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Friday 15 May

Chemical Physics

Reweighting free energy profiles between universal machine learning interatomic potentials for fast consensus building

Sauradeep Majumdar, Miguel Steiner, Johannes C. B. Dietschreit et al. (+4 more)

Free energy profiles serve as a fundamental bridge between microscopic atomic fluctuations and macroscopic thermodynamic observables. Estimating the free energy profile along a reaction coordinate, referred to as the potential of mean force (PMF), with density functional theory (DFT) accuracy is computationally expensive. Universal machine learning interatomic potentials (MLIPs) drastically reduce this cost, but their accuracy is strongly determined by their training data and hence can be uncertain for a given system. In this work, we present a systematic and scalable framework for reweighting PMFs, initially sampled with a single 'source' MLIP, across a representative suite of target MLIPs. Because traditional direct exponential reweighting fails for large system sizes due to low phase-space overlap between potentials, we deploy robust analytical corrections. Applying this to a complex 601-atom system of Li$^+$ transport in a nanoconfined electrolyte, we demonstrate that a mean energy-gap approximation effectively bypasses statistical collapse, producing a highly stable PMF matching the target PMF. Using this approach, we recover high-fidelity target thermodynamics across multiple DFT reference levels (PBE+D3, PBE-sol, r$^2$SCAN,r$^2$SCAN-D4) at a fraction of the computational cost of full simulations. Furthermore, thermodynamic analysis reveals that the studied MLIPs partition into two distinct clusters driven by their training data. Our reweighting framework successfully recovers target thermodynamic properties–specifically, reaction and activation free energies–even when the phase-space overlap between potentials is critically low. Ultimately, this approach establishes a vital diagnostic protocol to achieve affordable cross-model consensus on materials chemistry properties without redundant, resource-intensive simulations.
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All authors Sauradeep Majumdar, Miguel Steiner, Johannes C. B. Dietschreit, Swagata Roy, Daniel Willimetz, Lukaš Grajciar, Rafael Gómez-Bombarelli

Optics

Parametrically driven pure-quartic solitons

Pengfei Li, Lijing Xing, Dongdong Wang et al. (+3 more)

Parametrically driven solitons are self-trapped modes in various physical settings, including optics, magnetics, etc. So far, the analysis was focused on the existence, stability, and dynamics of such solitons in systems including the second-order group-velocity dispersion (GVD), linear loss, parametric gain, and cubic nonlinearity. Here, we report the existence of quiescent parametrically driven pure-quartic solitons (PDPQSs) in the full system, and moving PDPQSs in the absence of losses. A systematic analysis reveals stability domains for the solitons in the system's parameter space. Evolution of unstable states is explored too, and it is demonstrated that collisions between traveling stable PDPQSs are elastic.
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All authors Pengfei Li, Lijing Xing, Dongdong Wang, Dumitru Mihalache, David Laroze, Boris A. Malomed

Instrumentation and Detectors

A Novel Segment-Based Tracking Algorithm for HLT under High-Occupancy and Complex Conditions

Pengkun Jia, Zhujun Fang, Hang Zhou et al. (+3 more)

In the High-Level Trigger (HLT) of both electron-positron and hadron collision experiments, the tracking process for large-volume gaseous detectors typically consumes a latency of hundreds of milliseconds. Upgrades of existing experiments and the development of next-generation facilities demand enhanced HLT tracking performance: handling higher detector occupancy and suppressing latency. To address high occupancy conditions, a novel HLT tracking algorithm based on track segments is proposed. This method involves constructing a pattern bank comprising 11 pre-defined patterns, optimizing edge-matrix formation using position, momentum, and timing criteria, and merging stereo superlayer segments to improve track consistency. These measures significantly reduce the number of stored segments and the size of the edge matrix, thereby lowering the complexity of global tracking. Even at 25% occupancy, the number of elements for global tracking is reduced to approximately 400-500, while the density of the edge matrix remains below 1%. With the depth-first search within connected components, the simulation results show that the algorithm maintains stable performance with occupancy ranging from 5% to 25%, achieving a data compression ratio of approximately 50% to 70%. Validation against the STCF offline reconstruction algorithm confirms that the HLT algorithm preserves high signal-hit retention without introducing significant adverse effects on offline tracking efficiency or on the reconstruction. These results demonstrate that the proposed algorithm can retain high-quality signal hits across a broad range of occupancy levels, indicating a strong potential for further development and adaptation to even more challenging, high-luminosity experimental conditions.
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All authors Pengkun Jia, Zhujun Fang, Hang Zhou, Yuhe Huang, Changqing Feng, Jianbei Liu

Computational Physics · Cross-listed from math.NA

Method of Fundamental Solutions for Maxwell's Equations in Bi-Periodic Multilayered Media

Jared Weed, Bowei Wu, Jingfang Huang et al. (+1 more)

