Showing 1–50 of 215 results for author: Zhou, S

Quantum Frequency Resolved Optical Gating of Few-Cycle Squeezed Vacuum

Authors: Thomas Zacharias, Elina Sendonaris, Robert Gray, James Williams, Ryoto Sekine, Maximilian Shen, Selina Zhou, Alireza Marandi

Abstract: Offering terahertz of bandwidths and femtosecond timescales, ultrafast optics is enabling both the study of fundamental quantum optical phenomena and the advancement of quantum-enhanced applications. However, unlocking the full potential of ultrafast quantum optics requires accessing the temporal characteristics of ultrashort quantum pulses across ultrabroad bandwidths. This is particularly import… ▽ More Offering terahertz of bandwidths and femtosecond timescales, ultrafast optics is enabling both the study of fundamental quantum optical phenomena and the advancement of quantum-enhanced applications. However, unlocking the full potential of ultrafast quantum optics requires accessing the temporal characteristics of ultrashort quantum pulses across ultrabroad bandwidths. This is particularly important in the near-infrared and visible range of the optical spectrum, which, unlike the terahertz and long-wave infrared, has remained beyond the reach of current techniques. Here, we break this barrier by translating frequency-resolved optical gating (FROG), a widely used technique for ultrafast classical pulse characterization, to the quantum regime. We show how such a quantum FROG can measure complex temporal modes and sub-optical-cycle quadrature covariances in the near-infrared, enabling complete characterization of microscopic Gaussian states. We experimentally use the quantum-FROG to report the measurement of quadrature correlations, complex temporal modes, and squeezing levels of multimode ultrafast squeezed vacuum states generated on a nanophotonic chip. We access multimode squeezing levels of a femtosecond quantum pulse approaching 7 dB and demonstrate FROG-based measurement bandwidths exceeding 100 THz. Quantum FROG enables measurement of previously inaccessible quantum features of ultrashort pulses at the sub-optical-cycle regime and highlights a practical path to accessing terahertz of bandwidths in quantum optics for applications in computing, sensing, and imaging. △ Less

Submitted 8 April, 2026; originally announced April 2026.

Liquid structure adjacent to solid surfaces follows the superposition principle

Authors: Qian Ai, Haiyi Wu, Lalith Krishna Samanth Bonagiri, Kaustubh S. Panse, Shan Zhou, Fujia Zhao, Yitong Li, Kenneth S. Schweizer, Narayana R. Aluru, Yingjie Zhang

Abstract: Liquid structure at solid-liquid interfaces is critical for many natural and engineered processes ranging from biological signal transduction to electrochemical energy conversion. Advanced experimental and computational methods have provided insights into the structure of liquids adjacent to planar substrates at the nanoscale. However, realistic solid-liquid interfaces are inevitably inhomogeneous… ▽ More Liquid structure at solid-liquid interfaces is critical for many natural and engineered processes ranging from biological signal transduction to electrochemical energy conversion. Advanced experimental and computational methods have provided insights into the structure of liquids adjacent to planar substrates at the nanoscale. However, realistic solid-liquid interfaces are inevitably inhomogeneous across multiple length scales, presenting a complexity that surpasses the capabilities of existing approaches. Here we bridge the complexity gap by discovering and utilizing a hitherto hidden principle of interfacial liquid--superposition. Experimentally, we use 3D atomic force microscopy (3D-AFM) to image the interfacial structure of a wide range of organic and aqueous solvents and electrolytes, uncovering universal liquid density oscillations and emergent liquid layer reconfigurations at heterogeneous substrate sites. We further develop an analytical model, coined solid-liquid superposition (SLS), which solves the interfacial liquid density distribution based on a key descriptor: the effective total correlation function (ETCF) between a liquid molecule and nearby solid atoms. SLS not only explains all the experimentally observed interfacial liquid distribution profiles from the angstrom to near-micron scale, but also predicts more precise atomic-scale interference patterns which are further corroborated by molecular dynamics (MD) simulations. This study unveils a key structural descriptor of interfacial liquids, and establishes a theoretical framework for rapidly and accurately predicting liquid structures adjacent to solid surfaces with arbitrary morphology and size scale. △ Less

Submitted 26 March, 2026; originally announced March 2026.

Optimality and annealing path planning of dynamical analog solvers

Authors: Shu Zhou, K. Y. Michael Wong, Juntao Wang, David Shui Wing Hui, Daniel Ebler, Jie Sun

Abstract: Recently proposed analog solvers based on dynamical systems, such as Ising machines, are promising platforms for large-scale combinatorial optimization. Yet, given the heuristic nature of the field, there is very limited insight on optimality guarantees of the solvers, as well as how parameter schedules shape dynamics and outcomes. Here, we develop a dynamical mean-field framework to analyze Ising… ▽ More Recently proposed analog solvers based on dynamical systems, such as Ising machines, are promising platforms for large-scale combinatorial optimization. Yet, given the heuristic nature of the field, there is very limited insight on optimality guarantees of the solvers, as well as how parameter schedules shape dynamics and outcomes. Here, we develop a dynamical mean-field framework to analyze Ising-machine dynamics for finding the ground state energy of the Sherrington-Kirkpatrick(SK) model of spin glasses and identify mechanisms that enable rapid convergence to provenly near-optimal energies. For a fixed target energy density Ec, we show that solutions are typically reached within O(1) matrix vector multiplications, indicating constant time complexity. We further delineate theoretical limitations arising from different parameter-scheduling trajectories and demonstrate a pronounced benefit of temperature-only annealing for the Coherent Ising Machine. Building on these insights, we propose a general framework for designing optimized parameter schedules, thereby improving the practical effectiveness of Ising machines for complex optimization tasks. The superior performance of the dynamical solvers is illustrated by the attainment of the ground state energy of the SK model. △ Less

Submitted 17 March, 2026; v1 submitted 14 March, 2026; originally announced March 2026.

ChemFlow:A Hierarchical Neural Network for Multiscale Representation Learning in Chemical Mixtures

Authors: Jinming Fan, Chao Qian, Wilhelm T. S. Huck, William E. Robinson, Shaodong Zhou

Abstract: Accurate prediction of the physicochemical properties of molecular mixtures using graph neural networks remains a significant challenge, as it requires simultaneous embedding of intramolecular interactions while accounting for mixture composition (i.e., concentrations and ratios). Existing approaches are ill-equipped to emulate realistic mixture environments, where densely coupled interactions pro… ▽ More Accurate prediction of the physicochemical properties of molecular mixtures using graph neural networks remains a significant challenge, as it requires simultaneous embedding of intramolecular interactions while accounting for mixture composition (i.e., concentrations and ratios). Existing approaches are ill-equipped to emulate realistic mixture environments, where densely coupled interactions propagate across hierarchical levels - from atoms and functional groups to entire molecules - and where cross-level information exchange is continuously modulated by composition. To bridge the gap between isolated molecules and realistic chemical environments, we present ChemFlow, a novel hierarchical framework that integrates atomic, functional group, and molecular-level features, facilitating information flow across these levels to predict the behavior of complex chemical mixtures. ChemFlow employs an atomic-level feature fusion module, Chem-embed, to generate context-aware atomic representations influenced by the mixture state and atomic characteristics. Next, bidirectional group-to-molecule and molecule-to-group attention mechanisms enable ChemFlow to capture functional group interactions both within and across molecules in the mixture. By dynamically adjusting representations based on concentration and composition, ChemFlow excels at predicting concentration-dependent properties and significantly outperforms state-of-the-art models in both concentration-sensitive and concentration-independent systems. Extensive experiments demonstrate ChemFlow's superior accuracy and efficiency in modeling complex chemical mixtures. △ Less

Submitted 3 March, 2026; originally announced March 2026.

Suppressed Rupture of Thin Metal Films via van der Waals Epitaxy

Authors: Wenxiang Wang, Jiaxing Wang, Guotong Wang, Zhichao Yan, Chenxiao Jiang, Siqin Zhou, Chuanli Yu, Jianhao Chen, Kun Zheng, Thomas Salez, Xiaoding Wei, Zhaohe Dai

Abstract: Ultrathin metal films exhibit liquid-like instabilities, rupturing via surface diffusion far below their melting points. This behavior constrains thermal budgets for advanced integrated circuits and emerging 2D-crystal devices. Here, we demonstrate that these instabilities can be fundamentally suppressed using graphene as a van der Waals (vdW) template. While conventional 20-nm-thick gold films br… ▽ More Ultrathin metal films exhibit liquid-like instabilities, rupturing via surface diffusion far below their melting points. This behavior constrains thermal budgets for advanced integrated circuits and emerging 2D-crystal devices. Here, we demonstrate that these instabilities can be fundamentally suppressed using graphene as a van der Waals (vdW) template. While conventional 20-nm-thick gold films break up into islands below 300 {\textdegree}C, templated films not only remain stable but also become structurally refined after annealing above 600 {\textdegree}C. This exceptional stability stems from a vdW-mediated crystallographic texture that reorganizes grain boundaries into a mechanically robust network. This mechanism significantly widens the processing window for nanoscale interconnects and enables high-temperature integration of metals with 2D-crystal technologies. △ Less

Submitted 23 February, 2026; originally announced February 2026.

Machine learning determines the Mg2SiO4 P-T phase diagram

Authors: Siyu Zhou, Daohong Liu, Chuanyu Zhang, Yu He, Xuben Wang, Xiaopan Zuo

Abstract: Phase transitions among Mg2SiO4 and its high-pressure polymorphs (wadsleyite and ringwoodite) are central to mantle dynamics and deep-mantle material cycling. However, the locations and Pressure-Temperature (P-T) dependences of these phase boundaries remain debated, largely due to experimental limitations at extreme conditions and the high computational cost of first-principles free-energy calcula… ▽ More Phase transitions among Mg2SiO4 and its high-pressure polymorphs (wadsleyite and ringwoodite) are central to mantle dynamics and deep-mantle material cycling. However, the locations and Pressure-Temperature (P-T) dependences of these phase boundaries remain debated, largely due to experimental limitations at extreme conditions and the high computational cost of first-principles free-energy calculations. Here, a machine-learning-potential driven workflow combining non-equilibrium thermodynamic integration (NETI) and two-phase coexistence simulations is employed to enable large-scale, long-timescale molecular dynamics sampling. Within this workflow, the melting curve of forsterite is evaluated and a complete P-T phase diagram is constructed. Relative to conventional ab initio approaches, this strategy reduces computational expense while retaining thermodynamic consistency in phase-stability assessment. The workflow is applicable to efficient evaluation of phase stability and thermodynamic properties in deep-Earth silicate systems. △ Less

Submitted 2 February, 2026; originally announced February 2026.

