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Physics Physics

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Saturday 21 March

Chemical Physics

Resolving Discrepancies in Disjoining Pressure Predictions for Liquid Nanofilms from Molecular Simulations

Yafan Yang, Zufeng Zuo, Jingyu Wan et al. (+2 more)

Literature values of disjoining pressure in liquid nanofilms from different molecular simulation methods show significant discrepancies. We demonstrate that these arise from neglecting long-range dispersion interactions and inconsistent definitions of film thickness in the original Peng method. A key insight is that long-range dispersion affects surface tension in a thickness-dependent manner, increasing it at large thickness but suppressing its enhancement at small thickness due to disjoining-pressure-induced normal compression and lateral expansion. This leads to crossover behavior in the surface tension of water nanofilms. Since disjoining pressure is obtained from the derivative of surface tension with respect to thickness, this nontrivial dependence strongly impacts its accuracy. With proper treatment of dispersion interactions and a consistent thickness definition, the revised Peng method agrees with the Bhatt method and yields more accurate Hamaker constants.
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All authors Yafan Yang, Zufeng Zuo, Jingyu Wan, Shuyu Sun, Denvid Lau

Optics

A spectral phase modulation transfer function for dispersive four-wave mixing

Linshan Sun and Sergio Carbajo

Indirect control of ultraviolet (UV) pulse phase through nonlinear frequency conversion is attractive when direct UV pulse shaping is limited by material loss, dispersion, and damage threshold. Here we cast dispersive four-wave mixing (DFWM) as a pump-conditioned spectral kernel and show that, in a locally one-to-one mapping regime, the signal-to-idler conversion admits a practical transfer function description. Starting from the exact frequency domain expression, we rewrite the idler field as a linear operator acting on the conjugated signal spectrum, with a two-frequency kernel set by the pump self-convolution and phase matching. Linearization around a reference operating point then yields a spectral phase-response kernel for small input perturbations. By probing this response with sinusoidal spectral-phase modulation of different spatial frequencies, we define a spectral phase-modulation transfer function (SPMTF), an MTF-like measure of the phase-transfer bandwidth of the nonlinear interaction. Simulations with different pump group-delay dispersion (GDD) values produce distinct SPMTF curves, showing that pump chirp directly controls how much fine spectral-phase structure survives the conversion. This framework provides a simple way to compare operating conditions and identify regimes favorable for programmable NIR-to-UV phase transfer.
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Optics

Resonant tunneling diode-integrated terahertz transceiver module for wireless communications

Weijie Gao, Nguyen H. Ngo, Daiki Ichikawa et al. (+10 more)

Terahertz bands enable ultra-broadband wireless communications but require compact, low-cost, and efficient transceiver modules. Conventional implementations based on metallic waveguides or silicon lenses suffer from high loss, bulkiness, and fabrication complexity. Here, we present a compact terahertz transceiver module enabled by a resonant tunneling diode (RTD) integrated with a photonic-electronic antenna chain. The RTD on InP is coupled to a modified Vivaldi antenna and an all-silicon effective-medium-clad waveguide, terminating in a rod antenna interfaced with a 3D-printed cyclic olefin copolymer lens. This architecture enables broadband directive radiation without matching networks or anti-reflection coatings. Packaged in a low-cost 3D-printed PLA enclosure, the module achieves realized gains of 28-33 dBi (E11x) and 30-33 dBi (E11y) across 220-330 GHz. As a receiver, it exhibits a noise voltage density of 5.6 x 10^-9 V/sqrt(Hz), a minimum noise equivalent power of 1.8 pW/sqrt(Hz), and an average responsivity of 6.8 kV/W. It supports error-free transmission up to 30 Gbit/s (OOK) and 80 Gbit/s (16-QAM) over 10 cm, and enables real-time uncompressed high-definition video streaming over 1 m. As a transmitter, it achieves error-free OOK transmission up to 12 Gbit/s at 332 GHz. These results demonstrate a promising terahertz transceiver architecture for 6G systems.
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All authors Weijie Gao, Nguyen H. Ngo, Daiki Ichikawa, Mingxiang Li, Yuta Inose, Yuki Morita, Hidemasa Yamane, Yoshiharu Yamada, Shuichi Murakami, Yosuke Nishida, Tadao Nagatsuma, Withawat Withayachumnankul, Masayuki Fujita

Computational Physics · Cross-listed from math.NA

On Optimal Convergence Rates for the Nonlinear Schrödinger Equation with a Wave Operator via Localized Orthogonal Decomposition

Hanzhang Hu, Zetao Ma and Lei Zhang

In this paper, we develop a Localized Orthogonal Decomposition (LOD) method for the two-dimensional time-dependent nonlinear Schrödinger equation with a wave operator. We prove that our method preserves conservation laws and admits a unique numerical solution; furthermore, we obtain unconditional (i.e., time-step restriction-free) optimal-order superconvergent \(L^p\) error estimates. To complement the theoretical analysis, we present a series of numerical simulations that verify the analytical results and further illustrate structural aspects of the problem.
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Applied Physics · Cross-listed from eess.SP

Sparse stability diagrams of LSCF method via strategic pole destabilization using orthogonal matching pursuit

