffusion beats nearest-neighbor retrieval by 32% relative MSE.
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All authors Avi Epstein, Snir Nehemia, Haim Suchowski, Lior Wolf

Computational Physics · Cross-listed from math.NA

A general synthetic iterative scheme with high-order spatial discretization for rarefied gas mixture flows

We develop a high-order discontinuous Galerkin formulation of the general synthetic iterative scheme (GSIS) for steady rarefied gas mixture flows. The resulting GSIS-DG discretizes the mesoscopic kinetic equations for monatomic gas mixtures and the macroscopic synthetic equations with the same polynomial degree and solves them alternately. The kinetic solution supplies nonequilibrium corrections to the stress and heat flux, while the synthetic equations accelerate the convergence toward the steady state. Asymptotic analysis shows that GSIS-DG recovers the continuum limit without requiring the spatial mesh to resolve the molecular mean free path. Numerical results over a wide range of Knudsen numbers demonstrate high-order spatial accuracy and rapid steady-state convergence, with more than an order-of-magnitude reduction in computational cost relative to conventional kinetic iteration in the near-continuum regime. Comparisons with second-order finite-volume GSIS further demonstrate that GSIS-DG achieves comparable or better accuracy on coarser physical meshes with fewer total spatial degrees of freedom.
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Computational Physics

HFS-TransNet: A Hybrid Fixed-Stress Transferable Neural Network for Quasi-Static Biot Poroelasticity

The quasi-static Biot system, which governs coupled fluid-solid interactions in poroelastic media, poses significant computational challenges due to its strong coupling and multiscale nature. To address these, we propose a hybrid fixed-stress transferable neural network (HFS-TransNet) method. In HFS-TransNet, a data-driven TransNet module first approximates observed data on an initialization domain to supply a high-quality starting point for the subsequent physics-informed stage, which then drives fixed-stress splitting iterations via TransNet and admits an error bound. After each iteration, a greedy update strategy on a validation domain prevents model degradation and a relative tolerance criterion governs convergence termination. HFS-TransNet thereby inherits the robustness of the fixed-stress splitting scheme, the flexibility of data-driven modeling, and the transferability of TransNet, effectively overcoming the strong coupling and locking instability inherent in the Biot system. Ablation studies and comparisons with FS-FEM and FS-PINN confirm HFS-TransNet's superior performance in capturing multiscale coupled physics across varying physical parameters and boundary conditions. By bridging classical decoupled iterative schemes with hybrid scientific machine learning, HFS-TransNet offers a novel perspective for complex poroelastic simulations, as demonstrated by its successful application to brain edema simulations.
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Atomic and Molecular Clusters · Cross-listed from quant-ph

Long-lived Coherent Phonons Reveal Competing Thermal and Many-Body Dynamics in $\alpha$-In$_{2}$Se$_{3}$

The fate of quantum coherence following photoexcitation is a central problem in nonequilibrium condensed-matter physics, especially in low-dimensional solids where electronic, structural and many-body energy scales are strongly coupled. Here, we investigate this interplay in ferroelectric $\alpha$-In$_{2}$Se$_{3}$ using broadband transient-grating spectroscopy with $\sim$5 fs laser pulses. Photoexcitation launches pronounced oscillations dominated by a $\sim$104 cm$^{-1}$ mode that persists for several picoseconds. Measurements from 10 to 300 K show that its frequency remains nearly unchanged while its coherence is progressively suppressed, distinguishing the lattice coordinate from thermally activated dephasing. Varying excitation energy reveals a distinct crossover in which increasing photoexcitation progressively modifies and damps the coherent response. First-principles calculations assign the dominant oscillation to a 101.47 cm$^{-1}$ $\Gamma$-point optical phonon involving collective In-Se displacement, while quantum-dynamical simulations reproduce the main transient-grating oscillations. These results establish $\alpha$-In$_{2}$Se$_{3}$ as a model system for independently probing lattice coherence, thermal fluctuations and carrier-density-dependent interactions, revealing how a polar van der Waals semiconductor evolves from coherent lattice motion toward an incoherent many-body state after ultrafast excitation.
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All authors Xuanchao Zhang, Dehao Yuan, Junhua Zhou, Vandana Tiwari, Fulu Zheng, Ajay Jha, Hong-Guang Duan

Biological Physics · Cross-listed from cond-mat.stat-mech

Multicatalyst reactions induce abrupt transition in a dense catalytic reaction network model