Enhanced 3D Gravity Inversion Using ResU-Net with Density Logging Constraints: A Dual-Phase Training Approach

Authors: Siyuan Dong, Jinghuai Gao, Shuai Zhou, Baohai Wu, Hongfa Jia

Abstract: Gravity exploration has become an important geophysical method due to its low cost and high efficiency. With the rise of artificial intelligence, data-driven gravity inversion methods based on deep learning (DL) possess physical property recovery capabilities that conventional regularization methods lack. However, existing DL methods suffer from insufficient prior information constraints, which le… ▽ More Gravity exploration has become an important geophysical method due to its low cost and high efficiency. With the rise of artificial intelligence, data-driven gravity inversion methods based on deep learning (DL) possess physical property recovery capabilities that conventional regularization methods lack. However, existing DL methods suffer from insufficient prior information constraints, which leads to inversion models with large data fitting errors and unreliable results. Moreover, the inversion results lack constraints and matching from other exploration methods, leading to results that may contradict known geological conditions. In this study, we propose a novel approach that integrates prior density well logging information to address the above issues. First, we introduce a depth weighting function to the neural network (NN) and train it in the weighted density parameter domain. The NN, under the constraint of the weighted forward operator, demonstrates improved inversion performance, with the resulting inversion model exhibiting smaller data fitting errors. Next, we divide the entire network training into two phases: first training a large pre-trained network Net-I, and then using the density logging information as the constraint to get the optimized fine-tuning network Net-II. Through testing and comparison in synthetic models and Bishop Model, the inversion quality of our method has significantly improved compared to the unconstrained data-driven DL inversion method. Additionally, we also conduct a comparison and discussion between our method and both the conventional focusing inversion (FI) method and its well logging constrained variant. Finally, we apply this method to the measured data from the San Nicolas mining area in Mexico, comparing and analyzing it with two recent gravity inversion methods based on DL. △ Less

Submitted 6 January, 2026; originally announced January 2026.

Proposal for energy modulation to demodulation in seeded free-electron lasers

Authors: Hanxiang Yang, Nanshun Huang, Zipeng Liu, Shengbin Ye, Wencai Cheng, Shudong Zhou, Cheng Yu, Tao Liu, Haixiao Deng

Abstract: Laser manipulation plays a critical role in precisely tailoring relativistic electron beams through energy modulation, enabling the generation of coherent, intense, and ultrashort radiation in accelerator-based light sources such as synchrotron radiation facilities and free-electron lasers (FELs). However, laser-induced energy modulation inevitably degrades electron beam quality by increasing ener… ▽ More Laser manipulation plays a critical role in precisely tailoring relativistic electron beams through energy modulation, enabling the generation of coherent, intense, and ultrashort radiation in accelerator-based light sources such as synchrotron radiation facilities and free-electron lasers (FELs). However, laser-induced energy modulation inevitably degrades electron beam quality by increasing energy spread. In this paper, a straightforward yet practical implementation method for verifying the electron beam demodulation process in seeded FELs is proposed. The method employs a dedicated demodulation undulator system, referred to as a demodulator, equipped with a phase shifter. Both one-dimensional analytical models and three-dimensional simulations demonstrate that introducing a $π$ phase shift in the demodulator enables simultaneous energy modulation and demodulation using only a single seed laser. Under optimized conditions with weak initial modulation, simulation results indicate that the energy modulation can be substantially reduced or nearly eliminated. With increasing laser intensity, the modulation amplitude is significantly suppressed by more than an order of magnitude, effectively mitigating energy spread degradation. The residual energy modulation can be characterized using complementary diagnostic techniques: the coherent undulator radiation method combined with the dispersion scan method. The proposed method is expected to enable precise control over electron beam energy modulation, potentially facilitating the development of high-repetition-rate, fully coherent X-ray sources with improved electron beam quality preservation. △ Less

Submitted 25 December, 2025; originally announced December 2025.

Comments: 13 pages, 14 figures

Corkscrew motion of Trypanosome brucei is driven by helical beating of the flagellum and facilitated by its bent shape

Authors: Sizhe Cheng, Devadyouti Das, Mykhaylo Barchuk, Raveen Armstrong, Michele M. Klingbeil, Becca Thomases, Shuang Zhou

Abstract: In the pathogenic parasite Trypanosoma brucei, a laterally attached flagellum drives rapid deformation of the complex cell body, producing puzzling dynamics. High-speed defocusing imaging reveals that surface points trace flower-like patterns in transverse planes. The petals arise from clockwise flagellar beating, which generates a right-handed helical wave propagating from the anterior tip along… ▽ More In the pathogenic parasite Trypanosoma brucei, a laterally attached flagellum drives rapid deformation of the complex cell body, producing puzzling dynamics. High-speed defocusing imaging reveals that surface points trace flower-like patterns in transverse planes. The petals arise from clockwise flagellar beating, which generates a right-handed helical wave propagating from the anterior tip along the body, advancing the cell like a twisted corkscrew. The central lobes result from slower counterclockwise body rotation required to balance the active torque. The bent cell shape underneath the flagellum superimposes these two chiral motions at different radial distances, producing the observed patterns. Three-dimensional hydrodynamic simulations using the method of regularized Stokeslets reproduce these dynamics and show that bent cell shape enhances swimming, suggesting an adaptive advantage of T. brucei's morphology. △ Less

Submitted 10 December, 2025; originally announced December 2025.

Comments: 41 pages, 5 figures in manuscript, 10 figures in supplementary materials

A Novel Pixel-Chip-Based Region-of-Interest Readout Circuit Design

Authors: Shi-Qiang Zhou, Li-Rong Xie, Dong Wang, Cheng Lian, Si-Ying Liu, Zi-Yi Zhang, Xiang-Ming Sun, Hong-Bang Liu, Chao-Song Gao, Jun Liu, Huan-Bo Feng, Di-Fan Yi

Abstract: This paper presents a novel pixel chip readout scheme: the Region-of-Interest Readout Circuit (ROIRC), which is designed for large area, large array pixel chips and Gas Pixel Detector (GPD). This design employs a sentinel pixel detection strategy, enabling rapid identification and prioritized readout of the pixel regions containing signal events. During the scanning readout of these signal events,… ▽ More This paper presents a novel pixel chip readout scheme: the Region-of-Interest Readout Circuit (ROIRC), which is designed for large area, large array pixel chips and Gas Pixel Detector (GPD). This design employs a sentinel pixel detection strategy, enabling rapid identification and prioritized readout of the pixel regions containing signal events. During the scanning readout of these signal events, ROIRC employs a Block-based readout approach, effectively minimizing the readout of non-signal pixels. The functionality of ROIRC has been successfully implemented on both the ASIC and FPGA platforms. In the tests of the ROIRC, the pixel chip embedded in the GPD is capable of detecting low-energy X-rays in the range of 2-10 keV and supports multiple event readouts, and the pixel chip can read out photo-electron signal events with the count rate up to 15k / (cm2 x s). △ Less

Submitted 19 November, 2025; originally announced November 2025.

Initial performance results of the JUNO detector

Authors: Angel Abusleme, Thomas Adam, Kai Adamowicz, David Adey, Shakeel Ahmad, Rizwan Ahmed, Timo Ahola, Sebastiano Aiello, Fengpeng An, Guangpeng An, Costas Andreopoulos, Giuseppe Andronico, João Pedro Athayde Marcondes de André, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, Didier Auguste, Margherita Buizza Avanzini, Andrej Babic, Jingzhi Bai, Weidong Bai, Nikita Balashov, Roberto Barbera, Andrea Barresi , et al. (1114 additional authors not shown)

Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) started physics data taking on 26 August 2025. JUNO consists of a 20-kton liquid scintillator central detector, surrounded by a 35 kton water pool serving as a Cherenkov veto, and almost 1000 m$^2$ of plastic scintillator veto on top. The detector is located in a shallow underground laboratory with an overburden of 1800 m.w.e. This paper present… ▽ More The Jiangmen Underground Neutrino Observatory (JUNO) started physics data taking on 26 August 2025. JUNO consists of a 20-kton liquid scintillator central detector, surrounded by a 35 kton water pool serving as a Cherenkov veto, and almost 1000 m$^2$ of plastic scintillator veto on top. The detector is located in a shallow underground laboratory with an overburden of 1800 m.w.e. This paper presents the performance results of the detector, extensively studied during the commissioning of the water phase, the subsequent liquid scintillator filling phase, and the first physics runs. The liquid scintillator achieved an attenuation length of 20.6 m at 430 nm, while the high coverage PMT system and scintillator together yielded about 1785 photoelectrons per MeV of energy deposit at the detector centre, measured using the 2.223 MeV $γ$ from neutron captures on hydrogen with an Am-C calibration source. The reconstructed energy resolution is 3.4% for two 0.511 MeV $γ$ at the detector centre and 2.9% for the 0.93 MeV quenched Po-214 alpha decays from natural radioactive sources. The energy nonlinearity is calibrated to better than 1%. Intrinsic contaminations of U-238 and Th-232 in the liquid scintillator are below 10$^{-16}$ g/g, assuming secular equilibrium. The water Cherenkov detector achieves a muon detection efficiency better than 99.9% for muons traversing the liquid scintillator volume. During the initial science runs, the data acquisition duty cycle exceeded 97.8%, demonstrating the excellent stability and readiness of JUNO for high-precision neutrino physics. △ Less

Submitted 18 November, 2025; originally announced November 2025.

Comments: 38 pages, 23 figures

Topmetal-L: A Low Noise Charge-Sensitive Pixel Sensor for POLAR2/LPD

Authors: Li-rong Xie, Shi-Qiang Zhou, Di-Fan Yi, Huan-Bo Feng, Zhu-Ke Feng, Dong Wang, Chao-song Gao, En-Wei Liang, Xiang-Ming Sun, Hong-Bang Liu

Abstract: POLAR-2 is a next-generation space astronomy platform led by China, with its core scientific objective focused on high-precision polarization measurements of gamma-ray bursts. As one of its key payloads, the Low-energy Polarization Detector (LPD) is designed to perform wide-field surveys to capture X-ray polarization information from gamma-ray bursts in the 2$\sim$10 keV energy range. This paper p… ▽ More POLAR-2 is a next-generation space astronomy platform led by China, with its core scientific objective focused on high-precision polarization measurements of gamma-ray bursts. As one of its key payloads, the Low-energy Polarization Detector (LPD) is designed to perform wide-field surveys to capture X-ray polarization information from gamma-ray bursts in the 2$\sim$10 keV energy range. This paper presents Topmetal-L, a dedicated charge-sensitive pixel sensor developed for the LPD prototype upgrade. Fabricated in a 130 nm CMOS process in 2024, the chip integrates a 356 $\times$ 512 pixel array with a pixel pitch of 45 $μ$m. Each pixel incorporates a 26 $\times$ 26 $μ$m$^2$ charge-collecting window and is capable of simultaneously outputting both energy and position information of deposited charges. Topmetal-L has been systematically optimized for power consumption, noise performance, and readout efficiency. It exhibits an input dynamic range of 0$\sim$4 ke$^{-}$, a typical charge-to-voltage conversion gain of 76.04 $μ$V/e$^{-}$, an average equivalent noise charge of approximately 22.8 e$^{-}$, a sensitive area exceeding 3.69 cm$^2$, and a total power consumption of 720 mW per chip. To meet the requirements of large-area, high-frame-rate readout for gas-based polarization detectors, a sentinel readout scheme is proposed, reducing the full-frame readout time to 730 $μ$s. A prototype Topmetal-L-based gas polarization detection system was evaluated across key energies: it exhibited a residual modulation of 0.26% $\pm$ 0.45% at 5.90 keV, a modulation factor of 66.67% $\pm$ 0.45% for a linearly polarized 8.05 keV source, and a count rate saturated at 15 k counts$\cdot$cm$^{-2}$$\cdot$s$^{-1}$ when tested at 5.40 keV. △ Less

Submitted 24 November, 2025; v1 submitted 12 November, 2025; originally announced November 2025.

