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Composing Flow-Matching Energies with Known Physics: Generation, OOD Detection, and Inversion on PDE Fields
Authors:
Yixuan Sun,
Anirban Samaddar,
Sandeep Madireddy
Abstract:
Probabilistic modeling of physical fields benefits from both a data-driven prior and known physical structure such as the governing equations. Energy-based models (EBMs) are a natural fit since energies compose additively, which enables augmenting physics information during inference. However, EBMs have been difficult to train and sample from due to the intractable partition function. We show in t…
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Probabilistic modeling of physical fields benefits from both a data-driven prior and known physical structure such as the governing equations. Energy-based models (EBMs) are a natural fit since energies compose additively, which enables augmenting physics information during inference. However, EBMs have been difficult to train and sample from due to the intractable partition function. We show in this work that flow matching models with a potential-induced velocity yield an explicit scalar energy at all transport times, whose gradient is exactly the converted learned score and which recovers the marginal negative log-density at the population optimum. The time-dependent energy functions are obtained purely from the matching regression objective on an independent linear Gaussian interpolation, without a variational form or additional MCMC steps, and the sampling retains the flow ODE. Access to the energy function from a trained model serves three roles: energy-corrected data generation, energy as a scoring function for out-of-distribution (OOD) detection, and energy compositional posterior sampling for inverse problems. In particular, we show the explicit energy permits general MCMC samplers in the predictor-corrector sampling framework, reducing PDE residual and spectral distance compared to the flow ODE baseline. Furthermore, we demonstrate utilizing the data energy and physics-based energy (e.g., PDE residuals) as complementary mechanisms to improve detection accuracy for OOD tasks. In addition, we explore the connection to MCMC-based inference for inverse problems by composing the energy with a quadratic observational likelihood that yields a posterior energy, used as an explicitly chosen family of inference-time targets.
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Submitted 18 August, 2026;
originally announced August 2026.
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Reconfigurable microwave photonic Fano filters based on optical Kerr microcombs
Authors:
Qi Zou,
Jiayang Wu,
Yang Sun,
Yang Li,
Guanghui Ren,
Thach G. Nguyen,
Xingyuan Xu,
Bill Corcoran,
Sai T. Chu,
Roberto Morandotti,
Arnan Mitchell,
David J. Moss
Abstract:
Microwave photonic (MWP) Fano filters, featuring asymmetric filter shapes that enable steep spectral transitions, are attractive for high bandwidth microwave signal processing such as frequency discrimination. However, achieving both steep spectral transitions and a high degree of reconfigurability remains challenging for conventional methods relying on direct mapping of Fano resonances generated…
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Microwave photonic (MWP) Fano filters, featuring asymmetric filter shapes that enable steep spectral transitions, are attractive for high bandwidth microwave signal processing such as frequency discrimination. However, achieving both steep spectral transitions and a high degree of reconfigurability remains challenging for conventional methods relying on direct mapping of Fano resonances generated by optical filters. Here, we propose and experimentally demonstrate a new way for realizing MWP Fano filters based on a microcomb-driven transversal filter system. Leveraging the large number of comb lines provided by microcombs as discrete taps, the transversal filter system can synthesize filter response that closely resembles Fano resonances, yielding high rolloff rates and slope rates up to 33.8 dB / GHz and 25.7 dB / GHz in our experiments, respectively. In addition, by simply programming the tap coefficients without changing any hardware, highly reconfigurable filter response can be realized. We experimentally demonstrate independent tuning of all three Fano characteristic parameters, including the asymmetry factor, resonance linewidth, and center frequency. These results verify the effectiveness of our approach for implementing highly reconfigurable MWP Fano filters with steep spectral transitions, offering strong versatility for meeting diverse requirements in practical applications.
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Submitted 15 August, 2026;
originally announced August 2026.
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Cross-frequency amplification of perturbations in a laminar separation bubble using resolvent analysis
Authors:
Md Rashidul Islam,
Yiyang Sun
Abstract:
A large-eddy simulation (LES) of a laminar separation bubble (LSB) induced by an adverse pressure gradient over a flat plate is performed at an inflow displacement-thickness-based Reynolds number of 410 and a free-stream Mach number of 0.25. With a mean peak reverse flow of 21.4%, the bubble sustains self-excited vortex shedding through a local region of absolute instability, in the absence of any…
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A large-eddy simulation (LES) of a laminar separation bubble (LSB) induced by an adverse pressure gradient over a flat plate is performed at an inflow displacement-thickness-based Reynolds number of 410 and a free-stream Mach number of 0.25. With a mean peak reverse flow of 21.4%, the bubble sustains self-excited vortex shedding through a local region of absolute instability, in the absence of any external forcing. Spectral proper orthogonal decomposition (SPOD) applied to the LES data identifies three dominant coherent structures within the LSB: two-dimensional and oblique Kelvin--Helmholtz (KH) waves in the separated shear layer at the vortex-shedding frequency, and stationary spanwise-periodic streaks near reattachment at near-zero frequency. Classical resolvent analysis of the mean flow identifies strong convective amplification of the KH waves over a range of spanwise wavenumbers, but predicts only weak amplification in the low-frequency, streak-forming region, where the leading gain is orders of magnitude smaller and no dominant rank-one mechanism is present. This discrepancy with the SPOD energy indicates that the streaks are not sustained by same-frequency linear amplification, but are instead energized by the intrinsic forcing, which the classical framework treats as an unexplained input. Harmonic resolvent analysis of the time-periodic base flow reveals the underlying mechanism: the base-flow unsteadiness couples the oblique KH wave at the shedding frequency to the stationary streak through cross-frequency amplification, yielding a gain far larger than that of the direct same-frequency amplification. This cross-frequency route provides a likely explanation for how the stationary streaks observed near reattachment are energized.
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Submitted 13 August, 2026;
originally announced August 2026.
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A unified reconstruction algorithm for reduced-frame structured illumination microscopy
Authors:
Jingxiang Zhang,
Tianyu Zhao,
Manming Shu,
Keru Mou,
Zheming Zhang,
Yihan Sun,
Mengrui Wang,
Yansheng Liang,
Shaowei Wang,
Ming Lei
Abstract:
Reduced-frame structured illumination microscopy (SIM) is attractive for live-cell imaging because it can improve temporal throughput and reduce photobleaching, but incomplete phase sampling makes reconstruction unstable and computationally demanding. Here we present URA-SIM, a unified reduced-acquisition framework that turns fixed reduced-frame measurements into pipeline- compatible raw stacks th…
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Reduced-frame structured illumination microscopy (SIM) is attractive for live-cell imaging because it can improve temporal throughput and reduce photobleaching, but incomplete phase sampling makes reconstruction unstable and computationally demanding. Here we present URA-SIM, a unified reduced-acquisition framework that turns fixed reduced-frame measurements into pipeline- compatible raw stacks through model-consistent phase-domain completion. Instead of solving a large object-level inverse problem or replacing established SIM reconstruction, URA-SIM estimates the missing phase content on the low-dimensional phase-harmonic manifold required by the target modality and then delegates order separation and image formation to classical reconstruction pipeline. This design combines three practical advantages: fidelity from the SIM forward structure, lightweight online computation, and direct compatibility with existing reconstruction workflows. For 2D-SIM, URA-SIM uses the first-harmonic phase structure of three-phase SIM to estimate a shared zero-order field and complete missing phase samples by direction-wise harmonic fitting. On calibration and biological 2D-SIM data, reduced-frame reconstructions preserve resolvable structures and remain competitive on COS7 mitochondria comparison data. In live-cell COS7 mitochondria imaging, URA-SIM reconstructs each time point from five acquired raw frames and resolves mitochondrial cristae across different temporal sampling regimes. Experiments on 3D-SIM and nonlinear SIM further show that the same design principle can be transferred when the phase model and reconstruction-pipeline interface are adapted to the target modality. These results support URA-SIM as a transparent, model-consistent and computationally lightweight route from fixed reduced-frame acquisition to classical SIM reconstruction workflows.
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Submitted 13 August, 2026;
originally announced August 2026.
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Linear and nonlinear benchmark of gyrokinetic simulation of energetic particle driven toroidal Alfven eigenmodes in ITPA TAE benchmark case
Authors:
Youjun Hu,
Yang Chen,
Lei Ye,
Zhiyong Qiu,
Youwen Sun
Abstract:
A new gyrokinetic code, TEK, was benchmarked in simulating energetic particle (EP) driven toroidal Alfven eigenmodes (TAEs) in the simple tokamak configuration chosen by the ITPA-EP group for code benchmarking purpose. Linear benchmark has been well established by other codes, whereas nonlinear benchmark for this case is lacking. This paper presents, besides the linear benchmark, nonlinear results…
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A new gyrokinetic code, TEK, was benchmarked in simulating energetic particle (EP) driven toroidal Alfven eigenmodes (TAEs) in the simple tokamak configuration chosen by the ITPA-EP group for code benchmarking purpose. Linear benchmark has been well established by other codes, whereas nonlinear benchmark for this case is lacking. This paper presents, besides the linear benchmark, nonlinear results for both single-n and multiple-n simulations (n is the toroidal mode number). The nonlinear results are in good agreement with an analytical theory on zonal field beat-driven by Alfven eigenmodes, partially verifying correctness of the nonlinear simulations. The saturation level and the resulting EP transport are examined. This provides data for future inter-code nonlinear benchmarking. In TEK, all species (electrons, thermal ions, EPs) are treated on the same footing using the gyrokinetic model (with electrons in the zero Larmor radius limit). The electromagnetic cancellation problem is mitigated by using the mixed-variable pullback method. Numerical details related to electromagnetic gyrokinetic simulation are discussed.
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Submitted 6 August, 2026;
originally announced August 2026.
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TIDE: A Physically Diverse 3D Turbulence Benchmark Dataset for Advancing Scientific Machine Learning
Authors:
Yilong Dai,
Yiming Sun,
Yiheng Chen,
Shengyu Chen,
Peyman Givi,
Xiaowei Jia,
Runlong Yu
Abstract:
Turbulence is a central testbed for machine learning on physical dynamics because its governing laws are known exactly. However, most existing studies remain in 2D, while 3D turbulence has fundamentally different physics and is far more costly to simulate. Existing 3D resources also typically provide only one realization per configuration, making it difficult to distinguish learning the dynamics f…
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Turbulence is a central testbed for machine learning on physical dynamics because its governing laws are known exactly. However, most existing studies remain in 2D, while 3D turbulence has fundamentally different physics and is far more costly to simulate. Existing 3D resources also typically provide only one realization per configuration, making it difficult to distinguish learning the dynamics from fitting the statistics of a single flow. In this paper, we introduce TIDE (Turbulent Incompressible DNS Ensembles), a 256^3 DNS corpus and benchmark for 3D incompressible turbulence, with 15 configurations on eight controlled axes, independent ensembles, pressure fields, and equation-level verification. The benchmark includes five tasks, standardized learned baselines, controlled generalization splits, and physical-fidelity metrics alongside pointwise error. Across the main forecasting configurations, current learned models barely outperform persistence and still make about twice the error of a spectral solver given the true equations. Moreover, lower pointwise error can coincide with severely distorted small-scale dynamics, showing that accuracy alone does not ensure physical fidelity. Generalization results further show that most regime shifts reflect limited training coverage, whereas forced-to-decay transfer exposes a missing conditioning variable: operators trained under forcing continue to predict driven evolution when the external drive is removed. Closing these accuracy, fidelity, and conditioning gaps is the central open problem made measurable by TIDE.
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Submitted 4 August, 2026;
originally announced August 2026.
