Applied Physics · Cross-listed from cs.AR
Co-Design of Memory-Storage Systems for Workload Awareness with Interpretable Models
Jay Sarkar, Vamsi Pavan Rayaprolu and Abhijeet Bhalerao
Solid-state storage architectures based on NAND or emerging
memory devices (SSD), are fundamentally architected and optimized for both reliability and performance. Achieving these simultaneous goals requires co-design of
memory components with firmware-architected Error Management (EM)
algorithms for density- and performance-scaled
memory technologies. We describe a Machine Learning (ML) for systems methodology and modeling for co-designing the EM subsystem together with the natural variance inherent to scaled silicon process of
memory components underlying SSD technology. The modeling analyzes NAND
memory components and EM
algorithms interacting with comprehensive suite of synthetic (stress-focused and JEDEC) and emulation (YCSB and similar) workloads across Flash Translation abstraction layers, by leveraging a statistically interpretable and intuitively explainable ML
algorithm. The generalizable co-design framework evaluates several thousand datacenter SSDs spanning multiple generations of
memory and storage technology. Consequently, the modeling framework enables continuous, holistic, data-driven design towards generational architectural advancements. We additionally demonstrate that the framework enables Representation Learning of the EM-workload domain for enhancement of the architectural design-space across broad spectrum of workloads.
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Atomic Physics · Cross-listed from quant-ph
Velocity-Enabled Quantum Computing with Neutral Atoms
Ohad Lib, Hendrik Timme, Maximilian Ammenwerth et al. (+5 more)
Realizing error-corrected logical
qubits is a central goal for the current development of digital
quantum computers. Neutral atoms offer the opportunity to coherently shuttle atoms for realizing efficient
quantum error correction based on long-range connectivity and parallel atom transport. Nevertheless, time overheads in shuttling atoms and complex control hardware pose challenges to scaling current architectures. Here, we introduce atom velocity as a new degree of freedom in neutral-atom architectures tailored to
quantum error correction. Through controlled Doppler shifts, we demonstrate velocity-selective mid-
circuit state preparation and measurement on moving atoms, leaving spectator atoms unaffected. Furthermore, we achieve on-the-fly local single-
qubit rotations by mapping micron-scale atom displacements to the spatial phase of global control beams. Complementing these techniques with CZ entangling gates with a fidelity of 99.86(4)%, we experimentally implement key primitives for
quantum error correction and measurement-based
quantum computing. We generate an eight-
qubit entangled cluster state with an average stabilizer value of 0.830(4), realize an [[4,2,2]] error-detection code with 99.0(3) % logical Bell-state fidelity, and perform stabilizer measurements using a flying ancilla. By enabling selective operations on continuously moving atoms using only global beams, this velocity-enabled architecture reduces hardware overhead while minimizing shuttling and transfer delays, opening a new pathway for fast, large-scale atom-based
quantum computation.
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All authors Ohad Lib, Hendrik Timme, Maximilian Ammenwerth, Flavien Gyger, Renhao Tao, Shijia Sun, Immanuel Bloch, Johannes Zeiher
Medical Physics · Cross-listed from math.OC
Notes on the primal-dual algorithm for convex optimization applied to X-ray tomographic image reconstruction
Emil Y. Sidky and Xiaochuan Pan
The purpose of these notes is to provide background on understanding the primal-dual
algorithm of Chambolle and Pock [1] for imaging scientists. The presentation focuses on providing intuition and an algorithmic system that is amenable to pre-conditioning. The document aims to be self-contained, providing background on the essential facts of non-smooth convex analysis.[2]
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Atomic Physics
Towards Collinear Laser Spectroscopy of Radioactive Molecules Utilizing In-trap Produced Molecular Ion Beam
W. C. Mei, S. J. Chen, X. F. Yang et al. (+14 more)
Molecules containing short-lived isotopes, namely radioactive molecules, are among the most promising candidates for probing new physics beyond the Standard Model, although their production and spectroscopic measurements remain technically challenging. Here, we demonstrate an integrated methodology that combines formation of molecular ion beams in a radiofrequency quadrupole cooler-buncher with collinear
laser spectroscopy. As a proof-of-principle experiment, we successfully produce molecular ions such as $\rm BaF^+$ and $\rm YbF^+$ via in-trap ion-molecule reactions and perform high-resolution
laser spectroscopy of the target molecule $\rm ^{138}BaF$. Vibrational and rotational structures of $\rm ^{138}BaF$ across different electronic states are obtained using resonance-enhanced multiphoton ionization schemes, confirming the feasibility of the proposed methodology. This work establishes a practical route for future formation and spectroscopic studies of short-lived radioactive molecules, such as those containing $\rm ^{225}Ra$, at radioactive ion beam facilities.
