Showing 1–50 of 227 results for author: Xu, T

The Ponderomotive Effects of Narrow-band, Superconducting Resonators in Open and Closed Loop

Authors: Jacob Brown, Alexander Sukhanov, Crispin Contreras-Martinez, Vyacheslav Yakovlev, Sang-hoon Kim, Shen Zhao, Ting Xu, Walter Hartung, Wei Chang

Abstract: In this work, we present measurements of ponderomotive instabilities in narrow-band, coaxial resonators in open and closed control loop systems. We show an analytical scheme we will use in future studies to examine the dependency of open loop stability on mechanical parameters. Analytical and simulation models are used to predict the onset of the oscillatory instability in half wave resonators wit… ▽ More In this work, we present measurements of ponderomotive instabilities in narrow-band, coaxial resonators in open and closed control loop systems. We show an analytical scheme we will use in future studies to examine the dependency of open loop stability on mechanical parameters. Analytical and simulation models are used to predict the onset of the oscillatory instability in half wave resonators with active disturbance rejection control for amplitude and phase stabilization. We demonstrate that for high amplitude controller bandwidths, ponderomotive oscillations can couple with the controller frequency response via higher harmonics and lower the threshold for the oscillatory instability. We reaffirm the superiority of in-phase/quadrature $(I/Q)$ component control in regards to preventing the oscillatory instability, and show how the phase controller can amplify the crosstalk of disturbances in amplitude and phase control. In cases with large disturbances, this effect can lead to instabilities not present in $I/Q$ control. △ Less

Submitted 3 August, 2026; v1 submitted 30 July, 2026; originally announced July 2026.

Report number: FERMILAB-PUB-26-0424-TD

The Research and Development of New Electronics System and its Testing on the JNE-1ton Prototype Detector

Authors: Haoyan Yang, Yuzi Yang, Yapeng Wang, Changxu Wei, Haoyang Fu, Haozhe Sun, Juntao Liu, Zhiyi Liu, Tao Xue, Jianmin Li, Yinong Liu, Zhe Wang, Shaomin Chen

Abstract: The Jinping Neutrino Experiment (JNE), a next-generation neutrino observatory under construction at the China Jinping Underground Laboratory II (CJPL-II), requires high-precision waveform-based event reconstruction, imposing stringent demands on its readout electronics. To meet these requirements, we have developed a high-performance readout system featuring 1 GSa/s real-time sampling, 14-bit phys… ▽ More The Jinping Neutrino Experiment (JNE), a next-generation neutrino observatory under construction at the China Jinping Underground Laboratory II (CJPL-II), requires high-precision waveform-based event reconstruction, imposing stringent demands on its readout electronics. To meet these requirements, we have developed a high-performance readout system featuring 1 GSa/s real-time sampling, 14-bit physical resolution with an effective number of bits (ENOB) of 10.6, a total data throughput of 64 Gbps, and a deterministic zero-delay clock distribution architecture. The new single-crate 64-channel system (PDS1500) was validated through bench tests and deployment on the upgraded JNE-1ton prototype detector. Its performance was further evaluated against a commercial reference system. The results demonstrate that all key metrics meet the JNE experimental requirements: zero data loss within a 1000 ns acquisition window, baseline noise reduced to one-third of the reference level, timing drift limited to 0.3 ns across power cycles, and an energy threshold as low as 0.1 MeV, enabling the detection of low-energy solar neutrinos. While the 14-bit physical resolution provides significantly higher waveform fidelity, the overall energy resolution in this test remains dominated by the intrinsic limitations of the JNE-1ton detector, as expected. Furthermore, the modular architecture provides the throughput and scalability required to support the full-scale 3000-channel JNE detector. These results collectively demonstrate that the newly developed electronics system fully satisfies the technical requirements of the future JNE experiment. △ Less

Submitted 28 July, 2026; v1 submitted 21 July, 2026; originally announced July 2026.

Motional Kerr-Cat States of an Atom in an Optical Tweezer

Authors: Steven K. Pampel, Gur Lubin, Dawson P. Hewatt, Conall McCabe, Jaeyong Hwang, Sean R. Muleady, Tianrui Xu, Ana Maria Rey, Cindy A. Regal

Abstract: Schrödinger cat states - quantum superpositions of classically or macroscopically distinct states - constitute a powerful resource for quantum computing, enhanced metrology, and probing coherence on large scales. Encoding such states in the phase space of an oscillator requires a nonlinearity, typically inherited from an auxiliary degree of freedom such as atomic spin or a Josephson junction. Neut… ▽ More Schrödinger cat states - quantum superpositions of classically or macroscopically distinct states - constitute a powerful resource for quantum computing, enhanced metrology, and probing coherence on large scales. Encoding such states in the phase space of an oscillator requires a nonlinearity, typically inherited from an auxiliary degree of freedom such as atomic spin or a Josephson junction. Neutral atoms trapped in reconfigurable optical tweezer arrays - a leading platform for quantum science and computing - provide an intrinsic nonlinearity via the motion of a single atom in a tightly focused trap. However, this self-Kerr mechanism has not previously been exploited for cat-state generation, and remains largely unexplored as a resource for motional-state control. Here we realize Schrödinger cat states in the quantized motion of a single neutral atom trapped in an optical tweezer. By modulating the depth and position, we demonstrate parity control of both Kerr-cat and Fock states alongside tunable nonlinearity, establishing a spin- and species-independent framework for controlling motion. We further show that the cat-state encoding is intrinsically robust against trap-frequency fluctuations that otherwise limit the fidelity of direct Fock-state transitions. These results establish Kerr-based control of neutral-atom motion as a new paradigm for cat-state and bosonic-state engineering in optical tweezers, providing a route toward quantum-error-correcting codes such as grid states, and toward quantum-enhanced sensing with arrays of non-Gaussian states. △ Less

Submitted 20 July, 2026; originally announced July 2026.

Impact of Residual Angular Chirp in a Petawatt-class Laser System on Laser-driven Proton Acceleration

Authors: Qingfan Wu, Minjian Wu, Jiarui Zhao, Ying Gao, Haoran Chen, Tan Song, Zhongshuai Zhang, Zhangyi Wu, Tianhao Liang, Shirui Xu, Ziyang Peng, Hui Zhang, Tianqi Xu, Qihang Han, Chenghao Hua, Ke Chen, Pengcheng Fan, Yuntian Xie, Xianduo Li, Peiqiang Liu, Xiangyu Nong, Shengxuan Xu, Liyong Ma, Yixing Geng, Chen Lin , et al. (3 additional authors not shown)

Abstract: Laser-driven proton acceleration has attracted considerable interest owing to its appealing potential in versatile applications including cancer therapy. Proton energies depend critically on the on-target intensities, yet the detrimental impact of focal spot degradation induced by spatiotemporal couplings on the acceleration remains insufficiently elucidated. In this study, we demonstrate that res… ▽ More Laser-driven proton acceleration has attracted considerable interest owing to its appealing potential in versatile applications including cancer therapy. Proton energies depend critically on the on-target intensities, yet the detrimental impact of focal spot degradation induced by spatiotemporal couplings on the acceleration remains insufficiently elucidated. In this study, we demonstrate that residual angular chirp (AC), stemming from minor misalignments of the grating compressor in a Petawatt-class laser system, acts as a critical bottleneck for proton acceleration. Experimental results reveal that even around 100 microradians of grating misalignment induces substantial focal-spot elongation and a pronounced reduction in peak intensity. By implementing an in situ spectral-blocking diagnostic, we effectively eliminated the residual AC and restored a near-diffraction-limited focus. This optimization led to a significant recovery of the on-target intensity, resulting in a twofold increase in the proton cutoff energy. Our work presents a successful demonstration of diagnosing and eliminating residual AC. This provides a practical reference for generating high-energy proton beams and supporting their diverse applications in a PW-class laser. △ Less

Submitted 14 July, 2026; originally announced July 2026.

Comments: Accepted by Matter and Radiation at Extremes (MRE)

HotLoop Optimization of Petawatt Laser Focal Spot via a Twin-Focus Scheme

Authors: Qingfan Wu, Ying Gao, Minjian Wu, Jiarui Zhao, Shiyou Chen, Tianhao Liang, Haoran Chen, Tan Song, Zhongshuai Zhang, Zhangyi Wu, Shirui Xu, Ziyang Peng, Tianqi Xu, Zhuo Pan, Yujia Zhang, Qihang Han, Ke Chen, Chenghao Hua, Pengcheng Fan, Yuntian Xie, Yifei Shen, Shengxuan Xu, Liyong Ma, Yixing Geng, Chen Lin , et al. (3 additional authors not shown)

Abstract: Achieving diffraction-limited focusing of high-power laser pulses to generate ultra-high intensities is crucial for developing compact laser-driven particle accelerators and exploring strong-field quantum electrodynamics. However, accurately diagnosing and optimizing the focal spots of petawatt (PW) laser pulses remains a significant challenge. In this work, we present an experimental methodology… ▽ More Achieving diffraction-limited focusing of high-power laser pulses to generate ultra-high intensities is crucial for developing compact laser-driven particle accelerators and exploring strong-field quantum electrodynamics. However, accurately diagnosing and optimizing the focal spots of petawatt (PW) laser pulses remains a significant challenge. In this work, we present an experimental methodology utilizing a twin-focus scheme to precisely characterize the intensity distribution and wavefront of focused PW femtosecond laser pulses, and employ it to elucidate their power-dependent evolution. Furthermore, we optimized the focal spots at full power via our in-situ wavefront correction method termed ``HotLoop', achieving a Strehl ratio of 0.80 for 1 PW laser pulses. Consequently, the cutoff proton energies in laser proton acceleration experiments were significantly enhanced. The success of this approach underscores the necessity of in-situ high-energy wavefront correction for ultra-high intensity laser-matter interactions. △ Less

Submitted 19 May, 2026; originally announced May 2026.

Comments: Accepted by Matter and Radiation at Extremes (MRE)

State-resolved multimodal contributions to stratospheric polar vortex predictability

Authors: Shuo Yang, Dan Zhao, Tingting Xue, Chunhua Zeng, Yongwen Zhang, Xiaosong Chen

Abstract: The dynamical basis of stratospheric polar vortex predictability remains unclear, particularly the relative roles of persistence, structural variability, and cross-level coupling. Here we provide a state-resolved and quantitative framework using eigen microstate theory applied to ERA5 geopotential height fields, enabling attribution of predictability to dynamically coherent circulation states via… ▽ More The dynamical basis of stratospheric polar vortex predictability remains unclear, particularly the relative roles of persistence, structural variability, and cross-level coupling. Here we provide a state-resolved and quantitative framework using eigen microstate theory applied to ERA5 geopotential height fields, enabling attribution of predictability to dynamically coherent circulation states via a mesoscopic Granger-causality approach. We show that short-term predictability is dominated by persistence of the leading stratospheric state, whereas extended predictability arises from higher-order stratospheric structures and tropospheric variability. These contributions exhibit strong lead-time dependence and become more distributed during sudden stratospheric warming events. Our results unify SPV predictability within a multimodal, state-resolved framework and provide a physically interpretable pathway for improving subseasonal-to-seasonal forecasts. △ Less

Submitted 13 May, 2026; originally announced May 2026.