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ScoreField: Neural Inverse Scattering with Score-Based Generative Priors
Authors:
Wenhan Guo,
Yuan Gao,
Yu Sun
Abstract:
Designing an effective electromagnetic inverse-scattering solver requires faithful enforcement of nonlinear full-wave physics together with an expressive prior on the unknown permittivity contrast. We propose ScoreField, a neural inverse scattering framework that integrates coupled implicit neural representations (INRs) with a pretrained score-based generative prior. ScoreField employs two INRs to…
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Designing an effective electromagnetic inverse-scattering solver requires faithful enforcement of nonlinear full-wave physics together with an expressive prior on the unknown permittivity contrast. We propose ScoreField, a neural inverse scattering framework that integrates coupled implicit neural representations (INRs) with a pretrained score-based generative prior. ScoreField employs two INRs to parameterize the permittivity contrast and the induced current fields, and jointly optimize them under the Lippmann-Schwinger equations. In addition to the implicit regularization by the INR architecture, the score model provides a learned prior gradient on the contrast, which is propagated to the contrast INR through the chain rule. This formulation enables ScoreField to effectively handle strong multiple scattering, where nonlinear wave interactions require accurate modeling of the coupled full-wave physics. We evaluate ScoreField on simulated weak- and strong-scattering benchmarks, the canonical Austria phantom, and experimental Fresnel measurements. We note that ScoreField significantly improves reconstruction fidelity and suppresses artifacts relative to classical full-wave methods and deep learning baselines, achieving an average PSNR improvement of $1.8 \, \mathrm{dB}$ over the best competing method on real Fresnel data.
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Submitted 3 August, 2026;
originally announced August 2026.
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Transverse coupled-bunch instabilities driven by high-order modes near the coupling resonance
Authors:
You Sun,
Weiwei Li,
Tianlong He,
Penghui Yang,
Xiaoyu Liu,
Zhenghe Bai
Abstract:
Betatron coupling near the difference resonance has been explored and adopted in several fourth-generation storage rings, yet its influence on high-order-mode-driven transverse coupled-bunch instabilities has not been systematically established. Using the Hefei Advanced Light Facility (HALF) as an example, we investigate this effect through theoretical analysis and macroparticle tracking simulatio…
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Betatron coupling near the difference resonance has been explored and adopted in several fourth-generation storage rings, yet its influence on high-order-mode-driven transverse coupled-bunch instabilities has not been systematically established. Using the Hefei Advanced Light Facility (HALF) as an example, we investigate this effect through theoretical analysis and macroparticle tracking simulations. The theoretical predictions agree well with macroparticle tracking simulations in both the weak- and strong-instability regimes, validating the description over the parameter ranges considered. For the vertical HOMs studied with HALF parameters, suitable betatron coupling effectively suppresses the instability, offering potential benefits for transverse stability control.
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Submitted 3 August, 2026;
originally announced August 2026.
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Spin-canting-induced Giant Nonlinear Optical Magnetochirality in a 2D Ferrotoroid
Authors:
Shian Xia,
Sheng Liu,
Wenhe Jia,
Fanglu Qin,
Xuanji Wang,
Haixiang Luo,
Yue Sun,
Vanessa Li Zhang,
Wenduo Chen,
Jiazheng Qin,
Cheng-Wei Qiu,
Ting Yu
Abstract:
Achieving magnetically switchable chiral light emission is an important goal for 2D opto-spintronics. However, conventional strategies face a fundamental trade-off between dynamic tunability and polarization contrast. Nonlinear optics, particularly the emerging mechanism of chiral second-harmonic generation (SHG), offers a distinct strategy to bypass this restriction, yet its experimental realizat…
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Achieving magnetically switchable chiral light emission is an important goal for 2D opto-spintronics. However, conventional strategies face a fundamental trade-off between dynamic tunability and polarization contrast. Nonlinear optics, particularly the emerging mechanism of chiral second-harmonic generation (SHG), offers a distinct strategy to bypass this restriction, yet its experimental realization remains elusive due to stringent symmetry requirements. Here, we report giant nonlinear optical magnetochirality in a centrosymmetric 2D ferrotoroid, bilayer (2L) CrSBr. We reveal that a field-induced spin-canting state breaks the parity-time (PT) symmetry of the unperturbed antiferromagnetic (AFM) ground state, activating a spin-chirality-driven i-type susceptibility. The coherent interference between this emergent i-type and intrinsic c-type SHG susceptibilities generates a macroscopic circularly polarized SHG signal whose helicity is magnetically switchable. Leveraging this sensitive mechanism, we uncover remanent magnetic states after field saturation that evade conventional linear probes. By exploiting the non-volatility of these states, we demonstrate magneto-optical memory and logic operations. Our work establishes a general symmetry-driven strategy for tailoring nonlinear magnetochirality, while providing a sensitive optical probe for subtle spin textures in the 2D limit.
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Submitted 30 July, 2026;
originally announced July 2026.
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Generation of high-fluence and high-intensity hard x-ray attosecond pulses at European XFEL
Authors:
Ichiro Inoue,
Ulrike Boesenberg,
Rustam Rysov,
Takahiro Sato,
Ichika Harima,
Chenzhi Xu,
Jia Liu,
Thomas M. Linker,
Zain Abhari,
Andrei Benediktovitch,
Uwe Bergmann,
Ye Chen,
Lu Cao,
Winfried Decking,
Gianluca Geloni,
Marc Guetg,
Trey Guest,
Aliaksei Halavanau,
Jörg Hallmann,
Takashi Kimura,
Naresh Kujala,
Aliaksandr Leonau,
Shan Liu,
Tianyun Long,
Johannes Möller
, et al. (19 additional authors not shown)
Abstract:
By combining hard x-ray attosecond pulses from the European XFEL with total-reflection focusing x-ray optics, we generated nanofocused hard x-ray attosecond pulses with intensities and fluences comparable to the highest values attained in the hard x-ray regime. A peak intensity on the order of 10$^{20}$ W/cm$^2$ is confirmed through the observation of saturation in amplified spontaneous emission f…
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By combining hard x-ray attosecond pulses from the European XFEL with total-reflection focusing x-ray optics, we generated nanofocused hard x-ray attosecond pulses with intensities and fluences comparable to the highest values attained in the hard x-ray regime. A peak intensity on the order of 10$^{20}$ W/cm$^2$ is confirmed through the observation of saturation in amplified spontaneous emission from copper atoms. These x-ray pulses enable new scientific opportunities, including the exploration of higher-order nonlinear light--matter interactions, damage-free structure determination, and coherent control of atoms and molecules.
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Submitted 31 July, 2026; v1 submitted 29 July, 2026;
originally announced July 2026.
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A corrective agentic hybrid RAG and an operations-grounded evaluation for a scientific facility
Authors:
Rajat Sainju,
Dariusz Jarosz,
Hairong Shang,
Michael Prince,
Ryan M. Aydelott,
Mathew J. Cherukara,
Yine Sun,
Michael D. Borland
Abstract:
Scientific user facilities accumulate decades of operational knowledge that no single search index covers: electronic logbooks, technical documents, internal wikis, operations chat messages, maintenance records, and live control-system data. We present APS-RAG, Advanced Photon Source Retrieval Augmented Generation, a deployed platform that makes the institutional knowledge at the Advanced Photon S…
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Scientific user facilities accumulate decades of operational knowledge that no single search index covers: electronic logbooks, technical documents, internal wikis, operations chat messages, maintenance records, and live control-system data. We present APS-RAG, Advanced Photon Source Retrieval Augmented Generation, a deployed platform that makes the institutional knowledge at the Advanced Photon Source (APS) accessible to staff through natural-language queries, along with an operations-grounded evaluation. The retrieval engine fuses dense, sparse, and knowledge-graph (KG) channels with query-type-adaptive reciprocal-rank fusion, adds a corrective agentic loop, and runs a native-tool ReAct executor over a Model Context Protocol (MCP) tooling layer. We construct APS-Bench, a 50-question, question-answering (QA) dataset with auditable gold answers. Every retrieval-augmented variant numerically improves strict vital-nugget recall over a naive BM25 baseline (63.8%), with the full corrective Agentic GraphRAG scoring (70.3%). The cross-encoder reranker contributes significantly to answer quality: removing it and allowing the LLM to score relevance drastically reduces strict vital recall by 32.8%. The graph channel and corrective loop contribute positively as expected, but the performance gains are marginal. Additionally, we also compare the performance of open-source and closed-source LLMs in final answer synthesis. We release the APS-Bench construction methodology, the six-layer evaluation harness, and the underlying codebase, along with the '/aps-rag' retrieval agent skill framework, to support reproduction and adoption at other facilities. Together, the deployed platform and its operations-grounded evaluation present a promising workflow for trustworthy, statistically grounded AI assistance in facility operations, transferable to other large scientific instruments.
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Submitted 27 July, 2026;
originally announced July 2026.
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Generation of bright quantum high-order harmonic driven by combined coherent and bright squeezed vacuum light
Authors:
Wentao Wang,
Yaoshun Sun,
Liyuan Wang,
Lingrui Hu,
Dajun Ding,
Xiangyu Tang,
Mingxuan Li,
Jianmin Yuan,
Sizuo Luo
Abstract:
Attosecond quantum light, formed by the superposition of high-order harmonics driven by intense quantum light, opens new routes to probe quantum-mechanical correlations in matter. In this study, we have investigated the macroscopic propagation effects of quantum high-order harmonics generated by the combination of strong coherent and weak bright squeezed vacuum (BSV) lasers interacting with atomic…
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Attosecond quantum light, formed by the superposition of high-order harmonics driven by intense quantum light, opens new routes to probe quantum-mechanical correlations in matter. In this study, we have investigated the macroscopic propagation effects of quantum high-order harmonics generated by the combination of strong coherent and weak bright squeezed vacuum (BSV) lasers interacting with atomic gas. Our results reveal that the pressure-dependent intensity of harmonics arising from absorbing or emitting BSV photons differs from that of harmonics generated using only strong coherent pulses. Macroscopic propagation simulations indicate that the action phase of harmonics is perturbed by the weak BSV pulses. This perturbation modulates the phase mismatch of sub-cycle attosecond bursts and affects their quantum properties when the gas pressure varies. The ability to generate bright quantum high-order harmonics lays a foundation for the establishment and application of attosecond quantum spectroscopy.
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Submitted 23 July, 2026;
originally announced July 2026.
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Quantum sensing of low-frequency electric signal enabled by modulated auxiliary field in Rydberg atoms
Authors:
Xiayang Fan,
Shenchao Jin,
Jiatian Liu,
Jialiang Zhang,
Qichao Qi,
Yuan Sun
Abstract:
Rydberg atoms have emerged as a versatile and efficient platform for high-sensitivity quantum sensing of free-space electric fields, with remarkable progress in detecting low-frequency signals. To date, low-frequency Rydberg receivers have relied on a constant bias field, typically realized via intra-cell electrodes or Rydberg plasmas generated by photoelectric effects or inter-atomic interactions…
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Rydberg atoms have emerged as a versatile and efficient platform for high-sensitivity quantum sensing of free-space electric fields, with remarkable progress in detecting low-frequency signals. To date, low-frequency Rydberg receivers have relied on a constant bias field, typically realized via intra-cell electrodes or Rydberg plasmas generated by photoelectric effects or inter-atomic interactions. While these approaches improve sensitivity, they suffer from inherent challenges in calibration, long-term stability, and robustness, hindering practical deployment. Here, we propose, design, and experimentally demonstrate a quantum sensing scheme for low-frequency electric signals using modulated auxiliary fields in Rydberg atoms. Unlike conventional methods that employ external DC electric fields that are often fully shielded by adsorbed atom layers on the cell walls, we introduce an AC-field modulation strategy. The incoming low-frequency signal mixes with the auxiliary field, and together they induce Stark shifts of the Rydberg level. These shifts are mapped onto the probe laser via electromagnetically induced transparency (EIT), in a manner analogous to heterodyne detection. We demonstrate a sensitivity of $7.5 \pm 2.6~\mathrm{μV/(cm\cdot Hz^{1/2})}$ at 5 kHz and a minimal detectable field of $0.26 \pm 0.04~\mathrm{μV/cm}$ with an integration time of 1000 s. Furthermore, we extend this approach to systematically analyze the performance of generalized auxiliary fields containing multiple frequency components. By virtue of modulated auxiliary field and quantum frequency mixing, our results establish a robust and systematic framework for quantum sensing of low-frequency electric fields with Rydberg atoms, offering improved sensitivity, stability, and immunity to environmental drifts.