We generalize the Furusawa–Kaneko model, a simple model of intracellular catalytic reaction networks, to multicatalyst reactions and analyze the generalized model using dynamical mean-field theory. In the thermodynamic and dense-network limit, we derive exact effective equations and analyze their fixed points for arbitrary degree distributions. Under nutrient-poor conditions, network heterogeneity suppresses the metabolic–starvation transition irrespective of the number of catalysts per reaction. In contrast, under nutrient-rich conditions, the bifurcation structure changes with the number of catalysts. With one catalyst per reaction, only continuous transitions occur, whereas two or more catalysts give rise to bistable phases and discontinuous transitions. The bifurcation structure also differs between two and three catalysts per reaction, with three catalysts allowing bistability between metabolic states with different cell growth rates. Our results provide a possible mechanism for bistability and abrupt switching in metabolic dynamics.
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Fluid Dynamics

Landau damping and mode-selective instability of a vortex gas

We show that a collisionless point-vortex gas behaves as a genuine Vlasov system. Starting from the non-canonical Hamiltonian structure of point-vortex dynamics, we derive a reduced Klimontovich equation and the corresponding Vlasov description directly on the physical plane, without introducing auxiliary momentum variables. The theory predicts a rich spectrum of collective phenomena, including vortex Rossby-like waves, global oscillations, resonant critical layers, and a dielectric response operator analogous to that of plasmas and self-gravitating systems. For smooth vortex distributions, differential rotation gives rise to a vortex analogue of Landau damping, whereby collective modes transfer energy and angular momentum to resonant vortex annuli in the absence of collisions or dissipation. Remarkably, differential rotation acts as a stringent mode-selection mechanism: for a Gaussian vortex cloud, only a single quadrupolar quasi-mode survives, while all higher multipoles are destroyed by phase mixing. We further predict a vortex counterpart of the beam–plasma instability, in which a thin vortex ring orbiting an Onsager patch selectively excites Kelvin modes with an azimuthal symmetry controlled by the ring population. These results establish kinetic theory as a natural framework for collective vortex dynamics and suggest new mechanisms for vortex transport, vortex avalanches, and rotational glitches in neutron-star superfluids.
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All authors H. Terças, J. L. Figueiredo, J. T, Mendonça

Saturday 3 October

General Physics

Collapse and causality in generalised trace dynamics: record selection in Connes time and the causal consistency of emergent records

Dynamical wave-function collapse must not violate causality: a record selected "now" has no frame-independent meaning, and a nonlinear law can let distant observers signal. We ask whether this conflict is avoided when classical spacetime, with its causal structure, itself arises from localisation, as proposed in generalized trace dynamics (GTD), where the fluctuations that select a record come from unresolved pregeometric degrees of freedom ordered by Connes time, not by a spacetime coordinate. The hypersurface question is then not posed where selection happens; it returns as the requirement that emergent records do not signal. We apply the standard no-signalling theorem to an effective collapse law of CSL type. The norm-preserving, response-free law of a naive coarse-graining never selects. In history form, record weights are martingales only if the fluctuation history leans towards the leading record with gain twice its own diffusion and, for operators with three or more collinear eigenvalues, the linear law carries its counter-term, which a smooth coefficient drive gives with the wrong sign; any other gain signals. For an equilibrium sea the fluctuation-dissipation relation fixes the gain, so the Born gain is an Einstein relation between coupling, temperature and correlation time. A rate that reads the entanglement of the conditioned state signals; enhancement must sit in fixed collective operators. Positive states annihilate the Grassmann bilinear carrying the collapse coefficient, so the physical block is a reconstruction with positive kinetic form. The coefficient noise is evaluated for the Sutherland texture of GTD's relational master matrix: a block coupled to its local strain acquires an Ohmic spectral density with computed friction, continuum criterion and recurrence, while a kinetic cross-coupling yields none. What remains is the projection supplying counter-term and gain.
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General Physics

Neutrino Spin–Flavor Dynamics and Quantum Rabi Model: Spectral Correspondence and QRM Benchmarks

We formulate a two-state neutrino spin–flavor system coupled through a transition magnetic moment to a single quantized electromagnetic mode and establish its operator-level correspondence with the quantum Rabi model (QRM). For the sector $\{\lvert\nu_{iL}\rangle,\lvert\nu_{jR}\rangle\}$, the diagonal splitting is $\Delta_s=(m_i^2-m_j^2)/(2E)+V_{iL}-V_{jR}$, while quantization of a transverse electromagnetic mode gives a coupling $g_\nu=\mu_{ij}B_{\rm zpf}$. The effective Hamiltonian consequently has the QRM form $H_\nu=\Delta_s\sigma_z/2+\omega_c a^\dagger a+g_\nu\sigma_x(a+a^\dagger)$. We then formulate the correspondence at the level of the exact QRM spectrum, focusing on its exceptional (Juddian) states, and transfer the QRM constraint polynomials directly to neutrino variables. This yields explicit algebraic conditions on the neutrino mass splitting, energy, transition magnetic moment, zero-point magnetic field, and mode frequency. We also identify QRM phenomena that would become conditional predictions of the quantized-field neutrino model—including counter-rotating corrections, parity structure, spin–field entanglement, and occupation-dependent dynamics. The trapped-ion QRM experiments provide benchmarks for the operator family, while none of these QRM phenomena is presented as an already observed neutrino effect.
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Plasma Physics · Cross-listed from astro-ph.SR