Prospects for geoneutrino detection with JUNO

Authors: Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Fengpeng An, João Pedro Athayde Marcondes de André, Costas Andreopoulos, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Didier Auguste, Marcel Büchner, Weidong Bai, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger, Svetlana Biktemerova, Thilo Birkenfeld, Simon Blyth , et al. (605 additional authors not shown)

Abstract: Geoneutrinos, which are antineutrinos emitted during the decay of long-lived radioactive elements inside Earth, serve as a unique tool for studying the composition and heat budget of our planet. The Jiangmen Underground Neutrino Observatory (JUNO) experiment in China, which has recently completed construction, is expected to collect a sample comparable in size to the entire existing world geoneutr… ▽ More Geoneutrinos, which are antineutrinos emitted during the decay of long-lived radioactive elements inside Earth, serve as a unique tool for studying the composition and heat budget of our planet. The Jiangmen Underground Neutrino Observatory (JUNO) experiment in China, which has recently completed construction, is expected to collect a sample comparable in size to the entire existing world geoneutrino dataset in less than a year. This paper presents an updated estimation of sensitivity to geoneutrinos of JUNO using the best knowledge available to date about the experimental site, the surrounding nuclear reactors, the detector response uncertainties, and the constraints expected from the TAO satellite detector. To facilitate comparison with present and future geological models, our results cover a wide range of predicted signal strengths. Despite the significant background from reactor antineutrinos, the experiment will measure the total geoneutrino flux with a precision comparable to that of existing experiments within its first few years, ultimately achieving a world-leading precision of about 8% over ten years. The large statistics of JUNO will also allow separation of the Uranium-238 and Thorium-232 contributions with unprecedented precision, providing crucial constraints on models of formation and composition of Earth. Observation of the mantle signal above the lithospheric flux will be possible but challenging. For models with the highest predicted mantle concentrations of heat-producing elements, a 3-sigma detection over six years requires knowledge of the lithospheric flux to within 15%. Together with complementary measurements from other locations, the geoneutrino results of JUNO will offer cutting-edge, high-precision insights into the interior of Earth, of fundamental importance to both the geoscience and neutrino physics communities. △ Less

Submitted 10 November, 2025; originally announced November 2025.

Comments: 32 pages, with 13 figures and 5 tables

Magneto-optical spectroscopy based on pump-probe strobe light

Authors: Shihao Zhou, Yujie Zhu, Chunli Tang, Rui Sun, Junming Wu, Yuzan Xiong, Ingrid E. Russell, Yi Li, Dali Sun, Frank Tsui, Binbin Yang, Valentine Novosad, Jia-Mian Hu, Wencan Jin, Wei Zhang

Abstract: We demonstrate a pump-probe strobe light spectroscopy for sensitive detection of magneto-optical dynamics in the context of hybrid magnonics. The technique uses a combinatorial microwave-optical pump-probe scheme, leveraging both the high-energy resolution of microwaves and the high-efficiency detection using optical photons. In contrast to conventional stroboscopy using a continuous-wave light, w… ▽ More We demonstrate a pump-probe strobe light spectroscopy for sensitive detection of magneto-optical dynamics in the context of hybrid magnonics. The technique uses a combinatorial microwave-optical pump-probe scheme, leveraging both the high-energy resolution of microwaves and the high-efficiency detection using optical photons. In contrast to conventional stroboscopy using a continuous-wave light, we apply microwave and optical pulses with varying pulse widths, and demonstrate magnetooptical detection of magnetization dynamics in Y3Fe5O12 films. The detected magneto-optical signals strongly depend on the characteristics of both the microwave and the optical pulses as well as their relative time delays. We show that good magneto-optical sensitivity and coherent stroboscopic character are maintained even at a microwave pump pulse of 1.5 ns and an optical probe pulse of 80 ps, under a 7 megahertz clock rate, corresponding to a pump-probe footprint of ~1% in one detection cycle. Our results show that time-dependent strobe light measurement of magnetization dynamics can be achieved in the gigahertz frequency range under a pump-probe detection scheme. △ Less

Submitted 28 October, 2025; originally announced October 2025.

Comments: 14 pages, 10 figures

Quadratic Supercontinuum Generation from UV to Mid-IR in Lithium Niobate Nanophotonics

Authors: Selina Zhou, Maximilian Shen, Ryoto Sekine, Nicolas Englebert, Thomas Zacharias, Benjamin Gutierrez, Robert M. Gray, Justin Widjaja, Alireza Marandi

Abstract: Supercontinuum light sources are widely used for applications ranging from imaging to sensing and frequency comb stabilization. The most common mechanisms for their generation rely on cubic nonlinearities, for instance in crystals, optical fibers, and integrated photonics. However, quadratic supercontinuum generation (QSCG) offers potential for enhanced energy efficiency and broader spectral cover… ▽ More Supercontinuum light sources are widely used for applications ranging from imaging to sensing and frequency comb stabilization. The most common mechanisms for their generation rely on cubic nonlinearities, for instance in crystals, optical fibers, and integrated photonics. However, quadratic supercontinuum generation (QSCG) offers potential for enhanced energy efficiency and broader spectral coverage because of the typically much stronger nonlinearity and ability to achieve both coherent up- and down-conversion via three-wave mixing processes. Despite such potentials, demonstrations of QSCG in integrated photonic waveguides have been sparse and have barely surpassed their cubic counterparts in terms of spectral coverage and energy-efficiency. Here, we introduce a new dispersion engineering principle and experimentally demonstrate purely quadratic supercontinuum generation in lithium niobate nano-waveguides substantially outperforming previous demonstrations in integrated photonics. In one device, by engineering a near-zero dispersion profile and using a single poling period for quasi-phase matched saturated second-harmonic generation, we achieve robust and energy efficient multi-octave QSCG with only femtojoules of pump pulse energy. In another device, we use a flat dispersion profile with two distant zero crossings of group velocity dispersion (GVD) to achieve broadband difference-frequency generation (DFG) for extending the spectral coverage further into the mid-IR and cover the entire transparency window of lithium niobate from 350 nm to 5000 nm. Our results showcase how DFG-assisted QSCG can access hard-to-access spectral regions in an energy-efficient fashion by properly utilizing dispersion engineering and quasi-phase matching. △ Less

Submitted 21 October, 2025; originally announced October 2025.

High harmonic generation light source with polarization selectivity and sub-100-$μ$m beam size for time- and angle-resolved photoemission spectroscopy

Authors: Haoyuan Zhong, Xuanxi Cai, Changhua Bao, Fei Wang, Tianyun Lin, Yudong Chen, Sainan Peng, Lin Tang, Chen Gu, Zhensheng Tao, Hongyun Zhang, Shuyun Zhou

Abstract: High-quality ultrafast light sources are critical for developing advanced time- and angle-resolved photoemission spectroscopy (TrARPES). While the application of high harmonic generation (HHG) light sources in TrARPES has increased significantly over the past decade, the optimization of the HHG probe beam size and selective control of the light polarization, which are important for TrARPES measure… ▽ More High-quality ultrafast light sources are critical for developing advanced time- and angle-resolved photoemission spectroscopy (TrARPES). While the application of high harmonic generation (HHG) light sources in TrARPES has increased significantly over the past decade, the optimization of the HHG probe beam size and selective control of the light polarization, which are important for TrARPES measurements, have been rarely explored. In this work, we report the implementation of high-quality HHG probe source with an optimum beam size down to 57 $μ$m $\times$ 90 $μ$m and selective light polarization control, together with mid-infrared (MIR) pumping source for TrARPES measurements using a 10 kHz amplifier laser. The selective polarization control of the HHG probe source allows to enhance bands with different orbital contributions or symmetries, as demonstrated by experimental data measured on a few representative transition metal dichalcogenide materials (TMDCs) as well as topological insulator Bi$_2$Se$_3$. Furthermore, by combining the HHG probe source with MIR pumping at 2 $μ$m wavelength, TrARPES on a bilayer graphene shows a time resolution of 140 fs, allowing to distinguish two different relaxation processes in graphene. Such high-quality HHG probe source together with the MIR pumping expands the capability of TrARPES in revealing the ultrafast dynamics and light-induced emerging phenomena in quantum materials. △ Less

Submitted 18 October, 2025; originally announced October 2025.

Comments: 15 pages, 5 figures

Journal ref: Ultrafast Sci. 4, 0063 (2024)

Design, waterproofing, and mass production of the 3-inch PMT frontend system of JUNO

Authors: Jilei Xu, Miao He, Cédric Cerna, Yongbo Huang, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Fengpeng An, Costas Andreopoulos, Giuseppe Andronico, João Pedro Athayde Marcondes de André, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Didier Auguste, Weidong Bai, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger , et al. (609 additional authors not shown)

Abstract: Over 25,600 3-inch photomultiplier tubes (PMTs) have been instrumented for the central detector of the Jiangmen Underground Neutrino Observatory. Each PMT is equipped with a high-voltage divider and a frontend cable with waterproof sealing. Groups of sixteen PMTs are connected to the underwater frontend readout electronics via specialized multi-channel waterproof connectors. This paper outlines th… ▽ More Over 25,600 3-inch photomultiplier tubes (PMTs) have been instrumented for the central detector of the Jiangmen Underground Neutrino Observatory. Each PMT is equipped with a high-voltage divider and a frontend cable with waterproof sealing. Groups of sixteen PMTs are connected to the underwater frontend readout electronics via specialized multi-channel waterproof connectors. This paper outlines the design and mass production processes for the high-voltage divider, the cable and connector, as well as the waterproof potting of the PMT bases. The results of the acceptance tests of all the integrated PMTs are also presented. △ Less

Submitted 22 January, 2026; v1 submitted 7 October, 2025; originally announced October 2025.

MesoNet: A Fundamental Principle for Multi-Representation Learning in Complex Chemical Systems

Authors: Jinming Fan, Chao Qian, Shaodong Zhou

Abstract: Accurate prediction of molecular properties in complex chemical systems is crucial for accelerating material discovery and chemical innovation. However, current computational methods often struggle to capture the intricate compositional interplay across complex chemical systems, from intramolecular bonds to intermolecular forces. In this work, we introduce MesoNet, a novel framework founded on the… ▽ More Accurate prediction of molecular properties in complex chemical systems is crucial for accelerating material discovery and chemical innovation. However, current computational methods often struggle to capture the intricate compositional interplay across complex chemical systems, from intramolecular bonds to intermolecular forces. In this work, we introduce MesoNet, a novel framework founded on the principle of multi-representation learning and specifically designed for multi-molecule modeling. The core innovation of MesoNet lies in the construction of context-aware representation-dynamically enriched atomic descriptors generated via Neural Circuit Policies. These parameters efficiently capture both intrinsic atomic properties and their dynamic compositional context through a cross-attention mechanism spanning both intramolecular and intermolecular message passing. Driven by this mechanism, the influence of the mixed system is progressively applied to each molecule and atom, making message passing both efficient and meaningful. Comprehensive evaluations across diverse public datasets, spanning both pure components and mixtures, demonstrate that MesoNet achieves superior accuracy and enhanced chemical interpretability for molecular properties. This work establishes a powerful, interpretable approach for modeling compositional complexity, aiming to advance chemical simulation and design. △ Less

Submitted 23 September, 2025; v1 submitted 22 September, 2025; originally announced September 2025.