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Submitted 21 July, 2026;
originally announced July 2026.
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Final assessment of radioactive impurities in the JUNO detector
Authors:
Thomas Adam,
Fengpeng An,
Costas Andreopoulos,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Nikita Balashov,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Beretta,
Antonio Bergnoli,
Nikita Bessonov,
Daniel Bick,
Lukas Bieger,
Svetlana Biktemerova,
Thilo Birkenfeld,
Simon Blyth,
Manuel Böhles,
Anastasia Bolshakova,
Mathieu Bongrand,
Matteo Borghesi
, et al. (549 additional authors not shown)
Abstract:
The Jiangmen Underground Neutrino Observatory (JUNO) collaboration has completed the construction of the 20,000-ton liquid scintillator detector and the associated muon veto detector system. To meet the physics objectives, the materials used in the detector must exhibit low radioactive contamination. The single-event rate in the fiducial volume (R $<$ 17.2 m) of the scintillator is required to be…
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The Jiangmen Underground Neutrino Observatory (JUNO) collaboration has completed the construction of the 20,000-ton liquid scintillator detector and the associated muon veto detector system. To meet the physics objectives, the materials used in the detector must exhibit low radioactive contamination. The single-event rate in the fiducial volume (R $<$ 17.2 m) of the scintillator is required to be approximately 7 Hz for energies above 0.7 MeV, resulting in an accidental coincidence background of about 1 event per day for reactor neutrino physics analyses. Since the beginning of the construction phase, we have screened the natural radioactivity content of thousands of materials, to select those that meet the design background budget. The radioactive impurity concentrations of the materials ultimately used in the JUNO detector are summarized in this paper. The construction of the entire detector and the subsequent filling of the liquid scintillator were completed in August 2025. From the initial data, the total count rate of natural radioactivity within the detector's fiducial volume has met the requirements and is sufficient to support the reactor antineutrino analysis.
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Submitted 19 July, 2026;
originally announced July 2026.
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Unconventional Spin Valve Based on Normal Metal/Chiral Molecule/Altermagnet Junctions
Authors:
Tian-Yi Zhang,
Peng-Yi Liu,
Yu-Fei Sun,
Ai-Min Guo,
Qing-Feng Sun
Abstract:
Chiral molecules have attracted broad interdisciplinary interest for their ability to produce highly spin-polarized current. This phenomenon, known as the chiral-induced spin selectivity effect, holds great potential in the field of spintronics. Here, we propose to combine chiral molecules with altermagnets to construct highly efficient and tunable spin valves. Using the nonequilibrium Green's fun…
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Chiral molecules have attracted broad interdisciplinary interest for their ability to produce highly spin-polarized current. This phenomenon, known as the chiral-induced spin selectivity effect, holds great potential in the field of spintronics. Here, we propose to combine chiral molecules with altermagnets to construct highly efficient and tunable spin valves. Using the nonequilibrium Green's function method and the Landauer-Büttiker formula, we obtain the conductance and the magnetoresistance of a normal metal/chiral molecule/altermagnet spin valve. Our theoretical results reveal that the conductance of the spin valve can be effectively tuned by reorienting the Néel vector of the altermagnet, and the magnetoresistance of the spin valve increases with molecular length and altermagnetic anisotropy. Moreover, the magnetoresistance vanishes for achiral molecules or in the absence of molecular spin-orbit coupling. Our work paves the way for developing efficient, controllable, and stray-field-free spintronic devices.
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Submitted 13 July, 2026;
originally announced July 2026.
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Five-Dimensional Beam Sigma Matrix Determination in Transport Lines with Differentiable Simulation
Authors:
Chenran Xu,
Louis Emery,
Osama Mohsen,
Ryan Roussel,
Kent P. Wootton,
Yine Sun,
Michael Borland
Abstract:
Precise measurement of the beam sigma matrix is essential for matching the optics in transport lines and ensuring reliable accelerator operation. In this work, we present a method for measuring and reconstructing the non-temporal five-dimensional beam sigma matrix using quadrupole scans performed in a dispersive transport region. The proposed approach enables characterization of the beam moments u…
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Precise measurement of the beam sigma matrix is essential for matching the optics in transport lines and ensuring reliable accelerator operation. In this work, we present a method for measuring and reconstructing the non-temporal five-dimensional beam sigma matrix using quadrupole scans performed in a dispersive transport region. The proposed approach enables characterization of the beam moments using only quadrupoles and beam transverse profile diagnostics, without requiring longitudinal diagnostics or a dedicated beamline section. To achieve robust and computationally efficient reconstruction, we formulate the problem within a differentiable simulation framework, allowing direct gradient-based optimization of the initial beam covariance matrix. We demonstrate the method experimentally in the Booster-to-Storage-ring (BTS) transport line at the Advanced Photon Source (APS), where it produces consistent reconstructions of the beam sigma matrix from measurements. We further show that the framework is flexible with respect to the number and placement of diagnostic screens, making it applicable to a broad range of existing transport-line configurations. These results establish the proposed 5D beam sigma matrix reconstruction method as a practical and broadly deployable approach for fast, efficient beam characterization during accelerator operation.
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Submitted 7 July, 2026;
originally announced July 2026.
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Continuum modeling of fluidic and elastic flow during growth-driven wound closure in partial-EMT cell monolayers
Authors:
Chaozhen Wei,
Han Jiang,
Yifan Gu,
Nonthakorn Olaranont,
Pengbo Wang,
Qi Wen,
Yubing Sun,
Min Wu
Abstract:
Large-scale circular gap closure occurs over a time scale on which cell growth and proliferation become important. Growth is the main driver of the closing process, while cell dynamics such as elongation and intercalation reflect elastic and fluidic contributions to tissue deformation. We develop a novel fluidized growth-elasticity framework as a nonlinear analogue of a Maxwell fluid with growth.…
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Large-scale circular gap closure occurs over a time scale on which cell growth and proliferation become important. Growth is the main driver of the closing process, while cell dynamics such as elongation and intercalation reflect elastic and fluidic contributions to tissue deformation. We develop a novel fluidized growth-elasticity framework as a nonlinear analogue of a Maxwell fluid with growth. The framework decomposes the experimentally observable strain rate into the additive sum of the growth, elastic, and fluidic strain rates, thus enabling the separate quantification of these contributions from tissue kinematics and allowing the roles of tissue elasticity and fluidity (the inverse of viscosity) to be characterized. We apply the model to large circular gaps ($\sim$1.7 mm in diameter) in confluent monolayers of mouse embryonic epicardial cells (MEC1) under two conditions, without and with TGF-$β$ treatment. We show that both tissue fluidity and the elastic properties associated with fiber reinforcement are critical for reproducing the closure kinematics. Specifically, we predict that the treated condition has lower fluidity, associated with a lower fluidic deformation rate and a higher elastic deformation rate than the untreated condition, in agreement with the experimental observations.
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Submitted 14 August, 2026; v1 submitted 7 July, 2026;
originally announced July 2026.
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Ai2-Kit: Streamlining AI-Accelerated Ab Initio Workflows for Complex Chemical Systems
Authors:
Sheng Bi,
Wei-Hong Xu,
Yong-Bin Zhuang,
Jia-Xin Zhu,
Jiang-Peng Qiu,
Yu-Hang Tang,
Xiang-Long Du,
Qi You,
Yun-Pei Liu,
Fu-Qiang Gong,
Yu-Xin Guo,
Yi-Ze Wang,
Cheng-Xuan Wang,
Zi-Heng Gong,
Zi-Qiang Chen,
Chang Liu,
Siyuan Han,
Jian Gu,
Jia-Xin Li,
Yi-Ming Chen,
Lin Huang,
Si-Jie Chen,
Bo-Ying Huang,
Jie-Zhen Xia,
Fan-Jie Xu
, et al. (25 additional authors not shown)
Abstract:
Molecular simulations of complex chemical systems, such as catalysis, electrochemistry, and energy storage, often need to capture the interplay of effects such as electronic structure, finite-temperature fluctuations, and electric-field response. Such complexity is difficult to address with traditional ab initio calculations, which are limited by the time and length scales they can reach. AI-accel…
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Molecular simulations of complex chemical systems, such as catalysis, electrochemistry, and energy storage, often need to capture the interplay of effects such as electronic structure, finite-temperature fluctuations, and electric-field response. Such complexity is difficult to address with traditional ab initio calculations, which are limited by the time and length scales they can reach. AI-accelerated ab initio (AI2) methods use machine learning potentials trained on first-principles data to replace expensive electronic-structure calculations, extending ab initio accuracy to these regimes, but their routine application requires reliable workflows that connect first-principles calculations, model training, molecular dynamics, enhanced sampling, trajectory analysis, and HPC orchestration. Here we present ai2-kit, a software toolkit for developing accessible, reproducible, and extensible AI2 workflows. ai2-kit provides high-semantic-density command-line interfaces and Python APIs for structure and dataset conversion, batch task generation, active-learning screening, job orchestration, and workflow recovery. We demonstrate ai2-kit in four representative applications: active-learning-based machine learning potential construction, free-energy perturbation for redox and acid-base processes, electrochemical machine learning potentials for electrified interfaces, and spectroscopies from machine learning molecular dynamics. ai2-kit also provides AI-agent skills that help users adapt these use cases into customized workflows for their own chemical systems and computational software stacks. Together, ai2-kit helps turn AI2 methods from bespoke computational protocols into reusable and extensible workflows for complex chemical systems, from model construction to property prediction.
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Submitted 14 July, 2026; v1 submitted 1 July, 2026;
originally announced July 2026.
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Observation of Non-Hermitian Skin Dynamics in the Liouvillian Regime
Authors:
Shu Yang,
Yeyang Sun,
Lingrui Hong,
Yi Yang
Abstract:
Open quantum systems generally do not perfectly preserve phase coherence: coupling to uncontrolled environments requires a density-matrix description based on the Liouvillian framework beyond pure-state wave evolution. Realizing and probing such dynamics in a programmable platform is therefore essential for connecting coherent physics to realistic dissipative settings. Here we implement a tunable…
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Open quantum systems generally do not perfectly preserve phase coherence: coupling to uncontrolled environments requires a density-matrix description based on the Liouvillian framework beyond pure-state wave evolution. Realizing and probing such dynamics in a programmable platform is therefore essential for connecting coherent physics to realistic dissipative settings. Here we implement a tunable open-system quantum walk in a photonic mesh lattice, where controlled phase noise produces adjustable dephasing and non-reciprocal gain-loss imbalance provides an independently tunable non-Hermitian drive. This allows us to continuously interpolate between coherent quantum walks and incoherent classical walks, and to observe how directional transport evolves in the Liouvillian regime. Using non-Hermitian skin dynamics as a probe, we measure the center-of-mass drift over both the coherence and non-Hermiticity parameters, revealing a crossover from coherence-enhanced to decoherence-enhanced transport in quantitative agreement with quantum-channel simulations. We further program spatial and temporal interfaces to demonstrate interface accumulation and a long-time drift governed by the instantaneous channel. Our results establish a controllable photonic platform for simulating open quantum dynamics and show that decoherence can actively reshape non-Hermitian transport.