Deriving the Continuous $\beta$-FPUT Model for Decayless Solar Coronal Oscillations Directly from Resistive MHD

We present an analytical framework deriving the fluid-continuum $\beta$-Fermi-Pasta-Ulam-Tsingou ($\beta$-FPUT) system directly from a third-order resistive magnetohydrodynamics (MHD) expansion to explain persistent, decayless transverse oscillations observed in solar coronal loops. For a continuous wave field propagating along a longitudinal magnetic field with cross-field density variations, a multi-scale expansion demonstrates that quadratic $\mathcal{O}(2)$ advective and Maxwell tension terms vanish identically due to out-of-plane polarization symmetry. Instead, the quadratic longitudinal ponderomotive force drives field-aligned density modulations that back-react on the primary transverse wave, yielding a cubic $\mathcal{O}(3)$ restoring force. In the long-wavelength limit, the governing equations reduce to a fluid-continuum Modified Korteweg-de Vries (mKdV) system where cross-field profile variation provides the non-linear dispersive mechanism. We prove that this internal fluid mechanism establishes stable, amplitude-dependent frequency self-focusing, which phase-locks adjacent elements and prevents phase-mixing wave attenuation without requiring external steady driving parameterizations. This framework enables macro-scale coronal seismology, providing closed-form expressions to invert observed decayless wave-packet durations to compute the unresolved cross-field density gradient scale length ($L_x$) and the internal volumetric filling factor ($f_V$) without relying on traditional emission measure or spectroscopic line-ratio diagnostics. Much like famous Enrico Fermi's historic use of macro-scale displacements to estimate complex atomic explosion yields, this framework establishes a paradigm where monitoring macroscopic oscillation durations empowers observers to extract fine-scale, otherwise unresolvable waveguide properties.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci

Time-Reversal Selection Rule for Twist Disorder

Random layer rotations are ubiquitous in layered matter, from turbostratic films to rotationally disordered crystals, and strongly suppress transport across the layers. Generated by a symmetry operation, this disorder is absent on the rotation axis, so the thickness laws of conduction are set by how fast backscattering vanishes there. We show that a time-reversal selection rule decides this: each twist harmonic of the interlayer bond is either a frame rotation, whose backscattering cancels, or a coupling change, which scatters. A zero-set theorem turns the rule into universal thickness laws for electrons and phonons, fixed by band-edge symmetry; random twist increments rescale the backscattering but keep its order. Where the axis is unprotected, band nodes provide a second route: a transparent energy with heavy-tailed disorder and an $N^{-3}$ law. A first-principles forward-channel model of black phosphorus shows both routes; its random-twist films act as a symmetry filter that, relative to aligned stacks, retains a hundred times more of the electron than of the hole conductance at 64 layers. The symmetry of band edges and phonon branches thus decides what crosses a disordered stack, making stacking disorder a design element.
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All authors Peng Kang, Da Wan, Shulin Bai, Pengfei Zhang, Vincent Michaud-Rioux, Zhen Li, Yu Liu, Lei Zheng, Li-Dong Zhao, Huibin Xu

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

Quantitative near-atomic-resolution oxidation-state mapping in complex oxide heterostructures by electron energy-loss spectroscopy