In this paper, we present an accurate numerical method for the time-harmonic Maxwell's equations for bi-periodic multilayered media with quasi-periodic incident waves using the Method of Fundamental Solutions in conjunction with a periodization scheme. Following an approach used in acoustic scattering problems, the electric and magnetic fields in each layer are expressed as a sum of near and distant interactions. The near interaction comprises interactions between the unit cell and its nearest neighboring copies, while the distant interaction is approximated by proxy source points placed on spheres surrounding the unit cell. Imposing continuity of tangential components at the layer interface, quasi-periodicity conditions on the walls of the unit cell, and Rayleigh-Bloch expansion for the radiation condition yields a system of equations for the unknown coefficients, which can be solved by Schur complement and a backward-stable solver. The scheme is verified with known solutions and exhibits exponential convergence close to $10^{-14}$ for both single and multiple interfaces. An example with 39 interfaces is presented to demonstrate the solver's performance. The paper provides promising results for extending this method to a fast and accurate boundary integral equation solver for many cutting-edge applications involving a large number of layers in electromagnetics and optics.
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All authors Jared Weed, Bowei Wu, Jingfang Huang, Min Hyung Cho

Optics

Diffractive cascades for polychromatic hard X-ray focusing

William Michaels, Simo Pajovic, Joshua Chen et al. (+2 more)

Diffractive focusing of hard X-rays has traditionally required structures with large aspect ratios due to the limited interaction of most materials with X-rays. This has increased the complexity of fabricating diffractive X- ray lenses, restricting their widespread deployment. Here, we utilize topology optimization to design diffractive cascades to focus X-rays. When restricting the structures to a maximum aspect ratio of 8, a diffractive cascade can achieve a focusing efficiency of 40%, far exceeding the 3% efficiency of a zone plate with the same aspect ratio. Diffractive cascades also allow the focusing of beams with energies beyond 20 keV and bandwidths exceeding 1%, loosening the restrictions on other system components. We characterize the robustness of these cascades to alignment, fabrication, and heating perturbations, demonstrating the ability of our designs to operate under real-world conditions. Finally, we exploit the flexibility of our framework to include multiple depths in the objective function. This enables a depth of focus exceeding that of a zone plate or a cascade designed using single-plane optimization. This work demonstrates the utility of topology optimization in the X-ray regime and the possibility of advancing X-ray manipulation across a range of tasks.
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All authors William Michaels, Simo Pajovic, Joshua Chen, Charles Roques-Carmes, Marin Soljačić

Instrumentation and Detectors

Mixing plant for JUNO liquid scintillator: Design, construction, installation and commissioning

Junyu Shao, Wenjie Li, Xilei Sun et al. (+13 more)

The most challenging part of building the Jiangmen Underground Neutrino Observatory (JUNO) is the production of 20 kilotons of ultra pure Liquid Scintillator (LS). This paper presents the design, construction, installation, and commissioning of the LS Mixing Plant, a core facility dedicated to blending the primary organic solvent (LAB) with essential functional solutes (PPO, bis-MSB, and BHT). The main purpose of the Mixing Plant is to prepare and purify the concentrated Master Solution (MS) to achieve a low radioactive contamination background. The amount of radioactive contaminants in the MS are lowered by approximately two orders of magnitude after acid and water extraction, followed by a multi-stage filtration procedure. The purified MS is mixed with LAB and then diluted into the LS for JUNO experiments. Commissioning results of the LS verify that the Mixing Plant achieved its design goal, delivering ultra pure LS that satisfies the stringent radiopurity requirements for neutrino physics.
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All authors Junyu Shao, Wenjie Li, Xilei Sun, Tao Hu, Li Zhou, Yayun Ding, Xiao Cai, Boxiang Yu, Jian Fang, Yuguang Xie, Jie Zhao, Lijun Sun, Wanjin Liu, Hansheng Sun, Mengchao Liu, Xin Ling

Classical Physics

On the Essence of Lagrange's Equations

Peng Shi

From a new perspective, this paper rederives Lagrange's equations. By applying the chain rule of differentiation, the intrinsic relationship between the momentum theorem and the kinetic energy theorem is first established. Subsequently, expressing the differential form of energy conservation in an arbitrary coordinate system and performing suitable differential operations yields Lagrange's equations. Generalized forces and generalized displacements are shown to be component representations of forces and displacements in a chosen coordinate system. Consequently, the essence of Lagrange's equations is identified as the transformation of the kinetic energy theorem into the momentum theorem via the chain rule for composite functions, thereby revealing how energy conservation constructs momentum conservation.
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Plasma Physics

Re-acceleration of Energetic Ions via Small-Scale Reconnection in Magnetic Fusion Plasmas

Cong Zhang, Shaodong Song, Di Luo et al. (+15 more)