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Submitted 25 June, 2026;
originally announced June 2026.
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Physics-Preserving Latent Compression for Zero-Shot Resolution Transfer in 3D Turbulence
Authors:
Yilong Dai,
Yiming Sun,
Yiheng Chen,
Ziyi Wang,
Shengyu Chen,
Xiaowei Jia,
Runlong Yu
Abstract:
High-resolution turbulence modeling is essential for scientific computing, but remains constrained by the cost of direct numerical simulation and the scarcity of full-resolution data. Existing scientific compressors reduce storage but typically operate on per-frame representations, whereas learned compressors yield compact latents that are often resolution-dependent and weakly aligned with the phy…
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High-resolution turbulence modeling is essential for scientific computing, but remains constrained by the cost of direct numerical simulation and the scarcity of full-resolution data. Existing scientific compressors reduce storage but typically operate on per-frame representations, whereas learned compressors yield compact latents that are often resolution-dependent and weakly aligned with the physics of turbulence. This raises the need for a compression framework that reduces data size, preserves physical diagnostics, and transfers from low-resolution training fields to high-resolution test fields without retraining. In this paper, we propose Physics-Preserving Latent Compression (PPLC), a patch-local latent compressor for three-dimensional turbulence. Motivated by inertial-range scale similarity, PPLC treats fixed-size patches as transferable units and applies a shared variational autoencoder independently of the global grid size. It combines exact mean preservation, zero-mean fluctuation encoding, an invertible Haar wavelet front-end, shift-consistency regularization, and overlap-aware reconstruction. Instantiated on forced isotropic turbulence, PPLC is trained only on stride-downsampled 256^3 fields and transfers zero-shot to 1024^3 fields. Experiments show that PPLC improves the balance between reconstruction accuracy and physical fidelity over classical and learned baselines, keeping diagnostics such as dissipation, enstrophy, energy spectra, and incompressibility closer to the ground truth. Beyond turbulence compression, PPLC offers a general strategy for physics-preserving latent representations that support data-efficient scientific surrogate modeling.
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Submitted 19 June, 2026;
originally announced June 2026.
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DKEKAN: A single-parameterized KAN surrogate for Drift Kinetic Equation Toward Fast Neoclassical Toroidal Viscosity Torque Modeling in Tokamaks
Authors:
Jinpeng Huang,
Xingting Yan,
Mingyu Zhang,
Nana Bao,
Zixuan Song,
Yuetao Meng,
Weiyong Zhou,
Youwen Sun
Abstract:
The neoclassical toroidal viscosity (NTV) torque is a critical driver of toroidal rotation in tokamaks, profoundly influencing plasma stability and performance. Consequently, incorporating NTV effects is essential for modern integrated modeling frameworks that aim to self-consistently unify multiple physical processes. However, the high computational cost of NTV modeling precludes its self-consist…
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The neoclassical toroidal viscosity (NTV) torque is a critical driver of toroidal rotation in tokamaks, profoundly influencing plasma stability and performance. Consequently, incorporating NTV effects is essential for modern integrated modeling frameworks that aim to self-consistently unify multiple physical processes. However, the high computational cost of NTV modeling precludes its self-consistent integration within such frameworks. This bottleneck arises because NTV calculation requires solving its governing equation--the drift kinetic equation (DKE)--in high-dimensional phase space. To address this issue, this study develops DKEKAN, a single-parameterized Kolmogorov-Arnold Network (SKAN) surrogate for solving DKE, to realize fast NTV modeling in tokamaks. The research process consists of the following steps: Firstly, a large dataset mapping DKE equation parameters to solutions is generated based on first-principle simulations under plasma parameters of the Experimental Advanced Superconducting Tokamak (EAST); Secondly, a surrogate model for solving DKE is developed based on the SKAN framework, which also incorporates a modular expert network design; Finally, the DKEKAN surrogate model is integrated with the NTV modeling framework to realize fast NTV calculation. With its physics-grouped expert layer and SKAN backbone, DKEKAN outperforms the tested MLP, KAN, and neural-operator baselines in overall prediction accuracy, while reducing the standalone DKE-solving time from 35.85s to 3.74s, corresponding to a speedup of approximately 9.6x, and reducing the total coupled NTVTOK runtime from 38.24s to 5.58s, corresponding to an overall speedup of approximately 6.9x. This work effectively overcomes the computational bottleneck in NTV simulations, thus supporting further integrated modeling that incorporates NTV effects.
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Submitted 8 June, 2026;
originally announced June 2026.
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Detective scaffolding for within-session reasoning development: a three-phase framework evaluated in polymer engineering and pre-university outreach
Authors:
Haolin Feng,
Holly Barrett,
Xinru Deng,
Dimitrios G Papageorgiou,
Yiwei Sun
Abstract:
This paper presents a detective scaffolding framework -- a three-phase instructional sequence (Hypothesis Activation -> Evidence Structuring -> Causal Integration) in which engineering students investigate a realistic industrial defect scenario using staged in-class polls as designed evidence probes. Unlike conventional uses of student response systems for engagement, the framework positions each…
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This paper presents a detective scaffolding framework -- a three-phase instructional sequence (Hypothesis Activation -> Evidence Structuring -> Causal Integration) in which engineering students investigate a realistic industrial defect scenario using staged in-class polls as designed evidence probes. Unlike conventional uses of student response systems for engagement, the framework positions each poll as an Evidence-Centred Design instrument targeting a specific reasoning capability. In the primary implementation, 80 Year~3 polymer engineering students progressed from prior-knowledge-driven misconception (71% attributing defects to temperature) to complete root-cause convergence (100\% identifying humidity; Fisher's exact test, $p < .001$) across four sequenced prompts within a single 90-minute lecture slot. A dual-accuracy analysis revealed that at one intermediate stage, textbook-correct and analytically valid responses diverged, illustrating why conventional scoring can misrepresent reasoning quality. In a transferability study, 26 Year~12 students with no engineering background achieved identical root-cause identification rates across two adapted scenarios, with significant gains in data-analysis confidence and AI explanation ability. The results suggest that the pedagogical structure, rather than disciplinary content, drives the convergence effect, implying portability across disciplines and educational levels.
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Submitted 5 June, 2026;
originally announced June 2026.
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Hyperon-Nucleon Spectrometer
Authors:
Xiaozhi Bai,
Xu Cao,
Zhe Cao,
Jinhui Chen,
Kai Chen,
Qibo Chen,
Shi Chen,
Xin Chen,
Yuquan Chen,
Zhenyu Chen,
Jianping Dai,
Heng-Tong Ding,
Dongshuo Du,
Shuxian Du,
Limin Duan,
Zhe Duan,
Anhui Feng,
Jie Feng,
Yicheng Feng,
Jinlin Fu,
Xiaofeng Fu,
Chaosong Gao,
Liang Ge,
Wenwen Ge,
Lisheng Geng
, et al. (215 additional authors not shown)
Abstract:
Chirality lies at the heart of low-energy QCD, governing the symmetry structure that shapes hadron masses and strong interaction dynamics. Among the most compelling open questions tied to chiral dynamics and spontaneous chiral symmetry breaking is the longstanding $Λ$ polarization puzzle, in which $Λ$ hyperons produced in unpolarized hadronic collisions exhibit a surprisingly large transverse pola…
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Chirality lies at the heart of low-energy QCD, governing the symmetry structure that shapes hadron masses and strong interaction dynamics. Among the most compelling open questions tied to chiral dynamics and spontaneous chiral symmetry breaking is the longstanding $Λ$ polarization puzzle, in which $Λ$ hyperons produced in unpolarized hadronic collisions exhibit a surprisingly large transverse polarization that remains theoretically unexplained. This whitepaper presents the proposal for the Hyperon-Nucleon Spectrometer (H-NS) at the High-Intensity heavy-ion Accelerator Facility (HIAF). Leveraging the high energy and high intensity of HIAF's proton and heavy-ion beams, the H-NS experiment will perform systematic studies of hyperon polarization phenomena and their underlying mechanisms in proton-proton ($pp$), proton-nucleus ($pA$), and nucleus-nucleus ($AA$) collisions in the fixed target mode. A wide-range beam energy scan, including proton beams from 3 GeV up to 9.3 GeV (HIAF) and up to 32 GeV (upgraded HIAF), will be conducted to examine the dependence of polarization on collision energy. The spectrometer is designed with specialized detectors capable of high-precision reconstruction of final-state baryon polarizations. Among its many interesting and important measurements, H-NS will simultaneously measure hyperon and proton spin observables to explore the polarization mechanism in hadronic interactions and the spin structure of baryons. Furthermore, the use of $pA$ and $AA$ collisions will enable detailed investigations of cold and hot nuclear matter effects on spin polarization. Its physics program and detector development will significantly benefit the future Electron-ion Collider in China.
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Submitted 4 June, 2026;
originally announced June 2026.
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Mid-infrared photon counting and resolving via efficient frequency upconversion
Authors:
Kun Huang,
Yinqi Wang,
Jianan Fang,
Weiyan Kang,
Ying Sun,
Heping Zeng
Abstract:
Optical detectors with single-photon sensitivity and large dynamic range would facilitate a variety of applications. Especially, the capability of extending operation wavelengths into the mid-infrared region is highly attractive. Here we implement a mid-infrared frequency upconversion detector for counting and resolving photons at 3 $μ$m. Thanks to the spectro-temporal engineering of the involved…
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Optical detectors with single-photon sensitivity and large dynamic range would facilitate a variety of applications. Especially, the capability of extending operation wavelengths into the mid-infrared region is highly attractive. Here we implement a mid-infrared frequency upconversion detector for counting and resolving photons at 3 $μ$m. Thanks to the spectro-temporal engineering of the involved optical fields, the mid-infrared photons could be spectrally translated into the visible band with a conversion efficiency of 80\%. In combination with a silicon avalanche photodiode, we obtained unprecedented performances with a high overall detection efficiency of 37\% and a low noise equivalent power of 1.8$\times$10$^{-17}$ W/Hz$^{1/2}$. Furthermore, photon-number-resolving detection at mid-infrared wavelengths was demonstrated, for the first time to our knowledge, with a multi-pixel photon counter. The implemented upconversion detector exhibited a maximal resolving photon number up to 9 with a noise probability per pulse of 0.14\% at the peak detection efficiency. The achieved photon counting and resolving performance might open up new possibilities in trace molecule spectroscopy, sensitive biochemical sensing, and free-space communications, among others.
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Submitted 2 June, 2026;
originally announced June 2026.
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A Method for Neutron-Gamma Pulse Shape Discrimination of CLYC Detector Based on a Gated Residual-Linear Attention Network
Authors:
Shiwei Jing,
Shengduo Liu,
Weiyang Zhang,
Jia Song,
Sijia Zhou,
Hailong Xu,
Yue Sun,
Zebin Li,
Yuxuan Gu,
Siqi Liu,
Tian Zhang,
Zhihua Gao,
Guofeng Qu,
Fuquan Jia
Abstract:
The discrimination of neutron and gamma pulse shapes is a key technology in fields such as nuclear safety monitoring and radiation assessment. An enhanced recursive gated cyclic residual-sparse linear attention network is developed on the CLYC detector experimental platform to overcome weak noise resistance, limited feature extraction and inferior real-time performance of conventional algorithms.…
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The discrimination of neutron and gamma pulse shapes is a key technology in fields such as nuclear safety monitoring and radiation assessment. An enhanced recursive gated cyclic residual-sparse linear attention network is developed on the CLYC detector experimental platform to overcome weak noise resistance, limited feature extraction and inferior real-time performance of conventional algorithms. The experimental dataset comprises 19,971 samples, which were pre-processed and stratified for model training and testing. Results indicate that the proposed algorithm achieves a quality factor of 2.2, with a classification accuracy of 98.7% and a recall rate of 99.4%. It achieves an accuracy of 95.1% under the 20 dB low signal-to-noise ratio condition, exhibiting excellent anti-noise ability.With around 2.8 million parameters, the model takes merely 0.05 ms to process a single pulse on GPU, satisfying real-time monitoring and embedded deployment demands.