Comments: 16 pages, 4 figures

Factoring $2048$ bit RSA integers with a half-million-qubit modular atomic processor

Authors: Tian Xue, Jacob P. Covey

Abstract: Shor's algorithm is one of the most promising applications of quantum computers. However, since $\sim 10^6$ physical qubits are believed to be required for established approaches, the algorithm will need to be distributed across many modules. In this paper, we provide a distributed compilation of Shor's algorithm on a modular atomic processor. We present an end-to-end compilation and optimization… ▽ More Shor's algorithm is one of the most promising applications of quantum computers. However, since $\sim 10^6$ physical qubits are believed to be required for established approaches, the algorithm will need to be distributed across many modules. In this paper, we provide a distributed compilation of Shor's algorithm on a modular atomic processor. We present an end-to-end compilation and optimization strategy that focuses on the interplay between the inter-module communication and the intra-module clock rate. With a half-million-qubit modular atomic processor with a communication rate of $10^5$ Bell pairs per second and a measurement time of 1 ms in a CPU-inspired architecture, we demonstrate that 2048-bit RSA integers can be factored in only 16\% more time than a single-module architecture. Our work presents the first end-to-end analysis and simulation of large-scale integer factorization on modular atomic hardware and it provides a blueprint for the future design of other large-scale modular algorithms. △ Less

Submitted 5 May, 2026; originally announced May 2026.

GMT: A Geometric Multigrid Transformer Solver for Microstructure Homogenization

Authors: Yu Xing, Yang Liu, Tianyang Xue, Lin Lu

Abstract: Lattice metamaterials enable lightweight, multifunctional structures, yet homogenization-based evaluation of their effective properties remains computationally expensive. Neural surrogates offer speed but often lack the accuracy and stability required for engineering-grade simulations. We introduce GMT, a Geometric Multigrid Transformer -- a neural solver with high numerical fidelity for fast and… ▽ More Lattice metamaterials enable lightweight, multifunctional structures, yet homogenization-based evaluation of their effective properties remains computationally expensive. Neural surrogates offer speed but often lack the accuracy and stability required for engineering-grade simulations. We introduce GMT, a Geometric Multigrid Transformer -- a neural solver with high numerical fidelity for fast and reliable lattice homogenization. GMT achieves architectural alignment with Geometric Multigrid (GMG) by restructuring Point Transformer V3 to operate across sparse GMG hierarchies, capturing long-range dependencies and cross-level interactions essential for multigrid convergence. To enforce physical consistency, GMT incorporates physics-aware positional encoding for strict enforcement of periodicity and predicts both the finest-level solution and multi-level residual corrections. These predictions deliver a spectrally-aligned initialization, enabling end-to-end training under physics-informed and solver-aware losses and requiring only a single GMG V-cycle refinement to reach convergence. This fusion of neural prediction and numerical rigor achieves relative residual errors of $10^{-5}$ with a $160\times$ speedup over state-of-the-art GPU-based solvers at equivalent accuracy -- particularly at high resolutions (e.g. $512^3$), where traditional methods become most costly. We validate GMT across mechanical and thermal domains, demonstrate robust generalization to unseen geometries and non-periodic settings, and showcase scalability to high resolutions -- enabling real-time design iteration, multi-scale simulations, high-throughput material discovery, and inverse design. △ Less

Submitted 29 April, 2026; originally announced April 2026.

Comments: SIGGRAPH 2026 journal track

A Spatial-Resolved Proton Energy Spectrometer Based on a Scintillation-Fiber Cube

Authors: Tan Song, Ying Gao, Di Wang, Yujia Zhang, Jiarui Zhao, Qingfan Wu, Zhuo Pan, Shirui Xu, Ziyang Peng, Yulan Liang, Tianqi Xu, Zihao Zhang, Haoran Chen, Qihang Han, Xuan Liu, Ye Yang, Maocheng Wang, Siguang Wang, Yihua Yan, Zhongming Wang, Wenjun Ma

Abstract: Advanced particle acceleration methods have produced high-peak-current ion beams with broad energy spread and complex spatial distribution. There is an urgent need to develop online spatial-resolved energy spectrometers for high-energy pulsed ions. This paper introduces a novel spectrometer based on a scintillation-fiber cube for online diagnosis of proton beams with broadband energy spread and co… ▽ More Advanced particle acceleration methods have produced high-peak-current ion beams with broad energy spread and complex spatial distribution. There is an urgent need to develop online spatial-resolved energy spectrometers for high-energy pulsed ions. This paper introduces a novel spectrometer based on a scintillation-fiber cube for online diagnosis of proton beams with broadband energy spread and complex spatial distribution. We present its working principles, experimental setup, and comprehensive calibration using monoenergetic and spatially uniform proton beams generated by a synchrotron accelerator. Calibration results confirm an energy measurement range of 6-93 MeV, a relative energy uncertainty of 0.6% at 80 MeV, and a pixel size of 0.5 mm for beam profile reconstruction. By exploiting a custom-designed energy degrader, we generated a complex proton beam and measured it with the scintillation-fiber cube spectrometer (SFICS). The results demonstrate the spectrometer's potential for online measurement of the energy spectrum and spatial distribution of complex proton beams. △ Less

Submitted 22 April, 2026; originally announced April 2026.

Comments: 21 pages, 12 figures

Machine-learning extraction of size-dependent temperature scales in the 2D XY model

Authors: Qingao Fan, Xu Li, Tingting Xue

Abstract: Machine learning has become a useful tool for studying phase transitions in statistical systems.For the two-dimensional classical XY model, however, the topological character of the Berezinskii-Kosterlitz-Thouless (BKT) transition and pronounced finite-size effects make it nontrivial to extract robust size-dependent pseudo-critical temperatures from configuration data. Existing studies often stop… ▽ More Machine learning has become a useful tool for studying phase transitions in statistical systems.For the two-dimensional classical XY model, however, the topological character of the Berezinskii-Kosterlitz-Thouless (BKT) transition and pronounced finite-size effects make it nontrivial to extract robust size-dependent pseudo-critical temperatures from configuration data. Existing studies often stop at phase classification, leaving open how standard neural-network outputs can be turned into quantitatively testable observables. Here we develop a machine learning-assisted framework for the 2D XY model that uses standard network outputs to extract the size-dependent sequence of pseudo-critical temperatures T(L). Specifically, we generate Monte Carlo configurations using embedded cluster updates, train a standard ResNet18 only on samples from the Quasi-ordered Phase and the Disordered Phase, and determine T(L) from bootstrap-averaged probability curves using the 50% crossing criterion. We then analyze the finite size drift of this temperature sequence using BKT-motivated scaling and compare it with susceptibility-peak temperatures. The resulting temperature sequence shows a systematic finitesize drift consistent with BKT-type behavior and remains in the same fluctuation window as the susceptibility peak, supporting its interpretation as a finite-size pseudo-critical temperature. More broadly, this framework provides a practical route for converting standard neural-network outputs into physically interpretable finite-size observables in systems with strong crossover or topological transition signatures △ Less

Submitted 31 March, 2026; originally announced April 2026.

Comments: 10 pages, 5 figures

Current-tunable room temperature ferromagnetism and current-driven phase transitions

Authors: Jianping Guo, Peng Rao, Xinhao Huang, Tailai Xu, Yuxuan Guo, Jian Shao, Cheng Sun, Anton Orekhov, Thomas N. G. Meier, Johannes Knolle, Christian H. Back, Lin Chen

Abstract: It is generally assumed that the application of a charge-current in ferromagnetic metals suppresses their ferromagnetic order through trivial Joule heating. Here, we demonstrate that a charge current can instead enhance magnetic ordering. Using a WTe2/Fe3Ge2Te (FGT) stack as a model system, we show that a charge current flowing in WTe2 controls the ferromagnetic properties and magnetic phase trans… ▽ More It is generally assumed that the application of a charge-current in ferromagnetic metals suppresses their ferromagnetic order through trivial Joule heating. Here, we demonstrate that a charge current can instead enhance magnetic ordering. Using a WTe2/Fe3Ge2Te (FGT) stack as a model system, we show that a charge current flowing in WTe2 controls the ferromagnetic properties and magnetic phase transition of the adjacent FGT via a current-induced effective magnetic-field arising from orbital magnetization. Remarkably, the charge current drives a substantial enhancement of the Curie temperature, boosting it well above room temperature. Furthermore, we show that the charge-current enables controlled tuning of the phase transitions in FGT, which confirms the scaling behaviour of a ferromagnet-paramagnet phase transition. This work provides a pathway for integrating two-dimensional ferromagnets into spintronic functionalities at technologically relevant temperatures and for exploring novel current-driven phenomena in ferromagnetic systems. △ Less

Submitted 28 March, 2026; originally announced March 2026.

NeuralFVM: Neural-physics-based Finite Volume Method for Turbulent Flows Using the $k$-$ω$ Model

Authors: Tingkai Xue, Yu Jiao, Te Ba, Jingliang Wang, Juntao Yang, Simon See, Boyang Chen, Claire E. Heaney, Christopher C. Pain, Chang Wei Kang, Mohamed Arif Bin Mohamed, Hongying Li

Abstract: In this work, we develop a neural-physics solver based on finite volume method (FVM), namely NeuralFVM, for turbulent flows by implementing the standard $k$-$ω$ model designed for efficient Graphics Processing Unit (GPU) execution. The governing equations for fluid flow and heat transfer are reformulated as local tensor operations using convolution-based stencil operators, which enables compatibil… ▽ More In this work, we develop a neural-physics solver based on finite volume method (FVM), namely NeuralFVM, for turbulent flows by implementing the standard $k$-$ω$ model designed for efficient Graphics Processing Unit (GPU) execution. The governing equations for fluid flow and heat transfer are reformulated as local tensor operations using convolution-based stencil operators, which enables compatibility with deep learning libraries while preserving the conservative properties of the FVM. A key challenge in implementing the turbulent model within such a framework is the treatment of the stiff destruction terms in the $k$ and $ω$ transport equations. To address this issue, an operator-splitting strategy is introduced in which the stiff destruction terms are handled semi-implicitly while the remaining terms are advanced explicitly. This formulation avoids global matrix assembly and allows the entire solver to be implemented using local tensor operations. In addition, the pressure-velocity coupling is solved using a convolution-based geometric multigrid algorithm embedded within a neural network architecture. The resulting NeuralFVM solver is validated through comparison with simulations conducted using the commercial CFD software ANSYS Fluent for several channel-flow configurations and an indoor airflow scenario. The results demonstrate close agreement in velocity, temperature, and turbulence quantities, confirming the accuracy of the proposed approach. The developed GPU framework achieves a speedup of around 19-46 times compared with its Central Processing Unit (CPU) counterpart under different meshes. Moreover, the proposed solver naturally integrates with machine learning workflows, providing a promising foundation for future data-driven turbulence modeling and optimization. △ Less

Submitted 23 March, 2026; originally announced March 2026.

Impact of heat treatments on the performance of low-frequency superconducting quarter-wave resonators at 4.3 K

Authors: Jacob Brown, Sang-hoon Kim, Walter Hartung, Ting Xu

Abstract: We applied heat treatments to 80.5 MHz quarter-wave resonators made from bulk niobium and prepared with buffered chemical polishing BCP. We evaluated their performance at 4.3 K. We found that a 48 hour, 120 C bake-out ("low-temperature bake out") reduces the surface resistance by a factor of 2 to 3, stemming from a reduction in the Bardeen-Cooper-Schrieffer contribution, consistent with previous f… ▽ More We applied heat treatments to 80.5 MHz quarter-wave resonators made from bulk niobium and prepared with buffered chemical polishing BCP. We evaluated their performance at 4.3 K. We found that a 48 hour, 120 C bake-out ("low-temperature bake out") reduces the surface resistance by a factor of 2 to 3, stemming from a reduction in the Bardeen-Cooper-Schrieffer contribution, consistent with previous findings. This decrease leads to a 38% decrease on average in the medium-field Q-slope when compared to cavities which had only BCP. Mechanisms for the change in quality factor with low-temperature baking have been explored. We observed no improvement in cavity performance after a 3-hour bake-out at 350 C ("medium-temperature bake out"), in contrast to observations for higher-frequency cavities. △ Less

Submitted 27 February, 2026; originally announced March 2026.