Mean-field Modeling of Social Interactions Using Classical Density Functional Theory

Authors: Ziheng Xu, Shenggao Zhou

Abstract: Incorporating social interactions is essential to an accurate modeling of epidemic spreading. This work proposes a novel local mean-field density functional theory model by using the sum-of-exponential approximation of convolution kernels for social interactions, which in turn converts the convolution terms into interaction potentials that are governed by the Debye-Hückel equation. Thanks to the l… ▽ More Incorporating social interactions is essential to an accurate modeling of epidemic spreading. This work proposes a novel local mean-field density functional theory model by using the sum-of-exponential approximation of convolution kernels for social interactions, which in turn converts the convolution terms into interaction potentials that are governed by the Debye-Hückel equation. Thanks to the local formulation of the proposed model, linear stability analysis is able to derive a novel instability condition associated with cross interactions. Global existence of the solution to the proposed model with a simplified self-repulsive interaction potential is established. Extensive numerical simulations are performed to assess the impact of cross social interactions on transmission and isolation, verify the instability conditions obtained from linear stability analysis, and provide theoretical guides for the control of disease spreading. △ Less

Submitted 7 September, 2025; originally announced September 2025.

Self-supervised neural operator for solving partial differential equations

Authors: Wen You, Shaoqian Zhou, Xuhui Meng

Abstract: Neural operators (NOs) provide a new paradigm for efficiently solving partial differential equations (PDEs), but their training depends on costly high-fidelity data from numerical solvers, limiting applications in complex systems. We propose a self-supervised neural operator (SNO) that generates accurate and diverse training data on the fly without numerical solvers. SNO consists of three parts: a… ▽ More Neural operators (NOs) provide a new paradigm for efficiently solving partial differential equations (PDEs), but their training depends on costly high-fidelity data from numerical solvers, limiting applications in complex systems. We propose a self-supervised neural operator (SNO) that generates accurate and diverse training data on the fly without numerical solvers. SNO consists of three parts: a physics-informed sampler (PI-sampler) based on Bayesian PINNs for efficient data generation, a function encoder (FE) for compact input-output representations, and an encoder-only Transformer for operator learning, mapping boundary/initial conditions, source terms, and geometries to PDE solutions. We validate SNO on 1D steady/unsteady nonlinear reaction-diffusion equations, a 2D nonlinear PDE with varying geometries, and vortex-induced vibration of a flexible cylinder in fluid dynamics. SNO achieves high accuracy in all cases, and lightweight finetuning (O(100) trainable variables) further improves predictions with only a few hundred steps. This work provides a new route toward pretrained foundation models as efficient PDE surrogates. △ Less

Submitted 9 September, 2025; v1 submitted 31 August, 2025; originally announced September 2025.

Room-temperature alignment-free magnetometry with boron vacancies in hot-pressed hexagonal boron nitride

Authors: Shuyu Wen, Raul Coto, Peiting Wen, Slawomir Prucnal, Manfred Helm, Jun-Wei Luo, Shengqiang Zhou, Yonder Berencén

Abstract: Magnetic field sensing is essential for applications in communication, environmental monitoring, and biomedical diagnostics. Quantum sensors based on solid-state spin defects, such as nitrogen-vacancy centers in diamond or boron vacancies in single-crystal hexagonal boron nitride (hBN), typically require precise alignment between the external magnetic field and the defect's spin quantization axis… ▽ More Magnetic field sensing is essential for applications in communication, environmental monitoring, and biomedical diagnostics. Quantum sensors based on solid-state spin defects, such as nitrogen-vacancy centers in diamond or boron vacancies in single-crystal hexagonal boron nitride (hBN), typically require precise alignment between the external magnetic field and the defect's spin quantization axis to achieve reliable sensing. This alignment constraint complicates device integration and hinders scalability. Here, we demonstrate room-temperature optically detected magnetic resonance (ODMR) from negatively charged boron vacancies (VB-) in commercially available hot-pressed polycrystalline hBN. The random grain orientation inherently samples a broad range of spin quantization axes, enabling alignment-free magnetic field detection. Numerical modeling further confirms that sensing remains feasible despite anisotropic sensitivity, establishing hot-pressed hBN as a robust and practical platform for quantum magnetometry. This approach paves the way toward low-cost, scalable, and mechanically stable quantum magnetic field sensors suitable for real-world deployment. △ Less

Submitted 31 August, 2025; originally announced September 2025.

Comments: 13 pages, 5 figures

Probing Cosmic Neutrino Background through Parametric Fluorescence

Authors: Guo-yuan Huang, Shun Zhou

Abstract: We point out that relic neutrinos from the Big Bang may induce the parametric fluorescence in atomic or molecular systems, which offers a novel way to discover cosmic neutrino background. By coherently scattering with molecular energy levels, a massive neutrino can spontaneously ``decay" into a lighter neutrino and an infrared signal photon, i.e., $ν^{}_{i} + M \to ν^{}_{j} + γ^{}_{\rm S} + M$, wh… ▽ More We point out that relic neutrinos from the Big Bang may induce the parametric fluorescence in atomic or molecular systems, which offers a novel way to discover cosmic neutrino background. By coherently scattering with molecular energy levels, a massive neutrino can spontaneously ``decay" into a lighter neutrino and an infrared signal photon, i.e., $ν^{}_{i} + M \to ν^{}_{j} + γ^{}_{\rm S} + M$, where the molecular state $M$ remains unchanged after the scattering. Because the amplitudes of different radiants are matched in phase, the rate is coherently enhanced and proportional to the squared density of ambient dipoles. When the energy transfer from neutrinos coincides with the energy-level difference, the fluorescence will be on resonance. Near the resonance, the rate is proportional to the square of the coherence time $T^{}_{\rm c}$ of the ensemble. For a nominal target volume of $5~{\rm m^3}$ (or $5~{\rm cm^3}$), the signal rate can reach $1~{\rm yr}^{-1}$ for $T^{}_{\rm c} = 10~{\rm ns}$ (or $T^{}_{\rm c} = 10~{\rm μs}$). This event rate appears to be very promising in consideration of an even longer coherence time that is achievable in solid systems. △ Less

Submitted 27 February, 2026; v1 submitted 14 July, 2025; originally announced July 2025.

Comments: 5 pages, 3 figures plus supplemental material; matches the published version; minor typos corrected

Journal ref: Phys. Rev. Lett. 136 (2026) 081003

Phase analysis of Ising machines and their implications on optimization

Authors: Shu Zhou, K. Y. Michael Wong, Juntao Wang, David Shui Wing Hui, Daniel Ebler, Jie Sun

Abstract: Ising machines, which are dynamical systems designed to operate in a parallel and iterative manner, have emerged as a new paradigm for solving combinatorial optimization problems. Despite computational advantages, the quality of solutions depends heavily on the form of dynamics and tuning of parameters, which are in general set heuristically due to the lack of systematic insights. Here, we focus o… ▽ More Ising machines, which are dynamical systems designed to operate in a parallel and iterative manner, have emerged as a new paradigm for solving combinatorial optimization problems. Despite computational advantages, the quality of solutions depends heavily on the form of dynamics and tuning of parameters, which are in general set heuristically due to the lack of systematic insights. Here, we focus on optimal Ising machine design by analyzing phase diagrams of spin distributions in the Sherrington-Kirkpatrick model. We find that that the ground state can be achieved in the phase where the spin distribution becomes binary, and optimal solutions are produced where the binary phase and gapless phase coexist. Our analysis shows that such coexistence phase region can be expanded by carefully placing a digitization operation, giving rise to a family of superior Ising machines, as illustrated by the proposed algorithm digCIM. △ Less

Submitted 16 July, 2025; v1 submitted 11 July, 2025; originally announced July 2025.

Comments: 5 pages, 4 figures

Moment-enhanced shallow water equations for non-slip boundary conditions

Authors: Shiping Zhou, Juntao Huang, Andrew J. Christlieb

Abstract: The shallow water equations often assume a constant velocity profile along the vertical axis. However, this assumption does not hold in many practical applications. To better approximate the vertical velocity distribution, models such as the shallow water moment expansion models have been proposed. Nevertheless, under non-slip bottom boundary conditions, both the standard shallow water equation an… ▽ More The shallow water equations often assume a constant velocity profile along the vertical axis. However, this assumption does not hold in many practical applications. To better approximate the vertical velocity distribution, models such as the shallow water moment expansion models have been proposed. Nevertheless, under non-slip bottom boundary conditions, both the standard shallow water equation and its moment-enhanced models struggle to accurately capture the vertical velocity profile due to the stiff source terms. In this work, we propose modified shallow water equations and corresponding moment-enhanced models that perform well under both non-slip and slip boundary conditions. The primary difference between the modified and original models lies in the treatment of the source term, which allows our modified moment expansion models to be readily generalized, while maintaining compatibility with our previous analysis on the hyperbolicity of the model. To assess the performance of both the standard and modified moment expansion models, we conduct a comprehensive numerical comparison with the incompressible Navier--Stokes equations -- a comparison that is absent from existing literature. △ Less

Submitted 2 October, 2025; v1 submitted 26 May, 2025; originally announced June 2025.

MSC Class: 35L65; 65M22; 65L04

Correlative angstrom-scale microscopy and spectroscopy of graphite-water interfaces

Authors: Lalith Krishna Samanth Bonagiri, Diana M. Arvelo, Fujia Zhao, Jaehyeon Kim, Qian Ai, Shan Zhou, Kaustubh S. Panse, Ricardo Garcia, Yingjie Zhang

Abstract: Water at solid surfaces is key for many processes ranging from biological signal transduction to membrane separation and renewable energy conversion. However, under realistic conditions, which often include environmental and surface charge variations, the interfacial water structure remains elusive. Here we overcome this limit by combining three-dimensional atomic force microscopy and interface-se… ▽ More Water at solid surfaces is key for many processes ranging from biological signal transduction to membrane separation and renewable energy conversion. However, under realistic conditions, which often include environmental and surface charge variations, the interfacial water structure remains elusive. Here we overcome this limit by combining three-dimensional atomic force microscopy and interface-sensitive Raman spectroscopy to characterize the graphite-water interfacial structure in situ. Through correlative analysis of the spatial liquid density maps and vibrational peaks within ~2 nm of the graphite surface, we find the existence of two interfacial configurations at open circuit potential, a transient state where pristine water exhibits strong hydrogen bond (HB) breaking effects, and a steady state with hydrocarbons dominating the interface and weak HB breaking in the surrounding water. At sufficiently negative potentials, both states transition into a stable structure featuring pristine water with a broader distribution of HB configurations. Our three-state model resolves many long-standing controversies on interfacial water structure. △ Less

Submitted 11 June, 2025; originally announced June 2025.