We present a theoretical framework for quantitative oxidation state mapping of transition-metal and rare-earth elements from near-atomic-resolution electron energy-loss spectroscopy (EELS) in complex oxide heterostructures. The total inelastic differential cross section of transition-metal L$_{2,3}$ and rare-earth M$_{4,5}$ edges is calculated by combining the relaxed Dirac-Hartree-Fock ionization cross section with ligand-field multiplet theory for the discrete transitions. We apply the approach to two correlated-oxide heterostructures, La$_{0.67}$Sr$_{0.33}$MnO$_3$/LaCr$_{0.2}$Mn$_{0.2}$Fe$_{0.2}$Co$_{0.2}$Ni$_{0.2}$O$_3$/SrTiO$_3$ and NdNiO$_3$/La$_{0.67}$Sr$_{0.33}$MnO$_3$/NdGaO$_3$, which include a wide range of transition-metal and rare-earth elements with overlapping features. The method resolves the oxidation states of Cr, Mn, Fe and Co and identifies the Ni contribution within the LaCr$_{0.2}$Mn$_{0.2}$Fe$_{0.2}$Co$_{0.2}$Ni$_{0.2}$O$_3$ layer at near-atomic resolution. We find predominantly Co$^{2+}$ together with mixed Mn$^{2+}$/Mn$^{3+}$/Mn$^{4+}$ character, indicating site-specific valence redistribution within the layer. We also separate overlapping spectral features, such as La-M$_{4,5}$ and Ni-L$_{2,3}$ edges in the NdNiO$_3$/La$_{0.67}$Sr$_{0.33}$MnO$_3$/NdGaO$_3$ heterostructure, thereby recovering the intrinsic Ni-L$_{2,3}$ excitation spectrum. We find that the effective Ni valence in NdNiO$_3$ deviates from the simple ionic picture. More broadly, this work establishes a generic method for quantitative valence mapping from near-atomic-resolution EELS, applicable to a wide range of experimental conditions for the study of local electronic structure of complex oxides.
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All authors Ioannis Iatrakis, Zitao Zhang, Ricardo Egoavil, Emma van der Minne, Christoph Baeumer, Frank de Groot

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

Jets with Streaks: the Global Dynamics and Structure of Striped Poynting flux dominated Jets

Striped jets, characterized by magnetically dominated regions with alternating polarity, can enable fast magnetic energy dissipation in global current sheets formed in between the stripes, and are thus considered as a viable source for the high-energy emission observed in blazars and gamma-ray burst prompt emission. We perform the first global axisymmetric GRMHD simulations that follow the evolution of striped jets from their launching, by accretion of poloidal magnetic loops with alternating polarity onto a spinning black-hole, to their energy dissipation at large distances. The accretion of each loop launches a Poynting-flux-dominated mini-jet carrying a helical magnetic field whose polarity is inherited from the loop, and the collection of which forms the jet core. The relativistic core is surrounded by a non-relativistic sheath composed of returning fieldlines from previously launched mini-jets in a nested configuration. Efficient mini-jet launching requires poloidal loops in the accretion disk to form close to the black hole ($r \lesssim 50\,r_g$); otherwise, they lose coherency due to turbulence. Once launched, the mini-jets accelerate electromagnetically, similar to steady-state jets, with the Lorentz factor increasing linearly with the jet cross-sectional radius as long as lateral causal contact with the jet axis is maintained. Current sheets form when two trailing mini-jets carrying oppositely directed magnetic fields come into contact. Early sheet formation is facilitated by the longitudinal expansion of the mini-jets, driven by internal pressure before the flow becomes super-fast-magnetosonic. We measure an energy dissipation rate of a few tens of percent of the jet Poynting power in the observer frame, within our simulation box of $10^4\,r_g$. Our results can account for the bright superluminal features observed in BL Lac type blazars.
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All authors Ho-Sang Chan, Anna Chashkina, Omer Bromberg, Gregory R. Werner, Hayk Hakobyan

Applied Physics · Cross-listed from eess.SP

Toward a Lean Formalization of Analog Computing with Microwaves

Analog computing with microwave signals can perform linear transformations directly in the analog domain, as the signals propagate through a microwave network. A fundamental question is which transformations can be computed with a given set of microwave components. In our previous work, we answered this question for networks of hybrid couplers and phase shifters by deriving a necessary and sufficient condition on the transformations these networks can compute, and we showed that the discrete Fourier transform (DFT) satisfies it. In this paper, we take a first step toward the formalization of analog computing with microwaves in Lean, a programming language and proof assistant that is increasingly adopted in mathematics. We formalize the considered components, their series and parallel connections, and the class of networks they can implement. Then, we formally prove the necessary and sufficient condition characterizing these networks, as well as the implementability of the DFT of any size power of two. All proofs are checked by the Lean kernel, and the code is openly available at: https://github.com/matteonerini/formalizing-analog-computing.
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Optics

Efficient Light Trapping Strategy in Solar Cells via Vertically Disordered Perovskite Nanowires

In this work, we investigated the absorption of light in perovskite nanowires (PrvNWs) for application as active layer in a solar cell. Specifically, we simulated PrvNWs with a random position inside the pores of an AAO membrane. The results demonstrate that this vertical disorder can boost light absorption, up to 28% in terms of short-circuit current, in comparison to the corresponding ordered PrvNW array. This performance boost is due to a combination of light trapping and anti-reflection effect. Thus, our findings suggest that vertically disordered PrvNWs can have a much better performance than ordered arrays. Also, we showed that it is not necessary to aim for a very narrow length distribution in the nanowires, easing the fabrication requirements.
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Data Analysis and Statistics · Cross-listed from gr-qc