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Submitted 25 May, 2026;
originally announced June 2026.
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Demonstrating CBM Capabilities by $Λ$ Baryon Reconstruction in Ni+Ni Collisions with the mCBM Experiment at SIS18 of GSI/FAIR
Authors:
CBM Collaboration,
A. Agarwal,
Z. Ahammed,
N. Ahmad,
L. J. Ahrens,
M. Al-Turany,
N. Alam,
J. An,
J. Andary,
A. Andronic,
H. Appelshäuser,
B. Arnoldi-Meadows,
B. Artur,
M. D. Azmi,
M. Balzer,
A. Bandyopadhyay,
V. A. Bâsceanu,
J. Becker,
A. Belousov,
A. Bercuci,
R. Berendes,
D. Bertini,
O. Bertini,
M. Beyer,
O. Bezshyyko
, et al. (318 additional authors not shown)
Abstract:
The Compressed Baryonic Matter (CBM) experiment at the upcoming Facility for Antiproton and Ion Research (FAIR) is a high-rate fixed-target experiment designed to investigate nuclear matter at extreme baryon densities in relativistic nucleus-nucleus collisions. To enable high-statistics measurements of rare probes, CBM is designed to operate at event rates up to 10 MHz. This necessitates the devel…
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The Compressed Baryonic Matter (CBM) experiment at the upcoming Facility for Antiproton and Ion Research (FAIR) is a high-rate fixed-target experiment designed to investigate nuclear matter at extreme baryon densities in relativistic nucleus-nucleus collisions. To enable high-statistics measurements of rare probes, CBM is designed to operate at event rates up to 10 MHz. This necessitates the development of fast and radiation-tolerant detectors, self-triggered front-end electronics, a free-streaming data acquisition architecture, and real-time event reconstruction capabilities. Prototype versions and pre-series productions of the CBM detector systems have been deployed in the mini-CBM demonstrator setup mCBM - an experimental precursor comprising sub-components of all major CBM systems, installed at the SIS18 facility of GSI/FAIR within the FAIR Phase-0 program. In 2024, Ni+Ni collisions at a kinetic beam energy of 1.93 AGeV and an average interaction rate of about 250 kHz were successfully recorded. This dataset enables a detailed evaluation of the operational performance of the detector systems as well as the complete CBM data chain, while the reconstruction of rare $Λ$ baryons serves as a natural benchmark. This paper presents the first results on $Λ$ signal reconstruction with the mCBM experiment, demonstrating the readiness of the detector technologies and the data chain for the upcoming full-scale CBM experiment.
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Submitted 1 June, 2026;
originally announced June 2026.
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Hybrid Full Waveform Inversion Assisted by Rytov Approximation for Musculoskeletal Ultrasound Computed Tomography
Authors:
Yifei Sun,
Yubing Li,
Chang Su,
Lekang Jiang,
Xiangwei Lu,
Ligang Cui,
He Sun,
Weijun Lin
Abstract:
Ultrasound computed tomography is emerging as a promising safe and accessible modality for soft-tissue medical imaging, with full waveform inversion playing a key role in unlocking its full potential for high-resolution, quantitative reconstructions. Frequency domain full waveform inversion (FDFWI) for reconstructing spatial maps of acoustic properties in the musculoskeletal system is highly sensi…
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Ultrasound computed tomography is emerging as a promising safe and accessible modality for soft-tissue medical imaging, with full waveform inversion playing a key role in unlocking its full potential for high-resolution, quantitative reconstructions. Frequency domain full waveform inversion (FDFWI) for reconstructing spatial maps of acoustic properties in the musculoskeletal system is highly sensitive to the quality of low-frequency signals, making the final imaging outcome vulnerable to issues such as inappropriate initial models and strong scatterings related to bones. To address these challenges, we propose a hybrid full waveform inversion (HFWI) algorithm that incorporates a traveltime inversion algorithm based on the generalized Rytov approximation into the FDFWI framework. This hybrid strategy enhances early-stage inversion quality and substantially reduces sensitivity to the initial model, all while maintaining computational efficiency. Importantly, HFWI achieves results comparable to those obtained using well-constructed initial models, without incurring extra computational cost, thus enabling accurate imaging under realistic, bandwidth-limited conditions. In addition, we introduce a near real-time strategy to update first-arrival traveltimes based on forward-scattered phase variations without requiring extra wavefield simulations. Numerical simulations, as well as \textit{in vitro} and \textit{in vivo} experiments confirm the robustness and efficiency of the proposed approach. HFWI also shows promise to extend to more complex scenarios of musculoskeletal parametric reconstruction.
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Submitted 24 May, 2026;
originally announced May 2026.
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Quantum compressed sensing
Authors:
Jianyong Hu,
Wei Li,
Shuxiao Wu,
Liwen Zhang,
Yongchuang Sun,
Jiazhao Tian,
Guosheng Feng,
Zhixing Qiao,
Jianqiang Liu,
Changgang Yang,
Ruiyun Chen,
Chengbing Qin,
Guofeng Zhang,
Liantuan Xiao,
Suotang Jia
Abstract:
How many measurements are fundamentally required to capture a signal. Shannon's information theory established the bedrock of this question in 1948, the Nyquist Shannon theorem set the first answer, and compressed sensing (CS) rewrote it in 2006 by reducing the required measurement number to M = O(Klog(N/K)) for a K sparse signal. Here, we propose quantum compressed sensing (QCS), a paradigm that…
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How many measurements are fundamentally required to capture a signal. Shannon's information theory established the bedrock of this question in 1948, the Nyquist Shannon theorem set the first answer, and compressed sensing (CS) rewrote it in 2006 by reducing the required measurement number to M = O(Klog(N/K)) for a K sparse signal. Here, we propose quantum compressed sensing (QCS), a paradigm that reframes signal acquisition as a unitary quantum evolution. By encoding high dimensional signal information into a single quantum probe state, then introducing domain-alignment evolution,a physically realizable unitary transformation that maps the sparse basis directly onto the measurement basis. QCS executes the support-set search at the quantum level without consuming measurement trials. The logarithmic penalty vanishes, compressing the required measurement number from the classical bound to M =O(K) and reducing reconstruction from ill posed optimization to linear estimation. We experimentally validate QCS using frequency and time domain sparse signals, confirming that the measurement number scales linearly with sparsity and decouples entirely from the signal dimension. Our work provides a physical pathway toward ultimate information acquisition efficiency, with broad implications for sensing, imaging, and communication.
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Submitted 15 May, 2026;
originally announced May 2026.
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Collective-Coordinate Fluctuations of Driven-Dissipative Solitons
Authors:
Yifan Sun,
Thomas Bunel,
Sofya Glazyrina,
Georges Semaan,
Fabien Bretenaker,
Stephane Coen,
Simon-Pierre Gorza,
François Leo
Abstract:
Fluctuations of nonequilibrium localized waves are shaped not only by direct stochastic forcing but also by deterministic transfer among coupled collective degrees of freedom. We develop a pathway-resolved stochastic collective-coordinate theory that makes this transfer explicit for stationary driven-dissipative solitons of the generalized Lugiato--Lefever equation with Raman response. The reducti…
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Fluctuations of nonequilibrium localized waves are shaped not only by direct stochastic forcing but also by deterministic transfer among coupled collective degrees of freedom. We develop a pathway-resolved stochastic collective-coordinate theory that makes this transfer explicit for stationary driven-dissipative solitons of the generalized Lugiato--Lefever equation with Raman response. The reduction yields a refined stationary phase-locking relation, providing a fixed point for the subsequent stochastic theory. Projecting field-level fluctuations onto four soliton coordinates: amplitude, frequency shift, temporal position, and global phase, yields a reduced Langevin model and, after linearization about a stable stationary state, an analytic power-spectral-density matrix. This framework separates direct stochastic injection from deterministic inter-coordinate conversion and thereby resolves how each observable spectrum is assembled from distinct internal fluctuation pathways. It shows that timing jitter is governed primarily by Gordon--Haus-type frequency-to-timing conversion, while phase noise is often dominated by amplitude-to-phase transfer rather than by direct phase diffusion. Raman response opens additional cascaded pathways, and the low-detuning hump in the intensity and phase spectra is traced to the driven response of an underdamped amplitude--phase subsystem preceding the breathing instability. Comparisons with stochastic simulations of both the reduced model and the full generalized Lugiato--Lefever equation show good agreement throughout most of the stable stationary single-soliton regime, with systematic deviations mainly near the Hopf boundary. The theory provides a general route for connecting internal fluctuation-transfer mechanisms of dissipative solitons to measurable noise observables.
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Submitted 14 May, 2026;
originally announced May 2026.
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Assessing foundational atomistic models for iron alloys under Earth's core conditions
Authors:
Tianqi Wan,
Liangrui Wei,
Zepeng Wu,
Renata M. Wentzcovitch,
Yang Sun
Abstract:
We assess the capability of recently developed foundational atomistic models (FAMs) to simulate iron alloys under the extreme pressures and temperatures of Earth's core. Static equations of state of hexagonal close-packed (hcp) and body-centered cubic (bcc) iron computed by 17 FAMs are benchmarked against ab initio calculations. Two representative models, MatterSim and MACE, are further evaluated…
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We assess the capability of recently developed foundational atomistic models (FAMs) to simulate iron alloys under the extreme pressures and temperatures of Earth's core. Static equations of state of hexagonal close-packed (hcp) and body-centered cubic (bcc) iron computed by 17 FAMs are benchmarked against ab initio calculations. Two representative models, MatterSim and MACE, are further evaluated for their ability to reproduce phonon spectra, liquid structure, and melting relations of iron at core conditions. While both models capture several key properties, MACE substantially overestimates the stability of bcc iron and fails to correctly describe the stability of hcp iron. Their performance is also examined for binary liquids, superionic phases, and a seven-component Fe-Ni-Si-S-O-H-C liquid. Although these FAMs were not explicitly trained on data from core conditions, they can reproduce several structural and dynamical properties across a wide range of compositions. However, none of the tested models consistently reproduces all first-principles benchmarks. By analyzing the origins of these discrepancies, we identify several limitations of current FAMs, particularly the lack of an explicit treatment of thermal electronic excitations, which significantly affect phase stability and thermodynamic properties under core conditions. We further discuss directions for improving FAMs to enable predictive simulations of core-forming materials under extreme conditions.
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Submitted 13 May, 2026;
originally announced May 2026.
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Substrate-engineered tunable bound states in the continuum and directional radiation in dielectric metasurfaces
Authors:
Hao Song,
Yanming Sun,
Jian Li,
Wanlin Wang,
Ming Chun Tang
Abstract:
Tunable bound states in the continuum (BICs) in metasurfaces offer powerful opportunities to control light-matter interactions, yet the role of out-of-plane symmetry breaking remains poorly understood. Here, we reveal a mechanism that enables tunable high-Q BICs and directional radiation through out-of-plane symmetry breaking in all-dielectric metasurfaces. A substrate-free metasurface composed of…
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Tunable bound states in the continuum (BICs) in metasurfaces offer powerful opportunities to control light-matter interactions, yet the role of out-of-plane symmetry breaking remains poorly understood. Here, we reveal a mechanism that enables tunable high-Q BICs and directional radiation through out-of-plane symmetry breaking in all-dielectric metasurfaces. A substrate-free metasurface composed of periodically arranged multilayer cylinders that support overlapping magnetic dipole and electric quadrupole resonances, yielding electric mirror and symmetry-protected BIC responses at 1550 nm. Introducing multilayer substrates breaks out-of-plane symmetry and excites guided modes. When the guided-mode wavelength matches that of the BIC and coupling to the substrate is suppressed, the BIC wavelength remains nearly invariant, while the Q factor increases with layer number. In contrast, spectral detuning and enhanced coupling lead to pronounced blueshifts and rapid Q degradation. The interplay between guided-mode matching and coupling strength thus governs whether a BIC remains robust or becomes tunable. These findings establish a general framework for BIC engineering via out-of-plane symmetry breaking and provide a versatile platform for tunable metasurfaces with potential applications in integrated optics.