Comments: 10 pages, 11 figures, 1 table

Liquid Crystal Theory of Biomembranes

Authors: Zhong-Can Ou-Yang, Tao Xu

Abstract: Biomembranes, primarily composed of lipid bilayers, are not merely passive barriers but dynamic and complex materials whose shapes are governed by the principles of soft matter physics. This review explores the shape problem in biomembranes through the lens of material science and liquid crystal theory. Beginning with classical analogies to crystals and soap bubbles, it details the application of… ▽ More Biomembranes, primarily composed of lipid bilayers, are not merely passive barriers but dynamic and complex materials whose shapes are governed by the principles of soft matter physics. This review explores the shape problem in biomembranes through the lens of material science and liquid crystal theory. Beginning with classical analogies to crystals and soap bubbles, it details the application of the Helfrich elastic model to explain the biconcave shape of red blood cells. The discussion extends to multi-layer systems, drawing parallels between the focal conic structures of smectic liquid crystals, the geometries of fullerenes and carbon nanotubes, and the reversible transitions in peptide assemblies. Furthermore, it examines icosahedral self-assemblies and shape formation in two-dimensional lipid monolayers at air/water interfaces. At the end of the paper, we find that the shapes such as cylinders, spheres, tori, biconcave discoids and Delaunay surfaces form a group. This result is merely an intrinsic geometric feature of these shapes and is independent of the biomembrane equation. When the pressure on the membrane, surface tension, and bending modules meet certain conditions, the biomembrane will take on these shapes. The review concludes by highlighting the unifying power of continuum elastic theories in describing a vast array of membrane morphologies across biological and synthetic systems. △ Less

Submitted 1 May, 2026; v1 submitted 17 February, 2026; originally announced February 2026.

Comments: 54 pages, 1 figure

PRISM: Photonics-Informed Inverse Lithography for Manufacturable Inverse-Designed Photonic Integrated Circuits

Authors: Hongjian Zhou, Haoyu Yang, Nicholas Gangi, Tianle Xu, Rena Huang, Jiaqi Gu

Abstract: Recent advances in photonic inverse design have demonstrated the ability to automatically synthesize compact, high-performance photonic components that surpass conventional, hand-designed structures, offering a promising path toward scalable and functionality-rich photonic hardware. However, the practical deployment of inverse-designed PICs is bottlenecked by manufacturability: their irregular, su… ▽ More Recent advances in photonic inverse design have demonstrated the ability to automatically synthesize compact, high-performance photonic components that surpass conventional, hand-designed structures, offering a promising path toward scalable and functionality-rich photonic hardware. However, the practical deployment of inverse-designed PICs is bottlenecked by manufacturability: their irregular, subwavelength geometries are highly sensitive to fabrication variations, leading to large performance degradation, low yield, and a persistent gap between simulated optimality and fabricated performance. Unlike electronics, photonics lacks a systematic, flexible mask optimization flow. Fabrication deviations in photonic components cause large optical response drift and compounding error in cascaded circuits, while calibrating fabrication models remains costly and expertise-heavy, often requiring repeated fabrication cycles that are inaccessible to most designers. To bridge this gap, we introduce PRISM, a photonics-informed inverse lithography workflow that makes photonic mask optimization data-efficient, reliable, and optics-informed. PRISM (i) synthesizes compact, informative calibration patterns to minimize required fabrication data, (ii) trains a physics-grounded differentiable fabrication model, enabling gradient-based optimization, and (iii) performs photonics-informed inverse mask optimization that prioritizes performance-critical features beyond geometry matching. Across multiple inverse-designed components with both electron-beam lithography and deep ultra-violet photolithography processes, PRISM significantly boosts post-fabrication performance and yield while reducing calibration area and turnaround time, enabling and democratizing manufacturable and high-yield inverse-designed photonic hardware at scale. △ Less

Submitted 1 June, 2026; v1 submitted 17 February, 2026; originally announced February 2026.

Comments: 26 pages. Accepted to ACM TODAES Special Issue on Co-Design and Design Automation for Optical/Photonic Computing Systems, 2026

Physics-Informed Uncertainty Enables Reliable AI-driven Design

Authors: Tingkai Xue, Chin Chun Ooi, Yang Jiang, Luu Trung Pham Duong, Pao-Hsiung Chiu, Weijiang Zhao, Nagarajan Raghavan, My Ha Dao

Abstract: Inverse design is a central goal in much of science and engineering, including frequency-selective surfaces (FSS) that are critical to microelectronics for telecommunications and optical metamaterials. Traditional surrogate-assisted optimization methods using deep learning can accelerate the design process but do not usually incorporate uncertainty quantification, leading to poorer optimization pe… ▽ More Inverse design is a central goal in much of science and engineering, including frequency-selective surfaces (FSS) that are critical to microelectronics for telecommunications and optical metamaterials. Traditional surrogate-assisted optimization methods using deep learning can accelerate the design process but do not usually incorporate uncertainty quantification, leading to poorer optimization performance due to erroneous predictions in data-sparse regions. Here, we introduce and validate a fundamentally different paradigm of Physics-Informed Uncertainty, where the degree to which a model's prediction violates fundamental physical laws serves as a computationally-cheap and effective proxy for predictive uncertainty. By integrating physics-informed uncertainty into a multi-fidelity uncertainty-aware optimization workflow to design complex frequency-selective surfaces within the 20 - 30 GHz range, we increase the success rate of finding performant solutions from less than 10% to over 50%, while simultaneously reducing computational cost by an order of magnitude compared to the sole use of a high-fidelity solver. These results highlight the necessity of incorporating uncertainty quantification in machine-learning-driven inverse design for high-dimensional problems, and establish physics-informed uncertainty as a viable alternative to quantifying uncertainty in surrogate models for physical systems, thereby setting the stage for autonomous scientific discovery systems that can efficiently and robustly explore and evaluate candidate designs. △ Less

Submitted 26 January, 2026; originally announced January 2026.

Two-port CW measurements on RF cavities: Notes on self-consistency assessment and indirect methods

Authors: Walter H. Hartung, Wei Chang, Sang-Hoon Kim, Taro Konomi, Ting Xu

Abstract: In the case of a radio-frequency (RF) cavity with a mismatched input coupler, a direct calculation of the power dissipation in the cavity and the intrinsic quality factor from continuous-wave (CW) measurements may have uncertainty due to systematic errors. Formulae for an indirect calculation of these quantities are derived for the case of a cavity with two couplers of fixed coupling strength. In… ▽ More In the case of a radio-frequency (RF) cavity with a mismatched input coupler, a direct calculation of the power dissipation in the cavity and the intrinsic quality factor from continuous-wave (CW) measurements may have uncertainty due to systematic errors. Formulae for an indirect calculation of these quantities are derived for the case of a cavity with two couplers of fixed coupling strength. In this approach, the signal from the pickup coupler is used to infer the amplitude of the "emitted wave" from the input coupler. A graphical method for self-consistency assessment is evaluated. The impact of frequency offsets is considered. Applications of these methods are presented, drawing on cold tests of superconducting cavities produced for the Facility for Rare Isotope Beams. △ Less

Submitted 20 January, 2026; originally announced January 2026.

Comments: 19 pages, 13 figures, 2 tables

Search for Cosmic Ray Electron Boosted Dark Matter with the CDEX-10 Experiment

Authors: R. Xu, L. T. Yang, Q. Yue, K. J. Kang, Y. J. Li, H. P. An, Greeshma C., J. P. Chang, H. Chen, Y. H. Chen, J. P. Cheng, J. Y. Cui, W. H. Dai, Z. Deng, Y. X. Dong, C. H. Fang, H. Gong, Q. J. Guo, T. Guo, X. Y. Guo, L. He, J. R. He, H. X. Huang, T. C. Huang, S. Karmakar , et al. (63 additional authors not shown)

Abstract: We present new constraints on the cosmic ray electron boosted light dark matter (CReDM) using the 205.4 kg$\cdot$day data of the CDEX-10 experiment located at the China Jinping Underground Laboratory. The cosmic ray electron spectrum and distribution in the Galaxy are generated by the $\tt GALPROP$ code package. In the calculation process of DM-electron scattering process in the Galaxy, we conside… ▽ More We present new constraints on the cosmic ray electron boosted light dark matter (CReDM) using the 205.4 kg$\cdot$day data of the CDEX-10 experiment located at the China Jinping Underground Laboratory. The cosmic ray electron spectrum and distribution in the Galaxy are generated by the $\tt GALPROP$ code package. In the calculation process of DM-electron scattering process in the Galaxy, we consider the energy-dependency of the DM-electron scattering cross section. The constraints on CReDM are set for both heavy and light mediator scenarios using the CDEX-10 dataset. The result exceeds previous Standard Halo Model (SHM) limits for DM mass lower than 0.6 MeV in heavy mediator case and corresponds to the best sensitivity among all direct detection experiments from 1 keV to 0.5 MeV in the light mediator scenario. △ Less

Submitted 13 January, 2026; originally announced January 2026.

Comments: 7 pages, 5 figures

Full symmetry-breaking of electronic and nuclear dynamics for low attosecond resolution of electronic chirality

Authors: Tianlv Xu, Jiawen Kong, Tianjing Zhou, Yan Wang, Jingqin Tu, Alireza Azizi, Steven R. Kirk, Samantha Jenkins

Abstract: Attosecond science is an emerging topic where chirality plays a central role. Here we demonstrate subjecting iodoacetylene, a geometrically achiral molecule, to a pair of simulated non-ionizing ultrafast circularly polarized laser pulses at the highest time resolution to date, by two orders of magnitude (3.87 attoseconds), of the continuously-valued S and R electronic chirality assignments. We par… ▽ More Attosecond science is an emerging topic where chirality plays a central role. Here we demonstrate subjecting iodoacetylene, a geometrically achiral molecule, to a pair of simulated non-ionizing ultrafast circularly polarized laser pulses at the highest time resolution to date, by two orders of magnitude (3.87 attoseconds), of the continuously-valued S and R electronic chirality assignments. We partner the only vector-based quantum chemical physics theory enabling full symmetry-breaking with electronic and nuclear dynamics simulations: the former does not require charge density differences or special symmetry positions. The resulting 'easy' and 'hard' directions of the total electronic charge density motion are quantified as a cardioid-like morphology for the duration of the simulated laser pulses and toroidal afterwards. Future research directions include determination of the underlying mechanism governing chiral induced spin selectivity, in addition to application to chiral spin selective phenomena in opto-spintronics and exotic superconductors, partnered with orbital-free density functional theory (OF-DFT). △ Less

Submitted 23 February, 2026; v1 submitted 11 January, 2026; originally announced January 2026.