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All authors W. C. Mei, S. J. Chen, X. F. Yang, J. H. Lv, D. Y. Chen, H. R. Hu, Y. F. Guo, Z. Yan, Y. P. Jing, C. Zhang, Y. P. Lin, T. X. Gao, X. Shen, S. W. Bai, R. F. Garcia Ruiz, J. Yang, Y. L. Ye
Computational Physics · Cross-listed from cs.LG
Building Trust in PINNs: Error Estimation through Finite Difference Methods
Aleksander Krasowski, René P. Klausen, Aycan Celik et al. (+3 more)
Physics-informed neural networks (PINNs) constitute a flexible deep learning approach for solving partial differential equations (PDEs), which model phenomena ranging from heat conduction to
quantum mechanical systems. Despite their flexibility, PINNs offer limited insight into how their predictions deviate from the true solution, hindering trust in their prediction quality. We propose a lightweight post-hoc method that addresses this gap by producing pointwise error estimates for PINN predictions, which offer a natural form of explanation for such models, identifying not just whether a prediction is wrong, but where and by how much. For linear partial differential equations, the error between a PINN approximation and the true solution satisfies the same differential operator as the original problem, but driven by the PINN's PDE residual as its source term. We solve this error equation numerically using finite difference methods requiring no knowledge of the true solution. Evaluated on several
benchmark PDEs, our method yields accurate error maps at low computational cost, enabling targeted and interpretable validation of PINNs.
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All authors Aleksander Krasowski, René P. Klausen, Aycan Celik, Sebastian Lapuschkin, Wojciech Samek, Jonas Naujoks
Instrumentation and Detectors
Characterization of Passive CMOS Strip Detectors After Proton Irradiation
Marta Baselga, Jan-Hendrik Arling, Naomi Davis et al. (+14 more)
Strip detectors are populating outer trackers of high-energy particle experiments. They are convenient for covering large areas of sensitive material since they use less power and have fewer readout channels compared to pixels sensors. Nevertheless, they are typically manufactured with a mask set that covers the full wafer, otherwise when using smaller reticles the strip implants have to be stitched. For this project, strip detectors were fabricated in a CMOS commercial foundry using different reticles to be stitched several times, proving the feasibility of this technology. LFoundry produced the passive CMOS strip detector with a production line of 150 nm node technology, using a 150 um thick FZ wafer. Those strip sensors have three different geometries to study different impacts of the CMOS technology. The strips have lengths of 2.1 cm and 4.1 cm, stitching 3 or 5 reticles respectively. This work shows results of 24 GeV
proton irradiated passive CMOS strip detectors. The detectors were irradiated at CERN and were tested with different set-ups, not showing any effect from the strips stitching. Proving that this technology is feasible for detecting high-energy particles opens the door to future large productions of passive strip detectors and also to produce active strip sensors in commercial CMOS foundries.
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All authors Marta Baselga, Jan-Hendrik Arling, Naomi Davis, Jochen Dingfelder, Ingrid Maria Gregor, Marc Hauser, Fabian Hügging, Karl Jakobs, Michael Karagounis, Roland Koppenhöfer, Kevin Alexander Kroeninger, Fabian Lex, Ulrich Parzefall, Simon Spannagel, Dennis Sperlich, Jens Weingarten, Iveta Zatocilova
Physics and Society · Cross-listed from cs.NI
ln(3): A Universal Percolation Constant for Collective Dynamics on One-Dimensional Proximity Networks
Jian Ji
We report the identification and proof of a universal constant, ln(3) = 1.09861, which governs the onset of bidirectional collective behavior in one-dimensional Poisson proximity networks. The constant - named the cooperative percolation constant and denoted by Lambda_c - is the unique positive solution to 2/(exp(x)-1) = 1 and equals the Shannon
entropy of three equiprobable states. For
agents distributed at intensity lambda and interacting within range L, bidirectional collective behavior is possible if and only if the topological density (lambda * L) >= ln(3). Below this threshold, no cooperative control policy can produce macroscopic coherence, as the proximity graph does not contain a bidirectional spanning cluster in expectation. The result is parameter-free and model-independent: the Poisson distribution is derived from memorylessness
symmetry axioms, making ln(3) a fundamental consequence of spatial
symmetry. The threshold is validated by two independent large-scale empirical
datasets. Analysis of the Chengdu V2X OBU
dataset (N = 19.7 million records) reveals a 1.60x reduction in speed variance at the predicted boundary. Furthermore, the highD German motorway
dataset (N = 163,896 observations) yields a best-fit LWR exponent theta = 1.033 +/- 0.088, placing the theoretical value ln(3) within 0.75 sigma of naturalistic trajectory data (R^2 = 0.8631). The remarkable consistency across geographical and physical scales - from motorway traffic to documented thresholds in 1D biological signal transmission - suggests that ln(3) represents a fundamental topological rent for cooperative information exchange.