Shogo Shimada and Akira Saito

In various engineering fields including mechanical, aerospace, and civil engineering, the identification of modal parameters, including natural frequencies, damping ratios, and mode shapes, is crucial for determining the vibration characteristics of engineered structures. A common method for identifying the modal parameters of structures involves experimental modal analysis using frequency response functions (FRFs) obtained from forced vibration tests. The least squares complex frequency (LSCF) domain method is a widely-used frequency-domain curve-fitting method for the FRFs using the polynomials of high order, which can extract modal parameters with high accuracy. However, increasing the polynomial order tends to result in the generation of non-physical spurious poles that need to be eliminated from the stability diagrams. To overcome this issue, we propose a method that strategically destabilize the stable yet spurious poles of the characteristic polynomials by making their coefficients as sparse as possible, via orthogonal matching pursuit (OMP). This results in sparse stability diagrams because unstable poles can be eliminated from the diagrams. In this paper, the proposed method is first applied to a numerically-obtained FRFs of a rectangular plate using finite element model, and its validity is discussed. Then, the method is applied to experimentally-obtained FRFs of rectangular plates with low-damping and with high-damping. Furthermore, to confirm its applicability to industrial applications with realistic complexity, it has also been applied to the FRFs of the electric machine's stator core used for electric vehicles. Based on the results, we have confirmed that the spurious roots can be eliminated from the stability diagrams without compromising accuracy for the cases considered.
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Applied Physics · Cross-listed from cond-mat.str-el

Intrinsic Topological Weyl Phase Transition Induced by a Magnetostructural Transformation in a Kagome Magnet

Tsung-Han Yang, Satoshi Okamoto, D. Alan Tennant et al. (+2 more)

Topological phase transitions provide a unique window into the interplay between structure, magnetism, and Weyl physics in magnetic Weyl semimetals. However, realizing an intrinsic Weyl phase transition between two distinct Weyl states near room temperature remains challenging. Here, we demonstrate that a magnetostructural transition effectively induces such a transition in the kagome magnet Mn$_3$Ga. High-resolution neutron diffraction, magnetization characterizations and first-principles calculations reveal that Mn$_3$Ga undergoes a chiral antiferromagnetic transition below 485 K, followed by a magnetostructural transition to a monoclinic structure with highly canted antiferromagnetic order near room temperature. These cooperative changes in lattice and magnetic symmetries reorganize Weyl nodes, driving a transition from a primary type-II Weyl state to a distinct Weyl state, accompanied by dramatic variations in the anomalous Hall effect and appearance of topological Hall effect. Our findings open a new pathway for discovering novel topological Weyl states and potential spintronic applications.
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All authors Tsung-Han Yang, Satoshi Okamoto, D. Alan Tennant, Michael A. McGuire, Qiang Zhang

Applied Physics · Cross-listed from cs.SC

Graph-based data-driven discovery of interpretable laws governing corona-induced noise and radio interference for high-voltage transmission lines

Hao Xu, Yuntian Chen, Chongqing Kang et al. (+1 more)

The global shift towards renewable energy necessitates the development of ultrahigh-voltage (UHV) AC transmission to bridge the gap between remote energy sources and urban demand. While UHV grids offer superior capacity and efficiency, their implementation is often hindered by corona-induced audible noise (AN) and radio interference (RI). Since these emissions must meet strict environmental compliance standards, accurate prediction is vital for the large-scale deployment of UHV infrastructure. Existing engineering practices often rely on empirical laws, in which fixed log-linear structures limit accuracy and extrapolation. Herein, we present a monotonicity-constrained graph symbolic discovery framework, Mono-GraphMD, which uncovers compact, interpretable laws for corona-induced AN and RI. The framework provides mechanistic insight into how nonlinear interactions among the surface gradient, bundle number and diameter govern high-field emissions and enables accurate predictions for both corona-cage data and multicountry real UHV lines with up to 16-bundle conductors. Unlike black-box models, the discovered closed-form laws are highly portable and interpretable, allowing for rapid predictions when applied to various scenarios, thereby facilitating the engineering design process.
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All authors Hao Xu, Yuntian Chen, Chongqing Kang, Dongxiao Zhang

Physics and Society

Conflict Avoidance in Pedestrian Merging in Controlled Experiments by Variance Indicator

Jiawei Zhang, Xiaolu Jia, Sakurako Tanida et al. (+3 more)

Pedestrian congestion at corridor intersections often originates from localized fluctuations in motion rather than from a macroscopic collapse of flow. Understanding pedestrian instability at corridor intersections remains challenging because existing studies mainly rely on density, average speed, or flow-based measures and limited datasets, making it difficult to separate geometric turning effects from interaction induced fluctuations in merging flows. In particular, the mechanism underlying the turning angle dependence in T junctions has not been resolved. Here, we analyze more than 300 controlled experiments conducted in L corridors with turning only and T corridors with turning and merging. Using Voronoi-based speed variance $V_s$ and velocity variance $V_v$, we systematically compare geometric and interaction effects. $V_s$ effectively captures interaction driven instability, while $V_v$ reflects directional adjustments due to geometry. The comparison reveals distinct fluctuation mechanisms and identifies a critical transition near $90{\deg}$, demonstrating the advantage of variance-based indicators for diagnosing pedestrian dynamics.
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All authors Jiawei Zhang, Xiaolu Jia, Sakurako Tanida, Claudio Feliciani, Daichi Yanagisawa, Katsuhiro Nishinari

Fluid Dynamics

Effects of fluid rheology and geometric disorder on the enhanced resistance of viscoelastic flows through porous media