Comments: Version 3: small changes in the text, typos removed

Electric-current control of anomalous Hall effect

Authors: Jianping Guo, Gusthavo M. S. Brizolla, Peng Rao, Jian Shao, Thomas N. G. Meier, Tailai Xu, Peirui Ji, Jonathan Finley, Jaroslav Fabian, Johannes Knolle, Christian Back, Lin Chen

Abstract: We demonstrate robust and reversible electric-current control of the anomalous Hall effect (AHE) in a two-dimensional WTe2/Fe3GeTe2 (FGT) stack. Applying a current through Td-WTe2 leads to a giant modulation of the AHE of the adjacent FGT layer, with the relative change of the AHE conductivity exceeding 180%. Control experiments show that i) the observed effect is absent in pure FGT, ii) the modul… ▽ More We demonstrate robust and reversible electric-current control of the anomalous Hall effect (AHE) in a two-dimensional WTe2/Fe3GeTe2 (FGT) stack. Applying a current through Td-WTe2 leads to a giant modulation of the AHE of the adjacent FGT layer, with the relative change of the AHE conductivity exceeding 180%. Control experiments show that i) the observed effect is absent in pure FGT, ii) the modulation weakens in thicker FGT films, confirming its interfacial origin, and iii) the modulation peaks for bilayer WTe2, indicating that the Berry-curvature dipole (BCD) plays the dominant role in the modulation. We propose that the charge current I generates an out-of-plane magnetization Mz via BCD in WTe2 and Mz modifies the exchange splitting of FGT via the inverse magnetic proximity effect, thereby altering its Berry curvature and nontrivially influencing the AHE. The demonstrated method of AHE control offers new possibilities for magnetism control, i.e., for the study of AHE-transistors as well as electric-current control of quantum magnets, especially magnetic insulators. △ Less

Submitted 7 January, 2026; originally announced January 2026.

Hybrid qubit-oscillator module from motional states of two interacting atoms

Authors: Jaeyong Hwang, Tianrui Xu, Sean R. Muleady, Steven K. Pampel, Gur Lubin, Dawson P. Hewatt, Cindy A. Regal, Ana Maria Rey

Abstract: We propose a qubit-oscillator platform based on the motional states of two interacting atoms in an optical tweezer. By stroboscopically modulating an engineered trap with tunable anharmonicity, we implement a complete set of bosonic operations and their qubit-controlled counterparts with high fidelity. This motional control enables accurate detection of magnetic dipolar interactions with $\sim10$… ▽ More We propose a qubit-oscillator platform based on the motional states of two interacting atoms in an optical tweezer. By stroboscopically modulating an engineered trap with tunable anharmonicity, we implement a complete set of bosonic operations and their qubit-controlled counterparts with high fidelity. This motional control enables accurate detection of magnetic dipolar interactions with $\sim10$ Hz sensitivity in one second, reaching sub-Hz resolution within a few minutes in a $20\times20$ tweezer array under realistic experimental imperfections. Our approach establishes a versatile platform for motional quantum control of two atoms, with applications to spin-boson physics and precision sensing of interaction potentials and trapping environments. △ Less

Submitted 17 July, 2026; v1 submitted 6 December, 2025; originally announced December 2025.

Differentiable Physics-Neural Models enable Learning of Non-Markovian Closures for Accelerated Coarse-Grained Physics Simulations

Authors: Tingkai Xue, Chin Chun Ooi, Zhengwei Ge, Fong Yew Leong, Hongying Li, Chang Wei Kang

Abstract: Numerical simulations provide key insights into many physical, real-world problems. However, while these simulations are solved on a full 3D domain, most analysis only require a reduced set of metrics (e.g. plane-level concentrations). This work presents a hybrid physics-neural model that predicts scalar transport in a complex domain orders of magnitude faster than the 3D simulation (from hours to… ▽ More Numerical simulations provide key insights into many physical, real-world problems. However, while these simulations are solved on a full 3D domain, most analysis only require a reduced set of metrics (e.g. plane-level concentrations). This work presents a hybrid physics-neural model that predicts scalar transport in a complex domain orders of magnitude faster than the 3D simulation (from hours to less than 1 min). This end-to-end differentiable framework jointly learns the physical model parameterization (i.e. orthotropic diffusivity) and a non-Markovian neural closure model to capture unresolved, 'coarse-grained' effects, thereby enabling stable, long time horizon rollouts. This proposed model is data-efficient (learning with 26 training data), and can be flexibly extended to an out-of-distribution scenario (with a moving source), achieving a Spearman correlation coefficient of 0.96 at the final simulation time. Overall results show that this differentiable physics-neural framework enables fast, accurate, and generalizable coarse-grained surrogates for physical phenomena. △ Less

Submitted 26 November, 2025; originally announced November 2025.

Integrated soliton microcombs beyond the turnkey limit

Authors: Ze Wang, Tianyu Xu, Yuanlei Wang, Kaixuan Zhu, Xinrui Luo, Haoyang Luo, Junqi Wang, Bo Ni, Yiwen Yang, Qihuang Gong, Yun-Feng Xiao, Bei-Bei Li, Qi-Fan Yang

Abstract: Soliton microcombs generated in optical microresonators are accelerating the transition of optical frequency combs from laboratory instruments to industrial platforms. Self injection locking (SIL) enables direct driving of soliton microcombs by integrated lasers, providing turnkey initiation and improved coherence, but it also pins the pump close to resonance, limiting both spectral span and tunin… ▽ More Soliton microcombs generated in optical microresonators are accelerating the transition of optical frequency combs from laboratory instruments to industrial platforms. Self injection locking (SIL) enables direct driving of soliton microcombs by integrated lasers, providing turnkey initiation and improved coherence, but it also pins the pump close to resonance, limiting both spectral span and tuning flexibility. Here we theoretically and experimentally demonstrate that introducing a thermally tunable auxiliary microresonator extends the bandwidth of SIL soliton microcombs. By engineering hybridization of the pumped resonance, we achieve deterministic access to single soliton states and then push operation into a far detuned regime inaccessible to direct initiation. The resulting combs reach a near 200 nm span at a 25 GHz repetition rate, while preserving the SIL-enabled noise suppression throughout. Moreover, the added degree of freedom afforded by the coupled resonator architecture enables orthogonal control of the comb's repetition rate and center frequency. These advances expand the spectral reach and controllability of integrated soliton microcombs for information processing and precision metrology. △ Less

Submitted 21 November, 2025; v1 submitted 10 November, 2025; originally announced November 2025.

Report on first plasma processing trial for a FRIB quarter-wave resonator cryomodule

Authors: Walter Hartung, Wei Chang, Yoo-Lim Cheon, Kyle Elliott, Sang-Hoon Kim, Taro Konomi, Patrick Tutt, Yuting Wu, Ting Xu

Abstract: Plasma processing has been shown to help mitigate degradation of the performance of superconducting radio-frequency cavities, providing an alternative to removal of cryomodules from the accelerator for refurbishment. Studies of plasma processing for quarter-wave resonators (QWRs) and half-wave resonators (HWRs) are underway at the Facility for Rare Isotope Beams (FRIB), where a total of 324 such r… ▽ More Plasma processing has been shown to help mitigate degradation of the performance of superconducting radio-frequency cavities, providing an alternative to removal of cryomodules from the accelerator for refurbishment. Studies of plasma processing for quarter-wave resonators (QWRs) and half-wave resonators (HWRs) are underway at the Facility for Rare Isotope Beams (FRIB), where a total of 324 such resonators are presently in operation. Plasma processing tests were done on several QWRs using the fundamental power coupler (FPC) to drive the plasma, with promising results. Driving the plasma with a higher-order mode allows for less mismatch at the FPC and higher plasma density. The first plasma processing trial for FRIB QWRs in a cryomodule was conducted in January 2024. Cold tests of the cryomodule showed a significant reduction in field emission X-rays after plasma processing. △ Less

Submitted 10 November, 2025; originally announced November 2025.

Comments: 20 pages, 18 figures

Journal ref: Condensed version of this report is published: Phys. Rev. Accel. Beams 29, 012003 (Jan 2026)

AI-driven Large-scale Electron Microscopy enables Whole-tissue Subcellular Digitization

Authors: Li Xiao, Liqing Liu, Hongjun Wu, Jiayi Zhong, Xixia Li, Yan Zhang, Junjie Hu, Sun Fei, Ge Yang, Tao Xu

Abstract: The distribution and interactions of cellular organelles play a critical role in mediating cellular physiology and pathology. Large-scale electron microscopy enables visualization of organelle distribution and interactions at the tissue level with nanometer resolution, but robust and efficient computational analysis tools are lacking. Here, we present a deep learning tool for universal large-scale… ▽ More The distribution and interactions of cellular organelles play a critical role in mediating cellular physiology and pathology. Large-scale electron microscopy enables visualization of organelle distribution and interactions at the tissue level with nanometer resolution, but robust and efficient computational analysis tools are lacking. Here, we present a deep learning tool for universal large-scale 2D/3D electron microscopy analysis, DeepOrganelle. This new tool enables high-throughput, cell-resolved spatiotemporal mapping and digitization of organelle distribution and interactions. When applied to spermatogenesis across 12 stages and 22 differentiation status of the germ cells, DeepOrganelle uncovered previously unrecognized, stage-dependent dynamics of mitochondria-endoplasmic reticulum contact sites within one subphase of prophase I during meiosis. It also revealed coordinated organelle redistribution in Sertoli cells towards the blood-testis barrier, digitizing the remodeling dynamics of the tissue. This study demonstrates that DeepOrganelle provides a powerful framework that captures subcellular dynamics at the whole-tissue level. △ Less

Submitted 21 February, 2026; v1 submitted 2 November, 2025; originally announced November 2025.

Comments: 17 pages,4 figures

Plasma Processing of FRIB Low-Beta Cryomodules using Higher-Order-Modes

Authors: P. Tutt, W. Chang, K. Elliott, W. Hartung, S. Kim, K. Saito, T. Xu

Abstract: Improvement in SRF accelerator performance after in-tunnel plasma processing has been seen at SNS and CEBAF. Plasma processing development for FRIB quarter-wave and half-wave resonators (QWRs, HWRs) was initiated in 2020. Plasma processing on individual QWRs (beta = 0.085) and HWRs (beta = 0.53) has been found to significantly reduce field emission. A challenge for the FRIB cavities is the relativ… ▽ More Improvement in SRF accelerator performance after in-tunnel plasma processing has been seen at SNS and CEBAF. Plasma processing development for FRIB quarter-wave and half-wave resonators (QWRs, HWRs) was initiated in 2020. Plasma processing on individual QWRs (beta = 0.085) and HWRs (beta = 0.53) has been found to significantly reduce field emission. A challenge for the FRIB cavities is the relatively weak fundamental power coupler (FPC) coupling strength (chosen for efficient continuous-wave acceleration), which produces a lot of mismatch during plasma processing at room temperature. For FRIB QWRs, driving the plasma with higher-order modes (HOMs) is beneficial to reduce the FPC mismatch and increase the plasma density. The first plasma processing trial on a spare FRIB QWR cryomodule was done in January 2024, with before-and-after bunker tests and subsequent installation into the linac tunnel. The first in-tunnel plasma processing trial was completed in September 2025. For both cryomodules, before-and-after cold tests showed a significant increase in the average accelerating gradient for field emission onset after plasma processing for some cavities. In parallel with the cryomodule trials, the use of dual-drive plasma is being explored with the goal of improving the effectiveness of plasma processing. △ Less

Submitted 3 November, 2025; originally announced November 2025.