Optimization of target film materials and protective coatings for sealed neutron generator

Authors: Yingying Cao, Sijia Zhou, Pingwei Sun, Jiayu Li, Shangrui Jiang, Shiwei Jing

Abstract: Magnesium target film has better thermal stability and neutron yield than titanium target, making it a potential neutron generator target film material. The radiation resistance of elemental magnesium targets is relatively weak, and their radiation resistance can be improved by alloying magnesium target films. The irradiation damage of pure magnesium targets and magnesium alloy target films was st… ▽ More Magnesium target film has better thermal stability and neutron yield than titanium target, making it a potential neutron generator target film material. The radiation resistance of elemental magnesium targets is relatively weak, and their radiation resistance can be improved by alloying magnesium target films. The irradiation damage of pure magnesium targets and magnesium alloy target films was studied using SRIM. The results indicate that the irradiation damage of magnesium alloy target films (magnesium-niobium, magnesium-zirconium alloys) is lower than that of pure magnesium targets. In addition, under the same alloy ratio, the radiation resistance of magnesium-niobium alloy target film is better than that of magnesium-zirconium alloy. In order to further in-vestigate the performance of magnesium alloy target films, the incident ion energy, protective coatings (nickel oxide, aluminum oxide, palladium oxide), magnesium alloy target films, and alloy doping ratios (0.2, 0.4, 0.6, 0.8, 1.0) were changed. After calculating the effects of the above conditions on the neutron generator yield, sputtering yield, and considering irradiation damage, it was determined that a magnesium-zirconium alloy with a doping rate of 0.2 and a nickel oxide protective coating with a thickness of 7.5 nm are potential target film materials for the neutron generator. △ Less

Submitted 5 June, 2025; originally announced June 2025.

Twenty-Five Years of the Intelligent Driver Model: Foundations, Extensions, Applications, and Future Directions

Authors: Shirui Zhou, Shiteng Zheng, Junfang Tian, Rui Jiang, and H. M. Zhang

Abstract: The Intelligent Driver Model (IDM), proposed in 2000, has become a foundational tool in traffic flow modeling, renowned for its simplicity, computational efficiency, and ability to capture diverse traffic dynamics. Over the past 25 years, IDM has significantly advanced car-following theory and found extensive application in intelligent transportation systems, including driver assistance systems an… ▽ More The Intelligent Driver Model (IDM), proposed in 2000, has become a foundational tool in traffic flow modeling, renowned for its simplicity, computational efficiency, and ability to capture diverse traffic dynamics. Over the past 25 years, IDM has significantly advanced car-following theory and found extensive application in intelligent transportation systems, including driver assistance systems and autonomous vehicle control. However, IDM's deterministic framework and simplified assumptions face limitations in addressing real-world complexities such as stochastic variability, driver heterogeneity, and mixed traffic conditions. This paper provides a systematic review and critical reflection on IDM's theoretical foundations, academic influence, practical applications, and model extensions. While highlighting IDM's contributions, we emphasize the need to extend the model into a modular and extensible framework. Future directions include integrating stochastic elements, human behavioral insights, and hybrid modeling approaches that combine physics-based structures with data-driven methodologies. By reimagining IDM as a flexible modeling basis, this paper aims to inspire its continued development to meet the demands of intelligent, connected, and increasingly complex traffic systems. △ Less

Submitted 23 November, 2025; v1 submitted 6 June, 2025; originally announced June 2025.

A Driving Regime-Embedded Deep Learning Framework for Modeling Intra-Driver Heterogeneity in Multi-Scale Car-Following Dynamics

Authors: Shirui Zhou, Jiying Yan, Junfang Tian, Tao Wang, Yongfu Li, Shiquan Zhong

Abstract: A fundamental challenge in car-following modeling lies in accurately representing the multi-scale complexity of driving behaviors, particularly the intra-driver heterogeneity where a single driver's actions fluctuate dynamically under varying conditions. While existing models, both conventional and data-driven, address behavioral heterogeneity to some extent, they often emphasize inter-driver hete… ▽ More A fundamental challenge in car-following modeling lies in accurately representing the multi-scale complexity of driving behaviors, particularly the intra-driver heterogeneity where a single driver's actions fluctuate dynamically under varying conditions. While existing models, both conventional and data-driven, address behavioral heterogeneity to some extent, they often emphasize inter-driver heterogeneity or rely on simplified assumptions, limiting their ability to capture the dynamic heterogeneity of a single driver under different driving conditions. To address this gap, we propose a novel data-driven car-following framework that systematically embeds discrete driving regimes (e.g., steady-state following, acceleration, cruising) into vehicular motion predictions. Leveraging high-resolution traffic trajectory datasets, the proposed hybrid deep learning architecture combines Gated Recurrent Units for discrete driving regime classification with Long Short-Term Memory networks for continuous kinematic prediction, unifying discrete decision-making processes and continuous vehicular dynamics to comprehensively represent inter- and intra-driver heterogeneity. Driving regimes are identified using a bottom-up segmentation algorithm and Dynamic Time Warping, ensuring robust characterization of behavioral states across diverse traffic scenarios. Comparative analyses demonstrate that the framework significantly reduces prediction errors for acceleration (maximum MSE improvement reached 58.47\%), speed, and spacing metrics while reproducing critical traffic phenomena, such as stop-and-go wave propagation and oscillatory dynamics. △ Less

Submitted 6 June, 2025; originally announced June 2025.

Intrinsic local Gauss's law preserving PIC method: A self-consistent field-particle update scheme for plasma simulations

Authors: Zhonghua Qiao, Zhenli Xu, Qian Yin, Shenggao Zhou

Abstract: In order to perform physically faithful particle-in-cell (PIC) simulations, the Gauss's law stands as a critical requirement, since its violation often leads to catastrophic errors in long-term plasma simulations. This work proposes a novel method that intrinsically enforces the Gauss's law for the Vlasov-Ampère/Vlasov-Poisson system without requiring auxiliary field corrections or specialized cur… ▽ More In order to perform physically faithful particle-in-cell (PIC) simulations, the Gauss's law stands as a critical requirement, since its violation often leads to catastrophic errors in long-term plasma simulations. This work proposes a novel method that intrinsically enforces the Gauss's law for the Vlasov-Ampère/Vlasov-Poisson system without requiring auxiliary field corrections or specialized current deposition techniques. The electric field is managed to get updated locally and consistently with the motion of particles via splitting the motion into sub-steps along each dimension of the computational mesh. To further obtain a curl-free electric field, a local update scheme is developed to relax the electric-field free energy subject to the Gauss's law. The proposed method avoids solving the Poisson's or Ampère's equation, resulting in a local algorithm of linear complexity for each time step which can be flexibly combined with various temporal discretization for particle motion in PIC simulations. Theoretical analysis verifies that the proposed method indeed maintains the discrete Gauss's law exactly. Numerical tests on classical benchmarks, including the Landau damping, two-stream instability and Diocotron instability, demonstrate the key advantages of the proposed method. It is expected that the local nature of the proposed method makes it a promising tool in parallel simulations of large-scale plasmas. △ Less

Submitted 2 June, 2025; originally announced June 2025.

Fourier ptychographic microscopy aided with transport of intensity equation for robust full phase spectrum reconstruction

Authors: Mikołaj Rogalski, Juan Martinez-Carranza, Bartosz Górski, Piotr Arcab, Michał Jóźwik, Piotr Zdańkowski, Magdalena Sobień, Marzena Stefaniuk, Shun Zhou, Chao Zuo, Maciej Trusiak

Abstract: Fourier ptychographic microscopy (FPM) is a pivotal computational imaging technique that achieves phase and amplitude reconstruction with high resolution and wide field of view, using low numerical aperture objectives and LED array illumination. Despite its unique strengths, FPM remains fundamentally limited in retrieving low spatial frequency phase information due to the absence of phase encoding… ▽ More Fourier ptychographic microscopy (FPM) is a pivotal computational imaging technique that achieves phase and amplitude reconstruction with high resolution and wide field of view, using low numerical aperture objectives and LED array illumination. Despite its unique strengths, FPM remains fundamentally limited in retrieving low spatial frequency phase information due to the absence of phase encoding in all brightfield illumination angles. To overcome this, we present a novel hybrid approach that combines FPM with the transport of intensity equation (TIE), enabling accurate, full-spectrum phase retrieval without compromising system simplicity. Our method extends standard FPM acquisitions with a single additional on-axis defocused image, from which low-frequency phase components are reconstructed via TIE method, employing large defocus distance to suppress low-frequency artifacts and enhance robustness to intensity noise. To additionally compensate for defocus-induced magnification variations caused by spherical wavefront illumination, we employ an affine transform-based correction scheme upon image registration. Notably, by restoring the missing low-frequency content, our hybrid method appears capable of recovering phase values beyond the conventional 0-2π range - an area where conventional FPM techniques often struggle when dealing with optically thick samples. We validated our method using a quantitative phase test target for benchmarking accuracy and biological cheek cells, mouse neurons, and mouse brain tissue slice samples to demonstrate applicability for in vitro bioimaging. Experimental results confirm substantial improvements in phase reconstruction fidelity across spatial frequencies, establishing this hybrid FPM+TIE framework as a practical and high-performance solution for quantitative phase imaging in biomedical and optical metrology applications. △ Less

Submitted 30 May, 2025; originally announced May 2025.

Dynamically Polarized SERF Atomic Comagnetometer

Authors: Xiaofei Huang, Kai Wei, Yang Rui, Dinghui Gong, Saixin Zhou, Jie Zheng, Wei Quan

Abstract: Atomic spin sensors are essential for beyond-the-standard-model exploration, biomagnetic measurement, and quantum navigation. While the traditional DC mode spin-exchange relaxation-free (SERF) comagnetometer achieves ultrahigh sensitivity, further improvements require suppressing technical noise and surpassing standard quantum limit. In this work, we develop a K-Rb-$^{21}$Ne SERF atomic comagnetom… ▽ More Atomic spin sensors are essential for beyond-the-standard-model exploration, biomagnetic measurement, and quantum navigation. While the traditional DC mode spin-exchange relaxation-free (SERF) comagnetometer achieves ultrahigh sensitivity, further improvements require suppressing technical noise and surpassing standard quantum limit. In this work, we develop a K-Rb-$^{21}$Ne SERF atomic comagnetometer that dynamically polarizes the electron and nuclear spins, shielding signals from direct interference by pump light. We establish a three-phase evolutionary model for hybrid spin ensemble dynamics, yielding a complete analytical solution, and analyze the responses to various spin perturbations. Additionally, we achieve an averaged 38.5 $\%$ suppression of the polarization noise and identify the key factors that limit sensitivity improvements. The dynamically polarized comagnetometer exhibits effective suppression of technical noise and holds the potential to overcome quantum noise limit, while offering promising applications in exploring new physics and precise magnetic field measurements. △ Less

Submitted 23 May, 2025; originally announced May 2025.

Photon emission gain in Er doped Si light emitting diodes by impact excitation

Authors: Huayou Liu, Jiayuan Zhao, Jing Zhang, Huan Liu, Jiajing He, Ulrich Kentsch, Shengqiang Zhou, Manfred Helm, Yaping Dan

Abstract: This work demonstrates photon emission gain, i.e., emission of multiple photons per injected electron, through impact excitation in Er-doped silicon light-emitting diodes (LEDs). Conventional methods for exciting Er ions in silicon suffer from low efficiency due to mismatched energy transfer between exciton recombination and Er excitation. Here, we propose a reverse-biased Si PN junction diode whe… ▽ More This work demonstrates photon emission gain, i.e., emission of multiple photons per injected electron, through impact excitation in Er-doped silicon light-emitting diodes (LEDs). Conventional methods for exciting Er ions in silicon suffer from low efficiency due to mismatched energy transfer between exciton recombination and Er excitation. Here, we propose a reverse-biased Si PN junction diode where ballistically accelerated electrons induce inelastic collisions with Er ions, enabling tunable excitation via electric field modulation. Theoretical modeling reveals that photon emission gain arises from multiple impact excitations by a single electron traversing the electroluminescence region, with the gain value approximating the ratio of emission region width to electron mean free path, i.e., G = Lex/l. Experimental results show an internal quantum efficiency (IQE) of 1.84% at 78 K, representing a 20-fold enhancement over room-temperature performance. This work provides a critical foundation for on-chip integration of silicon-based communication-band lasers and quantum light sources. △ Less

Submitted 23 May, 2025; originally announced May 2025.