Simon J Haward and Amy Q Shen

Recent works reveal the importance of chaotic flow fluctuations as a mechanism for the enhanced resistance observed in viscoelastic porous media flows, and also show how chaotic fluctuations are affected by the structural disorder of porous media. We seek further insight by performing pressure drop measurements and flow velocimetry on two viscoelastic fluids of contrasting rheology (one with constant viscosity, another strongly shear thinning) in flow through microfluidic post arrays. Ordered hexagonal arrays have posts either “staggered” or “aligned” along the mean flow direction and disorder is applied to each configuration by randomly displacing each post about its initial location. Both polymer solutions show the expected increase in flow resistance for Weissenberg numbers, Wi > 1. In both cases, the flow resistance enhancement increases with the geometric disorder in aligned arrays, but is independent of disorder in staggered arrays. At sufficient randomisation, aligned and staggered arrays become indistinguishable. Flow velocimetry performed over a range of Wi reveals no sign of chaotic fluctuations for the constant viscosity fluid. In this case, the observation of elastic wakes between the stagnation points of the posts evokes the coil-stretch transition and implicates the extensional viscosity as the cause of the enhanced flow resistance. For the shear thinning fluid chaotic fluctuations are observed for Wi > 1, which broadly correlate with the flow resistance in this case. We also show that the first normal stress is insufficient to account for the flow resistance observed for the constant viscosity fluid, but may account for the resistance observed in the shear thinning case. Our results suggest that the dominant mechanism for resistance enhancement in viscoelastic porous media flow may emerge depending on the specific combination of fluid rheology and geometric complexity.
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Space Physics · Cross-listed from cs.RO

Unified Orbit-Attitude Estimation and Sensor Tasking Framework for Autonomous Cislunar Space Domain Awareness Using Multiplicative Unscented Kalman Filter

Smriti Nandan Paul and Siwei Fan

The cislunar regime departs from near-Earth orbital behavior through strongly non-linear, non-Keplerian dynamics, which adversely affect the accuracy of uncertainty propagation and state estimation. Additional challenges arise from long-range observation requirements, restrictive sensor-target geometry and illumination conditions, the need to monitor an expansive cislunar volume, and the large design space associated with space/ground-based sensor placement. In response to these challenges, this work introduces an advanced framework for cislunar space domain awareness (SDA) encompassing two key tasks: (1) observer architecture optimization based on a realistic cost formulation that captures key performance trade-offs, solved using the Tree of Parzen Estimators algorithm, and (2) leveraging the resulting observer architecture, a mutual information-driven sensor tasking optimization is performed at discrete tasking intervals, while orbital and attitude state estimation is carried out at a finer temporal resolution between successive tasking updates using an error-state multiplicative unscented Kalman filter. Numerical simulations demonstrate that our approach in Task 1 yields observer architectures that achieve significantly lower values of the proposed cost function than baseline random-search solutions, while using fewer sensors. Task 2 results show that translational state estimation remains satisfactory over a wide range of target-to-observer count ratios, whereas attitude estimation is significantly more sensitive to target-to-observer ratios and tasking intervals, with increased rotational-state divergence observed for high target counts and infrequent tasking updates. These results highlight important trade-offs between sensing resources, tasking cadence, and achievable state estimation performance that influence the scalability of autonomous cislunar SDA.
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Space Physics · Cross-listed from cs.RO

Current state of the multi-agent multi-view experimental and digital twin rendezvous (MMEDR-Autonomous) framework

Logan Banker, Michael Wozniak, Mohanad Alameer et al. (+6 more)

As near-Earth resident space objects proliferate, there is an increasing demand for reliable technologies in applications of on-orbit servicing, debris removal, and orbit modification. Rendezvous and docking are critical mission phases for such applications and can benefit from greater autonomy to reduce operational complexity and human workload. Machine learning-based methods can be integrated within the guidance, navigation, and control (GNC) architecture to design a robust rendezvous and docking framework. In this work, the Multi-Agent Multi-View Experimental and Digital Twin Rendezvous (MMEDR-Autonomous) is introduced as a unified framework comprising a learning-based optical navigation network, a reinforcement learning-based guidance approach under ongoing development, and a hardware-in-the-loop testbed. Navigation employs a lightweight monocular pose estimation network with multi-scale feature fusion, trained on realistic image augmentations to mitigate domain shift. The guidance component is examined with emphasis on learning stability, reward design, and systematic hyperparameter tuning under mission-relevant constraints. Prior Control Barrier Function results for Clohessy-Wiltshire dynamics are reviewed as a basis for enforcing safety and operational constraints and for guiding future nonlinear controller design within the MMEDR-Autonomous framework. The MMEDR-Autonomous framework is currently progressing toward integrated experimental validation in multi-agent rendezvous scenarios.
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All authors Logan Banker, Michael Wozniak, Mohanad Alameer, Smriti Nandan Paul, David Meisinger, Grant Baer, Trevor Hunting, Ryan Dunham, Jay Kamdar

Optics

An Optically Addressable Transmissive Liquid Crystal Metasurface Spatial Light Modulator

Jared Sisler, Claudio U. Hail, Zoey S. Davidson et al. (+5 more)

Active wavefront control in high-power laser illumination systems is important for technologies such as additive manufacturing, free-space laser communication, and power transmission. Conventional spatial light modulators (SLMs) and mechanical beam-steering devices are unsuitable for such applications as they rely on metal mirrors and electrical contacts which are damaged under high laser irradiances. Here, we report on the design and realization of an optically addressable metasurface liquid crystal (LC)-based SLM for the modulation of high-power transmitted light. Our device uses a photoactive top contact which is optically addressed with a patterned 435 nm laser, creating a transient electrical contact that selectively switches the underlying LC medium. A TiO$_2$ metasurface, resonant in the 915-985 nm wavelength range, is embedded within a thin (~2 $\mu$m) LC layer and enables large optical tunability. We demonstrate 90$^\circ$ linear polarization rotation in reconfigurable patterns across a 5x5 mm$^2$ active area with an overall transmittance of >60%. Additionally, we develop a multiphysics approach to simulate transmittance modulation in our device by modeling the LC interactions with TiO$_2$ nanopillars under an applied electrostatic field. This model exhibits good agreement with measurements and provides improved understanding of how LCs interact with both transmitted light and nanoscale metastructures in active devices. We show that our design and fabrication approach can yield high-efficiency transmissive metasurface SLM devices and lay the groundwork for the design of future LC-based active nanophotonics.
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All authors Jared Sisler, Claudio U. Hail, Zoey S. Davidson, Austin M. K. Fehr, Jiannan Gao, Ruzan Sokhoyan, Selim Elhadj, Harry A. Atwater