We report the first observation on the EXL-50U spherical torus that energetic particles injected by neutral beam injection (NBI) can be stably accelerated to significantly higher energies - reaching up to 2.5 times the injection energy, occurring without significant large-scale magnetohydrodynamic (MHD) bursts. Simulations based on EXL-50U parameters indicate that small-scale magnetic reconnection, mediated by multiple magnetic islands, fails to accelerate bulk thermal ions but efficiently energizes seed fast ions. Unlike global MHD events, such small-scale reconnection is ubiquitous in magnetic confinement devices and does not degrade core confinement. This mechanism offers a novel and potentially universal channel for auxiliary ion heating in future fusion reactors.
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All authors Cong Zhang, Shaodong Song, Di Luo, Kai Huang, Linge Zang, Huibo Tang, Yanchao Li, Yihang Zhao, Ao Wang, Hanqing Wang, Zhenxing Wang, Lei Han, Xuxu Zhang, Jia Li, Dong Guo, Yunfeng Liang, Minsheng Liu, Yuejiang Shi

Thursday 14 May

General Physics

Flat Bundles on Function Manifolds and Evolution Equations in Quantum Field Theories

S. Srednyak

In this paper we discuss extensions of the canonical quantization procedure in quantum field theories. We focus specifically on S-matrix representation as a T-exponent. This extension involves flat bundles on certain infinite dimensional functional manifolds of local time. The motivating problem is first principles treatment of bound states in quantum chromodynamics as well as precision physics of hydrogen atom and the muonium. Our main results include systematic treatment of flat bundles in an infinite dimensional setting, generalization of Hamiltonian evolution and functional renormalization group evolution equations in quantum field theories. We discuss several results from finite dimensional theory that have analogies in the functional setting. This includes construction of moduli space of flat connections and isomonodromic deformations. One of the outcomes of our analysis is a construction of a rich family of functional flat bundles with rational connections. This class of connections exhibits a rich set of mathematical properties. In particular, we construct examples of spaces fundamental groups of which have a definable continuum of generators. Physical states correspond to points in the moduli space of bundles on these spaces. On the physics side of things, we conclude that spacetime notions, such as spaces of particle configurations, emerge effectively as spectral sets of functional differential operators.
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Instrumentation and Detectors

Enhanced Ionization Charge Identification in the Short-Baseline Neutrino Program Neutrino Detectors with Deep Neural Networks

ICARUS Collaboration and SBND Collaboration

We present a deep neural net-based region of interest detection method (DNN ROI) for signal processing in the liquid argon time projection chambers of the Short-Baseline Neutrino (SBN) Program, SBND and ICARUS. DNN ROI addresses limitations of the traditional wire-by-wire thresholding algorithm by leveraging the full two-dimensional detector readout and cross-plane matching information. To account for detector performance variations, we explore training with augmented samples. We find that DNN ROI outperforms the traditional method in both low-level ROI identification performance and high-level reconstruction metrics for high-energy cosmic and accelerator neutrino interaction products, while also being more robust against detector variations, with or without sample augmentation.
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Applied Physics

High-Efficiency InGaP-on-Insulator Microresonator Nonlinear Conversion and Entanglement Generation

Xuefeng Li, Lillian Thiel, Yiming Pang et al. (+9 more)

InGaP-on-insulator (InGaP-OI), with its intrinsically high $\chi^{\left(2\right)}$ optical nonlinearity, has emerged as an efficient and bright integrated photonic platform for frequency conversion and on-chip entanglement generation, but high waveguide propagation loss in the visible wavelength range has limited its overall performance. Here, we identify the dominant loss mechanism through mode-profile analysis and effectively mitigate the loss using a surface treatment method. Statistical analysis of the resonator quality factor and propagation loss reveals the optimal ring radius that maintains a strong nonlinear interaction while suppressing significant bending related loss, resulting in loss as low as 0.49 dB/cm (4.31 dB/cm) at 1560 nm (780 nm). The method provides a 3.5–4$\times$ quality factor enhancement at 780 nm, enabling a second-harmonic generation efficiency of $3.01\times10^{5}$ \,%/W and a degenerate photon-pair generation rate of $4.27\,\textrm{MHz}/\mu\textrm{W}$ and coincidence-to-accidental ratio as high as 10,000. The quasi-phase matching condition is experimentally verified, and nonlinear conversion is systematically characterized across the entire parameter space. This work establishes a scalable pathway for classical and quantum photonics in a low-loss, highly nonlinear, and wafer-scale integration platform.
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All authors Xuefeng Li, Lillian Thiel, Yiming Pang, Amalu Shimamura, Lucas Wang, Joshua Castro, Max Meunier, Nicholas Lewis, John Bowers, Kevin Silverman, Richard Mirin, Galan Moody

Atmospheric and Oceanic Physics · Cross-listed from cs.LG

Njord: A Probabilistic Graph Neural Network for Ensemble Ocean Forecasting

Daniel Holmberg, Joel Oskarsson, Erik Wikingsson et al. (+2 more)

Ocean dynamics are inherently chaotic, yet existing machine learning ocean models produce only deterministic forecasts. We introduce Njord, a probabilistic data-driven model for ocean forecasting, applicable to both global and regional domains. Njord combines a deep latent variable framework with a graph neural network architecture, enabling sampling each forecast step in a single forward pass. We apply Njord globally at 0.25{\deg} resolution and regionally to the Baltic Sea at 2 km resolution. To scale to these large ocean grids we introduce K-means cluster meshes that adapt to irregular sea surface geometry. Experiments demonstrate strong performance on both domains compared to deterministic machine learning baselines, while also providing uncertainty estimates from the sampled ensemble forecasts. On the global OceanBench benchmark, Njord achieves the lowest errors on average across upper-ocean variables when evaluated against real-world observations, with the largest improvements in surface temperature prediction.
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All authors Daniel Holmberg, Joel Oskarsson, Erik Wikingsson, Fredrik Lindsten, Teemu Roos