Comments: 9 pages, 3 figures

Scalable physics-informed deep generative model for solving forward and inverse stochastic differential equations

Authors: Shaoqian Zhou, Wen You, Ling Guo, Xuhui Meng

Abstract: Physics-informed deep learning approaches have been developed to solve forward and inverse stochastic differential equation (SDE) problems with high-dimensional stochastic space. However, the existing deep learning models have difficulties solving SDEs with high-dimensional spatial space. In the present study, we propose a scalable physics-informed deep generative model (sPI-GeM), which is capable… ▽ More Physics-informed deep learning approaches have been developed to solve forward and inverse stochastic differential equation (SDE) problems with high-dimensional stochastic space. However, the existing deep learning models have difficulties solving SDEs with high-dimensional spatial space. In the present study, we propose a scalable physics-informed deep generative model (sPI-GeM), which is capable of solving SDE problems with both high-dimensional stochastic and spatial space. The sPI-GeM consists of two deep learning models, i.e., (1) physics-informed basis networks (PI-BasisNet), which are used to learn the basis functions as well as the coefficients given data on a certain stochastic process or random field, and (2) physics-informed deep generative model (PI-GeM), which learns the distribution over the coefficients obtained from the PI-BasisNet. The new samples for the learned stochastic process can then be obtained using the inner product between the output of the generator and the basis functions from the trained PI-BasisNet. The sPI-GeM addresses the scalability in the spatial space in a similar way as in the widely used dimensionality reduction technique, i.e., principal component analysis (PCA). A series of numerical experiments, including approximation of Gaussian and non-Gaussian stochastic processes, forward and inverse SDE problems, are performed to demonstrate the accuracy of the proposed model. Furthermore, we also show the scalability of the sPI-GeM in both the stochastic and spatial space using an example of a forward SDE problem with 38- and 20-dimension stochastic and spatial space, respectively. △ Less

Submitted 4 March, 2026; v1 submitted 23 March, 2025; originally announced March 2025.

Noise-strength-adapted approximate quantum codes inspired by machine learning

Authors: Shuwei Liu, Shiyu Zhou, Zi-Wen Liu, Jinmin Yi

Abstract: We demonstrate that machine learning provides a powerful tool for discovering new approximate quantum error-correcting (AQEC) codes beyond conventional algebraic frameworks. Building upon direct observations through hybrid quantum-classical learning, we discover two new 4-qubit amplitude damping codes with an innovative noise-strength-adaptive (NSA) feature where the codeword varies with noise str… ▽ More We demonstrate that machine learning provides a powerful tool for discovering new approximate quantum error-correcting (AQEC) codes beyond conventional algebraic frameworks. Building upon direct observations through hybrid quantum-classical learning, we discover two new 4-qubit amplitude damping codes with an innovative noise-strength-adaptive (NSA) feature where the codeword varies with noise strength. They are NSA self-complementary and NSA pair-complementary codes. We show that they can both outperform conventional codes for amplitude damping (AD) noise. The 4-qubit self-complementary NSA code outperforms the standard LNCY AD code in fidelity and Knill-Laflamme condition violation. The pair-complementary code, which has no known non-NSA analog, achieves even better performance with higher-order loss suppression and better fidelity. We further generalize both approaches to families of NSA AD codes for arbitrary system size, as well as an NSA variant of the 0-2-4 binomial code for single-photon loss. Our results demonstrate that adaptation to noise strength can systematically lead to significant improvements in error correction capability, and also showcase how machine learning can help discover new valuable code formalisms that may not emerge from traditional design approaches. △ Less

Submitted 25 March, 2025; v1 submitted 14 March, 2025; originally announced March 2025.

Comments: 6+17 pages, 1+3 figures

Simulation of the Background from $^{13}$C$(α, n)^{16}$O Reaction in the JUNO Scintillator

Authors: JUNO Collaboration, Thomas Adam, Kai Adamowicz, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Fengpeng An, Costas Andreopoulos, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, João Pedro Athayde Marcondes de André, Didier Auguste, Weidong Bai, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger, Svetlana Biktemerova , et al. (608 additional authors not shown)

Abstract: Large-scale organic liquid scintillator detectors are highly efficient in the detection of MeV-scale electron antineutrinos. These signal events can be detected through inverse beta decay on protons, which produce a positron accompanied by a neutron. A noteworthy background for antineutrinos coming from nuclear power reactors and from the depths of the Earth (geoneutrinos) is generated by ($α, n$)… ▽ More Large-scale organic liquid scintillator detectors are highly efficient in the detection of MeV-scale electron antineutrinos. These signal events can be detected through inverse beta decay on protons, which produce a positron accompanied by a neutron. A noteworthy background for antineutrinos coming from nuclear power reactors and from the depths of the Earth (geoneutrinos) is generated by ($α, n$) reactions. In organic liquid scintillator detectors, $α$ particles emitted from intrinsic contaminants such as $^{238}$U, $^{232}$Th, and $^{210}$Pb/$^{210}$Po, can be captured on $^{13}$C nuclei, followed by the emission of a MeV-scale neutron. Three distinct interaction mechanisms can produce prompt energy depositions preceding the delayed neutron capture, leading to a pair of events correlated in space and time within the detector. Thus, ($α, n$) reactions represent an indistinguishable background in liquid scintillator-based antineutrino detectors, where their expected rate and energy spectrum are typically evaluated via Monte Carlo simulations. This work presents results from the open-source SaG4n software, used to calculate the expected energy depositions from the neutron and any associated de-excitation products. Also simulated is a detailed detector response to these interactions, using a dedicated Geant4-based simulation software from the JUNO experiment. An expected measurable $^{13}$C$(α, n)^{16}$O event rate and reconstructed prompt energy spectrum with associated uncertainties, are presented in the context of JUNO, however, the methods and results are applicable and relevant to other organic liquid scintillator neutrino detectors. △ Less

Submitted 2 May, 2025; v1 submitted 2 March, 2025; originally announced March 2025.

Comments: 25 pages, 14 figures, 4 tables

Floquet-Volkov interference in a semiconductor

Authors: Changhua Bao, Haoyuan Zhong, Benshu Fan, Xuanxi Cai, Fei Wang, Shaohua Zhou, Tianyun Lin, Hongyun Zhang, Pu Yu, Peizhe Tang, Wenhui Duan, Shuyun Zhou

Abstract: Intense light-field can dress both Bloch electrons inside crystals and photo-emitted free electrons in the vacuum, dubbed as Floquet and Volkov states respectively. These quantum states can further interfere coherently, modulating light-field dressed states. Here, we report experimental evidence of the Floquet-Volkov interference in a semiconductor - black phosphorus. A highly asymmetric modulatio… ▽ More Intense light-field can dress both Bloch electrons inside crystals and photo-emitted free electrons in the vacuum, dubbed as Floquet and Volkov states respectively. These quantum states can further interfere coherently, modulating light-field dressed states. Here, we report experimental evidence of the Floquet-Volkov interference in a semiconductor - black phosphorus. A highly asymmetric modulation of the spectral weight is observed for the Floquet-Volkov states, and such asymmetry can be further controlled by rotating the pump polarization. Our work reveals the quantum interference between different light-field dressed electronic states, providing insights for material engineering on the ultrafast timescale. △ Less

Submitted 11 February, 2025; originally announced February 2025.

Journal ref: Phys. Rev. B 111, L081106 (2025)

Two-optical-cycle pulses from nanophotonic two-color soliton compression

Authors: Robert M. Gray, Ryoto Sekine, Maximilian Shen, Thomas Zacharias, James Williams, Selina Zhou, Rahul Chawlani, Luis Ledezma, Nicolas Englebert, Alireza Marandi

Abstract: Few- and single-cycle optical pulses and their associated ultra-broadband spectra have been crucial in the progress of ultrafast science and technology. Moreover, multi-color waveforms composed of independently manipulable ultrashort pulses in distinct spectral bands offer unique advantages in pulse synthesis and attosecond science. However, the generation and control of ultrashort pulses has requ… ▽ More Few- and single-cycle optical pulses and their associated ultra-broadband spectra have been crucial in the progress of ultrafast science and technology. Moreover, multi-color waveforms composed of independently manipulable ultrashort pulses in distinct spectral bands offer unique advantages in pulse synthesis and attosecond science. However, the generation and control of ultrashort pulses has required bulky and expensive optical systems at the tabletop scale and has so far been beyond the reach of integrated photonics. Here, we break these limitations and demonstrate two-optical-cycle pulse compression using quadratic two-color soliton dynamics in lithium niobate nanophotonics. By leveraging dispersion engineering and operation near phase matching, we achieve extreme compression, energy-efficient operation, and strong conversion of pump to the second harmonic. We experimentally demonstrate generation of $\sim$13-fs pulses at 2 $μ$m using only $\sim$3 pJ of input energy. We further illustrate how the demonstrated scheme can be readily extended to on-chip single-cycle pulse synthesis with sub-cycle control. Our results provide a path towards realization of single-cycle ultrafast systems in nanophotonic circuits. △ Less

Submitted 18 February, 2025; v1 submitted 25 January, 2025; originally announced January 2025.

Comments: 24 pages, 5 figures

Developing an Agent-Based Mathematical Model for Simulating Post-Irradiation Cellular Response: A Crucial Component of a Digital Twin Framework for Personalized Radiation Treatment

Authors: Ruirui Liu, Marciek H. Swat, James A. Glazier, Yu Lei, Sumin Zhou, Kathryn A. Higley

Abstract: In this study, we present the Physical-Bio Translator, an agent-based simulation model designed to simulate cellular responses following irradiation. This simulation framework is based on a novel cell-state transition model that accurately reflects the characteristics of irradiated cells. To validate the Physical-Bio Translator, we performed simulations of cell phase evolution, cell phenotype evol… ▽ More In this study, we present the Physical-Bio Translator, an agent-based simulation model designed to simulate cellular responses following irradiation. This simulation framework is based on a novel cell-state transition model that accurately reflects the characteristics of irradiated cells. To validate the Physical-Bio Translator, we performed simulations of cell phase evolution, cell phenotype evolution, and cell survival. The results indicate that the Physical-Bio Translator effectively replicates experimental cell irradiation outcomes, suggesting that digital cell irradiation experiments can be conducted via computer simulation, offering a more sophisticated model for radiation biology. This work lays the foundation for developing a robust and versatile digital twin at multicellular or tissue scales, aiming to comprehensively study and predict patient responses to radiation therapy. △ Less

Submitted 19 November, 2025; v1 submitted 20 January, 2025; originally announced January 2025.