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Submitted 10 May, 2026;
originally announced May 2026.
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A bent straw as a tool for an affordable student-safe experiment in vortex ring dynamics
Authors:
Elijah James,
Yukun Sun,
Yicong Fu,
Jena Shields,
Cade Sbrocco,
Christopher Dougherty,
Chris Roh
Abstract:
Vortex dynamics are an important topic in fluid dynamics, explaining phenomena like drag and lift generation, jet propulsion, and corner flows. It is also often excluded from introductory or undergraduate fluid dynamics courses on account of its complexity and the inaccessibility of practical and engaging experiments. We present an affordable student-safe experiment to generate vortex rings and st…
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Vortex dynamics are an important topic in fluid dynamics, explaining phenomena like drag and lift generation, jet propulsion, and corner flows. It is also often excluded from introductory or undergraduate fluid dynamics courses on account of its complexity and the inaccessibility of practical and engaging experiments. We present an affordable student-safe experiment to generate vortex rings and study their dynamics using a bent straw and dyed water that allows students to control key parameters, can be imaged using a smartphone camera, and explains the complex physics with simple and easily measured parameters. Vortex rings are produced that parallel seminal experiments, demonstrating secondary structures and the mirroring effect. Meanwhile, nonplanar and triangular jet exits are used to demonstrate asymmetric vortex rings and vortex ring inversion.
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Submitted 8 May, 2026;
originally announced May 2026.
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Pre-training Enables Extraordinary All-optical Image Denoising
Authors:
Xudong Lv,
Yuxiang Sun,
Shuo Wang,
Nanxing Chen,
Jun Guan,
Jingtian Hu
Abstract:
Optical neural networks are emerging as powerful machine learning and information processing tools because of their potential advantages in speed and energy efficiency. The training methods of these physical models, however, remain underexplored compared to their digital counterparts and are leading to suboptimal performance. This paper reports a pre-training-driven approach that leads to snapshot…
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Optical neural networks are emerging as powerful machine learning and information processing tools because of their potential advantages in speed and energy efficiency. The training methods of these physical models, however, remain underexplored compared to their digital counterparts and are leading to suboptimal performance. This paper reports a pre-training-driven approach that leads to snapshot image denoising with substantially improved quality. We demonstrated effective free-space optical denoising by a diffractive network optimized by a two-step process including (1) pre-training using a massive dataset of 3.45 million diverse but simple images and (2) fine-tuning with the corresponding task-specific datasets. Compared to conventional Fourier-domain filtering and directly trained diffractive networks, such a transfer learning process exhibited prominent advantages for denoising images degraded by severe noise, peak signal-to-noise ratio (PSNR) below 8 dB, while preserving fine image features and improving the PSNR to above 18 dB. Importantly, the same pre-trained optical network could be consistently fine-tuned to process degraded images from highly diverse styles ranging from handwritten digits (MNIST) and chest X-rays (ChestMNIST) to CIFAR-10 images and human faces (CelebA). We further demonstrated the critical role of our optical denoisers in vision-based applications, including face detection, plate recognition, and localization of UAVs in noisy conditions.
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Submitted 8 May, 2026;
originally announced May 2026.
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From flat to narrow bands: Engineering quantum emission in a one-dimensional Lieb lattice
Authors:
Zhiyong Liu,
Yue Sun,
Ying Hu
Abstract:
We develop a comprehensive theoretical framework that unifies quantum emission dynamics in one-dimensional Lieb lattices, bridging the gap between ideal flat-band coherence and realistic narrow-band dissipation. By coupling an emitter to sublattices with finite flat-band wavefunction overlap, we activate a collective, size-independent interaction fundamentally distinct from dispersive-band process…
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We develop a comprehensive theoretical framework that unifies quantum emission dynamics in one-dimensional Lieb lattices, bridging the gap between ideal flat-band coherence and realistic narrow-band dissipation. By coupling an emitter to sublattices with finite flat-band wavefunction overlap, we activate a collective, size-independent interaction fundamentally distinct from dispersive-band processes. Controllably breaking lattice symmetry transforms the flat band into a narrow dispersive band, enabling a continuous crossover from non-Markovian to Markovian dynamics governed by the competition between coupling strength and engineered bandwidth. Crucially, we derive explicit scaling laws that provide a quantitative blueprint for tuning spontaneous emission from coherent trapping to Markovian decay. Our work provides a unified framework that connects idealized flat-band physics to emerging narrow-band platforms such as moir$\rm\acute{e}$ photonic crystals, offering a practical toolkit for interpreting experiments and engineering quantum emission in structured photonic environments.
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Submitted 7 May, 2026;
originally announced May 2026.
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Agentic Discovery of Exchange-Correlation Density Functionals
Authors:
Titouan Duston,
Jiashu Liang,
Yuanheng Wang,
Weihao Gao,
Xuelan Wen,
Nan Sheng,
Weiluo Ren,
Yang Sun,
Yixiao Chen
Abstract:
The development of accurate exchange-correlation (XC) functionals remains a longstanding challenge in density functional theory (DFT). The vast majority of XC functionals have been hand designed by human researchers combining physical insight, exact constraints, and empirical fitting. Recent advances in large language models enable a systematic, automated alternative to this human-driven design lo…
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The development of accurate exchange-correlation (XC) functionals remains a longstanding challenge in density functional theory (DFT). The vast majority of XC functionals have been hand designed by human researchers combining physical insight, exact constraints, and empirical fitting. Recent advances in large language models enable a systematic, automated alternative to this human-driven design loop. This report presents an agentic search system in which an LLM proposes structured functional-form changes guided by evolutionary history. The system attempts to improve functional performance through an iterative plan-execute-summarize loop, where improvements are measurable by optimizing functional parameters against a standard thermochemistry dataset, then evaluating performance on a held-out subset. The strongest discovered functional, SAFS26-a (Seed Agentic Functional Search 2026), improves upon the gold-standard ωB97M-V baseline by ~9%. These results also surface a cautionary lesson for AI-assisted science: models powerful enough to discover genuine improvements are equally capable of exploiting unphysical shortcuts to game the benchmark; domain expertise translated into explicitly enforced constraints remains essential to keeping results scientifically grounded.
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Submitted 6 May, 2026;
originally announced May 2026.
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Embedded underwater front-end electronics for the 3-inch photomultipliers in the JUNO experiment
Authors:
Cédric Cerna,
Miao He,
Xiaoshan Jiang,
Juan Pedro Ochoa-Ricoux,
Frédéric Perrot,
Angel Abusleme,
Thomas Adam,
Fengpeng An,
Costas Andreopoulos,
Giuseppe Andronico,
João Pedro Athayde Marcondes de André,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Didier Auguste,
Nikita Balashov,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Beretta,
Antonio Bergnoli,
Nikita Bessonov,
Daniel Bick,
Lukas Bieger,
Svetlana Biktemerova
, et al. (576 additional authors not shown)
Abstract:
The Jiangmen Underground Neutrino Observatory (JUNO) is a 20-kton liquid scintillator-based, low-radioactivity, multi-purpose neutrino detector located 693 meters (1800 m.w.e.) underground in the Guangdong province, China. To detect scintillation light produced in the target, the detector is equipped with 17,612 20-inch photomultipliers (PMTs), forming the Large PMT system (LPMT). In addition, 25,…
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The Jiangmen Underground Neutrino Observatory (JUNO) is a 20-kton liquid scintillator-based, low-radioactivity, multi-purpose neutrino detector located 693 meters (1800 m.w.e.) underground in the Guangdong province, China. To detect scintillation light produced in the target, the detector is equipped with 17,612 20-inch photomultipliers (PMTs), forming the Large PMT system (LPMT). In addition, 25,600 3-inch photomultipliers (the Small Photomultiplier System or SPMT) are deployed in the gaps between the LPMTs.
This paper presents the design and performance of the underwater front-end electronics developed for the SPMT system. It details the individual electronics boards and their key components, the inter-board interfaces, the system-level design, and the firmware architecture that supports data acquisition and control. It also outlines mechanical and thermal integration, board validation procedures, and system performance metrics. The readout chain includes digitization of 128 PMT channels per unit, synchronized time-stamping, charge measurement, event packaging, and bandwidth management. Comprehensive validation confirms the system's readiness to meet JUNO's stringent physics goals. The underwater electronics achieve noise levels as low as 0.04 photoelectrons with minimal crosstalk (below 0.4%) and a bandwidth of 57 MB/s, ensuring reliable single photo-electron detection and operation under high-rate conditions. The SPMT system has now been fully integrated and installed in JUNO. Its commissioning and physics performance will be reported in a future publication.
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Submitted 1 June, 2026; v1 submitted 28 April, 2026;
originally announced April 2026.
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Wave-number-dependent closure condition for fluid moment equations
Authors:
Yong Sun,
Shijia Chen,
Minqing He,
Sizhong Wu,
Rui Cheng,
Jie Yang,
Lei Yang,
Zhiyu Sun,
Liangwen Chen,
Hua Zhang
Abstract:
Fluid models offer crucial computational efficiency for plasma simulations, yet accurately capturing kinetic effects like Landau damping remains a fundamental challenge. While conventional closures (e.g., Hammett-Perkins and Hunana) are widely used, their fidelity relative to exact kinetic response degrades significantly depending on the perturbation wave number. Here, we propose a novel wave-numb…
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Fluid models offer crucial computational efficiency for plasma simulations, yet accurately capturing kinetic effects like Landau damping remains a fundamental challenge. While conventional closures (e.g., Hammett-Perkins and Hunana) are widely used, their fidelity relative to exact kinetic response degrades significantly depending on the perturbation wave number. Here, we propose a novel wave-number-dependent closure condition for the three-moment fluid equations that explicitly preserves the primary dispersion relation. By mapping Padé approximant coefficients directly to the kinetic roots of the collisionless Vlasov-Poisson system, we derive an analytical closure that rigorously embeds exact kinetic scaling across all spatial scales. We further demonstrate that this framework readily extends to collisional plasmas via the BGK model. This deterministic approach precisely captures the long-term macroscopic evolution of fluid moments and field energy, offering a rigorous foundation for high-fidelity fluid modeling.
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Submitted 28 April, 2026; v1 submitted 27 April, 2026;
originally announced April 2026.
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VOLT: Volumetric Wide-Field Microscopy via 3D-Native Probabilistic Transport
Authors:
Yetao He,
Wenhan Guo,
Deliang Wei,
Evan Bel,
Ji Yi,
Yu Sun
Abstract:
Three-dimensional (3D) wide-field fluorescence microscopy is a widely used modality for volumetric imaging, but suffers from characteristic out-of-focus blur. Existing reconstruction methods either struggle to operate on high-dimensional volumes or fail to provide credibility characterization of the reconstruction. In this work, we introduce Volumetric Transport (VOLT), a 3D-native probabilistic f…
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Three-dimensional (3D) wide-field fluorescence microscopy is a widely used modality for volumetric imaging, but suffers from characteristic out-of-focus blur. Existing reconstruction methods either struggle to operate on high-dimensional volumes or fail to provide credibility characterization of the reconstruction. In this work, we introduce Volumetric Transport (VOLT), a 3D-native probabilistic framework for wide-field fluorescence microscopy reconstruction. VOLT combines a transport-based formulation that maps degraded measurements to clean volumes via stochastic interpolants with a 3D-native anisotropic network that separates lateral and axial processing. This design operates directly in voxel space and achieves improved scalability to large volumes without relying on slice-wise approximations. We develop both stochastic (SDE) and deterministic (ODE) variants within the same framework. We validate VOLT on simulated wide-field microscopy datasets. Our results show that VOLT significantly improves reconstruction quality in both lateral and axial directions while providing voxel-wise credibility estimates.