Friday 20 March

Physics Education

Rusty Flying Robots: Learning a Full Robotics Stack with Real-Time Operation on an STM32 Microcontroller in a 9 ECTS MS Course

Wolfgang Hoenig, Christoph Scherer and Khaled Wahba

We describe a novel masters-level projects class that teaches robotics along the traditional robotics pipeline (dynamics, state estimation, controls, planning). One key motivational part is that students have to directly apply the algorithms they learn on a highly constrained compute platform, effectively making a robot fly. We teach nonlinear algorithms as deployed in state-of-the-art flight stacks such as PX4. Didactically, we rely on two core concepts: 1) avoidance of provided black-box software infrastructure, and 2) usage of the safe and efficient programming language Rust that is used on the PC (for simulation) and an STM32 microcontroller (for robot deployment). We discuss our methodology and the student feedback over two years with ten students each. Teaching material: https://imrclab.github.io/teaching/flying-robots
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General Physics

Building an analogue simulator of a photonic quantum computer with transparent tape, maple syrup, and cat lasers, and implementing first quantum algorithms in the classroom

Ghislain Lefebvre

This work presents the implementation of single-qubit gates, including $R_x$ and $R_z$ gates realized using transparent adhesive tape, and $R_y$ gates obtained with optically active maple and agave solutions. These gates form the native gate set of a simple photonic system and are subsequently used to construct a Hadamard gate. Two forms of two-qubit gates are introduced using a combination of a calcite crystal and transparent tape. The setups employ both the polarization and the path degree of freedom of a photon as qubits, illustrating how readily accessible materials can be used to manipulate and transform the quantum information they convey. Calculations are performed to determine the birefringence of two different types of tape and to quantify the specific rotations introduced by multiple layers of transparent tape. Finally, simple algorithms and exercises are proposed for students. These experimental setups are designed to facilitate hands-on manipulation of quantum effects while lowering the barrier to accessing quantum systems, with total costs kept below \$50 CAD for the single-qubit gates and below \$100 CAD for all experiments combined. The configurations presented serve as an analog simulator of a photonic quantum computer: although the laser beams used can be described classically, all theoretical considerations and experimental procedures remain valid for quantized systems employing single-photon emitters and single-photon detectors.
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Computational Physics

Spatio-Temporal Uncertainty-Modulated Physics-Informed Neural Networks for Solving Hyperbolic Conservation Laws with Strong Shocks

Darui Zhao, Ze Tao and Fujun Liu

Physics-Informed Neural Networks (PINNs) frequently encounter difficulties in accurately resolving shock waves within high-speed compressible flows, a failure largely attributed to the "gradient pathology" arising from extreme stiffness at discontinuities. To overcome this limitation, we propose the Spatio-Temporal Uncertainty-Modulated PINN (UM-PINN), a probabilistic framework that reinterprets the training process as a multi-task learning problem governed by homoscedastic aleatoric uncertainty. By integrating a gradient-based spatial mask with learnable variance parameters, our method dynamically balances the conflicting contributions of Partial Differential Equation (PDE) residuals and initial conditions across the spatiotemporal domain, further stabilized by Quasi-Monte Carlo Sobol sampling. We validate the framework against challenging benchmarks, including the one-dimensional (1D) Sod shock tube, the high-frequency Shu-Osher problem, and the complex two-dimensional (2D) Riemann interaction, where standard gradient-based weighting schemes typically fail. Experimental results demonstrate that UM-PINN achieves orders of magnitude improvement in accuracy and shock resolution compared to baseline methods, establishing a robust new paradigm for mesh-free Computational Fluid Dynamics in hyperbolic systems.
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Instrumentation and Detectors

Semiautomatic dimensional screening of plastic scintillator cubes using image analysis and robotics

Tatsuya Kikawa, Mao Tani, Atsuko K. Ichikawa et al. (+3 more)

Large-scale particle physics detectors often contain millions of repeated components, making precise and efficient quality control essential. We have developed a semiautomatic system for dimensional screening of 1 cm$^3$ plastic scintillator cubes for their potential use in future neutrino detectors. The system employs a motorized rotating stage, six high-resolution cameras, and image analysis software to measure cube size, surface protrusions, and the positions of holes for wavelength-shifting fibers used in optical readout. Based on these measurements, each cube is automatically classified as either acceptable or defective. We constructed and validated a prototype system, achieving a measurement precision of 10 $\mu$m and over 80% consistency with manual screening. To enable classification of cubes into 48 groups based on hole positions while preserving their orientation, we introduced a 6-axis robotic arm. The completed system achieved a rejection rate of 3.1%. Our approach contributes to scalable, precise, and efficient quality control for future large-scale particle physics detectors.
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All authors Tatsuya Kikawa, Mao Tani, Atsuko K. Ichikawa, Tsunayuki Matsubara, Tsuyoshi Nakaya, Tomohisa Ogawa