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Optics
Separating partially coherent light
Paul-Alexis Mor, Anne R. Kroo, Carson G. Valdez et al. (+9 more)
Recent advances in optical imaging and communication increasingly involve high-dimensional, partially coherent light, creating a growing need for scalable tools to measure and manipulate coherence. Here, we demonstrate the automatic separation of spatially partially coherent light into "coherence modes" – its orthogonal and mutually incoherent components. To make this separation possible, we exploit variational processing in layered self-configuring interferometer architectures in a silicon photonic
circuit. This process formally finds and measures the eigenvectors and
eigenvalues of the coherency
matrix, hence measuring the partially coherent state, while leaving it intact and separated after optimization. Furthermore, we show that mutually incoherent beams, if spatially orthogonal, can be automatically separated even if they are completely overlapped, hence separating unknown
laser beams based only on their mutual incoherence. Our experiment finds and separates the two strongest coherence modes starting from a nine-mode sampling of the partially or fully overlapping fields from two independent
lasers. The method requires a number of physical components that scales linearly with the rank $r$ of the coherency
matrix and operates through a sequence of $r$ in situ gradient-based optimizations enabled by electronic drive frequency multiplexing of interferometer phase shifters. We
benchmark its performance against a mixture-based tomographic method, also implemented on chip. These results establish a scalable framework for programmable coherence analysis and control in imaging, communication, and photonic information processing.
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All authors Paul-Alexis Mor, Anne R. Kroo, Carson G. Valdez, Marko Šimić, Aviv Karnieli, Gabriele Cavicchioli, Zhanghao Sun, Vittorio Grimaldi, Shanhui Fan, Olav Solgaard, David A. B. Miller, Charles Roques-Carmes
Optics
A systematic design approach for one-dimensional and crossed photonic nanobeam cavities for quantum dot integration
Oscar Camacho Ibarra, Jan-Gabriel Hartel, Atzin David Ruiz Perez et al. (+2 more)
We present a systematic workflow for the design of one-dimensional photonic
crystal nanobeam cavities with non-zero cavity lengths. By simultaneously optimizing the
lattice periodicity, air-hole geometry, and cavity length, our approach enables precise control of optical confinement while mitigating radiative losses and linewidth broadening effects. The method is further extended to the design of crossed nanobeam cavities with both matching and mismatched resonance frequencies. This strategy significantly reduces the need for extensive parameter sweeps, providing an efficient route toward optimized cavity designs for integrated
quantum photonic applications. Moreover, the resulting structures are inherently compatible with the integration of single-
photon emitters.
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All authors Oscar Camacho Ibarra, Jan-Gabriel Hartel, Atzin David Ruiz Perez, Sonja Barkhofen, Klaus D. Jöns
Atomic Physics
Vibronic quantum dynamics of ultralong-range high-$\ell$ Rydberg molecules
Felix Giering, Rohan Srikumar and Peter Schmelcher
We investigate the non-adiabatic
quantum dynamics of ultralong-range Rydberg molecules using a vibronically coupled two-channel treatment. The two-channels are composed of coupled trilobite and butterfly electronic states, formed as a result of $S$-wave and $P$-wave scattering of high angular momentum Rydberg electrons with perturbing ground state atoms. Within the Born-Oppenheimer treatment, the $P$-wave scattering channel introduces an adiabatic decay pathway that affects the stability and lifetimes of trilobite states. Our numerical results show that the vibronic coupling is dependent on the principal
quantum number $n$, and for certain $n$ there is non-adiabatic stabilization against internal molecular decay, facilitating previously studied dynamical effects in pure trilobite molecules. Apart from the internal diffraction effect caused by the backscattering of vibrational wavepackets from the trilobite potential, we also observe interesting multi-well tunneling effects during low-energy oscillations for a range of $n$-values. Our work serves to highlight that the unique vibrational coordinate dependent electronic structure of these polar molecules, along with high level densities, promise many exciting dynamical effects.
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Optics
Noise and dynamics in acoustoelectric waveguides
Ryan O. Behunin, Andrew Shepherd, Ruoyu Yuan et al. (+5 more)
We present a
quantum field theoretic formulation of acoustoelectric interactions in waveguide-like systems of arbitrary cross-section. Building on an open
quantum systems approach, we derive a unified description of plasmon-
phonon coupling that incorporates dissipation, noise, and the influence of drift currents. Our analysis captures both bulk and surface plasmon modes, highlighting how drift currents Doppler-shift plasmonic resonances and reshape the
phonon noise spectrum. The resulting Heisenberg-Langevin equations yield closed-form expressions for frequency shifts, gain, and noise power spectra, enabling direct evaluation of performance metrics such as the noise factor in acoustoelectric amplifiers and oscillators. In the appropriate limits, this framework reproduces known results while extending them to complex geometries.