Fluid Dynamics

On the fundamental solution for viscous internal waves and Brinkman flows. Part 1. Two dimensions

Saikumar Bheemarasetty and Stefan G. Llewellyn Smith

We obtain the viscous and diffusive fundamental solution for monochromatic internal waves in a uniformly stratified medium and for anisotropic Brinkman flow. These solutions take the form of single integrals with logarithmic singularities, and can be computed numerically in an efficient manner for possible use in boundary integral methods. Far-field asymptotic results are obtained, giving solutions valid far from and inside a “beam” corresponding to the internal wave angle in the internal wave case, consistent with Thomas & Stevenson (1972). For Prandtl numbers $\text{Pr} \gtrsim O(1)$, the wave field is given by a superposition of wave- and Stokeslet-like terms. Unlike previous studies, a uniform asymptotic expansion of the wave-field for $\text{Pr} \gtrsim O(1)$ can be computed rigorously. Density diffusion attenuates the wave amplitude as to $(1+\text{Pr}^{-1})^{-2/3}$ and broadens the beam width according to $(1+\text{Pr}^{-1})^{1/3}$. Evanescent waves in a stratified medium and anisotropic Brinkman flows have similar behaviour. Anisotropic Brinkman flow is purely real, dominated by a single circulation cell. As anisotropy increases, the flow becomes increasingly confined to the direction with least resistance. The stratified evanescent wave field has near-vertical cells in its real part, and a dominant single circulation cell in its imaginary part.
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Fluid Dynamics

Assimilation of wall-pressure measurements in direct numerical simulations of high-speed flow over a cone-flare geometry

Pierluigi Morra, Brett Tillman, Stuart Laurence et al. (+1 more)

Ensemble-variational (EnVar) assimilation of wall-pressure measurements in direct numerical simulations of Mach 6 flow over a cone-flare is performed. The experimental data include pressure spectra and intensities from seven wall-mounted PCB sensors positioned upstream, within, and downstream of the separation region induced by the compression corner. Assimilation of the first two sensors only, all upstream of separation, is insufficient to accurately predict the downstream flow. Assimilating all the sensor data is shown to be essential to correctly predict separation onset and the downstream wall-pressure data. Similar to the experiments, the assimilated flow features intense rope-like structures in the attached region. The simulations additionally predict a localized amplification of disturbances beneath the separation shock, where experimental data are not available. This amplification results from the interaction of the boundary-layer instability modes with the compression shock. The simulations also capture the sharp decrease in wall-pressure intensity across separation, and the amplification of low-frequency three-dimensional disturbances within the recirculation bubble. Additionally, the computations highlight the uncertainty in the post-separation predictions due to the low-frequency unsteadiness of the separation shock. Oscillations of the streamwise velocity modulate the boundary-layer thickness, which in turn introduces variability in disturbance amplification.
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All authors Pierluigi Morra, Brett Tillman, Stuart Laurence, Tamer A. Zaki

Fluid Dynamics · Cross-listed from math.OC

Control of the Fluidic Pinball using the Quadratic-Quadratic Regulator

Ali Bouland and Jeff Borggaard

The fluidic pinball presents a significant benchmark for nonlinear flow control, managing the complex interactions of three cylinder wakes. This study addresses the stabilization of the fluidic pinball to its unstable steady-state solution using a model-based nonlinear feedback strategy. We propose a framework that combines interpolatory model order reduction (IMOR) with the quadratic-quadratic regulator (QQR), a feedback control methodology that is specifically suited to the quadratic nonlinearity of the Navier-Stokes equations. A finite element model (FEM) of the problem coupled with IMOR is used to produce a reduced-order model (ROM) that accurately represents the input-output dynamics of the actuated wake. The performance of the QQR control is evaluated against the traditional linear feedback control for two different Reynolds numbers, $Re_D = 30$ and $Re_D = 50$. At $Re_D = 30$, the QQR controller is able to stabilize the wake and reaches the desired performance criteria 40.1% faster than using a linear feedback controller. More significantly, at $Re_D = 50$, the QQR controller successfully stabilizes the wake, whereas the linear controller fails to overcome the nonlinearity of the flow. The QQR control effectively suppresses vortex shedding, resulting in the elimination of lift oscillations and a reduction in the drag coefficient. These results demonstrate that the IMOR-QQR framework provides an effective model-based control strategy that can manage nonlinear hydrodynamic instabilities in such complex wake flows.
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Plasma Physics

Delayed current sheet formation due to an external field in pulsed-power-driven reconnection experiments