Plasma Physics

Physics-informed tritium fuel cycle modelling workflow for fusion reactors

Rémi Delaporte-Mathurin, Ross MacDonald, James Dark et al. (+3 more)

In this work, we present a multi-fidelity, physics-informed framework for tritium fuel cycle modelling based on the open-source PathSim/PathView platform. Three complementary modelling approaches are demonstrated within a unified dynamic simulation environment. First, a zero-dimensional residence time model is used to reproduce the fuel cycle behaviour of an ARC-class fusion power plant, providing a baseline system-level description. Second, an intermediate-fidelity component model based on coupled one-dimensional ordinary differential equations is developed to describe tritium mass transfer in a liquid metal bubble column reactor and validated against published literature before integration into the full fuel cycle. Finally, high-fidelity multi-dimensional tritium transport models implemented using the finite element code FESTIM are coupled directly to the system model, enabling the inclusion of multi-dimensional effects, material interfaces, and complex transport phenomena. This work demonstrates how fuel cycle components of varying physical fidelity can be combined consistently within a single, open-source framework. The proposed approach enables more physically grounded fuel cycle analyses while retaining the flexibility required for system-level studies and provides a foundation for future integration with neutronics, fluid dynamics, and surrogate modelling tools.
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All authors Rémi Delaporte-Mathurin, Ross MacDonald, James Dark, Milan Rother, Tasnim Zulfiqar, Kevin B. Woller

Instrumentation and Detectors

Enhancing Neutrinoless Double-Beta Decay Sensitivity of Liquid-Xenon Time Projection Chamber with Augmented Convolutional Neural Network

E. Aprile, J. Aalbers, K. Abe et al. (+173 more)

Dual-phase time projection chamber (TPC) that employs a multi-ton-scale liquid xenon (LXe) target mass is a pioneering detector technology to search for dark matter. Beyond its advantage in dark matter direct detection efforts, the natural xenon target allows it to search for the neutrinoless double-beta decay ($0\nu\beta\beta$) process, which would violate lepton number conservation and indicate that neutrinos are Majorana particles. However, such $0\nu\beta\beta$ searches have been limited by gamma-ray backgrounds originating from the detector materials. In this work, we designed an augmented convolutional neural network (A-CNN) model to extract additional event-topology information from detector data. Using simulation and calibration data from XENONnT, a leading LXe TPC experiment, our model achieved over 60% background rejection while maintaining 90% signal acceptance. This rejection power improves XENONnT's projected sensitivity of the $^{136}$Xe $0\nu\beta\beta$ search by about 40%. The implementation of A-CNN in the data analysis of future liquid xenon observatories, such as XLZD, will further enhance their sensitivities for $0\nu\beta\beta$ with $^{136}$Xe.
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All authors E. Aprile, J. Aalbers, K. Abe, M. Adrover, S. Ahmed Maouloud, L. Althueser, B. Andrieu, E. Angelino, D. Antón Martin, S. R. Armbruster, F. Arneodo, L. Baudis, M. Bazyk, L. Bellagamba, R. Biondi, A. Bismark, K. Boese, R. M. Braun, G. Bruni, G. Bruno, R. Budnik, C. Cai, C. Capelli, J. M. R. Cardoso, A. P. Cimental Chávez, A. P. Colijn, J. Conrad, J. J. Cuenca-García, V. D'Andrea, L. C. Daniel Garcia, M. P. Decowski, A. Deisting, C. Di Donato, P. Di Gangi, S. Diglio, K. Eitel, S. el Morabit, R. Elleboro, A. Elykov, A. D. Ferella, C. Ferrari, H. Fischer, T. Flehmke, M. Flierman, R. Frankel, D. Fuchs, W. Fulgione, C. Fuselli, R. Gaior, F. Gao, R. Giacomobono, F. Girard, R. Glade-Beucke, L. Grandi, J. Grigat, H. Guan, M. Guida, P. Gyorgy, R. Hammann, A. Higuera, C. Hils, L. Hoetzsch, N. F. Hood, M. Iacovacci, Y. Itow, J. Jakob, F. Joerg, Y. Kaminaga, M. Kara, S. Kazama, P. Kharbanda, M. Kobayashi, D. Koke, K. Kooshkjalali, A. Kopec, H. Landsman, R. F. Lang, L. Levinson, A. Li, I. Li, S. Li, S. Liang, Z. Liang, Y.-T. Lin, S. Lindemann, M. Lindner, K. Liu, M. Liu, F. Lombardi, J. A. M. Lopes, G. M. Lucchetti, T. Luce, Y. Ma, C. Macolino, J. Mahlstedt, F. Marignetti, T. Marrodán Undagoitia, K. Martens, J. Masbou, S. Mastroianni, V. Mazza, A. Melchiorre, J. Merz, M. Messina, A. Michel, K. Miuchi, A. Molinario, S. Moriyama, K. Morå, M. Murra, J. Müller, K. Ni, C. T. Oba Ishikawa, U. Oberlack, S. Ouahada, B. Paetsch, Y. Pan, Q. Pellegrini, R. Peres, J. Pienaar, M. Pierre, G. Plante, T. R. Pollmann, A. Prajapati, L. Principe, J. Qin, D. Ramírez García, A. Ravindran, A. Razeto, R. Singh, L. Sanchez, J. M. F. dos Santos, I. Sarnoff, G. Sartorelli, J. Schreiner, P. Schulte, H. Schulze Eißing, M. Schumann, L. Scotto Lavina, M. Selvi, F. Semeria, F. N. Semler, P. Shagin, S. Shi, H. Simgen, Z. Song, A. Stevens, C. Szyszka, A. Takeda, Y. Takeuchi, P.-L. Tan, D. Thers, G. Trinchero, C. D. Tunnell, K. Valerius, S. Vecchi, S. Vetter, G. Volta, C. Weinheimer, M. Weiss, D. Wenz, C. Wittweg, V. H. S. Wu, Y. Xing, D. Xu, Z. Xu, M. Yamashita, J. Yang, L. Yang, J. Ye, M. Yoshida, L. Yuan, G. Zavattini, Y. Zhao, M. Zhong, T. Zhu