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All authors Ryan O. Behunin, Andrew Shepherd, Ruoyu Yuan, Taylor Ray, Matthew J. Storey, Peter T. Rakich, Nils T. Otterstrom, Matt Eichenfield
Plasma Physics
Investigation of Laser Plasma Instabilities driven by Coupled High-Power Laser Beams in Magnetized Underdense Plasmas
C.L.C. Lacoste, D. Oportus, J. Béard et al. (+10 more)
Stimulated Brillouin and Raman scattering (SBS and SRS) are instabilities that affect the propagation of high-power
lasers in
plasmas. The latter is further affected by Cross-Talk (CT) effects when multiple
laser beams are simultaneously propagated in the
plasma, as found in the schemes proposed for inertial confinement fusion (ICF). Here we develop a new theoretical model that allows us to evaluate the impact of CT on SBS and SRS in low-density
plasmas. As supported by experiments, we demonstrate that CT can lead to a reduction of both SBS and SRS, due to the destabilization of the individually triggered instabilities. We further demonstrate that this destabilization effect is accelerated by applying an externally
magnetic field to the
plasma, which is also beneficial for the hydrodynamics or fuel heating of ICF. By shedding new light on the promising scheme of magnetized ICF, our findings thus offer beneficial prospects for ICF.
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All authors C.L.C. Lacoste, D. Oportus, J. Béard, S.N. Chen, I. Cohen, R. Lelievre, T. Waltenspiel, W. Yao, M. Bardon, F.P. Condamine, P. Antici, J. Fuchs, E. D'Humières
Computational Physics
Introduction to the artificial neural network-based variational Monte Carlo method
William Freitas
The construction of trial wave functions based on neural networks combined with the variational Monte Carlo method is discussed. The mathematical formulation for representing
quantum states as artificial neural networks is introduced. The advantages of employing such trial states and how machine learning works are discussed. It is shown that the variational method is a kind of unsupervised learning
algorithm, where the multiple minima landscape is used as an asset that leads to a stable optimization procedure. The feature representation plays an important role on interpretability and on extracting physical insights from nontrivial trial wave functions. The
algorithm is illustrated for the Yukawa potential and the hydrogen molecule.
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Fluid Dynamics
Wave propagation through periodic arrays of freely floating rectangular floes
Lloyd Dafydd and Richard Porter
The two-dimensional propagation of small-amplitude waves through an infinite periodic array of freely-floating rectangular floes is considered under the assumptions of inviscid linearised wave theory. Fluid gaps between adjacent floes allow a complex interaction of the fluid with heave, surge and pitch motions. In particular, the presence of fluid resonance in the vertical channels between floes has a significant influence on wave propagation around certain critical frequencies. Bloch-Floquet theory is used and encodes the wavenumber for propagating waves into periodic boundary conditions. Solutions of the resulting boundary-value problem posed in a fundamental
cell are formulated in terms of integral equations in which the three rigid body modes of the problem are treated individually. The dispersion relationship between frequency and wavenumber is expressed in terms of the vanishing of a 3 x 3 determinant which encodes the hydrodynamic coupling between the modes. Accurate numerical solutions are determined using Galerkin's method to approximate solutions to the integral equations. A particular focus of the paper is determining simple explicit approximations for the dispersion relation by assuming the gap between adjacent floes is small compared to the submerged draft of the floe. Approximations are shown to compare well to numerical results for a large range of gap sizes and some surprising results emerge for low-frequency wave propagation. This is particularly relevant to the application area that motivates this study: the modelling of wave propagation through broken ice. Supplementary Material: https://github.com/LloydDafydd/pre-prints/blob/caa889f1ee1eb51980785271bd8d27ce5213bda7/wave-propogation-fff-supp-mat.pdf
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Applied Physics
Physics-Informed Deep Neural Network Design of Reactively Loaded Metasurfaces
Malik Almunif, John Le and Anthony Grbic
A tandem deep neural network approach is presented for the inverse design of reactively loaded metasurfaces with prescribed far-field radiation characteristics. The proposed approach integrates a deep neural network (DNN) with a physics-based microwave network forward solver. The DNN maps target far-field patterns to distributions of reactive loads across the metasurface unit
cells. The predicted distribution of reactive loads is evaluated by the forward solver to compute the resulting radiation pattern and guide the learning process through a cosine-similarity loss function. The forward solver enables a fast evaluation of the metasurface's electromagnetic response, significantly reducing the computational cost required for training. The proposed approach is applied to a metasurface with aperture-coupled unit
cells loaded with reactances. Several design examples are presented to demonstrate the accurate synthesis of shaped and steered radiation patterns. Full-wave electromagnetic simulations are performed to validate the accuracy of the designed beamforming metasurfaces.
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Physics and Society
Estimating Absolute Web Crawl Coverage From Longitudinal Set Intersections
Michael Paris, Grigori Paris and Fabian Baumann
Web archives preserve portions of the web, but quantifying their completeness remains challenging. Prior approaches have estimated the coverage of a crawl by either comparing the outcomes of multiple crawlers, or by comparing the results of a single crawl to external ground truth
datasets. We propose a method to estimate the absolute coverage of a crawl using only the archive's own longitudinal data, i.e., the data collected by multiple subsequent crawls. Our key insight is that coverage can be estimated from the empirical URL overlaps between subsequent crawls, which are in turn well described by a simple urn process. The parameters of the urn model can then be inferred from longitudinal crawl data using linear regression. Applied to our focused crawl configuration of the German Academic Web, with 15 semi-annual crawls between 2013-2021, we find a coverage of approximately 46 percent of the crawlable URL space for the stable crawl configuration regime. Our method is extremely simple, requires no external ground truth, and generalizes to any longitudinal focused crawl.