Covariance scaling and a dual-mode torque diagnostic in measurements of the gravitational constant

Laboratory determinations of the Newtonian gravitational constant $G$ disagree by more than their quoted uncertainties allow. We examine the sixteen determinations comprising the CODATA-2018 archive using a proportional covariance-scale model that retains the full reported covariance matrix. Because the 2026 NIST torsion-balance redetermination shares apparatus lineage with the BIPM Mark II balance, our primary historical fit excludes the BIPM-14 determination, giving $\hat{\lambda} = 2.967$ for the remaining fifteen measurements. Evaluated against this historical model under the declared uniform covariance-scaling convention, the correlated four-configuration NIST result is highly unlikely under the archive's reported, unscaled covariance but is statistically unremarkable once the historically inferred extra dispersion is applied ($Q_\lambda = 4.840$; finite-sample $F$ tail $p = 0.382$); a mean-only scaling sensitivity leaves the vector discrepant. Retaining the complete archive also gives a comparable result. We further examine four matched free-minus-servo torque differences reported by NIST. They are consistent with a single common absolute torque offset across the four tested configurations, $\widehat{\Delta N} = 1.918 \pm 0.215$ pN m, and poorly described by an equally simple fractional-scale alternative under the stated independent-Type-A treatment, with a chi-square contrast of $\Delta\chi^{2} = 11.041$ between the two torque models. The paper provides a covariance audit of the historical archive, a lineage-qualified consistency check, and an experimentally testable diagnostic for dual-mode torsion balances, without proposing a revised value of $G$.
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Accelerator Physics

Design of the Electron-Beam Collimator for the Electron-Ion Collider

The design and optimization of a beam collimator for the Electron Storage Ring (ESR) of the Electron-Ion Collider (EIC) are presented. The collimator must efficiently intercept stray beam particles while maintaining acceptable beam coupling impedance, surviving rapid accidental beam impacts, and withstanding steady-state beam-induced heating. An integrated design approach combining beam-loss tracking, electromagnetic-shower simulations, thermomechanical analysis, and impedance calculations is developed and benchmarked against published simulations and beam-impact experiments. A comparison of candidate absorber materials identifies Al2219-T62 as providing a favorable balance of beam-impact robustness, thermal and electrical conductivity, mechanical strength, and ultra-high-vacuum compatibility. For the ultimate ESR bunch charge of 28 nC at 10 GeV, the Al2219-T62 jaw remains below the adopted practical thermal-shock threshold for approximately 50 fully intercepted bunches and below the localized melting threshold for approximately 100 bunches under the reference impact conditions considered. These results provide an engineering input to the machine-protection requirements, for which a complete protection response within several machine turns is required. Optimization of the absorber-tip length yields a 70 mm tapered jaw that balances collimation performance, beam-impact robustness, and impedance. The resulting design maintains acceptable impedance margins and remains below both the yield and ultimate tensile strengths under a conservative 3.6 kW beam-induced heating scenario. The results establish a baseline ESR collimator design and a benchmarked methodology for evaluating collimator robustness in high-current electron storage rings.
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All authors Andrii Natochii, Elke-Caroline Aschenauer, Jay Best, Alexei Blednykh, Xiaofeng Gu, Kuppan Gunavathi, Charles Hetzel, Christoph Montag

Plasma Physics · Cross-listed from astro-ph.SR

Measured energy exchange in coronal hole solar wind from its solar origins to the heliosphere

Coordinated ground- and space-based remote observations are used to provide a comprehensive, multi-perspective view of the solar atmosphere that we connect with in situ measurements in the heliosphere centered around the April 8 2024 Total Solar Eclipse observed across North America. These near-contemporaneous, multi-wavelength datasets are used to directly derive the plasma parameters and compute an energy budget of a solar wind stream at its low-coronal birthplace (at an altitude of 1.05Rsun). The energy budget is also independently computed at and beyond the Alfvén surface from the in situ observations of the same stream. The total wave energy flux dominates the low-coronal budget (11 W m-2 Alfvén, 7 to 23 W m-2 in compressive MHD modes), while enthalpy (13 W m-2) and work done against gravity from 1.0Rsun (2.5 W m-2) make up the remainder. The total coronal energy budget is consistent with the total measured in situ by Parker Solar Probe if and only if compressive energy flux is included and attributed to the fast magnetosonic mode. Nearly all this thermal and wave energy is converted to ion heating, acceleration and gravitational potential energy within the Alfvén surface. The stream evolution is well-described as a thermal-pressure driven wind with additional energy deposited by MHD fluctuations. The observed evolution of the Alfvénic component of these fluctuations follows a near-dissipation-free curve below the Alfvén surface while deviating from it more strongly above this critical surface.
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All authors Yeimy J. Rivera, Alin R. Paraschiv, Samuel T. Badman, Alberto M. Vasquez, Federico A. Nuevo, Ryan J. French, Momchil Molnar, Roberto Susino, Zihao Yang, Marco Romoli, Richard A. Frazin, Michael L. Stevens, Stuart D. Bale, Deborah Baker, Jasper Halekas, Thomas A. Schad, Christopher J. Owen, Philippe Louarn, Jenna Samra, Giuliana de Toma, Daniela A. Lacatus, Giulio Del Zanna, Chad A. Madsen, Enrico Landi, Manolis K. Georgoulis, Amir Caspi, Éric Buchlin, Nour E. Raouafi, Luca Franci, Miho Janvier, Cooper Downs, Roberto Livi, Phyllis Whittlesey, Ali Rahmati, Davin Larson, Nikos Sioulas