Optics · Cross-listed from quant-ph

Triply Resonant Photonic Crystal Nanobeam Cavities for Unconditional Photon Blockade

Richard Dong, Abhinav Kala, Andrew Lingenfelter et al. (+3 more)

The development of many scalable quantum technologies requires single-photon nonlinearity, such as single-photon blockade, in solid-state systems. Recently, it has been shown that single-photon Fock states can, in principle, be unconditionally generated using arbitrarily small intrinsic optical nonlinearities in photonic cavities. We investigate the feasibility of such a scheme in achieving photon blockade in an on-chip silicon photonics platform. We show that a triply resonant nanobeam cavity pumped with three monochromatic lasers could achieve such functionalities with quality factors $\sim 10^7$ and effective mode volumes $\sim 10^{-2} \mu m^3$, for experimentally feasible incident powers. Using quantum optical simulations, we propose an experimental protocol to generate single photons under this scheme. The constraints on the cavity design and experimental conditions are thoroughly explored to determine feasible regimes of operation.
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All authors Richard Dong, Abhinav Kala, Andrew Lingenfelter, Michael S. Polania Vivas, Matthew D. Stearns, Arka Majumdar

Plasma Physics

Phase-controlled direct laser acceleration enabled by longitudinal variation of the laser-driven quasi-static plasma magnetic field

R. Bhakta, I-L. Yeh, K. Tangtartharakul et al. (+2 more)

Direct laser acceleration (DLA) enables energy transfer from an ultra-high-intensity laser to plasma electrons and underpins many laser-driven particle and radiation-source concepts. A laser-driven azimuthal plasma magnetic field is a key player in this process: it confines energetic electrons, induces betatron oscillations, and makes possible a resonant interaction between the betatron motion and the laser field. While this betatron resonance can enhance electron energy gain, the gain itself generally drives frequency detuning and promotes largely reversible energy exchange that limits net acceleration. Here we show, using a test-electron model with prescribed fields, that a slow longitudinal increase of the quasi-static plasma magnetic field qualitatively changes DLA by introducing hysteresis in the ratio of the betatron frequency to the laser frequency experienced by the electron, so that this ratio depends on the prior evolution of the electron even at the same energy. This hysteresis enables phase control of the electron-laser energy exchange and suppresses the usual reversibility of DLA, allowing electrons to retain the acquired energy and sustain energy gain without intermittent losses.
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All authors R. Bhakta, I-L. Yeh, K. Tangtartharakul, L. Willingale, A. Arefiev

General Physics

Observational constraints on viscous cosmology in $f(T,L_m)$ gravity

M. Koussour, Alnadhief H. A. Alfedeel, S. Muminov et al. (+1 more)

We investigate the late-time cosmic acceleration within the framework of viscous $f(T,L_m)$ gravity, where the gravitational action depends on both the torsion scalar $T$ and the matter Lagrangian $L_m$. In this context, the Universe is modeled as a bulk viscous fluid, allowing for dissipative effects that generate an effective negative pressure capable of driving acceleration without invoking a cosmological constant. We adopt a simple linear model $f(T,L_m) = \alpha T + \beta L_m$ and assume a constant bulk viscosity coefficient $\zeta = \zeta_0 > 0$. The model parameters are constrained using a joint analysis of recent observational datasets, including 31 Hubble parameter measurements, the Pantheon+ sample of 1701 Type Ia Supernovae, and the latest baryon acoustic oscillation data from DESI, employing a Markov Chain Monte Carlo (MCMC) approach. The best-fit results, $H_0 = 68.16 \pm 0.65$, $\alpha = 1.53^{+0.49}_{-0.61}$, $\beta = 0.40 \pm 0.96$, and $\zeta_0 = 2.15^{+0.69}_{-0.81}$, are consistent with current cosmological observations and indicate that bulk viscosity plays a significant role in the late-time dynamics. The deceleration parameter $q_0 = -0.33 \pm 0.41$ confirms the current accelerated expansion, while the effective equation of state (EoS) evolves from a matter-like regime at high redshift toward a quintessence phase at late times. The $Om(z)$ diagnostic further supports this behavior, suggesting a mild deviation from $\Lambda$CDM toward a dynamical dark energy component. Although information criteria ($\Delta \mathrm{AIC} = 2.2$, $\Delta \mathrm{BIC} = 13.13$) slightly favor the simpler $\Lambda$CDM model, the viscous $f(T,L_m)$ framework remains a viable and physically motivated alternative capable of explaining cosmic acceleration through the combined effects of torsion-matter coupling and viscosity.
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All authors M. Koussour, Alnadhief H. A. Alfedeel, S. Muminov, J. Rayimbaev