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Accelerator Physics
Pair beams unlock beyond-terawatt attosecond free-electron laser pulses
Çağr{\i} Erciyes, Christoph H. Keitel and Matteo Tamburini
Free-electron
lasers (FELs) generate the brightest coherent X-ray pulses available, enabling atomic-resolution and femtosecond-timescale studies across physics, chemistry, and biology. Realising their full potential at extreme peak powers and attosecond pulse durations critically depends on sustaining coherent gain across the full bunch length. Yet, the quasi-static longitudinal space-charge field in the ultrahigh-current regime imprints a slice-dependent energy detuning that quenches gain growth, so that current schemes typically sustain efficient lasing only across a limited fraction of the bunch. Here we demonstrate that a quasi-neutral electron-positron pair beam cancels this self-field and enables full-bunch high-gain lasing in ultracompressed beams without external compensation. Three-dimensional particle-in-
cell simulations in a single-pass, untapered undulator confirm the mechanism across operating regimes: in the soft X-ray regime, the pair beam reaches $1.85\,\mathrm{TW}$ at $345\,\mathrm{as}$ with enhanced odd-harmonic emission and improved spatial coherence, while the electron-only beam fails to saturate; and a high-harmonic pair-cascade configuration yields ${\sim}10\,\mathrm{TW}$ in isolated ${\sim}3.5\,\mathrm{as}$ spikes with coherent amplification extending to
photon energies of ${\sim}177\,\mathrm{keV}$. These results establish a new operating regime for ultrahigh-power attosecond light sources and open a direct route to coherent gamma-ray emission ($\geq\!100\,\mathrm{keV}$) currently inaccessible to
magnetic-undulator FELs, with broad implications for ultrafast structural, electronic, and
nuclear sciences.
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Optics
High-performance Sources of Multidimensionally Engineered Quantum Light Based on Monolithic Microcavity-metalens Interfaces
Jiantao Ma, Dong Liu, Shunfa Liu et al. (+15 more)
The ultimate non-classic light sources for modern photonic
quantum technology require on-demand generation of indistinguishable
quantum light with high brightness and flexible engineering of
quantum emission in multiple degrees of freedom. In this work, we present monolithic microcavity-metalens interfaces consisting of
quantum-dot-micropillar single-
photon sources and ultra-thin metalenses accurately aligned on opposite sides of an III-V compound
semiconductor chip. The pronounced cavity
quantum electrodynamics effect enabled by the micropillar cavity facilitates single-
photon emission from
quantum dots with simultaneous high degrees of single-
photon purity, source brightness and
photon indistinguishability while the multi-functional metalenses concurrently tailor
quantum emission in multiple physical degrees of freedom including radiation divergence, emission directionality, polarization state and orbital angular momentum (OAM). Furthermore, high-fidelity polarization-OAM
entanglement and single
photons with local
spin topologies are successfully generated in our integrated device. In particular, we demonstrate stable propagations of single-
photon skrymions in atmospheric
turbulence and reveal their topological advantages over the conventional structured
quantum light. Our work advances the research fields of integrated
quantum photonics and meta-optics, providing integrated high-dimensional
quantum light sources for advanced photonic
quantum science and technology.
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All authors Jiantao Ma, Dong Liu, Shunfa Liu, Jiawei Yang, Nilo Mata-Cervera, Bo Chen, Xueshi Li, Guixin Qiu, Kaixuan Chen, Hanqing Liu, Haiqiao Ni, Dunzhao Wei, Zhichuan Niu, Ying Yu, Yijie Shen, Liu Liu, Xuehua Wang, Jin Liu
Applied Physics
Effect of spin disorder on the specific loss power of a nanomagnet
A. Michels and H. Kachkachi
Spin non-collinearities in
magnetic nanostructures arise from a variety of sources, including structural defects, finite-size effects, boundary or surface effects, Dzyaloshinskii-Moriya exchange coupling, and
magnetic vortex formation. While strong forms of
spin disorder generally require a numerical treatment, relatively weak non-collinearities induced by surface anisotropy are amenable to the analytical framework of the effective one-
spin problem (EOSP). In this work, we exploit this framework to present a qualitative, semi-analytical study of the effect of
spin disorder on the specific loss power (SLP) of a single nanomagnet within linear-response theory. Surface-induced
spin misalignment mainly manifests as an additional quartic (cubic-
symmetry) contribution to the anisotropy energy, parametrized by the ratio $\zeta \equiv K_4/K_2$. We derive a semi-analytical expression for the SLP as a function of $\zeta$ by combining the $\zeta$-dependent
equilibrium susceptibility and the relaxation rate obtained within Langer's approach. Our results show that, for systems in the slow-relaxation regime, the SLP is enhanced by
spin misalignment, predominantly through the increase of the relaxation rate caused by the lowering of the effective energy barrier. Retaining the full Debye factor reveals that for moderate reduced barriers $\sigma$, where the system is close to the superparamagnetic regime, the SLP can actually decrease with increasing
spin disorder. The enhancement is asymmetric with respect to the sign of $\zeta$ and depends on the nanomagnet shape (sphere versus cube) through the
geometric prefactors in the EOSP mapping.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG
FuXiWeather2: Learning accurate atmospheric state estimation for operational global weather forecasting
Xiaoze Xu, Xiuyu Sun, Songling Zhu et al. (+5 more)