Comments: 7 pages, 6 figures, presented at the 22nd International Conference on RF Superconductivity, Tokyo, Japan, September 2025

Photoacoustics on the go: An Embedded Photoacoustic Sensing Platform

Authors: Talia Xu, Caitlin Smith, Charles Lo, Jami Shepherd, Gijs van Soest, Marco Zuniga

Abstract: Several centimeters below the skin lie multiple biomarkers, such as glucose, oxygenation, and blood flow. Monitoring these biomarkers regularly and in a non-invasive manner would enable early insight into metabolic status and vascular health. Currently, there are only a handful of non-invasive monitoring systems. Optical methods offer molecular specificity (i.e., multi-biomarker monitoring) but ha… ▽ More Several centimeters below the skin lie multiple biomarkers, such as glucose, oxygenation, and blood flow. Monitoring these biomarkers regularly and in a non-invasive manner would enable early insight into metabolic status and vascular health. Currently, there are only a handful of non-invasive monitoring systems. Optical methods offer molecular specificity (i.e., multi-biomarker monitoring) but have shallow reach (a few millimeters); ultrasound penetrates deeper but lacks specificity; and MRI is large, slow, and costly. Photoacoustic (PA) sensing combines the best of optical and ultrasound methods. A laser transmitter emits pulses that are absorbed by different molecules, providing specificity. These light pulses generate pressure changes that are captured by an ultrasound receiver, providing depth. Photoacoustic sensing is promising, but the current platforms are bulky, complex, and costly. We propose the first embedded PA platform. Our contributions are fourfold. First, inspired by LiDAR technology, we propose a novel transmitter that emits pulses similar to those in the state-of-the-art (SoA), but instead of using high-voltage sources and complex electronic interfaces, we use a simple low-power microcontroller (MCU). Second, we carry out a thorough analysis of our custom transmitter and a commercial system. Third, we build a basic ultrasound receiver that is able to process the faint signal generated by our transmitter. Lastly, we compare the performance of our platform against a SoA commercial system, and show that we can detect glucose and (de)oxygenated hemoglobin in two controlled solution studies. The resulting signal characteristics indicate a plausible path toward noninvasive, real-time, at-home sensing relevant to diabetes care. More broadly, this platform lays the groundwork for translating the promise of PA sensing into a broader practical reality. △ Less

Submitted 29 October, 2025; originally announced October 2025.

Constraints on ultraheavy dark matter from the CDEX-10 experiment at the China Jinping Underground Laboratory

Authors: Y. F. Wang, L. T. Yang, Q. Yue, K. J. Kang, Y. J. Li, H. P. An, Greeshma C., J. P. Chang, H. Chen, Y. H. Chen, J. P. Cheng, J. Y. Cui, W. H. Dai, Z. Deng, Y. X. Dong, C. H. Fang, H. Gong, Q. J. Guo, T. Guo, X. Y. Guo, L. He, J. R. He, H. X. Huang, T. C. Huang, S. Karmakar , et al. (63 additional authors not shown)

Abstract: We report a search for ultraheavy dark matter (UHDM) with the CDEX-10 experiment at the China Jinping Underground Laboratory. Using a Monte Carlo framework that incorporates Earth shielding effects, we simulated UHDM propagation and energy deposition in p-type point-contact germanium detectors. Analysis of 205.4 kg$\cdot$day exposure in the 0.16--4.16 keVee range showed no excess above background.… ▽ More We report a search for ultraheavy dark matter (UHDM) with the CDEX-10 experiment at the China Jinping Underground Laboratory. Using a Monte Carlo framework that incorporates Earth shielding effects, we simulated UHDM propagation and energy deposition in p-type point-contact germanium detectors. Analysis of 205.4 kg$\cdot$day exposure in the 0.16--4.16 keVee range showed no excess above background. Our results exclude the spin-independent UHDM-nucleon scattering with two cross section scales, with the UHDM mass from $10^6$ to $10^{11}$ GeV, and provide the most stringent constraints with solid-state detectors below $10^8$ GeV. △ Less

Submitted 28 March, 2026; v1 submitted 24 October, 2025; originally announced October 2025.

Comments: 8 pages, 5 figures. Version updated to match PRD version

Journal ref: Phys. Rev. D 113, 052011 (2026)

Improved high-gradient performance for medium-velocity superconducting half-wave resonators: Surface preparation and trapped flux mitigation

Authors: Yuting Wu, Kenji Saito, Alex Taylor, Andrei Ganshyn, Chris Compton, Ethan Metzgar, Kyle Elliott, Laura Popielarski, Sam Miller, Sang-hoon Kim, Spencer Combs, Taro Konomi, Ting Xu, Walter Hartung, Wei Chang, Yoo-Lim Cheon

Abstract: A development effort to improve the performance of superconducting radio-frequency half-wave resonators (SRF HWRs) is underway at the Facility for Rare Isotope Beams (FRIB), where 220 such resonators are in operation. Our goal was to achieve an intrinsic quality factor (Q0) of >= 2E10 at an accelerating gradient (Ea) of 12 MV/m. FRIB production resonators were prepared with buffered chemical polis… ▽ More A development effort to improve the performance of superconducting radio-frequency half-wave resonators (SRF HWRs) is underway at the Facility for Rare Isotope Beams (FRIB), where 220 such resonators are in operation. Our goal was to achieve an intrinsic quality factor (Q0) of >= 2E10 at an accelerating gradient (Ea) of 12 MV/m. FRIB production resonators were prepared with buffered chemical polishing (BCP). First trials on electropolishing (EP) and post-EP low temperature baking (LTB) of FRIB HWRs allowed us to reach higher gradient (15 MV/m, limited by quench) with a higher quality factor at high gradient, but Q0 was still below our goal. Trapped magnetic flux during the Dewar test was found to be a source of Q0 reduction. Three strategies were used to reduce the trapped flux: (i) adding a local magnetic shield (LMGS) to supplement the ``global'' magnetic shield around the Dewar for reduction of the ambient magnetic field; (ii) performing a ``uniform cool-down'' (UC) to reduce the thermoelectric currents; and (iii) using a compensation coil to further reduce the ambient field with active field cancellation (AFC). The LMGS improved the Q0, but not enough to reach our goal. With UC and AFC, we exceeded our goal, reaching Q0 = 2.8E10 at Ea = 12 MV/m. △ Less

Submitted 21 October, 2025; originally announced October 2025.

Comments: 20 pages, 17 figures, submitted to Phys Rev Accel Beams

Journal ref: Phys. Rev. Accel. Beams 29, 033102 (Mar 2026)

Constraints on inelastic dark matter from the CDEX-1B experiment

Authors: Y. F. Liang, L. T. Yang, Q. Yue, K. J. Kang, Y. J. Li, H. P. An, Greeshma C., J. P. Chang, H. Chen, Y. H. Chen, J. P. Cheng, J. Y. Cui, W. H. Dai, Z. Deng, Y. X. Dong, C. H. Fang, H. Gong, Q. J. Guo, T. Guo, X. Y. Guo, L. He, J. R. He, H. X. Huang, T. C. Huang, S. Karmakar , et al. (63 additional authors not shown)

Abstract: We present limits on spin-independent inelastic weakly interacting massive particles (WIMP)-nucleus scattering using the 737.1 kg$\cdot$day dataset from the CDEX-1B experiment. Expected nuclear recoil spectra for various inelastic WIMP masses $m_χ$ and mass splittings $δ$ are calculated under the standard halo model. An accurate background model of CDEX-1B is constructed by simulating all major ba… ▽ More We present limits on spin-independent inelastic weakly interacting massive particles (WIMP)-nucleus scattering using the 737.1 kg$\cdot$day dataset from the CDEX-1B experiment. Expected nuclear recoil spectra for various inelastic WIMP masses $m_χ$ and mass splittings $δ$ are calculated under the standard halo model. An accurate background model of CDEX-1B is constructed by simulating all major background sources. The model parameters are then determined through maximum likelihood estimation and Markov chain Monte Carlo fitting. The resulting 90\% confidence level upper limits on the WIMP-nucleon cross section $σ_{\mathrm{n}}$ exclude certain DAMA/LIBRA allowed regions: the $χ^2 < 4$ regions for $δ< 30$ keV at $m_χ= 250$ GeV and the $χ^2 < 9$ region for $δ< 50$ keV at $m_χ= 500$ GeV. The method is applicable to other inelastic dark matter scenarios, and the upcoming CDEX-50 experiment is expected to improve sensitivity by four orders of magnitude. △ Less

Submitted 31 December, 2025; v1 submitted 9 October, 2025; originally announced October 2025.

Comments: 10 pages, 8 figures. Version updated to match PRD version

Journal ref: Phys. Rev. D 112, 112025 (2025)

Electrically-pumped soliton microcombs on thin-film lithium niobate

Authors: Xiaomin Lv, Ze Wang, Tianyu Xu, Chen Yang, Xing Jin, Binbin Nie, Du Qian, Yanwu Liu, Kaixuan Zhu, Bo Ni, Qihuang Gong, Fang Bo, Qi-Fan Yang

Abstract: Thin-film lithium niobate (TFLN) has enabled efficient on-chip electro-optic modulation and frequency conversion for information processing and precision measurement. Extending these capabilities with optical frequency combs unlocks massively parallel operations and coherent optical-to-microwave transduction, which are achievable in TFLN microresonators via Kerr microcombs. However, fully integrat… ▽ More Thin-film lithium niobate (TFLN) has enabled efficient on-chip electro-optic modulation and frequency conversion for information processing and precision measurement. Extending these capabilities with optical frequency combs unlocks massively parallel operations and coherent optical-to-microwave transduction, which are achievable in TFLN microresonators via Kerr microcombs. However, fully integrated Kerr microcombs directly driven by semiconductor lasers remain elusive, which has delayed integration of these technologies. Here we demonstrate electrically pumped TFLN Kerr microcombs without optical amplification. With optimized laser-to-chip coupling and optical quality factors, we generate soliton microcombs at a 200 GHz repetition frequency with an optical span of 180 nm using only 25 mW of pump power. Moreover, self-injection locking enables turnkey initiation and substantially narrows the laser linewidth. Our work provides integrated comb sources for TFLN-based communicational, computational, and metrological applications. △ Less

Submitted 30 September, 2025; originally announced October 2025.

Quantum Semiconductor Heterostructures for meV Axion Dark Matter Detection

Authors: Jaanita Mehrani, Tao Xu, Andrey Baydin, Michael J. Manfra, Henry O. Everitt, Andrew J. Long, Kuver Sinha, Junichiro Kono, Shengxi Huang

Abstract: We propose a novel strategy and a new class of detectors for the direct detection of axion dark matter in the meV mass range, based on resonantly enhanced axion-photon conversion through the inverse Primakoff effect in engineered radiometers composed of quantum semiconductor heterostructures. Semiconductor-Quantum-Well Axion Radiometer Experiments (SQWAREs) are multiple quantum well structures for… ▽ More We propose a novel strategy and a new class of detectors for the direct detection of axion dark matter in the meV mass range, based on resonantly enhanced axion-photon conversion through the inverse Primakoff effect in engineered radiometers composed of quantum semiconductor heterostructures. Semiconductor-Quantum-Well Axion Radiometer Experiments (SQWAREs) are multiple quantum well structures forming magnetoplasmonic cavities, containing high-mobility two-dimensional electron gases, realizing tunable epsilon-near-zero resonances in the terahertz frequency range. By controlling the orientation of the cavity within a strong external magnetic field, both the resonance frequency and the axion-induced current are optimized $\it{in\,situ}$, enabling efficient scanning across a broad mass range without the need for complex mechanical adjustments. The axion-induced electromagnetic signal radiatively emitted from the cavity is then detected by a photodetector. We present the theoretical basis for resonant enhancement, detail the experimental design and benchmarks through extensive simulations, project the sensitivity of an example SQWARE for several realistic configurations, and demonstrate the modularity and flexibility of the design to fit reasonably with any lab's existing capabilities and target unique axion mass ranges. Our results demonstrate that the SQWAREs can probe the well-motivated quantum chromodynamics axion parameter space and close a critical gap in direct searches at meV masses. △ Less

Submitted 26 June, 2026; v1 submitted 17 September, 2025; originally announced September 2025.