General Physics

The group height of spicules links their acceleration and velocity

Leonard A Freeman

This study reveals a new feature of many solar jets: a group height, which links their acceleration and velocity. The acceleration and velocity (a,V) for jets such as spicules, often displayed as scattergraphs, show a strong correlation. This can be represented empirically by the equation, V = pa + q, where p and q are two arbitrary non-zero constants. This study reanalyses the (a,V) data for nine different groups of jets, in order to test an alternative proposal that a simpler relationship directly links (a,V) to the mean height for the group of jets, without needing the empirical constants p and q. A standard mathematical test: plotting log(a) against log(V) , tests whether V ~ a^n and if so, gives the value of n. When this is done for a wide range of jets the index n is consistently found to be close to 0.5 The nine groups of jets include spicules, macrospicules and dynamic fibrils. The result, V ~ a^0.5, or equivalently V^2 = ka , with only one constant, provides as close a match to the data as the equation V = pa + q, which requires two unknown constants. It is found that the constant k, is a known quantity: just twice the mean height, s̄, of the group of jets being analysed. This then gives the equation V^2 = 2as̄ for the jets in the group. This more succinct relationship links the acceleration and maximum velocity of every jet in the group to a well-defined quantity: the mean height of the group of spicules, without needing extra constants.
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Atmospheric and Oceanic Physics

Watch an AI Weather Model Learn (and Overshoot) Tropical Cyclones

Rebecca Baiman, Ankur Mahesh and Elizabeth A. Barnes

In a changing climate, artificial intelligence (AI) weather models have the potential to provide cheaper, faster, and more accurate forecasts of high-impact weather events. To realize this potential and gauge trustworthiness, there is a need for more research on how models learn extreme events and how that learning might be improved. Here, we investigate how a Spherical Fourier Neural Operator (SFNO) learns tropical cyclones (TCs) by saving every checkpoint from training and analyzing storm-specific metrics. We find that a subset of storms show early TC intensity forecast skill that degrades into systematic overprediction in the second half of training. Moisture perturbation experiments show a causal relationship between anomalously moist environments and this skill degradation. This work provides a first example of leveraging task-specific training dynamics to further our understanding of how AI weather models learn extreme events.
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Accelerator Physics

High-$Q_0$ Treatment of CEBAF 1.5 GHz SRF Cavities

Pashupati Dhakal

The Continuous Electron Beam Accelerator Facility (CEBAF) was the first large-scale accelerator to employ superconducting radiofrequency (SRF) cavities for continuous-wave operation. Ongoing research and development efforts continue to focus on increasing the intrinsic quality factor ($Q_0$) of these cavities in order to reduce cryogenic losses while maintaining operational gradients. In this work, we report on the application of high-$Q_0$ surface treatments to single-cell and multicell C100 and C75 style 1.5 GHz niobium cavities used in the CEBAF accelerator. Nitrogen infusion and oxygen alloying via medium-temperature baking were applied under heat-treatment constraints relevant to existing cavity hardware. Both processes yielded substantial improvements in $Q_0$ at moderate accelerating gradients, achieving values of approximately 2 $\times$ 10$^{10}$ at 2.07 K and 20 MV/m. The effectiveness of nitrogen infusion at reduced annealing temperatures and the successful extension of oxygen alloying to multicell cavities are demonstrated. These results establish viable pathways for implementing high-$Q_0$ treatments in CEBAF-compatible cavities and support future integration into cryomodules for reduced operational cryogenic load.
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Applied Physics

Degradation Dynamics of Perovskite Solar Cells Under Fixed Reverse Current Injection

Fangyuan Jiang, Haruka Koizumi, Hannah Contreras et al. (+8 more)

Previous studies of reverse-bias stability in perovskite solar cells have focused primarily on voltage controlled reverse-bias tests. Here we instead present an investigation of perovskite solar cell degradation under well-defined, constant reverse-current stress. We show that the choice of hole-transport layer dictates the dominant degradation pathway: cells using thick poly(triphenylamine) (PTAA) layers with better indium-doped tin oxide (ITO) coverage can tolerate high reverse bias but quickly undergo catastrophic breakdown under fixed reverse current near their one-sun maximum power-point. In contrast, cells modified with the phosphonic-acid interface layer MeO-2PACz, with poorer ITO coverage compared to PTAA, exhibit soft, gradual, and largely recoverable degradation, regardless of the shading conditions. For MeO-2PACz devices, degradation increases with both current magnitude and duration. Importantly, when normalized by injected charge (current times duration), lower currents applied over longer times cause more severe degradation than higher currents over shorter periods. Combining electrical measurements with spatially resolved photoluminescence imaging, we argue against shunt formation and instead support an ion- and charge-mediated interfacial electrochemical degradation mode.
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All authors Fangyuan Jiang, Haruka Koizumi, Hannah Contreras, Rajiv Giridharagopal, Akash Dasgupta, Zixu Huang, Ryan A. DeCrescent, Kell Fremouw, Michael D. McGehee, Neal R. Armstrong, David S. Ginger

Applied Physics

Neutralization of the impact of belt speed on screen printed copper metallization by LECO on PERC homogeneous emitter

Abasifreke Ebong, Donald Intal, Sandra Huneycutt et al. (+6 more)

Copper fire-through metallization is a cost-effective alternative to Ag counterpart for industrial high efficiency solar cells. The fire through dielectric metallization relies on belt speed, which dictates the ramp up and ramp down rates for effective contact formation. In this paper three belt speeds (325oC, 360oC, 390oC) at constant peak firing temperature, were used to process PERC (homogeneous emitter) cells. After the contact firing the electrical parameters were dependent on belt speed, but after LECO treatment, they were identical. The SEM/EDS cross sectional analyses showed increased elemental Cu with belt speed, and the series resistance was lowest for the middle belt speed before LECO. However, after the LECO treatment, the series resistance dropped, respectively, to 0.503 ohm-cm-2, 0.428 ohm-cm-2 and 0.500 ohm-cm-2 leading to efficiency of 20.8% on homogeneous PERC emitter.
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All authors Abasifreke Ebong, Donald Intal, Sandra Huneycutt, Ajeet Rohatgi, Vijay Upadhyaya, Sagnik Dasgupta, Ruohan Zhong, Thad Druffel, Ruvini Dharmadasa