Numerical weather prediction has long been constrained by the computational bottlenecks inherent in data assimilation and numerical modeling. While machine learning has accelerated
forecasting, existing models largely serve as "emulators of reanalysis products," thereby retaining their systematic biases and operational latencies. Here, we present FuXiWeather2, a unified end-to-end neural framework for assimilation and
forecasting. We align training objectives directly with a combination of real-world observations and reanalysis data, enabling the framework to effectively rectify inherent errors within reanalysis products. To address the distribution shift between NWP-derived background inputs during training and self-generated backgrounds during deployment, we introduce a recursive unrolling training method to enhance the precision and stability of analysis generation. Furthermore, our model is trained on a hybrid
dataset of raw and simulated observations to mitigate the impact of observational distribution inconsistency. FuXiWeather2 generates high-resolution ($0.25^{\circ}$) global analysis fields and 10-day forecasts within minutes. The analysis fields surpass the NCEP-GFS across most variables and demonstrate superior accuracy over both ERA5 and the ECMWF-HRES system in lower-tropospheric and surface variables. These high-quality analysis fields drive deterministic forecasts that exceed the skill of the HRES system in 91% of evaluated metrics. Additionally, its outstanding performance in typhoon track prediction underscores its practical value for rapid response to extreme weather events. The FuXiWeather2 analysis
dataset is available at https://doi.org/10.5281/zenodo.18872728.
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All authors Xiaoze Xu, Xiuyu Sun, Songling Zhu, Xiaohui Zhong, Yuanqing Huang, Zijian Zhu, Jun Liu, Hao Li
Applied Physics · Cross-listed from quant-ph
Error semitransparent universal control of a bosonic logical qubit
Saswata Roy, Owen C. Wetherbee and Valla Fatemi
Bosonic codes offer hardware-efficient approaches to logical
qubit construction and hosted the first demonstration of beyond-break even logical
quantum memory. However, such accomplishments were done for idling information, and realization of fault-tolerant logical operations remains a critical bottleneck for universal
quantum computation in scaled systems. Error-transparent (ET) gates offer an avenue to resolve this issue, but experimental demonstrations have been limited to phase gates. Here, we introduce a framework based on dynamic encoding subspaces that enables simple linear drives to accomplish universal gates that are error semi-transparent (EsT) to oscillator
photon loss. With an EsT logical gate set of {X, H, T}, we observe a five-fold reduction in infidelity conditioned on
photon loss, demonstrate extended active-manipulation lifetimes with
quantum error correction, and construct a composite EsT non-Clifford operation using a sequence of eight gates from the set. Our approach is compatible with methods for detectable ancilla errors, offering an approach to error-mitigated universal control of bosonic logical
qubits with the standard
quantum control toolkit.
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Biological Physics
Mathematical and Computational Modeling of Amoeboid Cell Crawling
Sergio Alonso and Carsten Beta
Amoeboid motion is a dynamic mode of
cell motility essential for processes such as the immune response and wound healing. This review examines recent developments in the mathematical and computational modeling of amoeboid crawling, focusing on the interplay between intracellular biochemical signaling and the physical mechanics of the
cell membrane. We discuss the core components of
cell motility and the integration of chemical and mechanical guidance cues suchg as chemotaxis and curvotaxis. We evaluate a range of modeling frameworks, from simple
stochastic descriptions of center of mass motion to more complicated phase-field, finite-element methods and Potts models that capture complex
cell shape deformations. Finally, we highlight emerging challenges, such as modeling interactions with complex topographies and large-scale multicellular coordination, as important steps toward a better understanding of
cell locomotion.
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Plasma Physics
Drift-reduced fluid modeling of rapidly rotating plasmas
Edward A. Tocco, Benjamin D. Dudson, Ian G. Abel et al. (+1 more)
In this paper, we investigate the effects of rapid rotation (Mach number M ~ 1) on
plasma fluid stability, focusing specifically on Kelvin-Helmholtz (KH) and interchange instabilities - including both
magnetic-
curvature-driven (CDI) and rotation-driven (RDI) interchanges. Building on previous studies of shear flow stabilization, we utilize a drift- reduced fluid approach rather than standard magnetohydrodynamics to capture finite Larmor-radius effects. To achieve this, the drift-reduced equations were modified to include the centrifugal force and implemented in hermes-3 (Dudson et al. 2024), an extension to the BOUT++ (Dudson et al. 2009) framework. Because
plasma rotation both drives the RDI and provides stabilizing shear flow, we find that the global
plasma stability is sensitive to background profile characteristics. We identify three distinct regimes of RDI behavior and establish a simple criterion based on the density and velocity profiles to predict RDI susceptibility. This approach is similar to recent local gyrokinetic studies of shear flow that compared instability growth rates to shearing rates (Ivanov et al. 2025). Finally, by examining cases where the
plasma is both interchange- and KH-unstable, we find that global KH modes make the
plasma less resistant to RDI.