Comments: Matches version published in PRL. 9+18 pages, 6+12 figures

Journal ref: Phys. Rev. Lett. 136, 241001 (2026)

Three-Dimensional Continuous Multi-Walled Carbon Nanotubes Network-Toughened Diamond Composite

Authors: Jiawei Zhang, Keliang Qiu, Tengfei Xu, Xi Shen, Junkai Li, Fengjiao Li, Richeng Yu, Huiyang Gou, Duanwei He, Liping Wang, Zhongzhou Wang, Guodong Li, Yusheng Zhao, Ke Chen, Fang Hong, Ruifeng Zhang, Xiaohui Yu

Abstract: Enhancing the fracture toughness of diamond while preserving its hardness is a significant challenge. Traditional toughening strategies have primarily focused on modulating the internal microstructural units of diamonds, including adjustments to stacking sequences, faults, nanotwinning, and the incorporation of amorphous phases, collectively referred to as intrinsic toughening. Here, we introduce… ▽ More Enhancing the fracture toughness of diamond while preserving its hardness is a significant challenge. Traditional toughening strategies have primarily focused on modulating the internal microstructural units of diamonds, including adjustments to stacking sequences, faults, nanotwinning, and the incorporation of amorphous phases, collectively referred to as intrinsic toughening. Here, we introduce an extrinsic toughening strategy to develop an unparalleled tough diamond composite with complex and abundant sp2-sp3 bonding interfaces, by incorporating highly dispersed multi-walled carbon nanotubes (MWCNTs) into the gaps of diamond grains to create a three-dimensional (3D) continuous MWCTNs network-toughen heterogeneous structure. The resultant composite exhibits a hardness of approximately 91.6 GPa and a fracture toughness of roughly 36.4 MPa.m1/2, which is six times higher than that of synthetic diamond and even surpasses that of tungsten alloys, surpassing the benefits achievable through intrinsic toughening alone. The remarkable toughening behavior can be attributed to the formation of numerous mixed sp2-sp3 bonding interactions at the 3D continuous network MWCNTs/diamond interfaces, which facilitate efficient energy dissipation. Our 3D continuous network heterogeneous structure design provides an effective approach for enhancing the fracture toughness of superhard materials, offering a new paradigm for the advanced composite ceramics. △ Less

Submitted 25 August, 2025; originally announced August 2025.

Zeolitic imidazolate framework glasses emit white light

Authors: Zhencai Li, Zihao Wang, Huotian Zhang, Xuan Ge, Ivan Hung, Bozhao Yin, Fengming Cao, Pritam Banerjee, Tianzhao Xu, Lars R. Jensen, Joerg Jinschek, Morten M. Smedskjaer, Zhehong Gan, Laurent Calvez, Guoping Dong, Jianbei Qiu, Donghong Yu, Feng Gao, Haomiao Zhu, Yuanzheng Yue

Abstract: Zeolitic imidazolate framework (ZIF) glasses represent a newly emerged class of melt-quenched glasses, characterized by their intrinsic nanoporous structure, good processability, and multifunctionalities such as gas separation and energy storage. However, creating photonic functionalities in Zn-based ZIF glasses remains elusive. Here we show a remarkable broadband white light-emitting behavior in… ▽ More Zeolitic imidazolate framework (ZIF) glasses represent a newly emerged class of melt-quenched glasses, characterized by their intrinsic nanoporous structure, good processability, and multifunctionalities such as gas separation and energy storage. However, creating photonic functionalities in Zn-based ZIF glasses remains elusive. Here we show a remarkable broadband white light-emitting behavior in a Zn-based ZIF glass, which can be enhanced by annealing. Furthermore, we discovered a sharp red shift upon increasing annealing temperature above the critical temperature of 1.07Tg, where Tg is the glass transition temperature, for a short duration of 30 min. Finally, we achieved a high absolute internal photoluminescence quantum yield of 12.2% upon annealing of ZIF glass at 1.13Tg. Based on the optimally annealed ZIF glass, we fabricated a white light-emitting diode (LED) with the luminous efficacy of 4.2 lm/W and high operational stability, retaining 74.1% of its initial luminous efficacy after 180 min of continuous operation. These results not only demonstrate the feasibility of utilizing ZIF glasses in LED applications but also mark a significant advancement in the development of durable, efficient, and multifunctional photonic materials. △ Less

Submitted 13 August, 2025; originally announced August 2025.

Holovibes: real-time ultrahigh-speed digital hologram rendering and short-time analysis

Authors: Marius Dubosc, Maxime Boy-Arnould, Jules Guillou, Titouan Gragnic, Arthur Courselle, Gustave Hervé, Alexis Pinson, Etienne Senigout, Bastien Gaulier, Simon Riou, Chloé Magnier, Noé Topeza, Oscar Morand, Thomas Xu, Samuel Goncalves, Edgar Delaporte, Adrien Langou, Paul Duhot, Julien Nicolle, Sacha Bellier, David Chemaly, Damien Didier, Philippe Bernet, Eliott Bouhana, Fabien Colmagro , et al. (29 additional authors not shown)

Abstract: Real-time ultrahigh-speed rendering of digital holograms from high-bitrate interferogram streams demands robust parallel computing and efficient data handling with minimal latency. We present Holovibes, a high-performance software engine that enables real-time holographic image reconstruction and short-time analysis at unprecedented throughput. Holovibes integrates spatial demodulation techniques,… ▽ More Real-time ultrahigh-speed rendering of digital holograms from high-bitrate interferogram streams demands robust parallel computing and efficient data handling with minimal latency. We present Holovibes, a high-performance software engine that enables real-time holographic image reconstruction and short-time analysis at unprecedented throughput. Holovibes integrates spatial demodulation techniques, such as Fresnel transformations and angular spectrum propagation, with temporal analysis methods including short-time Fourier transform (STFT) and principal component analysis (PCA) in a unified pipeline. By leveraging CUDA-based GPU acceleration, multithreaded parallelism, and efficient buffering, the system achieves high-throughput, low-latency processing suitable for demanding computational imaging applications. We demonstrate sustained real-time hologram rendering of 256x256-pixel from interferograms acquired by a streaming camera at 71,400 frames per second on commodity hardware with no frame loss, while maintaining an end-to-end latency of 30 ms. The engine also supports simultaneous recording of raw or processed data, enabling high-speed acquisition workflows essential for experimental applications. This work represents a significant advance over prior digital holography systems and provides a versatile platform for ultra-high-speed, real-time computational imaging. △ Less

Submitted 5 August, 2025; originally announced August 2025.

Comments: 10 pages, 3 figures

Tentative demonstration of all-silicon photodetector: from near-infrared to mid-infrared

Authors: Jiaxin Ming, Yubing Du, Tongtong Xue, Yunyun Dai, Yabin Chen

Abstract: Metastable silicon phases have attracted extensive attention these years, due to their fundamentally distinct photoelectric properties compared to the conventional diamond cubic (I) counterpart. Certain metastable phases, prepared via thermal heating method, can exhibit direct bandgap characteristics, significantly enhancing their light absorbance and quantum efficiency. Herein, we tentatively dem… ▽ More Metastable silicon phases have attracted extensive attention these years, due to their fundamentally distinct photoelectric properties compared to the conventional diamond cubic (I) counterpart. Certain metastable phases, prepared via thermal heating method, can exhibit direct bandgap characteristics, significantly enhancing their light absorbance and quantum efficiency. Herein, we tentatively demonstrate an all-silicon photodetector working from near- to mid-infrared bands through precisely selective laser annealing strategy. We systematically investigated the optical properties and optoelectronic response of III/XII mixture, IV phase, and III/XII-I homojunctions. The obtained results reveal that III/XII composite and IV phase exhibit negative and positive photoconductivity, respectively. Furthermore, the established laser heating approach facilitates us to fabricate all-silicon homostructures with tunable photoconductive properties, such as III/XII-I and IV-I junctions. These findings can expand the potential applications of metastable semiconducting materials in optoelectronics and photodetectors. △ Less

Submitted 5 August, 2025; originally announced August 2025.

Comments: 13 pages, 5 figures

DiffSpectra: Molecular Structure Elucidation from Spectra using Diffusion Models

Authors: Liang Wang, Yu Rong, Tingyang Xu, Zhenyi Zhong, Zhiyuan Liu, Pengju Wang, Deli Zhao, Qiang Liu, Shu Wu, Liang Wang, Yang Zhang

Abstract: Molecular structure elucidation from spectra is a fundamental challenge in molecular science. Conventional approaches rely heavily on expert interpretation and lack scalability, while retrieval-based machine learning approaches remain constrained by limited reference libraries. Generative models offer a promising alternative, yet most adopt autoregressive architectures that overlook 3D geometry an… ▽ More Molecular structure elucidation from spectra is a fundamental challenge in molecular science. Conventional approaches rely heavily on expert interpretation and lack scalability, while retrieval-based machine learning approaches remain constrained by limited reference libraries. Generative models offer a promising alternative, yet most adopt autoregressive architectures that overlook 3D geometry and struggle to integrate diverse spectral modalities. In this work, we present DiffSpectra, a generative framework that formulates molecular structure elucidation as a conditional generation process, directly inferring 2D and 3D molecular structures from multi-modal spectra using diffusion models. Its denoising network is parameterized by the Diffusion Molecule Transformer, an SE(3)-equivariant architecture for geometric modeling, conditioned by SpecFormer, a Transformer-based spectral encoder capturing multi-modal spectral dependencies. Extensive experiments demonstrate that DiffSpectra accurately elucidates molecular structures, achieving 40.76% top-1 and 99.49% top-10 accuracy. Its performance benefits substantially from 3D geometric modeling, SpecFormer pre-training, and multi-modal conditioning. To our knowledge, DiffSpectra is the first framework that unifies multi-modal spectral reasoning and joint 2D/3D generative modeling for de novo molecular structure elucidation. △ Less

Submitted 5 November, 2025; v1 submitted 9 July, 2025; originally announced July 2025.

In situ Thermal Trimming of Waveguides in a Standard Active Silicon Photonics Platform

Authors: Tianyuan Xue, Hannes Wahn, Andrei Stalmashonak, Joyce K. S. Poon, Wesley D. Sacher

Abstract: We present suspended heater structures fabricated in a standard C- and O-band silicon (Si) photonics platform that can achieve sufficiently high local temperatures to induce effective refractive index trimming of Si and silicon nitride (SiN) waveguides with 30 - 90 mW of applied electrical power. Following thermal trimming at moderate powers ($\leq$ 40 mW), maximum changes in the averaged waveguid… ▽ More We present suspended heater structures fabricated in a standard C- and O-band silicon (Si) photonics platform that can achieve sufficiently high local temperatures to induce effective refractive index trimming of Si and silicon nitride (SiN) waveguides with 30 - 90 mW of applied electrical power. Following thermal trimming at moderate powers ($\leq$ 40 mW), maximum changes in the averaged waveguide effective refractive index of $-5.18 \times 10^{-3}$ and $-7.9 \times 10^{-4}$ are demonstrated in SiN and Si waveguides, respectively, at a wavelength of 1550 nm. At higher powers, SiN waveguides exhibit positive averaged effective index changes up to $\approx$0.02, demonstrating bi-directional index trimming. As an example application, we demonstrate bias point trimming of a carrier injection Mach-Zehnder switch. Through investigations of the origin of the thermal trimming effect, we hypothesize that changes in the silica (SiO$_2$) waveguide cladding may be a primary underlying mechanism at temperatures $\gtrsim$300$^{\circ}$C, with significant trimming of SiN waveguide cores occurring at larger temperatures $\gtrsim$510$^{\circ}$C. As the trimming experiments represent a form of accelerated thermal aging, we estimate the aging behavior of the suspended heaters by fitting and extrapolating the measured datasets to 100 - 200$^{\circ}$C operating temperatures over five years. △ Less

Submitted 16 June, 2025; originally announced June 2025.