Plasma Physics

Modeling Temperature Profiles in the Pedestal of NSTX with Reduced Models

P.-Y. Li, D. R. Hatch, L. A. Leppin et al. (+5 more)

This paper describes new modeling capabilities for predicting H-mode pedestal profiles in spherical tokamaks. Temperature profiles for NSTX discharges 132543 and 132588 are modeled by coupling the astra transport solver with neoclassical transport and gyrokinetic-based reduced models for electron temperature gradient (ETG) and kinetic ballooning mode (KBM) instabilities. A quasi-linear surrogate model for ion-scale transport is developed using linear gene simulations, requiring only a single free parameter calibrated to one discharge. Time-evolving the temperatures with fixed density yields good agreement with experiments for both discharges. Systematic analysis of the transport mechanisms reveals that neoclassical transport is huge across the entire pedestal region for the ion channel. ETG turbulence is large in the plasma edge and low density gradient region, contributing substantially to the electron channel. However, KBM/MHD-like modes also drive significant transport in both the ion and electron thermal channels, making them essential for accurate pedestal modeling. Further refinements, including explicit $E \times B$ shear suppression and scaled ETG transport, produce quantitative but not qualitative improvements. This work lays the foundation for predictive modeling of future devices.
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All authors P.-Y. Li, D. R. Hatch, L. A. Leppin, J. Schmidt, J. F. Parisi, M. Lampert, M. Kotschenreuther, S. M. Mahajan

Applied Physics

Critical look at the atmospheric Cu fire-through dielectric metallization for cost-effective and high efficiency silicon solar cells

Donald Intal, Sandra Huneycutt, Abasifreke Ebong et al. (+6 more)

The formation of stable copper-silicide (Cu3Si) interfaces is crucial for cost-effective, high-efficiency solar cells. However, copper's diffusivity and electromigration issues pose challenges for contact stability. This study employs Laser-Enhanced Contact Optimization (LECO) to induce localized nano-scale Joule heating at the Cu-Si interface in phosphorus-doped p-PERC solar cells. High-resolution STEM and bright field analyses confirm stable Cu3Si formation in LECO-treated samples, with significantly reduced material segregation compared to nonLECO samples. SEM and post-etch EDS mapping demonstrate improved chemical resistance and interface cleanliness. Electrically, LECO treatmenet reduces series resistance by a factor 3, enhancing fill factor and efficiency while preserving diode quality. These results highlight LECO as a scalable method for reliable, silver-free solar cell metallization.
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All authors Donald Intal, Sandra Huneycutt, Abasifreke Ebong, Ajeet Rohatgi, Vijay Upadhyaya, Sagnik Dasgupta, Ruohan Zhong, Thad Druffel, Ruvini Dharmadasa

Chemical Physics

A unified machine-learning framework for ab initio multiscale modeling of liquids

Anna T. Bui and Stephen J. Cox

Understanding and predicting the behavior of liquid matter across length scales, using only the microscopic interactions encoded in the Schrödinger equation, remains a central challenge in the physical sciences. Achieving this goal requires not only an accurate and efficient description of intermolecular forces but also a consistent framework that bridges the micro-, meso-, and macroscales. Here, by combining machine-learned interatomic potentials (MLIPs) with neural classical density functional theory (neural cDFT), we present such a framework. The underlying idea is simple: MLIPs trained on quantum-mechanical energies and forces are used to generate inhomogeneous microscopic density profiles, which in turn serve as the training data for neural cDFT. The resulting ab initio neural cDFT is not only significantly more computationally efficient than molecular simulations, but also provides a conceptually transparent route to the thermodynamics of both homogeneous and inhomogeneous systems. We demonstrate the approach for both water and carbon dioxide using several exchange-correlation functionals. Beyond accurately reproducing bulk equations of state and liquid-vapor phase diagrams, ab initio neural cDFT predicts, from first principles, how confinement modifies liquid-vapor coexistence in water. It also captures complex behavior in supercritical carbon dioxide such as the Fisher-Widom and Widom lines. Ab initio neural cDFT establishes a general first-principles route to multiscale modeling of fluids within a single unified conceptual framework.
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Plasma Physics

An analytical criterion for significant runaway electron generation in activated tokamaks

Björn Zaar, István Pusztai, Ida Ekmark et al. (+1 more)

A disrupting plasma in a high-performance tokamak such as ITER or SPARC may generate large runaway electron currents that, upon impact with the tokamak wall, can cause serious damage to the device. To quickly identify regions of safe operation in parameter space, it is useful to develop reduced models and analytical criteria that predict when a significant fraction of the Ohmic current is converted into a current of runaway electrons. In deuterium-tritium plasmas, the seed runaway current may have a significant contribution from - or may even be dominated by - tritium beta decay and Compton scattering. In this work, a criterion for significant runaway electron generation that includes tritium beta decay and Compton scattering sources is developed. The avalanche gain factor includes the effects of partial screening of injected noble gases. The result is an analytical model that can predict significant runaway electron generation in the next generation of activated tokamak devices. The model is validated by fluid simulations using DREAM (Hoppe et al. 2021 Comput. Phys. Commun., vol. 268, p. 108098) and is shown to delineate regions in parameter space where significant runaway electron generation may occur.
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All authors Björn Zaar, István Pusztai, Ida Ekmark, Tünde Fülöp