T. W. O. Varnish, G. V. Dowhan, M. Chen et al. (+8 more)

We present results from pulsed-power-driven magnetic reconnection experiments, in which we drove two exploding wire arrays in parallel to produce colliding plasma flows with anti-parallel magnetic fields of 1.2$\pm$0.2 T. The experimental volume was surrounded by a Helmholtz coil pair capable of externally applying a field of up to 2 T, parallel to the reconnecting electric field. We diagnosed these experiments using laser interferometric imaging in the direction of the anti-parallel magnetic fields, gated extreme ultraviolet pinhole imaging, and in situ inductive probes. For zero and weak (0.5 T) external fields, we reproduce previous observations in which a dense reconnection layer forms between the two wire arrays. However, when we apply a strong external field (2 T), we observe a void between the arrays rather than a dense layer, and we hypothesise that the external field is frozen out of the plasma and provides a back-pressure which decelerates the flows. Our experimental results are compared with three-dimensional magnetohydrodynamic simulations of the experiment, which qualitatively support this hypothesis. These simulations allow us to study the pressure balance and dynamics of the current sheet aspect ratio, demonstrating the delayed formation of the reconnection layer due to the external field.
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All authors T. W. O. Varnish, G. V. Dowhan, M. Chen, D. M. Johnson, N. M. Jordan, J. Lee, A. P. Shah, R. Shapovalov, B. J. Sporer, R. D. McBride, J. D. Hare

Optics · Cross-listed from quant-ph

Entanglement Dynamics of Separable Squeezed States in Finite Memory Structured Reservoir

Austen Couvertier and Ting Yu

Entanglement in continuous-variable Gaussian systems is a key resource, and common reservoirs can both suppress and generate correlations. Existing work focused on pre-entangled states or Markovian baths, leaving open whether separable squeezed inputs entangle in structured environments or under modulation. We study two bosonic modes coupled to a common reservoir, each initialized in a separable squeezed vacuum. Dynamics are analyzed utilizing Gaussian covariance methods, evolved under approximate Non-Markovian quantum state diffusion (QSD), finite-temperature pseudomode embeddings, and Bures-based non-Markovian diagnostics. We identify three mechanisms absent in Markovian dynamics: (1) A detuning condition that freezes entanglement trajectories across reservoir correlation times; (2) birth, death, and revival of entanglement from orthogonal inputs; and (3) integer-locked beating with square-wave oscillations produced by periodic detuning. All mechanisms persist at finite temperature, with deviations bounded within 5% in cryogenic regimes and 20% at moderate occupations. These deviation bounds align with cryogenic cavity, phononic, and optomechanical platforms, where structured spectral densities and detuning modulation are already accessible. Structured reservoirs are shown to emerge as tunable entanglement resources for continuous-variable quantum technologies.
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Optics

A Differentiable Ray-Wave Framework for Hybrid Refractive-Diffractive System Modeling and Optimization

Jiazhou Cheng, Margaret Gao, Yixuan Shao et al. (+3 more)

Hybrid optical systems combining refractive and diffractive optical responses have the potential to support new types of optical behavior, but they are difficult to model and optimize due to the disparate spatial scales and physics exhibited by ray and wave phenomena. In this work, we present a differentiable ray-wave framework for modeling hybrid refractive-diffractive optical systems that operates as a plug-and-play module within standard ray tracing pipelines. Our model uniquely applies to both planar and curvilinear diffractive surfaces and accommodates arbitrary scalar holographic profiles with high spatial frequency responses, with each simulation evaluated at a single wavelength. We analyze ray-wave modeling regimes that optimally account for the spatial frequency properties and spatial curvature of the diffractive surfaces, and we demonstrate the gradient-based end-to-end optimization of hybrid refractive-diffractive systems featuring planar and conformal diffractive surfaces. We anticipate that these modeling capabilities will enable new classes of hybrid optical systems relevant to computational imaging and display applications.
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All authors Jiazhou Cheng, Margaret Gao, Yixuan Shao, Chenkai Mao, Tom D. Milster, Jonathan A. Fan

Optics

Second-order moment equivalence of twisted Gaussian Schell model beams and orbital angular momentum eigenmodes