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All authors Edward A. Tocco, Benjamin D. Dudson, Ian G. Abel, Ben Zhu
Computational Physics · Cross-listed from quant-ph
Ab Initio Study of Erbium Point Defects in 4H-SiC for Quantum Devices
Michael Kuban
Identifying scalable materials systems that exhibit
quantum behavior is a central challenge in
quantum information science. Point defects in certain wide-bandgap
semiconductors are promising in this regard due to the maturity of
semiconductor manufacturing and ion implantation technology. Single erbium defect centers in 4H-SiC are examples of such defects that provide access to discrete defect-induced electron energy levels within the bulk material bandgap, which can be utilized for a variety of
quantum technologies, such as single-
photon emission for secure communication and distributed
quantum computing. This work presents a first-principles study of erbium point defects in 4H-SiC using density functional theory. These results provide materials-level support for the development of Er point defects in 4H-SiC as a scalable platform for
quantum devices, helping to bridge the gap between
quantum physics and the practical realization of
quantum networks.
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Space Physics
Automatic Characterization of Mid-latitude Multiple Ionospheric Plasma Structures from All-sky Airglow Images using Deep Learning Technique
Jeevan Upadhyaya, Satarupa Chakrabarti, Rahul Rathi et al. (+5 more)
The F-region ionospheric
plasma structures are propagating high and or low electron density regions in the Earth ionosphere. These
plasma structures can be observed using ground based all-sky airglow imagers which can capture faint airglow emissions originating from the F-region of ionosphere. This study introduces a novel automatic method for determining the propagation parameters (horizontal velocity and orientation) of these multiple ionospheric
plasma structures observed in O(1D) 630.0 nm all-sky airglow images from Hanle, India located in the mid-latitude region. We have used a deep learning-based
segmentation model called YOLOv8 (You Only Look Once) to localize and BoT-SORT tracker to track individual mid-latitude ionospheric
plasma structures. Three different automatic
algorithms are used to characterize the observed
plasma structures utilizing the segmented outputs from the YOLO model. Finally, an additional quality control step is introduced that filters the results from the three automatic
algorithms and generates a flag to retain the most reliable estimate. The results of the proposed fully automated pipeline are systematically compared with a previously developed semi-automatic approach to assess the estimation efficacy. The automatic technique developed in this study is particularly valuable for all-sky airglow imaging systems having large
datasets, where manual intervention or semi-automatic analysis is impractical.
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All authors Jeevan Upadhyaya, Satarupa Chakrabarti, Rahul Rathi, Virendra Yadav, Dipjyoti Patgiri, Gaurav Dixit, M.V. Sunil Krishna, Sumanta Sarkhel
Optics
Phase retrieval technique from regions of unresolvable fringe density using Phase Shifting Interferometry and Liquid Crystal on Silicon (LCOS) Spatial Light Modulator (SLM)
Indrani Bhattacharya
This paper presents a simple method to recover phase information from regions of unresolvable fringe density, specifically, at the camera corners, where interference fringes are not resolved by the camera using Phase Shifting Interferometry and
Liquid Crystal on Silicon (LCOS) Spatial Light Modulator (SLM). The method works well with wavefront compensation. This work is a continuation and advancement of reported research work [14].
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Chemical Physics · Cross-listed from cs.LG
A Kolmogorov-Arnold Surrogate Model for Chemical Equilibria: Application to Solid Solutions
Leonardo Boledi, Dirk Bosbach and Jenna Poonoosamy
The computational cost of geochemical solvers is a challenging matter. For reactive transport simulations, where chemical calculations are performed up to billions of times, it is crucial to reduce the total computational time. Existing publications have explored various machine-learning approaches to determine the most effective data-driven surrogate model. In particular, multilayer perceptrons are widely employed due to their ability to recognize nonlinear relationships. In this work, we focus on the recent Kolmogorov-Arnold networks, where learnable spline-based functions replace classical fixed activation functions. This architecture has achieved higher accuracy with fewer trainable parameters and has become increasingly popular for solving partial differential equations. First, we train a surrogate model based on an existing cement system
benchmark. Then, we move to an application case for the geological disposal of
nuclear waste, i.e., the determination of radionuclide-bearing solids solubilities. To the best of our knowledge, this work is the first to investigate co-precipitation with radionuclide incorporation using data-driven surrogate models, considering increasing levels of thermodynamic complexity from simple mechanical mixtures to non-ideal solid solutions of binary (Ba,Ra)SO$_4$ and ternary (Sr,Ba,Ra)SO$_4$ systems. On the cement
benchmark, we demonstrate that the Kolmogorov-Arnold architecture outperforms multilayer perceptrons in both absolute and relative error metrics, reducing them by 62% and 59%, respectively. On the binary and ternary radium solid solution models, Kolmogorov-Arnold networks maintain median prediction errors near $1\times10^{-3}$. This is the first step toward employing surrogate models to speed up reactive transport simulations and optimize the safety assessment of deep geological waste repositories.