Comments: 19 pages, 13 figures

Journal ref: Opt. Express 33, 43542-43560 (2025)

Efficient algorithms for quantum chemistry on modular quantum processors

Authors: Tian Xue, Jacob P. Covey, Matthew Otten

Abstract: Quantum chemistry is a promising application of future quantum computers, but the requirements on qubit count and other resources suggest that modular computing architectures will be required. We introduce an implementation of a quantum chemistry algorithm that is distributed across several computational modules: the distributed unitary selective coupled cluster (dUSCC). We design a packing scheme… ▽ More Quantum chemistry is a promising application of future quantum computers, but the requirements on qubit count and other resources suggest that modular computing architectures will be required. We introduce an implementation of a quantum chemistry algorithm that is distributed across several computational modules: the distributed unitary selective coupled cluster (dUSCC). We design a packing scheme using the pseudo-commutativity of Trotterization to maximize the parallelism while optimizing the scheduling of all inter-module gates around the buffering of inter-module Bell pairs. We demonstrate dUSCC on a 3-cluster (H$_4$)$_3$ chain and show that it naturally utilizes the molecule's structure to reduce inter-module latency. We show that the run time of dUSCC is unchanged with inter-module latency up to $\sim$20$\times$ slower than intra-module gates in the (H$_4$)$_3$ while maintaining chemical accuracy. dUSCC should be "free" in the weakly entangled systems, and the existence of "free" dUSCC can be found efficiently using classical algorithms. This new compilation scheme both leverages pseudo-commutativity and considers inter-module gate scheduling, and potentially provides an efficient distributed compilation of other Trotterized algorithms. △ Less

Submitted 23 January, 2026; v1 submitted 16 June, 2025; originally announced June 2025.

Inverse Design of Metamaterials with Manufacturing-Guiding Spectrum-to-Structure Conditional Diffusion Model

Authors: Jiawen Li, Jiang Guo, Yuanzhe Li, Zetian Mao, Jiaxing Shen, Tashi Xu, Diptesh Das, Jinming He, Run Hu, Yaerim Lee, Koji Tsuda, Junichiro Shiomi

Abstract: Metamaterials are artificially engineered structures that manipulate electromagnetic waves, having optical properties absent in natural materials. Recently, machine learning for the inverse design of metamaterials has drawn attention. However, the highly nonlinear relationship between the metamaterial structures and optical behaviour, coupled with fabrication difficulties, poses challenges for usi… ▽ More Metamaterials are artificially engineered structures that manipulate electromagnetic waves, having optical properties absent in natural materials. Recently, machine learning for the inverse design of metamaterials has drawn attention. However, the highly nonlinear relationship between the metamaterial structures and optical behaviour, coupled with fabrication difficulties, poses challenges for using machine learning to design and manufacture complex metamaterials. Herein, we propose a general framework that implements customised spectrum-to-shape and size parameters to address one-to-many metamaterial inverse design problems using conditional diffusion models. Our method exhibits superior spectral prediction accuracy, generates a diverse range of patterns compared to other typical generative models, and offers valuable prior knowledge for manufacturing through the subsequent analysis of the diverse generated results, thereby facilitating the experimental fabrication of metamaterial designs. We demonstrate the efficacy of the proposed method by successfully designing and fabricating a free-form metamaterial with a tailored selective emission spectrum for thermal camouflage applications. △ Less

Submitted 8 June, 2025; originally announced June 2025.

Comments: 20 pages, 7 figures

Thermally Induced Refractive Index Trimming of Visible-Light Silicon Nitride Waveguides Using Suspended Heaters

Authors: Hong Chen, Tianyuan Xue, Zheng Yong, Xianshu Luo, Hongyao Chua, Andrei Stalmashonak, Guo-Qiang Lo, Joyce K. S. Poon, Wesley D. Sacher

Abstract: We demonstrate refractive index trimming of visible-light silicon nitride (SiN) waveguides using suspended heater structures. The thermal isolation of the suspended heaters enabled a semi-uniform temperature distribution with estimated temperatures of $\sim$350°C in the waveguides without reaching potentially damaging temperatures in the titanium nitride resistive heaters. The thermal isolation al… ▽ More We demonstrate refractive index trimming of visible-light silicon nitride (SiN) waveguides using suspended heater structures. The thermal isolation of the suspended heaters enabled a semi-uniform temperature distribution with estimated temperatures of $\sim$350°C in the waveguides without reaching potentially damaging temperatures in the titanium nitride resistive heaters. The thermal isolation also enabled trimming temperatures to be reached with a moderate power dissipation of 30 to 40 mW. At a wavelength of 561 nm, modal effective index changes up to $-8.3 \times 10^{-3}$ were observed following thermal trimming, and the index changes were stable over an observation period of 97 days. The devices were fabricated as part of our visible-light integrated photonics platform on 200-mm diameter silicon wafers. The suspended heaters also functioned as efficient thermo-optic phase shifters with power dissipation for a $π$ phase shift of about $1.2-1.8$ mW. The trimming method was applied to set the bias points of thermo-optic Mach-Zehnder interferometer switches to reduce the bias power of five devices from $0.29-2.32$ mW to $0.1-0.16$ mW. Thermal trimming at a wavelength of 445 nm was also demonstrated. Through material analysis before and after thermal treatment, we hypothesize that index trimming of the silica (SiO$_2$) waveguide cladding may be a potential underlying mechanism. Additionally, via extrapolations of the measured trimming data, we estimate the thermal aging behavior of the SiN waveguides in the suspended heaters at lower (125 - 250°C) operating temperatures. △ Less

Submitted 29 April, 2025; originally announced April 2025.

Comments: 21 pages, 8 figures

Journal ref: Opt. Express 33, 48925-48944 (2025)

Focusing of Relativistic Electron Beams With Permanent Magnetic Solenoid

Authors: T. Xu, C. J. R. Duncan, P. Denham, B. H. Schaap, A. Kulkarni, D. Garcia, S. D. Anderson, P. Musumeci, R. J. England

Abstract: Achieving strong focusing of MeV electron beams is a critical requirement for advanced beam applications such as compact laboratory X-ray sources, high gradient accelerators, and ultrafast electron scattering instrumentation. To address these needs, a compact radially magnetized permanent magnetic solenoid (PMS) has been designed, fabricated, and tested. The solenoid provides a compact and inexpen… ▽ More Achieving strong focusing of MeV electron beams is a critical requirement for advanced beam applications such as compact laboratory X-ray sources, high gradient accelerators, and ultrafast electron scattering instrumentation. To address these needs, a compact radially magnetized permanent magnetic solenoid (PMS) has been designed, fabricated, and tested. The solenoid provides a compact and inexpensive solution for delivering high axial magnetic fields (1 Tesla) to focus MeV electron beams. Field characterization of the solenoid demonstrates excellent agreement with analytical models, validating the PMS design. The electron beam test employs a high-brightness photoinjector to study the focusing properties of the PMS. The results indicate a focal length of less than 10 cm and a significant reduction in beam size with small spherical aberrations. Two application cases are evaluated: angular magnification in ultrafast electron diffraction setups and strong focusing for Compton scattering or other microfocus uses. △ Less

Submitted 29 April, 2025; originally announced April 2025.

Comments: 10 pages, 9 figures

Beyond Terabit/s Integrated Neuromorphic Photonic Processor for DSP-Free Optical Interconnects

Authors: Benshan Wang, Qiarong Xiao, Tengji Xu, Li Fan, Shaojie Liu, Jianji Dong, Junwen Zhang, Chaoran Huang

Abstract: The rapid expansion of generative AI drives unprecedented demands for high-performance computing. Training large-scale AI models now requires vast interconnected GPU clusters across multiple data centers. Multi-scale AI training and inference demand uniform, ultra-low latency, and energy-efficient links to enable massive GPUs to function as a single cohesive unit. However, traditional electrical a… ▽ More The rapid expansion of generative AI drives unprecedented demands for high-performance computing. Training large-scale AI models now requires vast interconnected GPU clusters across multiple data centers. Multi-scale AI training and inference demand uniform, ultra-low latency, and energy-efficient links to enable massive GPUs to function as a single cohesive unit. However, traditional electrical and optical interconnects, relying on conventional digital signal processors (DSPs) for signal distortion compensation, increasingly fail to meet these stringent requirements. To overcome these limitations, we present an integrated neuromorphic optical signal processor (OSP) that leverages deep reservoir computing and achieves DSP-free, all-optical, real-time processing. Experimentally, our OSP achieves a 100 Gbaud PAM4 per lane, 1.6 Tbit/s data center interconnect over a 5 km optical fiber in the C-band (equivalent to over 80 km in the O-band), far exceeding the reach of state-of-the-art DSP solutions, which are fundamentally constrained by chromatic dispersion in IMDD systems. Simultaneously, it reduces processing latency by four orders of magnitude and energy consumption by three orders of magnitude. Unlike DSPs, which introduce increased latency at high data rates, our OSP maintains consistent, ultra-low latency regardless of data rate scaling, making it ideal for future optical interconnects. Moreover, the OSP retains full optical field information for better impairment compensation and adapts to various modulation formats, data rates, and wavelengths. Fabricated using a mature silicon photonic process, the OSP can be monolithically integrated with silicon photonic transceivers, enhancing the compactness and reliability of all-optical interconnects. This research provides a highly scalable, energy-efficient, and high-speed solution, paving the way for next-generation AI infrastructure. △ Less

Submitted 21 April, 2025; originally announced April 2025.

Comments: 22 pages, 6 figures

Constraints on dark matter boosted by supernova shock within the effective field theory framework from the CDEX-10 experiment

Authors: J. Z. Wang, L. T. Yang, Q. Yue, K. J. Kang, Y. J. Li, H. P. An, Greeshma C., J. P. Chang, H. Chen, Y. H. Chen, J. P. Cheng, W. H. Dai, Z. Deng, C. H. Fang, X. P. Geng, H. Gong, Q. J. Guo, T. Guo, X. Y. Guo, L. He, J. R. He, H. X. Huang, T. C. Huang, S. Karmakar, H. B. Li , et al. (62 additional authors not shown)

Abstract: Supernova shocks can boost dark matter (DM) particles to high, yet nonrelativistic, velocities, providing a suitable mechanism for analysis within the framework of the nonrelativistic effective field theory (NREFT). These accelerated DM sources extend the experimental ability to scan the parameter space of light DM into the sub-GeV region. In this study, we specifically analyze DM accelerated by t… ▽ More Supernova shocks can boost dark matter (DM) particles to high, yet nonrelativistic, velocities, providing a suitable mechanism for analysis within the framework of the nonrelativistic effective field theory (NREFT). These accelerated DM sources extend the experimental ability to scan the parameter space of light DM into the sub-GeV region. In this study, we specifically analyze DM accelerated by the Monogem Ring supernova remnant, whose age ($\sim 68000$ yr) and distance to Earth ($\sim 300$ parsec) are strategically matched to enable detection with current terrestrial detectors. Utilizing the 205.4 kg$\cdot$day data obtained from the CDEX-10 experiment at the China Jinping Underground Laboratory, we derive new constraints on boosted DM within the NREFT framework. The NREFT coupling constant exclusion regions now penetrate the sub-GeV mass range, with optimal sensitivity achieved for operators $\mathcal{O}_{3}$, $\mathcal{O}_{6}$, $\mathcal{O}_{15}$ in the 0.4--0.6 GeV mass range. △ Less

Submitted 18 November, 2025; v1 submitted 4 April, 2025; originally announced April 2025.