T. Ferreira, G. Santos, S. Ayala et al. (+5 more)

We show that the covariance matrix of any cylindrically symmetric coherent orbital angular momentum (OAM) eigenmode with quantum number $\ell$ takes a universal form depending only on $\langle r^2\rangle$, $\langle k_r^2\rangle$, and $\ell$, independently of the radial profile, and that this form is identical to the covariance matrix of a twisted Gaussian Schell-model (TGSM) beam.} More specifically, both matrices share the same pattern of zero and nonzero entries, with the off-diagonal blocks proportional to $\ell$ and the TGSM twist parameter $u$, respectively. This result holds for an arbitrary radial profile and provides direct term-by-term identification of parameters between the two sets of beams. We work out the correspondence in detail for three important families: Laguerre–Gaussian (LG), Bessel–Gaussian, and perfect vortex beams (PVBs), and derive the conditions under which each coherent OAM mode maps onto a physically realizable TGSM beam. {Because the covariance matrix governs second-moment evolution under arbitrary ABCD (symplectic) transformations, any two beams sharing the same covariance matrix are second-order indistinguishable at every propagation plane. In particular, the matched TGSM and coherent OAM beams share identical beam-width evolution, far-field divergence, and $M^2$ beam-quality factor.} In particular, the well-developed TGSM propagation toolbox applies directly to the second-order moment evolution of the three coherent families. We further show that within each beam family the covariance matrix uniquely determines the beam parameters, with exact uniqueness established for LG modes. Additional results include cross-family second-moment equivalence conditions and a proof that PVB modes form a complete orthonormal basis in the limit $w\to 0$.
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All authors T. Ferreira, G. Santos, S. Ayala, Lucas Hutter, E. S. Gómez, G. Lima, G. Cañas, S. P. Walborn

Computational Physics · Cross-listed from cs.LG

Breakeven complexity: A new perspective on neural partial differential equation solvers

Yijing Zhang, Nicholas Roberts, Tanya Marwah et al. (+1 more)

Neural surrogate solvers of partial differential equations (PDEs) promise dramatic speedups over numerical methods, especially in scenarios requiring many solves. However, current accuracy-based evaluations do not fully consider two central issues: (1) neural solvers incur substantial up-front costs for data generation, training, and tuning; and (2) classical solvers can also generate low-fidelity solutions at a sufficiently low simulation cost. To explicitly account for these realities and fully incorporate end-to-end costs, we propose an evaluation framework centered on breakeven complexity, a metric that counts the forward solves before a learned solver is cost-effective relative to an error-equivalent traditional solver. To evaluate this measure, we apply scaling laws to determine how much training budget to allocate to data generation and discuss how to achieve smooth error-matching in diverse settings. We evaluate the breakeven complexity of multiple neural PDE solvers on three PDEs on 2D periodic domains from APEBench and a novel benchmark of flows past multiple obstacles generated by the GPU-native PyFR code. Among other findings, our results suggest that neural PDE solvers become more effective as problems get harder in terms of cost, dimension, rollout, physics regime (e.g. higher Reynolds number), etc.
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All authors Yijing Zhang, Nicholas Roberts, Tanya Marwah, Mikhail Khodak

Optics

Frequency-domain Event-based Imaging for Selective Surveillance

Megan Birch, James Rick, Adrish Kar et al. (+2 more)

Event-based cameras (EBCs) are an attractive sensing modality for surveillance due to their reporting of pixel-level radiance changes with microsecond resolution and high dynamic range, enabling motion extraction while suppressing background. Their asynchronous, sparse output, however, necessitate algorithms that identify targets in event-space without processing full frames. We introduce Frequency Rate Information for Event Space (FRIES), a neuromorphic processing framework that detects periodicity in events, such as rotor rotation and mechanical vibrations, to discriminate and monitor man-made objects. FRIES first applies a time gate to suppress background and noise, then aggregates events into a pixel-wise activity (e.g., density) map and clusters pixels into regions-of-interest (ROIs). A localized spectral analysis is applied to each ROI to extract dominant frequencies used to distinguish structured object signatures from unstructured background and noise. Discriminated targets are visualized using a Resonant Time Surface (RTS), a frequency-selective method that weights events by their phase coherence with the extracted frequencies, rewarding in-sync content and suppressing out-of-sync clutter. We demonstrate FRIES and RTS in a controlled indoor experiment to recover the rotational frequency of a mechanical chopper and drone rotors against a moving background. We further test these methods on an outdoor data to detect a hovering drone against a realistic treeline. These preliminary results establish frequency-domain event processing as a promising front-end for selective surveillance in neuromorphic pipelines and a complementary surveillance modality, leveraging the high temporal resolution to enable spectral discrimination.
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All authors Megan Birch, James Rick, Adrish Kar, Jason Zutty, Joseph L. Greene

Applied Physics · Cross-listed from cond-mat.mes-hall

Radio-frequency reflectometry in silicon carbide large-area transistors

Alexander Zotov, Conor McGeough, Megan Powell et al. (+1 more)

Radio-frequency (RF) reflectometry is widely used for high-bandwidth readout of semiconductor quantum devices at cryogenic temperatures, but its application has mainly been limited to nanoscale structures with relatively small capacitances. Here, we investigate RF readout in a different regime by applying gate-based reflectometry to a large-area silicon carbide transistor with parasitic capacitances orders of magnitude larger than those of typical quantum devices, conditions normally expected to hinder RF readout. We observe a gate-dependent RF response which degrades and eventually vanishes as temperature is lowered, although MOSFET operation in DC transport is maintained down to deep cryogenic temperatures. We attribute this behaviour to impedance changes introduced by carrier freeze-out in the transistor drift region, and propose a modified circuit configuration designed to restore sensitivity under these conditions. These results establish how parasitic pathways and device geometry can limit RF readout, providing insight into the design of scalable cryogenic-CMOS quantum systems.
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All authors Alexander Zotov, Conor McGeough, Megan Powell, Alessandro Rossi