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Atomic Physics
Breakdown of the isotropic asymptotic approximation in two-colour photoionisation
Sooraj Rajendran, Miguel Benito de Lama, Praveen Kumar Maroju et al. (+24 more)
The Wigner delay is defined as the energy derivative of the scattering phase of a particle in a given potential, unveiling the time taken (or gained) due to the interaction. The characterisation of this delay plays a central role in attosecond science, where the time resolution allows to gain information on the time interval required for a photoelectron to be emitted into the continuum after the absorption of a single
photon. Attosecond interferometric techniques, based on two-colour (extreme ultraviolet and near-infrared) photoionisation schemes, cannot provide a direct measurement of the Wigner delay, because the low-frequency
photon contributes with an additional delay, which is imprinted on the outgoing photoelectron. The isolation of the Wigner delay is usually achieved by appealing to the asymptotic approximation, which assumes that the two-
photon delay is separable into a Wigner and a near-infrared-induced phase and provides a universal analytical expression for the latter. In this study, we introduce a self-referencing approach based on the implementation of non-consecutive extreme ultraviolet harmonics, in order to test the validity of the asymptotic approximation. We demonstrate its breakdown by observing a deviation of a few tens of milliradians (corresponding to a few attoseconds) between its predictions and the experimentally measured phases of the sideband oscillations generated in our scheme, in agreement with full-dimensional simulations.
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All authors Sooraj Rajendran, Miguel Benito de Lama, Praveen Kumar Maroju, Michele Di Fraia, Oksana Plekan, David Busto, Ioannis Makos, Marvin Schmoll, Luca Giannessi, Enrico Allaria, Primož Rebernik Ribič, Giovanni De Ninno, Alexander Demidovich, Miltcho Danailov, Marco Zangrando, Kenneth J. Schafer, Richard J. Squibb, Raimund Feifel, Tamás Csizmadia, Fabio Frassetto, Luca Poletto, Kevin C. Prince, Johan Mauritsson, Carlo Callegari, Johannes Feist, Alicia Palacios, Giuseppe Sansone
Data Analysis and Statistics · Cross-listed from cond-mat.dis-nn
Extreme-Value Criticality and Gain Decomposition at the Integer Quantum Hall Transition
Wei-Han Li and Abbas Ali Saberi
Extreme-value fluctuations at
quantum critical points remain poorly understood in the presence of strong correlations and openness. At the integer
quantum Hall transition in the open Chalker–Coddington network, we show that the maximal wave-function amplitude separates into a global gain and an intrinsic extreme component, $|\psi|_{\max}=A\,|\tilde{\psi}|_{\max}$. We introduce extreme-moment scaling for $|\psi|_{\max}$ and observe an approximately
parabolic exponent function $\tau_{\max}(q)$ over moderate $q$, while $\ln|\psi|_{\max}$ displays an almost Gaussian bulk over the studied sizes. The gain factor is close to log-normal and largely controls the raw extremes. Gain normalization reorganizes the statistics: $\tilde{\tau}_{\max}(q)$ changes qualitatively and $|\tilde{\psi}|_{\max}$ does not support a single-parameter generalized extreme-value collapse under standard centering/scaling in the accessible size window. Extreme observables thus provide a robust probe of correlated criticality in open
quantum systems.
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Fluid Dynamics
Numerical study of the sharp stratification limit towards bilayer models
Théo Fradin
In the study of oceanic flows at the geophysical scale, the phenomenon of density stratification plays a central role in the dynamics of the system. Two categories of mathematical models are commonly used to describe the role played by the density stratification: on the one hand, continuously stratified models - such as the stratified Euler equations in a strip, considered in the present article - offer an accurate description of vertical effects, but come with a high level of complexity, both at the theoretical and numerical levels. On the other hand,
bilayer models approximate the stratification by a piecewise constant profile. In the latter case, the main point is to study the
evolution of the free interface between both layers, which leads to a substantially simplified model. In the present article, we compare both approaches in the framework of the linearized stratified Euler equations around density profiles that are close to piecewise constant profiles, and prove the convergence towards the
bilayer Euler equations. However, in the presence of a shear flow,
bilayer models have a range of validity limited by the presence of Kelvin-Helmholtz instabilities. In this case, we use a suitable normal modes decomposition to compute numerically the dispersion relation of this linearized model, and provide numerical evidence that the Kelvin-Helmholtz instabilities limit the applicability of two widely used
bilayer models, namely the
bilayer Euler equations and the
bilayer shallow-water equations.
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