Energy-Efficient Ultrashort-Pulse Characterization using Nanophotonic Parametric Amplification

Authors: Thomas Zacharias, Robert Gray, Ryoto Sekine, James Williams, Selina Zhou, Alireza Marandi

Abstract: The growth of ultrafast nanophotonic circuits necessitates the development of energy-efficient on-chip pulse characterization techniques. Nanophotonic realizations of Frequency Resolved Optical Gating, a common pulse characterization technique in bulk optics, have been challenging due to their non-collinear nature and the lack of efficient nonlinear optical processes in the integrated platform. He… ▽ More The growth of ultrafast nanophotonic circuits necessitates the development of energy-efficient on-chip pulse characterization techniques. Nanophotonic realizations of Frequency Resolved Optical Gating, a common pulse characterization technique in bulk optics, have been challenging due to their non-collinear nature and the lack of efficient nonlinear optical processes in the integrated platform. Here, we experimentally demonstrate a novel FROG-based technique compatible with the nanophotonic platform that leverages the high gain-bandwidth of a dispersion-engineered degenerate optical parametric amplifier for energy-efficient ultrashort pulse characterization. We demonstrate on-chip pulse characterization of sub-80-fs, ~1-fJ pulses using just ~60-fJ of gate pulse energy, which is several orders of magnitude lower than the gate pulse energy required for characterizing similar pulses in the bulk counterpart. In the future, we anticipate our work will enable the characterization of ultraweak-ultrashort pulses with energies at the single photon level. △ Less

Submitted 19 January, 2025; originally announced January 2025.

Healing of the edge magnetic island in the island divertor configuration on J-TEXT

Authors: Zhangrong Hou, Song Zhou, Nengchao Wang, Yonghua Ding, Zhonghe Jiang, Yunfeng Liang, Zhengkang Ren, Feiyue Mao, Qinghu Yang, Jiaming Wang, Xin Xu, Yutong Yang, Jiankun Hua, Zijian Xuan, Chuanxu Zhao, Yangbo Li, Lei Yu, Donghui Xia, Zhipeng Chen, Zhoujun Yang, the J-TEXT team

Abstract: The phenomena of island healing and configuration transition induced by high-power electron cyclotron resonance heating (ECRH) have been investigated in the island divertor configuration on the J-TEXT tokamak. Experimental results reveal that the size of the edge open magnetic island with mode number m/n = 3/1 decreases substantially under specific ECRH conditions. This process, referred to as isl… ▽ More The phenomena of island healing and configuration transition induced by high-power electron cyclotron resonance heating (ECRH) have been investigated in the island divertor configuration on the J-TEXT tokamak. Experimental results reveal that the size of the edge open magnetic island with mode number m/n = 3/1 decreases substantially under specific ECRH conditions. This process, referred to as island healing, occurs when ECRH with a power of 500~600 kW is deposited in the plasma core or when 250 kW of ECRH is deposited at r = 0.5 a, where a is the minor radius. The reduction of the island width makes the island divertor ineffective and transition into the limiter configuration. A model incorporating the influence of ECRH on the scrape-off layer (SOL) thermoelectric current is proposed to explain the observed changes in the edge magnetic topology of the island divertor configuration. These findings suggest that ECRH should be deposited at the plasma core with carefully controlled power to ensure the stable and compatible operation of ECRH and the island divertor configuration in tokamaks. The results can provide insights into achieving robust operation of an island divertor in tokamaks. △ Less

Submitted 14 January, 2025; originally announced January 2025.

Light-induced ultrafast glide-mirror symmetry breaking in black phosphorus

Authors: Changhua Bao, Fei Wang, Haoyuan Zhong, Shaohua Zhou, Tianyun Lin, Hongyun Zhang, Xuanxi Cai, Wenhui Duan, Shuyun Zhou

Abstract: Symmetry breaking plays an important role in fields of physics, ranging from particle physics to condensed matter physics. In solid-state materials, phase transitions are deeply linked to the underlying symmetry breakings, resulting in a rich variety of emergent phases. Such symmetry breakings are often induced by controlling the chemical composition and temperature or applying an electric field a… ▽ More Symmetry breaking plays an important role in fields of physics, ranging from particle physics to condensed matter physics. In solid-state materials, phase transitions are deeply linked to the underlying symmetry breakings, resulting in a rich variety of emergent phases. Such symmetry breakings are often induced by controlling the chemical composition and temperature or applying an electric field and strain, etc. In this work, we demonstrate an ultrafast glide-mirror symmetry breaking in black phosphorus through Floquet engineering. Upon near-resonance pumping, a light-induced full gap opening is observed at the glide-mirror symmetry protected nodal ring, suggesting light-induced breaking of the glide-mirror symmetry. Moreover, the full gap is observed only in the presence of the light-field and disappears almost instantaneously ($\ll$100 fs) when the light-field is turned off, suggesting the ultrafast manipulation of the symmetry and its Floquet engineering origin. This work not only demonstrates light-matter interaction as an effective way to realize ultrafast symmetry breaking in solid-state materials, but also moves forward towards the long-sought Floquet topological phases. △ Less

Submitted 9 December, 2024; originally announced December 2024.

Journal ref: ACS Nano 18, 32038 (2024)

Manipulating the symmetry of photon-dressed electronic states

Authors: Changhua Bao, Michael Schüler, Teng Xiao, Fei Wang, Haoyuan Zhong, Tianyun Lin, Xuanxi Cai, Tianshuang Sheng, Xiao Tang, Hongyun Zhang, Pu Yu, Zhiyuan Sun, Wenhui Duan, Shuyun Zhou

Abstract: Strong light-matter interaction provides opportunities for tailoring the physical properties of quantum materials on the ultrafast timescale by forming photon-dressed electronic states, i.e., Floquet-Bloch states. While the light field can in principle imprint its symmetry properties onto the photon-dressed electronic states, so far, how to experimentally detect and further engineer the symmetry o… ▽ More Strong light-matter interaction provides opportunities for tailoring the physical properties of quantum materials on the ultrafast timescale by forming photon-dressed electronic states, i.e., Floquet-Bloch states. While the light field can in principle imprint its symmetry properties onto the photon-dressed electronic states, so far, how to experimentally detect and further engineer the symmetry of photon-dressed electronic states remains elusive. Here by utilizing time- and angle-resolved photoemission spectroscopy (TrARPES) with polarization-dependent study, we directly visualize the parity symmetry of Floquet-Bloch states in black phosphorus. The photon-dressed sideband exhibits opposite photoemission intensity to the valence band at the $Γ$ point,suggesting a switch of the parity induced by the light field. Moreover, a "hot spot" with strong intensity confined near $Γ$ is observed, indicating a momentum-dependent modulation beyond the parity switch. Combining with theoretical calculations, we reveal the light-induced engineering of the wave function of the Floquet-Bloch states as a result of the hybridization between the conduction and valence bands with opposite parities, and show that the "hot spot" is intrinsically dictated by the symmetry properties of black phosphorus. Our work suggests TrARPES as a direct probe for the parity of the photon-dressed electronic states with energy- and momentum-resolved information, providing an example for engineering the wave function and symmetry of such photon-dressed electronic states via Floquet engineering. △ Less

Submitted 9 December, 2024; originally announced December 2024.

Journal ref: Nature Communications 15, 10535 (2024)

A high-performance all-silicon photodetector enabling telecom-wavelength detection at room temperature

Authors: Mohd Saif Shaikh, Mircea-Traian Catuneanu, Ahmad Echresh, Rang Li, Shuyu Wen, Guillermo Godoy-Pérez, Slawomir Prucnal, Manfred Helm, Yordan M. Georgiev, Kambiz Jamshidi, Shengqiang Zhou, Yonder Berencén

Abstract: Photonic integrated circuits (PICs) are crucial for advancing optical communications, promising substantial gains in data transmission speed, bandwidth, and energy efficiency compared to conventional electronics. Telecom-wavelength photodetectors, operating near 1550 nm, are indispensable in PICs, where they enable the sensitive and low-noise conversion of optical signals to electrical signals for… ▽ More Photonic integrated circuits (PICs) are crucial for advancing optical communications, promising substantial gains in data transmission speed, bandwidth, and energy efficiency compared to conventional electronics. Telecom-wavelength photodetectors, operating near 1550 nm, are indispensable in PICs, where they enable the sensitive and low-noise conversion of optical signals to electrical signals for efficient data processing. While silicon is ideal for passive optical components, its limited absorption in the optical telecommunication range (1260-1625 nm) typically necessitates integrating an alternative material, such as germanium, for photodetection - a process that introduces significant fabrication challenges. Here, we present a high-performance, all-silicon waveguide-coupled photodetector, which operates at room temperature within the optical telecom C band. By introducing deep-level impurities into silicon at concentrations close to the solid-solubility limit, we enable efficient sub-bandgap absorption without compromising recombination carrier lifetimes and mobilities. This detector achieves a responsivity of 0.56 A/W, a quantum efficiency of 44.8%, a bandwidth of 2 GHz, and a noise-equivalent power of 4.2E-10 W/Hz1/2 at 1550 nm, fulfilling requirements for telecom applications. Our approach provides a scalable and cost-effective solution for the monolithic integration of telecom-wavelength photodetectors into silicon-based PICs, advancing the development of compact photonic systems for modern communication infrastructures. △ Less

Submitted 31 August, 2025; v1 submitted 8 December, 2024; originally announced December 2024.

Comments: 22 pages, 3 figures, 1 table

Bending, breaking, and reconnecting of the electrical double layers at heterogeneous electrodes

Authors: Qian Ai, Lalith Krishna Samanth Bonagiri, Kaustubh S. Panse, Jaehyeon Kim, Shan Zhou, Yingjie Zhang

Abstract: In electrochemical systems, the structure of electrical double layers (EDLs) near electrode surfaces is crucial for energy conversion and storage functions. While the electrodes in real-world systems are usually heterogeneous, to date the investigation of EDLs is mainly limited to flat model solid surfaces. To bridge this gap, here we image the EDL structure of an ionic liquid-based electrolyte at… ▽ More In electrochemical systems, the structure of electrical double layers (EDLs) near electrode surfaces is crucial for energy conversion and storage functions. While the electrodes in real-world systems are usually heterogeneous, to date the investigation of EDLs is mainly limited to flat model solid surfaces. To bridge this gap, here we image the EDL structure of an ionic liquid-based electrolyte at a heterogeneous graphite electrode using our recently developed electrochemical 3D atomic force microscopy. These interfaces feature the formation of thin, nanoscale adlayer/cluster domains that closely mimic the early-stage solid-electrolyte interphases in many battery systems. We observe multiple discrete layers in the EDL near the flat electrode, which restructures at the heterogeneous interphase sites. Depending on the local size of the interphase clusters, the EDLs exhibit bending, breaking, and/or reconnecting behaviors, likely due to the combined steric and long-range interaction effects. These results shed light on the fundamental structure and reconfiguration mechanism of EDLs at heterogeneous interfaces. △ Less

Submitted 3 December, 2024; v1 submitted 2 October, 2024; originally announced October 2024.