Optics · Cross-listed from quant-ph

Single Spatio-Temporal Mode Bright Twin-Beam Source Across the Near- and Mid-Infrared

Gabriel Demontigny, Patrick Cusson, Amauri Perraton Elorza et al. (+6 more)

We introduce an ultrafast, bright, entangled twin-beam source generated by type-0 parametric down-conversion in periodically-poled lithium niobate at MHz repetition rate, with continuously tunable Schmidt number $K$ set by the pump pulse duration. Photon-number statistics characterization via $g^{(2)}(0)$ and singular-value decomposition of the signal spectral density matrix yield $K\simeq1.05$ and $K\simeq1.03$, respectively, maintained over multiple orders of magnitude in brightness. Group-delay dispersion of the pump drives a continuous transition from single-mode operation to a controlled multimode regime, consistent with the temporal gain window departing from the inverse phase-matching bandwidth. Strong non-degeneracy of the source (signal at 1.37 um, idler at 4.0 um, $\sim 100$ fs duration) decouples a mid-infrared interaction wavelength, which overlaps with molecular vibrational resonances, from a near-infrared detection band, establishing a practical platform for quantum-enhanced metrology, nonlinear interferometry, and mid-infrared spectroscopic sensing. We show that in the bright few-mode limit, the total entanglement resource is clearly separated between modal and occupational degrees of freedom, and that our source allocates up to 95-97% of that resource to the occupational sector.
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All authors Gabriel Demontigny, Patrick Cusson, Amauri Perraton Elorza, Esteban Murillo Zapata, Eli Martel, Andrei Rasputnyi, Maria Chekhova, Stéphane Virally, Denis Seletskiy

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

Chemical Origins of Non-Bonded Interactions Within and Between Solids

Paul J. Robinson, Adam Rettig, Hieu Q. Dinh et al. (+2 more)

Non-bonded interactions govern structure, stability, and function across a wide range of solid-state materials, yet their chemical origins are often difficult to resolve from total energies alone. Here we generalize absolutely localized molecular orbital energy decomposition analysis to quantify and interpret non-bonded interactions within and between solids at the density functional theory level. Across molecular crystals, moiré heterobilayers, and layered perovskite heterostructures, this framework separates lattice-formation energies, interlayer binding energies, and band-structure changes into chemically intuitive contributions from frozen interactions, polarization, and charge transfer. The analysis reveals how dispersion controls polymorph stability in pharmaceutical crystals, how local stacking modulates interlayer coupling in MoS2/WSe2, and how alkali-cation substitution switches the quantum-well character of layered perovskite heterostructures. By connecting emergent solid-state properties to microscopic interaction mechanisms, this framework provides a chemically transparent basis for understanding and designing complex materials.
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All authors Paul J. Robinson, Adam Rettig, Hieu Q. Dinh, Anton Z. Ni, Joonho Lee

Fluid Dynamics · Cross-listed from eess.SY

A Variational Lagrangian Framework for Log-Homotopy Particle Flow Filters

Olivér Törő, Domonkos Csuzdi and Tamás Bécsi

The log-homotopy particle flow filter resolves the Bayesian update by transporting particles along a continuous trajectory in pseudo-time. However, the governing partial differential equation for the flow velocity is fundamentally underdetermined, admitting an infinite family of valid solutions. In this work, we regard the particle flow as the motion of a pressureless inviscid fluid. We define a Lagrangian action based on the kinetic energy of the system, subject to the constraints imposed by the continuity equation and the log-homotopy evolution. By applying the principle of least action, we obtain the Euler–Lagrange equations for the optimal flow, which yields an irrotational potential flow structure. We show that this variational framework yields a coupled Hamilton–Jacobi equation structurally isomorphic to Madelung's hydrodynamic formulation of quantum mechanics. In this analogy, the log-homotopy constraint acts as a generalized quantum potential that generates the force required to guide the probability fluid along the exact Bayesian update path. Finally, we derive the material acceleration of the flow, shifting the formulation from a kinematic to a dynamical description. This perspective could enable the application of higher-order symplectic integrators for improved numerical stability and provide a physics-based metric for adaptive stiffness detection in high-dimensional filtering.
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Computational Physics · Cross-listed from quant-ph

Measurement-Efficient Variational Quantum Linear Solver for Carleman-Linearized Nonlinear Dynamics

Yunya Liu and Pai Wang

We present hybrid quantum-classical pipelines for solving the Duffing equation that leverage Carleman linearization and the Variational Quantum Linear Solver (VQLS). First, we demonstrate that Carleman linearization accurately approximates the weakly nonlinear Duffing equation, with errors diminishing as the truncation order increases. Next, across IBM and Xanadu platforms, we deploy VQLS with symmetry-grouped Hadamard Test evaluations under both global and local cost formulations, compare distinct Hermitianization within a common cost framework, and benchmark hardware-efficient ansatz architectures under a fixed Hermitianization. Across block-banded test cases, each method achieves near-unity fidelity and vanishing relative residuals. These results show that topology-agnostic ansatz, optimized Hermitianization, and efficient cost formulation enable VQLS to recover quantum states proportional to classical solutions for Carleman-structured systems, providing a portable recipe for quantum-in-the-loop simulation of nonlinear dynamics.
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Instrumentation and Detectors