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Submitted 20 April, 2026;
originally announced April 2026.
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FlowRefiner: Flow Matching-Based Iterative Refinement for 3D Turbulent Flow Simulation
Authors:
Yilong Dai,
Yiming Sun,
Yiheng Chen,
Shengyu Chen,
Xiaowei Jia,
Runlong Yu
Abstract:
Accurate autoregressive prediction of 3D turbulent flows remains challenging for neural PDE solvers, as small errors in fine-scale structures can accumulate rapidly over rollout. In this paper, we propose FlowRefiner, a flow matching-based iterative refinement framework for 3D turbulent flow simulation. The method replaces stochastic denoising refinement with deterministic ODE-based correction, us…
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Accurate autoregressive prediction of 3D turbulent flows remains challenging for neural PDE solvers, as small errors in fine-scale structures can accumulate rapidly over rollout. In this paper, we propose FlowRefiner, a flow matching-based iterative refinement framework for 3D turbulent flow simulation. The method replaces stochastic denoising refinement with deterministic ODE-based correction, uses a unified velocity-field regression objective across all refinement stages, and introduces a decoupled sigma schedule that fixes the noise range independently of refinement depth. These design choices yield stable and effective refinement in the small-noise regime. Experiments on large-scale 3D turbulence with rich multi-scale structures show that FlowRefiner achieves state-of-the-art autoregressive prediction accuracy and strong physical consistency. Although developed for turbulent flow simulation, the proposed framework is broadly applicable to iterative refinement problems in scientific modeling.
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Submitted 24 April, 2026; v1 submitted 18 April, 2026;
originally announced April 2026.
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Large-eddy simulation of the FDA benchmark blood pump: validation against experiments and implications for turbulent flow mechanisms
Authors:
Xuanming Huang,
Chi Ding,
Yujie Sun,
Shidi Huang,
Andrea Cioncolini,
Damiano Padovani,
Ju Liu
Abstract:
This study presents a systematic validation and comparative assessment of computational fluid dynamics (CFD) strategies for centrifugal blood pump simulations using the U.S. Food and Drug Administration benchmark model. A scale-resolving large eddy simulation (LES) with transient sliding-interface (SI) coupling is evaluated and compared against Reynolds-averaged Navier-Stokes (RANS) approaches emp…
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This study presents a systematic validation and comparative assessment of computational fluid dynamics (CFD) strategies for centrifugal blood pump simulations using the U.S. Food and Drug Administration benchmark model. A scale-resolving large eddy simulation (LES) with transient sliding-interface (SI) coupling is evaluated and compared against Reynolds-averaged Navier-Stokes (RANS) approaches employing both multiple reference frame and SI formulations. Numerical predictions are validated through direct comparison with particle image velocimetry measurements under two representative operating conditions. The results indicate that LES with transient rotor-stator coupling achieves consistently improved agreement with experimental velocity fields compared with RANS-based methods, particularly in the diffuser region where strong intermittency and wall-bounded turbulence are present. In contrast, RANS-based approaches exhibit noticeable discrepancies in these regions. A mesh sensitivity study and an assessment of temporal averaging effects are conducted for LES. The quality of the LES results is further quantified using three complementary metrics, demonstrating that a mesh resolution of approximately 80 million cells achieves a well-resolved LES regime. Building on the validated scale-resolving simulations, detailed analyses of vortical structures, turbulent kinetic energy distributions, and velocity energy spectra are performed to characterize the internal flow physics of the pump. This study demonstrates that scale-resolving, transient simulation approaches are essential for accurately capturing the highly unsteady, turbulence-dominated flow features in ventricular assist devices and provides practical guidance for future high-fidelity hemodynamic and hemocompatibility studies.
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Submitted 17 April, 2026;
originally announced April 2026.
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A Data-Free, Physics-Informed Surrogate Solver for Drift Kinetic Equation: Enabling Fast Neoclassical Toroidal Viscosity Torque Modeling in Tokamaks
Authors:
Xingting Yan,
Yuetao Meng,
Nana Bao,
Youwen Sun,
Weiyong Zhou,
Jinpeng Huang
Abstract:
Toroidal rotation is crucial for maintaining stable and high performance plasmas in tokamak fusion reactors. Among its driving mechanisms, the neoclassical toroidal viscosity (NTV) torque--induced by three-dimensional magnetic perturbations--is particularly significant due to its strong impact and controllability, especially for reactor-scale devices like ITER where conventional momentum injection…
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Toroidal rotation is crucial for maintaining stable and high performance plasmas in tokamak fusion reactors. Among its driving mechanisms, the neoclassical toroidal viscosity (NTV) torque--induced by three-dimensional magnetic perturbations--is particularly significant due to its strong impact and controllability, especially for reactor-scale devices like ITER where conventional momentum injection method becomes less effective. However, traditional first-principle NTV modeling is computationally expensive, as it requires solving the drift kinetic equation (DKE) in high-dimensional phase space, therefore precluding any real-time applications such as active control or nonlinear integrated modeling of tokamak plasma. Although surrogate solver shows promising ability for accelerating scientific computations, obtaining the data required to train such model is still very challenging. In this work, we present a novel, data-free approach for developing fast surrogate solver of DKE, by training neural network solely based on physical constraints. Such physical constraints are implemented in two ways: First, the loss function is defined based on physical governing equations; Second, the boundary condition is hard-coded into the predicting model. The proposed model is validated against the dataset generated by first-principle numerical solver, which is found to achieve accurate DKE solution with significantly reduced time consuming. In particular, physics-driven surrogate shows higher physical consistency than data-driven surrogate. In general, our study provides a new idea for developing surrogate solvers in data-scarce scenarios, and demonstrates the potential of purely physics-driven neural networks to accelerate demanding scientific computations.
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Submitted 14 April, 2026;
originally announced April 2026.
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Magnetically Tunable Chiral Phonon Polaritons with Magneto-optical Bound States in the Continuum
Authors:
Yu Sun,
Jue Li,
Wei Li,
Bo Li,
Qinghua Song,
Mengyao Li
Abstract:
Chiral phonon-polaritonic states are of interest for handedness-dependent light-matter interactions, yet their realization and magnetic control remain challenging, while direct magneto-optical tunability of phonon-polaritonic media is limited. Here, we propose a hybrid platform in which an hBN phonon polariton couples to a chiral bound state in the continuum supported by a magneto-optical photonic…
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Chiral phonon-polaritonic states are of interest for handedness-dependent light-matter interactions, yet their realization and magnetic control remain challenging, while direct magneto-optical tunability of phonon-polaritonic media is limited. Here, we propose a hybrid platform in which an hBN phonon polariton couples to a chiral bound state in the continuum supported by a magneto-optical photonic crystal, enabling strong and selective photonic coupling. The interaction gives rise to pronounced mode splitting and the formation of hybrid states, and their modal composition is quantified by phonon-proportion analysis and described by a coupling theory. Importantly, the hybridization can be controlled by magnetic bias through the magneto-optical response of the photonic component, providing control over the modal composition and spectral response. In addition, the hybrid states exhibit handedness-selective absorption under circularly polarized excitation. This work offers a feasible route toward magnetically tunable chiral phonon-polaritonic devices and hybrid polaritonic functionalities
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Submitted 14 April, 2026;
originally announced April 2026.
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Broadband hard X-ray attosecond pulses from extremely chirped electron beams
Authors:
River Robles,
Veronica Guo,
David Cesar,
Paris Franz,
Aliaksei Halavanau,
Alberto Lutman,
Takahiro Sato,
Sanghoon Song,
Nicholas Sudar,
Yanwen Sun,
Zhen Zhang,
Diling Zhu,
Agostino Marinelli
Abstract:
Attosecond pulses from free-electron lasers have opened the doors to atomic site-specific studies of bound electronic dynamics on their natural, sub-femtosecond timescales. Key to their success has been electron beam shaping techniques enabling the generation of sub-femtosecond current spikes with peak currents on the order of 10 kA. We demonstrate in an RF linac the generation of current spikes w…
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Attosecond pulses from free-electron lasers have opened the doors to atomic site-specific studies of bound electronic dynamics on their natural, sub-femtosecond timescales. Key to their success has been electron beam shaping techniques enabling the generation of sub-femtosecond current spikes with peak currents on the order of 10 kA. We demonstrate in an RF linac the generation of current spikes with extreme chirps on the order of 350 MeV/micron, directly competitive with the chirps expected from beam-driven plasma wakefield accelerators. Leveraging chirp-taper compensation, we use these highly chirped beams to generate hard X-ray attosecond pulses with bandwidths exceeding 30 eV, a factor of two beyond previous demonstrations. We simultaneously present the first explicit experimental evidence of chirp-taper compensation in an attosecond XFEL, finding that optimal tapering improves the bandwidth and pulse energy by factors of two and five, respectively, for our conditions. In addition to the immediate utility of such broadband hard X-ray pulses, electron beams with such extreme chirps can be utilized for unique new experimental modalities by performing further compression after the undulators. Such post-lasing compression can enable subsequent superradiant light emission at longer wavelengths, or direct excitation of quantum systems with the beam's intense space-charge field for unique attosecond pump-probe possibilities.
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Submitted 19 August, 2026; v1 submitted 10 April, 2026;
originally announced April 2026.
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Temporal soliton generation in an ultra-high-effective-Q Kerr resonator enabled by Raman gain
Authors:
Georges Semaan,
Yifan Sun,
Nicolas Englebert,
Simon-Pierre Gorza,
François Leo
Abstract:
We demonstrate temporal pattern formation in a coherently driven fiber ring cavity whose effective finesse is continuously reconfigured using distributed Raman amplification. We achieve an effective finesse of up to $\mathcal{F}_{\mathrm{eff}}\approx800$, corresponding to a linewidth of approximately 725 Hz ($Q\approx2.7\times10^{11}$) at 1555 nm. By exploiting the resulting increase in effective…
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We demonstrate temporal pattern formation in a coherently driven fiber ring cavity whose effective finesse is continuously reconfigured using distributed Raman amplification. We achieve an effective finesse of up to $\mathcal{F}_{\mathrm{eff}}\approx800$, corresponding to a linewidth of approximately 725 Hz ($Q\approx2.7\times10^{11}$) at 1555 nm. By exploiting the resulting increase in effective photon lifetime, we excite stable temporal cavity solitons and generate a low-repetition-rate frequency comb with a spacing of 580~kHz. Finally, we analyze the impact of the Raman loss-compensation mechanism, particularly its associated noise and show that a trade-off exists between soliton excitation threshold and stability.
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Submitted 2 April, 2026;
originally announced April 2026.