SciDVS: A Scientific Event Camera with 1.7% Temporal Contrast Sensitivity at 0.7 lux

Authors: Rui Graca, Sheng Zhou, Brian McReynolds, Tobi Delbruck

Abstract: This paper reports a Dynamic Vision Sensor (DVS) event camera that is 6x more sensitive at 14x lower illumination than existing commercial and prototype cameras. Event cameras output a sparse stream of brightness change events. Their high dynamic range (HDR), quick response, and high temporal resolution provide key advantages for scientific applications that involve low lighting conditions and spa… ▽ More This paper reports a Dynamic Vision Sensor (DVS) event camera that is 6x more sensitive at 14x lower illumination than existing commercial and prototype cameras. Event cameras output a sparse stream of brightness change events. Their high dynamic range (HDR), quick response, and high temporal resolution provide key advantages for scientific applications that involve low lighting conditions and sparse visual events. However, current DVS are hindered by low sensitivity, resulting from shot noise and pixel-to-pixel mismatch. Commercial DVS have a minimum brightness change threshold of >10%. Sensitive prototypes achieved as low as 1%, but required kilo-lux illumination. Our SciDVS prototype fabricated in a 180nm CMOS image sensor process achieves 1.7% sensitivity at chip illumination of 0.7 lx and 18 Hz bandwidth. Novel features of SciDVS are (1) an auto-centering in-pixel preamplifier providing intrascene HDR and increased sensitivity, (2) improved control of bandwidth to limit shot noise, and (3) optional pixel binning, allowing the user to trade spatial resolution for sensitivity. △ Less

Submitted 15 September, 2024; originally announced September 2024.

Comments: Presented at ESSERC 2024

Modeling of a continuous superradiant laser on the sub-mHz $^1$S$_0\,\rightarrow\,^3$P$_0$ transition in neutral strontium-88

Authors: Swadheen Dubey, Georgy A. Kazakov, Benedikt Heizenreder, Sheng Zhou, Shayne Bennetts, Stefan Alaric Schäffer, Ananya Sitaram, Florian Schreck

Abstract: Continuous superradiance using a narrow optical transition has the potential to improve the short-term stability of state-of-the-art optical clocks. Even though pulsed superradiant emission on a mHz linewidth clock transition has been shown, true continuous operation, without Fourier limitation, has turned out to be extremely challenging. The trade-off between maintaining a high atomic flux while… ▽ More Continuous superradiance using a narrow optical transition has the potential to improve the short-term stability of state-of-the-art optical clocks. Even though pulsed superradiant emission on a mHz linewidth clock transition has been shown, true continuous operation, without Fourier limitation, has turned out to be extremely challenging. The trade-off between maintaining a high atomic flux while minimizing decoherence effects presents a significant obstacle. Here, we discuss the design of a machine that could overcome this problem by combining a high-flux continuous beam of ultra cold strontium atoms with a bowtie cavity for the generation of superradiant lasing. To evaluate the feasibility of our design, we present simulation results for continuous high-efficiency cooling, loading, and pumping to the upper lasing state inside the bowtie cavity. We then present two different models for stimulating the generated superradiant field by taking into account position-dependent shifts, collisional decoherence, light shifts, and atom loss. Finally, we estimate a laser linewidth of less than 100 mHz, limited by atom number fluctuations, and resulting in an output power of hundreds of fW. △ Less

Submitted 10 February, 2025; v1 submitted 10 September, 2024; originally announced September 2024.

Comments: 22 pages, 9 figures

Journal ref: Phys. Rev. Research 7, 013292 (2025)

Machine Learning for Methane Detection and Quantification from Space - A survey

Authors: Enno Tiemann, Shanyu Zhou, Alexander Kläser, Konrad Heidler, Rochelle Schneider, Xiao Xiang Zhu

Abstract: Methane ($CH_4$) is a potent anthropogenic greenhouse gas, contributing 86 times more to global warming than Carbon Dioxide ($CO_2$) over 20 years, and it also acts as an air pollutant. Given its high radiative forcing potential and relatively short atmospheric lifetime (9$\pm$1 years), methane has important implications for climate change, therefore, cutting methane emissions is crucial for effec… ▽ More Methane ($CH_4$) is a potent anthropogenic greenhouse gas, contributing 86 times more to global warming than Carbon Dioxide ($CO_2$) over 20 years, and it also acts as an air pollutant. Given its high radiative forcing potential and relatively short atmospheric lifetime (9$\pm$1 years), methane has important implications for climate change, therefore, cutting methane emissions is crucial for effective climate change mitigation. This work expands existing information on operational methane point source detection sensors in the Short-Wave Infrared (SWIR) bands. It reviews the state-of-the-art for traditional as well as Machine Learning (ML) approaches. The architecture and data used in such ML models will be discussed separately for methane plume segmentation and emission rate estimation. Traditionally, experts rely on labor-intensive manually adjusted methods for methane detection. However, ML approaches offer greater scalability. Our analysis reveals that ML models outperform traditional methods, particularly those based on convolutional neural networks (CNN), which are based on the U-net and transformer architectures. These ML models extract valuable information from methane-sensitive spectral data, enabling a more accurate detection. Challenges arise when comparing these methods due to variations in data, sensor specifications, and evaluation metrics. To address this, we discuss existing datasets and metrics, providing an overview of available resources and identifying open research problems. Finally, we explore potential future advances in ML, emphasizing approaches for model comparability, large dataset creation, and the European Union's forthcoming methane strategy. △ Less

Submitted 27 August, 2024; originally announced August 2024.

Continuous cavity-QED with an atomic beam

Authors: Francesca Famà, Sheng Zhou, Benedikt Heizenreder, Mikkel Tang, Shayne Bennetts, Simon B. Jäger, Stefan A. Schäffer, Florian Schreck

Abstract: Atoms coupled to cavities provide an exciting playground for the study of fundamental interactions of atoms mediated through a common channel. Many of the applications of cavity-QED and cold-atom experiments more broadly, suffer from limitations caused by the transient nature of an atomic loading cycle. The development of continuous operation schemes is necessary to push these systems to the next… ▽ More Atoms coupled to cavities provide an exciting playground for the study of fundamental interactions of atoms mediated through a common channel. Many of the applications of cavity-QED and cold-atom experiments more broadly, suffer from limitations caused by the transient nature of an atomic loading cycle. The development of continuous operation schemes is necessary to push these systems to the next level of performance. Here we present a machine designed to produce a continuous flux of collimated atoms that traverse an optical cavity. The atom-light interaction is enhanced by a fast-decaying cavity optimal for studying phenomena where atomic properties dominate. We demonstrate the transition to a collective strong coupling regime heralded by a normal-mode splitting. We observe a second phase with a binary normal-mode splitting born from an offset in the mean velocity of the atoms. Inverting the atomic ensemble in the collective strong coupling regime, we measure continuous optical gain. This work sets the stage for studying threshold conditions for continuous collective phenomena, such as continuous superradiant lasing. △ Less

Submitted 26 July, 2024; originally announced July 2024.

Journal ref: Phys. Rev. A 110, 063721 (2024)

Study of the decay and production properties of $D_{s1}(2536)$ and $D_{s2}^*(2573)$

Authors: M. Ablikim, M. N. Achasov, P. Adlarson, O. Afedulidis, X. C. Ai, R. Aliberti, A. Amoroso, Q. An, Y. Bai, O. Bakina, I. Balossino, Y. Ban, H. -R. Bao, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann , et al. (645 additional authors not shown)

Abstract: The $e^+e^-\rightarrow D_s^+D_{s1}(2536)^-$ and $e^+e^-\rightarrow D_s^+D^*_{s2}(2573)^-$ processes are studied using data samples collected with the BESIII detector at center-of-mass energies from 4.530 to 4.946~GeV. The absolute branching fractions of $D_{s1}(2536)^- \rightarrow \bar{D}^{*0}K^-$ and $D_{s2}^*(2573)^- \rightarrow \bar{D}^0K^-$ are measured for the first time to be… ▽ More The $e^+e^-\rightarrow D_s^+D_{s1}(2536)^-$ and $e^+e^-\rightarrow D_s^+D^*_{s2}(2573)^-$ processes are studied using data samples collected with the BESIII detector at center-of-mass energies from 4.530 to 4.946~GeV. The absolute branching fractions of $D_{s1}(2536)^- \rightarrow \bar{D}^{*0}K^-$ and $D_{s2}^*(2573)^- \rightarrow \bar{D}^0K^-$ are measured for the first time to be $(35.9\pm 4.8\pm 3.5)\%$ and $(37.4\pm 3.1\pm 4.6)\%$, respectively. The measurements are in tension with predictions based on the assumption that the $D_{s1}(2536)$ and $D_{s2}^*(2573)$ are dominated by a bare $c\bar{s}$ component. The $e^+e^-\rightarrow D_s^+D_{s1}(2536)^-$ and $e^+e^-\rightarrow D_s^+D^*_{s2}(2573)^-$ cross sections are measured, and a resonant structure at around 4.6~GeV with a width of 50~MeV is observed for the first time with a statistical significance of $15σ$ in the $e^+e^-\rightarrow D_s^+D^*_{s2}(2573)^-$ process. It could be the $Y(4626)$ found by the Belle collaboration in the $D_s^+D_{s1}(2536)^{-}$ final state, since they have similar masses and widths. There is also evidence for a structure at around 4.75~GeV in both processes. △ Less

Submitted 10 July, 2024; originally announced July 2024.

Structural changes in Ge1-xSnx and Si1-x-yGeySnx thin films on SOI substrates treated by pulse laser annealing

Authors: Oliver Steuer, Daniel Schwarz, Michael Oehme, Florian Bärwolf, Yu Cheng, Fabian Ganss, René Hübner, René Heller, Shengqiang Zhou, Manfred Helm, Gianaurelio Cuniberti, Yordan M. Georgiev, Slawomir Prucnal

Abstract: Ge1-xSnx and Si1-x-yGeySnx alloys are promising materials for future opto- and nanoelectronics applications. These alloys enable effective band-gap engineering, broad adjustability of their lattice parameter, exhibit much higher carrier mobility than pure Si, and are compatible with the CMOS technology. Unfortunately, the equilibrium solid solubility of Sn in Si1-xGex is less than 1% and the pseud… ▽ More Ge1-xSnx and Si1-x-yGeySnx alloys are promising materials for future opto- and nanoelectronics applications. These alloys enable effective band-gap engineering, broad adjustability of their lattice parameter, exhibit much higher carrier mobility than pure Si, and are compatible with the CMOS technology. Unfortunately, the equilibrium solid solubility of Sn in Si1-xGex is less than 1% and the pseudomorphic growth of Si1-x-yGeySnx on Ge or Si can cause in-plane compressive strain in the grown layer, degrading the superior properties of these alloys. Therefore, post-growth strain engineering by ultrafast non-equilibrium thermal treatments like pulse laser annealing (PLA) is needed to improve the layer quality. In this article, Ge0.94Sn0.06 and Si0.14Ge0.8Sn0.06 thin films grown on silicon-on-insulator substrates by molecular beam epitaxy were post growth thermally treated by PLA. The material is analyzed before and after the thermal treatments by transmission electron microscopy, X-ray diffraction (XRD), Rutherford backscattering spectrometry, secondary ion mass spectrometry, and Hall effect measurements. It is shown that after annealing, the material is single-crystalline with improved crystallinity than the as-grown layer. This is reflected in a significantly increased XRD reflection intensity, well-ordered atomic pillars, and increased active carrier concentrations up to 4x1019 cm-3. △ Less

Submitted 13 June, 2024; originally announced June 2024.