Plasma Physics · Cross-listed from astro-ph.IM

Xenia: A Table-Driven Code for Astrophysical Multi-Fluid Hydrodynamics

Models of escaping planetary atmospheres require neutral and ion species with distinct velocities and thermal pressures, coupled by photoionization, recombination, radiation, and collisions. Implementing and extending such coupled models is often hindered when species definitions and stiff interactions are embedded in solver-specific kernels. We present Xenia, a table-driven code for astrophysical multi-fluid hydrodynamics designed to lower this barrier. Species, coupling channels, chemistry, heating and cooling, and radiation channels are declared in Python, compiled to symbolic tapes, and passed through a versioned interface to shared C/Kokkos kernels; changing a problem therefore changes data rather than kernel code. For ionized configurations, electrons provide a pressure-only quasi-neutral closure: electron density follows from ion populations, electron mass and momentum are not advanced, and only electron pressure is transported. Stiff coupling is treated by operator splitting into a radial radiation scan, hyperbolic transport, and a cell-local implicit source solve. The same symbolic tapes yield an analytic finite-difference-free Jacobian for a direct dense LU solve. The public v0.1 release is validated with acoustic convergence, dustybox drag relaxation, conservation and closure contracts, two-fluid cloud-shock coupling, curvilinear geometry bookkeeping, three escape chains, and 394 passing tests. Conservation and positivity are not claimed to match mature production codes; radiation uses a radial Beer-Lambert prefix product rather than a general solver; escape chains are reproducibility checks rather than new science predictions; and backend evidence is limited to functional deployment and equivalence fingerprints. Xenia is released under GPLv2 at https://github.com/YFG-tec/xenia.
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Optics

Phase-matching in high-order harmonic generation with a plasma-reshaped driving field

The transition from titanium-sapphire to ytterbium-based laser technology enables turnkey implementations of high-order harmonic generation (HHG) setups at high repetition rates, opening up new applications, e.g., in semiconductor metrology. This, however, requires exploring and understanding the impact of new experimental conditions. Here, we study HHG in neon over the spectral range 8-17 nm with high spectral resolution, using a post-compressed ytterbium laser. Our measurements reveal a large pulse-energy- and pressure-dependent spectral shift, spanning more than two harmonic orders. The femto-chirp of the harmonic emission combined with the blueshift of the fundamental field allows us to relate the observed spectral shifts to the temporal window of harmonic generation, which is determined by phase-matching. To understand these dynamics, it is essential to consider the reshaping of the driving laser field inside the plasma, despite the low driving intensity and long pulse duration. We introduce an on-axis phase-matching description that captures these effects and reproduces the experimental and simulated trends. These results demonstrate the central role of plasma-induced laser reshaping in phase-matching of HHG, which should be accounted for when optimizing sources in a multi-parameter landscape.
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All authors Gaspard Beaufort, Venus Poulain, Melvin Redon, Robin Weissenbilder, Elisa Appi, Filip Salbrink, Saga Westerberg, Aimee J. Ross, Sylvianne Roscam Abbing, David P. O'Dwyer, Yin Tao, Per Eng-Johnsson, Cord L. Arnold, Anne L'Huillier, Peter Smorenburg, Anne-Lise Viotti

Classical Physics · Cross-listed from math-ph

Dynamical quasi-symmetry of the classical Kepler-Coulomb problem and the conservation of the Laplace-Runge-Lenz vector