Comments: 9 pages, 5 figures. Version updated to match PRD version

Journal ref: Phys. Rev. D 112, 092011 (2025)

Power-efficient ultra-broadband soliton microcombs in resonantly-coupled microresonators

Authors: Kaixuan Zhu, Xinrui Luo, Yuanlei Wang, Ze Wang, Tianyu Xu, Du Qian, Yinke Cheng, Junqi Wang, Haoyang Luo, Yanwu Liu, Xing Jin, Zhenyu Xie, Xin Zhou, Min Wang, Jian-Fei Liu, Xuening Cao, Ting Wang, Shui-Jing Tang, Qihuang Gong, Bei-Bei Li, Qi-Fan Yang

Abstract: The drive to miniaturize optical frequency combs for practical deployment has spotlighted microresonator solitons as a promising chip-scale candidate. However, these soliton microcombs could be very power-hungry when their span increases, especially with fine comb spacings. As a result, realizing an octave-spanning comb at microwave repetition rates for direct optical-microwave linkage is consider… ▽ More The drive to miniaturize optical frequency combs for practical deployment has spotlighted microresonator solitons as a promising chip-scale candidate. However, these soliton microcombs could be very power-hungry when their span increases, especially with fine comb spacings. As a result, realizing an octave-spanning comb at microwave repetition rates for direct optical-microwave linkage is considered not possible for photonic integration due to the high power requirements. Here, we introduce the concept of resonant-coupling to soliton microcombs to reduce pump consumption significantly. Compared to conventional waveguide-coupled designs, we demonstrate (i) a threefold increase in spectral span for high-power combs and (ii) up to a tenfold reduction in repetition frequency for octave-spanning operation. This configuration is compatible with laser integration and yields reliable, turnkey soliton generation. By eliminating the long-standing pump-power bottleneck, microcombs will soon become readily available for portable optical clocks, massively parallel data links, and field-deployable spectrometers. △ Less

Submitted 15 July, 2025; v1 submitted 3 March, 2025; originally announced March 2025.

Compact Turnkey Soliton Microcombs at Microwave Rates via Wafer-Scale Fabrication

Authors: Yuanlei Wang, Ze Wang, Chenghao Lao, Tianyu Xu, Yinke Cheng, Zhenyu Xie, Junqi Wang, Haoyang Luo, Xin Zhou, Bo Ni, Kaixuan Zhu, Yanwu Liu, Xing Jin, Min Wang, Jian-Fei Liu, Xuening Cao, Ting Wang, Qihuang Gong, Bei-Bei Li, Fangxing Zhang, Yun-Feng Xiao, Qi-Fan Yang

Abstract: Soliton microcombs generated in nonlinear microresonators facilitate the photonic integration of timing, frequency synthesis, and astronomical calibration functionalities. For these applications, low-repetition-rate soliton microcombs are essential as they establish a coherent link between optical and microwave signals. However, the required pump power typically scales with the inverse of the repe… ▽ More Soliton microcombs generated in nonlinear microresonators facilitate the photonic integration of timing, frequency synthesis, and astronomical calibration functionalities. For these applications, low-repetition-rate soliton microcombs are essential as they establish a coherent link between optical and microwave signals. However, the required pump power typically scales with the inverse of the repetition rate, and the device footprint scales with the inverse of square of the repetition rate, rendering low-repetition-rate soliton microcombs challenging to integrate within photonic circuits. This study designs and fabricates silicon nitride microresonators on 4-inch wafers with highly compact form factors. The resonator geometries are engineered from ring to finger and spiral shapes to enhance integration density while attaining quality factors over 10^7. Driven directly by an integrated laser, soliton microcombs with repetition rates below 10 GHz are demonstrated via turnkey initiation. The phase noise performance of the synthesized microwave signals reaches -130 dBc/Hz at 100 kHz offset frequency for 10 GHz carrier frequencies. This work enables the high-density integration of soliton microcombs for chip-based microwave photonics and spectroscopy applications. △ Less

Submitted 15 February, 2025; originally announced February 2025.

Comments: 10 pages, 6 figures

Scintillation response of Ga2O3 excited by laser accelerated ultra-high dose rate proton beam

Authors: Yulan Liang, Tianqi Xu, Shirui Xu, Qingfan Wu, Chaoyi Zhang, Haoran Chen, Qihang Han, Chenhao Hua, Jianming Xue, Huili Tang, Bo Liu, Wenjun Ma

Abstract: The temporal and spectral profile of \b{eta}-Ga2O3 excited by ultra-high dose rate proton beam has been investigated. The unique short bright and broad spectra characteristics of laser-accelerated protons were utilized to investigate the scintillation response difference under different dose rate. Our results indicate that for sufficiently high dose rate delivered, the average decay time of \b{eta… ▽ More The temporal and spectral profile of \b{eta}-Ga2O3 excited by ultra-high dose rate proton beam has been investigated. The unique short bright and broad spectra characteristics of laser-accelerated protons were utilized to investigate the scintillation response difference under different dose rate. Our results indicate that for sufficiently high dose rate delivered, the average decay time of \b{eta}-Ga2O3 decreases by a factor of two. The overlap of carriers generated by high dose rate protons enhances the nonradiative recombination like Auger recombination and exciton-exciton annihilation which shortens the decay time significantly. The study opens up new avenues for investigating the luminescent properties of other scintillator materials using laser-accelerated high dose rate proton beams. △ Less

Submitted 8 February, 2025; originally announced February 2025.

SolarDesign: An Online Photovoltaic Device Simulation and Design Platform

Authors: Wei E. I. Sha, Xiaoyu Wang, Wenchao Chen, Yuhao Fu, Lijun Zhang, Liang Tian, Minshen Lin, Shudi Jiao, Ting Xu, Tiange Sun, Dongxue Liu

Abstract: SolarDesign (https://solardesign.cn/) is an online photovoltaic device simulation and design platform that provides engineering modeling analysis for crystalline silicon solar cells, as well as emerging high-efficiency solar cells such as organic, perovskite, and tandem cells. The platform offers user-updatable libraries of basic photovoltaic materials and devices, device-level multi-physics simul… ▽ More SolarDesign (https://solardesign.cn/) is an online photovoltaic device simulation and design platform that provides engineering modeling analysis for crystalline silicon solar cells, as well as emerging high-efficiency solar cells such as organic, perovskite, and tandem cells. The platform offers user-updatable libraries of basic photovoltaic materials and devices, device-level multi-physics simulations involving optical-electrical-thermal interactions, and circuit-level compact model simulations based on detailed balance theory. Employing internationally advanced numerical methods, the platform accurately, rapidly, and efficiently solves optical absorption, electrical transport, and compact circuit models. It achieves multi-level photovoltaic simulation technology from ``materials to devices to circuits'' with fully independent intellectual property rights. Compared to commercial software, the platform achieves high accuracy and improves speed by more than an order of magnitude. Additionally, it can simulate unique electrical transport processes in emerging solar cells, such as quantum tunneling, exciton dissociation, and ion migration. △ Less

Submitted 27 December, 2024; originally announced December 2024.

Comments: 12 pages, 7 figures, 3 tables

Journal ref: Chinese Physics B 34(1): 018801, 2024

Online training and pruning of multi-wavelength photonic neural networks

Authors: Jiawei Zhang, Weipeng Zhang, Tengji Xu, Lei Xu, Eli A. Doris, Bhavin J. Shastri, Chaoran Huang, Paul R. Prucnal

Abstract: CMOS-compatible photonic integrated circuits (PICs) are emerging as a promising platform in artificial intelligence (AI) computing. Owing to the compact footprint of microring resonators (MRRs) and the enhanced interconnect efficiency enabled by wavelength division multiplexing (WDM), MRR-based photonic neural networks (PNNs) are particularly promising for large-scale integration. However, the sca… ▽ More CMOS-compatible photonic integrated circuits (PICs) are emerging as a promising platform in artificial intelligence (AI) computing. Owing to the compact footprint of microring resonators (MRRs) and the enhanced interconnect efficiency enabled by wavelength division multiplexing (WDM), MRR-based photonic neural networks (PNNs) are particularly promising for large-scale integration. However, the scalability and energy efficiency of such systems are fundamentally limited by the MRR resonance wavelength variations induced by fabrication process variations (FPVs) and environmental fluctuations. Existing solutions use post-fabrication approaches or thermo-optic tuning, incurring high control power and additional process complexity. In this work, we introduce an online training and pruning method that addresses this challenge, adapting to FPV-induced and thermally induced shifts in MRR resonance wavelength. By incorporating a power-aware pruning term into the conventional loss function, our approach simultaneously optimizes the PNN accuracy and the total power consumption for MRR tuning. In proof-of-concept on-chip experiments on the Iris dataset, our system PNNs can adaptively train to maintain a 96% classification accuracy, while achieving a 44.7% reduction in tuning power via pruning. Additionally, our approach reduces the power consumption by orders-of-magnitude on larger datasets. By addressing chip-to-chip variation and minimizing power requirements, our approach significantly improves the scalability and energy efficiency of MRR-based integrated analog photonic processors, paving the way for large-scale PICs to enable versatile applications including neural networks, photonic switching, LiDAR, and radio-frequency beamforming. △ Less

Submitted 11 June, 2025; v1 submitted 11 December, 2024; originally announced December 2024.

Comments: 21 pages, 5 figures

Journal ref: Nanophotonics 14, 5035-5046 (2025)

Perfecting Imperfect Physical Neural Networks with Transferable Robustness using Sharpness-Aware Training

Authors: Tengji Xu, Zeyu Luo, Shaojie Liu, Li Fan, Qiarong Xiao, Benshan Wang, Dongliang Wang, Chaoran Huang

Abstract: AI models are essential in science and engineering, but recent advances are pushing the limits of traditional digital hardware. To address these limitations, physical neural networks (PNNs), which use physical substrates for computation, have gained increasing attention. However, developing effective training methods for PNNs remains a significant challenge. Current approaches, regardless of offli… ▽ More AI models are essential in science and engineering, but recent advances are pushing the limits of traditional digital hardware. To address these limitations, physical neural networks (PNNs), which use physical substrates for computation, have gained increasing attention. However, developing effective training methods for PNNs remains a significant challenge. Current approaches, regardless of offline and online training, suffer from significant accuracy loss. Offline training is hindered by imprecise modeling, while online training yields device-specific models that can't be transferred to other devices due to manufacturing variances. Both methods face challenges from perturbations after deployment, such as thermal drift or alignment errors, which make trained models invalid and require retraining. Here, we address the challenges with both offline and online training through a novel technique called Sharpness-Aware Training (SAT), where we innovatively leverage the geometry of the loss landscape to tackle the problems in training physical systems. SAT enables accurate training using efficient backpropagation algorithms, even with imprecise models. PNNs trained by SAT offline even outperform those trained online, despite modeling and fabrication errors. SAT also overcomes online training limitations by enabling reliable transfer of models between devices. Finally, SAT is highly resilient to perturbations after deployment, allowing PNNs to continuously operate accurately under perturbations without retraining. We demonstrate SAT across three types of PNNs, showing it is universally applicable, regardless of whether the models are explicitly known. This work offers a transformative, efficient approach to training PNNs, addressing critical challenges in analog computing and enabling real-world deployment. △ Less

Submitted 19 November, 2024; originally announced November 2024.

Comments: 24 pages, 4 figures