Status of Barrel Imaging Calorimeter in Korea for the Electron-Ion Collider

Jeongsu Bok

The Electron-Ion Collider (EIC) is a next-generation particle accelerator facility designed to probe the fundamental structure of matter such as the origins of nucleon mass, spin, and the dynamic behavior of quarks and gluons within nucleon and nucleus. As the electromagnetic calorimeter in the barrel region, the Barrel Imaging Calorimeter (BIC) is tasked with precise energy measurements of electrons and photons as well as efficient separation of these particles from background pions. The BIC integrates Pb/SciFi sampling layers and AstroPix silicon pixel sensors for three-dimensional shower imaging. The Korean group has actively contributed through silicon chip testing, module assembly, prototype development, beam test, readout system design, and detailed simulations. This presentation highlights the recent progress and plans for the R&D of the Barrel Imaging Calorimeter in Korea.
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Applied Physics

Motional-Current-Sensing Method and Simplified Closed-Loop Control Strategy for Piezoelectric-Resonator-based DC-DC Converters

Zhiyang Cao, Linbo Shao and Liyan Zhu

Piezoelectric resonators (PRs) have been seen as a competitive alternative to magnetic components. In PR-based converters, the motional current (in the LC series branch of the equivalent circuit) is vital for control proposes but cannot be measured directly. The difficulties to detect the zero-crossing points or to measure the amplitude of the motional current has been one of the most dominating obstacles that complicates the control strategies and limits the frequency range of the PR-based converters. This work discusses a ring-dot shaped piezoelectric transformer (PT) based motional current sensing method that provides current information with low-delay, low-loss and intrinsic isolation. It is physically proven that the proposed method is robust with various non-ideal factors of the piezoceramic and circuit implementation. Based on this, an event-driven control strategy is introduced, consisting of only a finite state machine, a PI loop, a low-speed ADC and several comparators. Experiments on a step-down PR-based converter verify that the proposed approach realize ZVS for all transitions within a switching cycle with reduced hardware and software resources, enhances stability and is capable of self-startup.
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Computational Physics · Cross-listed from cs.LG

Eradicating Negative Transfer in Multi-Physics Foundation Models via Sparse Mixture-of-Experts Routing

Ellwil Sharma and Arastu Sharma

Scaling Scientific Machine Learning (SciML) toward universal foundation models is bottlenecked by negative transfer: the simultaneous co-training of disparate partial differential equation (PDE) regimes can induce gradient conflict, unstable optimization, and plasticity loss in dense neural operators. In particular, broadband open-channel fluid dynamics and boundary-dominated porous media flows impose incompatible spectral and geometric demands on a single dense parameter path. We introduce Shodh-MoE, a sparse-activated latent transformer architecture for multi-physics transport. Shodh-MoE operates on compressed 16^3 physical latents produced by a physics-informed autoencoder with an intra-tokenizer Helmholtz-style velocity parameterization, restricting decoded states to divergence-free velocity manifolds. The model guarantees exact mass conservation, achieving a physically verifiable velocity divergence of ~2.8 x 10^-10 (evaluated post-hoc in FP64) on 128^3 grids. A Top-1 soft-semantic router dynamically assigns localized latent patches to expert subnetworks, enabling specialized parameter paths for distinct physical mechanisms while preserving shared experts for universal symmetries. In a 20,000-step distributed pretraining run over mixed three-dimensional physical tensors, routing telemetry shows autonomous domain bifurcation: held-out validation tokens from the open-channel domain route exclusively to Expert 0, while porous-media tokens route exclusively to Expert 1. The model converges simultaneously across both regimes, achieving latent validation MSEs of 2.46 x 10^-5 and 9.76 x 10^-6, and decoded physical MSEs of 2.48 x 10^-6 and 1.76 x 10^-6. These results support sparse expert routing as a practical architectural mechanism for mitigating multi-physics interference in universal neural operators.
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Plasma Physics

Axion magnetohydrodynamics and reconnection-driven axion bursts

H. Terças

We formulate axion magnetohydrodynamics beyond the ideal limit, retaining axion inertia and the essential physics of non-ideal plasmas from first principles. In this framework, regions where magnetic flux freezing breaks down acquire a new physical role: whenever $\mathbf{E} \cdot\ \mathbf{B} \neq 0$, magnetic dissipation acts as a localized source of axion radiation. We show that magnetic reconnection naturally excites mixed Alfvén-axion modes, enabling coherent energy exchange between magnetic fields and axions in magnetically dominated environments. In neutron stars and magnetars, this mechanism leads generically to transient axion bursts powered by reconnection–driven Alfvénic dissipation. We connect this production process to observational prospects and derive a characteristic sensitivity to the axion–photon coupling, complementary to searches based on static magnetic fields.
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