The paper studies a classical non-relativistic particle moving in $\mathbb{R}^{N}$, $(N\geqslant2)$, in the presence of the Kepler-Coulomb force $\boldsymbol{F}(\boldsymbol{r})=\alpha\boldsymbol{r}/r^{3}$, $(\alpha\neq0)$. It is shown that the extended-configuration-space transformation involving the projective transformation of the radius vector $\boldsymbol{r}\to\boldsymbol{R}=\boldsymbol{r}/(1+\boldsymbol{c}\cdot\boldsymbol{r})$ and the differential time scaling $\mathrm{d}t\to\mathrm{d}T=\mathrm{d}t/(1+\boldsymbol{c}\cdot\boldsymbol{r})^{2}$, where $\boldsymbol{c}$ is a real vector-valued parameter with dimensions of inverse length, constitutes a dynamical quasi-symmetry in the sense that it maps Newton's equation of motion $m(\mathrm{d}^{2}\boldsymbol{r}/\mathrm{d}t^{2})=\alpha\boldsymbol{r}/r^{3}$ into the equation $m(\mathrm{d}^{2}\boldsymbol{R}/\mathrm{d}T^{2})=(\alpha\boldsymbol{R}/R^{3}) \operatorname{sgn}(1-\boldsymbol{c}\cdot\boldsymbol{R})$. This quasi-symmetry is independent of, yet complementary to, the well-known Kepler-Coulomb dynamical symmetry, which is SO($N+1$) for negative energies and SO($N,1$) for positive energies. A detailed analytical and graphical analysis of induced mappings between non-degenerate conic trajectories associated with the original and transformed systems is presented. Mappings between velocity hodographs are also briefly discussed. It is then proved that the conservation of energy in the transformed motion implies the conservation of the Laplace-Runge-Lenz vector in the original dynamics.
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Optics · Cross-listed from astro-ph.IM

Vector field dark matter search with Sagnac interferometer

We present the first calculation showing that a material-asymmetric Sagnac speed meter can improve quantum-noise-limited sensitivity to $B-L$ vector dark matter by nearly two orders of magnitude over a Fabry–Perot Michelson position meter at the low-mass end of the band. We introduce material contrast into a dual-ring interferometer to probe composition-dependent $B-L$ forces and compare the two configurations at equal incident power, input-mirror transmissivity, and cavity round-trip length. For sapphire mirrors and a one-week benchmark, the quantum-noise-only median expected $95\%$ CL upper limit reaches $1.2\times10^{-27}$ at $m_A=4.1\times10^{-14}\,\mathrm{eV}/c^2$ ($10\,\mathrm{Hz}$), a factor-$57$ improvement. This band-edge forecast assumes negligible classical noise; sensitivity at $10\,\mathrm{Hz}$ is not established for a realizable suspension and isolation system. The material-induced displacement is essentially identical in both configurations, with the gain arising from reduced low-frequency quantum backaction. These results identify speed-meter readout as a promising route to lower-mass vector-dark-matter searches.
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Computational Physics · Cross-listed from cond-mat.stat-mech

MUTACO: Simulator-Efficient Response Matching in Stochastic Nonlinear Systems via Compatibility-Aware Sequential Design

Many physical inverse problems are mediated by expensive stochastic simulators for which response gradients, adjoint sensitivities, or a differentiable simulator interface are unavailable. We introduce Multiple Target-based Confident Acquisition (MUTACO), an uncertainty-aware sequential-design method for response matching that requires only noisy forward evaluations and learns the multicomponent response together with its predictive uncertainty. We develop and evaluate MUTACO for a disordered network of stochastic phase oscillators. The inverse task is to infer statistical properties of the local potential and interactions from macroscopic rotation and synchronization curves under multiple driving conditions. Rather than requiring unique recovery of these statistical properties, MUTACO searches for parameter configurations whose predicted rotation and synchronization responses are compatible with the target response while accounting for predictive uncertainty. This response-centered formulation is appropriate when experimentally accessible observables characterize ensemble statistics rather than a particular microscopic realization. Under strictly limited simulation budgets, MUTACO achieves the lowest held-out response error among the tested adaptive-search, space-filling, and simulation-based inference methods, while also yielding lower parameter-recovery error than the compared methods. These results demonstrate that response-targeted sequential design is a simulator-efficient approach to inverse modeling from finite noisy forward evaluations and suggest broader applicability to stochastic physical systems with correlated multicomponent responses and weakly constrained parameter directions.
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All authors Ege Karadeniz, İlter Onat Korkmaz, Umut Can Turhan, Cem Tekin, Ayd{\i}n Cem Keser