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Double-Freeform Lens Design for Angular-Spatial Control of Light Fields
Authors:
Yuou Sun,
Bailin Deng,
Juyong Zhang
Abstract:
Precise simultaneous control of both angular and spatial light-field distributions remains a longstanding challenge in optical design, often requiring complex multi-element configurations. In this work, we propose a compact single-lens solution that achieves unified angular-spatial modulation through the co-optimization of double freeform surfaces. The problem is formulated as an extended caustic…
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Precise simultaneous control of both angular and spatial light-field distributions remains a longstanding challenge in optical design, often requiring complex multi-element configurations. In this work, we propose a compact single-lens solution that achieves unified angular-spatial modulation through the co-optimization of double freeform surfaces. The problem is formulated as an extended caustic design that enforces prescribed irradiance patterns on two distinct receptive planes, where the dual-plane constraint implicitly defines the directional characteristics of the light field while preserving spatial accuracy. This framework eliminates the need for auxiliary optical components while delivering performance comparable to that of conventional multi-lens systems. Comprehensive numerical simulations verify the method's effectiveness, demonstrating accurate and stable control of both angular and spatial light-field properties. The proposed approach establishes a practical foundation for compact, high-performance optical systems and provides a promising route toward integrated angular-spatial light-field engineering.
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Submitted 1 April, 2026;
originally announced April 2026.
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Observation of Floquet erratic non-Hermitian skin effect in photonic mesh lattice
Authors:
Yeyang Sun,
Shu Yang,
Yi Yang
Abstract:
In ordered, translationally invariant non-Hermitian systems, the skin effect is understood as a boundary phenomenon: nonreciprocal hopping drives an extensive accumulation of eigenstates towards the edges, whereas the periodic-boundary spectrum remains Bloch extended. Here we experimentally reveal the opposite limit -- a disorder-enabled, boundary-independent, and intrinsically bulk form of skin l…
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In ordered, translationally invariant non-Hermitian systems, the skin effect is understood as a boundary phenomenon: nonreciprocal hopping drives an extensive accumulation of eigenstates towards the edges, whereas the periodic-boundary spectrum remains Bloch extended. Here we experimentally reveal the opposite limit -- a disorder-enabled, boundary-independent, and intrinsically bulk form of skin localization -- the recently predicted erratic non-Hermitian skin effect (ENHSE), realized in a driven photonic platform. Using a time-multiplexed photonic mesh lattice with programmable gain, loss, and phase modulation, we engineer spatially fluctuating imaginary gauge fields and realize a Floquet non-Hermitian lattice whose global reciprocity can be tuned independently of strong local nonreciprocity. We observe a disorder-driven non-Hermitian topological transition between two oppositely directed disordered skin phases through a critical point of global reciprocity. At this transition, boundary skin accumulation disappears, yet the wave dynamics self-organizes into bulk-localized patterns without any interface, providing direct evidence of ENHSE. The measured localization profiles agree with simulations and exhibit the defining feature that distinct eigenstates share a common bulk-localized envelope determined by the disordered imaginary gauge fields. By further introducing controllable on-site disorder, we reveal the competition between ENHSE and Anderson localization, and show how increasing scattering progressively suppresses erratic skin dynamics. Our results help establish ENHSE as a unique disorder-induced non-Hermitian phenomenon and open a route to engineering localization, transport, and topology beyond conventional Bloch and boundary-based paradigms.
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Submitted 31 March, 2026;
originally announced April 2026.
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Real-Time Wiener Deconvolution for feature reconstruction in JUNO
Authors:
L. Lastrucci,
M. Grassi,
A. Triossi,
J. Hu,
X. Jiang,
R. Brugnera,
A. Garfagnini,
V. Cerrone,
L. V. D'Auria,
A. Gavrikov,
R. M. Guizzetti,
A. Serafini,
G. Andronico,
V. Antonelli,
A. Barresi,
D. Basilico,
M. Beretta,
A. Bergnoli,
M. Borghesi,
A. Brigatti,
R. Bruno,
A. Budano,
B. Caccianiga,
A. Cammi,
R. Caruso
, et al. (52 additional authors not shown)
Abstract:
In particle physics, experiments generate substantial amounts of data that can be difficult to process without preliminary scaling. To avoid losing potentially crucial data, experimental collaborations are studying novel techniques for real-time data processing to extract features for further physics analysis. A common approach, especially in neutrino physics, is to use FPGAs for data acquisition…
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In particle physics, experiments generate substantial amounts of data that can be difficult to process without preliminary scaling. To avoid losing potentially crucial data, experimental collaborations are studying novel techniques for real-time data processing to extract features for further physics analysis. A common approach, especially in neutrino physics, is to use FPGAs for data acquisition and pre-processing. This paper presents an advanced Real-Time Wiener deconvolution algorithm designed to leverage the processing capabilities of the FPGA integrated into the readout boards of the Jiangmen Underground Neutrino Observatory (JUNO). The goal is to enable real-time reconstruction of the signal generated by photomultiplier tubes (PMTs) when neutrino interactions are detected. By exploiting online reconstruction of the signal generated by PMTs, we expect to improve the detection of low-energy depositions, such as those produced by transient astrophysical phenomena. These depositions are usually not saved because of the significant background that affects the low end of the energy spectrum, which would result in a large trigger rate, hence a large amount of data required for storage. This paper presents the features of the algorithm, including its ability to manage high-throughput data streams with minimal latency, adaptability, and resilience in discerning the characteristics of input data. Performance is evaluated on a JUNO electronic board. This study further demonstrates the potential of FPGA-based solutions for neutrino physics.
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Submitted 26 March, 2026;
originally announced March 2026.
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Enhancement of signal-to-noise ratio at a high-order exceptional point of coherent perfect absorption
Authors:
Zi-Qi Wang,
Yi-Ming Sun,
Yao-Dong Hu,
Yi-Pu Wang,
Rui-Chang Shen,
Wei-Jiang Wu,
J. Q. You
Abstract:
Exceptional points (EPs) in non-Hermitian systems offer a remarkably strong response to weak perturbations, but the nonorthogonal nature of the corresponding eigenvectors causes noise to diverge, hindering EPs practical application. Here, we report a twelve-fold enhancement of signal-to-noise ratio (SNR) in magnetic field sensing enabled by a third-order EP of coherent perfect absorption (CPA EP3)…
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Exceptional points (EPs) in non-Hermitian systems offer a remarkably strong response to weak perturbations, but the nonorthogonal nature of the corresponding eigenvectors causes noise to diverge, hindering EPs practical application. Here, we report a twelve-fold enhancement of signal-to-noise ratio (SNR) in magnetic field sensing enabled by a third-order EP of coherent perfect absorption (CPA EP3) in a passive cavity magnonic system. This non-Hermitian magnonic platform comprises two identical yttrium iron garnet (YIG) spheres coherently coupled to a cavity mode, in which the CPA EP3 is realized by engineering the three-mode loss to form a pseudo-Hermitian absorption Hamiltonian. By independently tailoring the absorption EP apart from the resonance EP, the system circumvents the noise divergence caused by eigenbasis collapse. Notably, we harness the sensitivity of the minimum output intensity near CPA to perturbations, yielding a seventyfold SNR improvement and a 400-fold increase in responsivity compared with non-CPA system. A comprehensive noise analysis over one hundred repeated measurements confirms the suppression of frequency noise near the CPA EP3. This demonstrates that our scheme not only avoids the noise divergence plaguing conventional higher-order EP sensors but also provides a general strategy to exploit both CPA and EP for SNR enhancement in passive non-Hermitian systems.
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Submitted 12 March, 2026;
originally announced March 2026.
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Sensing Low-Frequency Field with Rydberg Atoms via Quantum Weak Measurement
Authors:
Ding Wang,
Shenchao Jin,
Xiayang Fan,
Hongjing Li,
Jiatian Liu,
Jingzheng Huang,
Guihua Zeng,
Yuan Sun
Abstract:
Recently, Rydberg atom has emerged as an attractive choice to realize quantum sensing of low-frequency electric field. The progress so far has mostly utilized the intensity and phase changes in probe laser and the corresponding detection mechanism still remains classical. Nevertheless, external field acting on the Rydberg state can induce the polarization variation of probe laser in the Rydberg el…
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Recently, Rydberg atom has emerged as an attractive choice to realize quantum sensing of low-frequency electric field. The progress so far has mostly utilized the intensity and phase changes in probe laser and the corresponding detection mechanism still remains classical. Nevertheless, external field acting on the Rydberg state can induce the polarization variation of probe laser in the Rydberg electromagnetically induced transparency (EIT) system embedded in realistic multi-state atoms. We experimentally observe this phenomenon and realize signal extraction by appropriately utilizing the polarization degrees of freedom. Based on such a mechanism, we further design and implement a quantum weak measurement scheme, which clearly suppresses the technical noise and leads to considerable improvement of performance. Evaluation of the sensitivities across different post-selection angles demonstrates that the weak measurement results agree well with the theoretical model predictions. The advantages of our method are analyzed from multiple aspects, including characterizing the responses over different frequencies and comparing the responses of the weak measurement scheme and the traditional transmission-based method. After accounting for the screening effect of a measured ratio 17\% where the $^\text{87}$Rb atoms experience a substantially reduced field inside the glass cell, the performance reaches 33 $μ\text{V}~\text{cm}^\text{-1}~\text{Hz}^\text{-1/2}$ in sensitivity and 1.0 $μ\text{V/cm}$ in minimal detectable field for an integration time of 1000 s, as perceived by the atoms.
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Submitted 10 March, 2026;
originally announced March 2026.
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Interface Engineered Moiré Graphene Superlattices: Breaking the Auger Carrier Multiplication Limit for Infrared Single-Photon Detection
Authors:
Sichao Du,
Ning Li,
Zhufeng Pan,
Munir Ali,
Hengrui Zhang,
Duokai Chang,
Yuehang Zhang,
Qiang Wen,
Shuo Zhang,
Hao Wu,
Yunlei Sun,
Qiuting Wang,
Hao Xie,
Chaohao Chen,
Zhenyi Ni,
Qiangbing Guo,
Duo Xiao,
Wen-Yan Yin
Abstract:
Hot electrons undergo Auger scattering during their relaxation process has a multiplication effect,which can generate more electrons above the Fermi level, thus improving the efficiency of photoelectric signal conversion.However,the photo-current gain brought by the Auger carrier multiplication is generally limited with a value less than 5,due to the rapid recombination of photo-generated charge-c…
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Hot electrons undergo Auger scattering during their relaxation process has a multiplication effect,which can generate more electrons above the Fermi level, thus improving the efficiency of photoelectric signal conversion.However,the photo-current gain brought by the Auger carrier multiplication is generally limited with a value less than 5,due to the rapid recombination of photo-generated charge-carriers and the inherently low light absorption of two-dimensional materials.Herein,by twisting graphene to an interlayer angle of 10<sub>o</sub>,we report a layer-dependent electronic correlations leading to an efficient carrier multiplication gain of 10<sup>3</sup>.This is primarily offered by the additional localized density-of-states at interface of the bi-layer 10<sub>o</sub>,moire graphene,and the enhanced interlayer coupling of electron waves in a five-layer moire graphene superlattice structure.Therefore,we can harvest the hot electrons during their energy relaxation through a thermalized optical phonon bottleneck effect.It is this effect that promotes the accumulated hot electrons to achieve a maximum Auger scattering rate ~ 10<sup>10</sup>*ps<sup>-1</sup>*cm<sup>-2</sup>.Furthermore,the ballistic transport of these hot electrons and Schottky barrier from a 90 nm thick silicon-on-insulator (SOI) silicon effectively block the thermal noise,thus leading to a highly sensitive near-infrared detection characteristic.At a low incident light power of ~ 10<sup>-13</sup> W/cm<sup>2</sup>,the resulting signal-to-noise ratio is more than 100 dB.The strengthened electromagnetic interaction from highly thermalized optical phonon in stacked moire graphene is utilized in this work.The hot electron multiplication suggests the applicability of Van der Waals moire superlattice architecture for harvesting charge carriers,thus paving the pathway to design infrared single-photon avalanche detectors.
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Submitted 10 March, 2026;
originally announced March 2026.