Computational Physics

Spectral properties of the Riemann zeta function and their physical applications

This work studies the Riemann $\zeta$ numerically with emphasis on its physical manifestations. Three areas are examined: (i) the spectral statistics of the non-trivial zeros, which we compare with the Gaussian Unitary Ensemble predictions, obtaining $\chi^2/\text{dof} = 1.2$; (ii) the role of $\zeta(\frac{3}{2})$ in determining the critical temperature for Bose-Einstein condensation, where we find $T_c = 0.13$ K for an ideal gas; and (iii) the application of $\zeta$-function regularisation to the Casimir effect, yielding the standard Casimir energy density $-\frac{\pi^2 \hbar c}{720 a^3}$, which for $a=1\,\mathrm{nm}$ gives $\sim -4.33\times10^{-4}\,\mathrm{J\,m^{-2}}$. The numerical results are consistent with the Montgomery-Odlyzko conjecture and with spectral approaches motivated by the Hilbert-Pólya conjecture, within the statistical limitations of the analysis.
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Computational Physics · Cross-listed from cs.AI

Recursive Improvement of a Differentiable Scientific Software Ecosystem

Differentiable programming connects scientific computation with gradient-based inference, learning and design. Extending these capabilities across a heterogeneous software ecosystem requires specialized effort to implement derivatives, integrate interfaces and evaluate quality. AI coding agents can accelerate this transformation, but translating their capabilities into useful scientific software requires identifying research needs and evaluating how well implementations meet them. We present an environment for agent-driven evolution of differentiable scientific software that connects demand identification, development and quality evaluation. A unified differentiation interface exposes reusable derivative rules alongside existing numerical routines, allowing research tasks to share these capabilities. Research requirements guide development, with implementations assessed through independent derivative checks, workflow tests and performance evaluation. Validated software, research programs and tests become shared resources for subsequent studies. We construct and validate automatic differentiation extensions across 20 packages spanning physical, chemical and biological modeling, with research workflows demonstrating reuse across tasks. Benchmarks demonstrate computational savings over finite differences in gradient evaluation and complete parameter estimation. Research-driven revisions make previously unsupported workflows differentiable, correct derivatives of scientific observables and eliminate redundant computation. Quantum-control and thermal-design studies revise objectives in response to physical evaluation, improving designs while reusing existing derivatives. This work provides a practical approach to expanding differentiable programming across established scientific software and organizing AI agents around the recursive improvement of a shared computational ecosystem.
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All authors Pengcheng Hou, Xiaojun Tan, Sihan Hu, Ruisi Wang, Shuo Chen, Lei Wang, Youjin Deng, Kun Chen

Atmospheric and Oceanic Physics

ClimateBench v2.0: Probabilistic Climate Model Benchmarking

We present ClimateBench v2, a standardized protocol for evaluating climate models on diagnostics expected to be informative for their skill in projecting mid-century regional temperature and precipitation changes. The protocol is designed to evaluate any physics-based, data-driven, or hybrid climate model on equal footing using a common set of observational and out-of-distribution tests. We define three tiers of evaluation. Tier I establishes physical credibility through entry-ticket tests of energy conservation, coupled (co-)variability, and basic forced responses. Tier II scores models against post-2015 observations of surface temperature, precipitation, radiative fluxes, sea ice, and key modes of variability using fair CRPS as the primary probabilistic score, complemented by distributional and ensemble-consistency diagnostics. Tier III tests out-of-distribution generalization through paleoclimate simulations spanning the Last Interglacial, Last Glacial Maximum, and Mid-Holocene, and through perfect-model experiments in which data-driven models must predict the future climate of existing Earth system models from historical data alone. We reserve all observational data after 2015 for testing, and submissions must include multiple ensemble members to enable probabilistic evaluation. This reservation exploits a new opportunity provided by the decade of observations accumulated since the end of the CMIP6 historical experiment, which constitutes an out-of-sample record of forced climate change (and internal variability) for the current generation of models, and we quantify, in an idealized setting, the information it carries about mid-century warming. We provide the evaluation code, observational reference datasets, and perfect-model training data as an open benchmark to drive measurable progress in climate projection across all modeling approaches.
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All authors Duncan Watson-Parris, Willa Tobin, Aytaç Paçal, Manuel Schlund, V. Balaji, Kevin Bowman, Chris Bretherton, Peter M. Caldwell, Will Chapman, William D. Collins, Gregory S. Elsaesser, Pierre Gentine, Helene Hewitt, Stephan Hoyer, Ralph Keeling, Nikolay Koldunov, David M. Lawrence, Christian Lessig, Daniel J. Lunt, J. David Neelin, Mike Pritchard, Sarah Purkey, Gavin Schmidt, Tapio Schneider, Michael Schulz, Tiffany Shaw, Isla R. Simpson, Graeme Stephens, Aneesh C. Subramanian, Joao Teixeira, Jessica Tierney, Andrew I. L. Williams, Laure Zanna, Veronika Eyring, Rose Yu