Showing 1–50 of 132 results for author: Sun, M

Final assessment of radioactive impurities in the JUNO detector

Authors: Thomas Adam, Fengpeng An, Costas Andreopoulos, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, João Pedro Athayde Marcondes de André, Didier Auguste, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger, Svetlana Biktemerova, Thilo Birkenfeld, Simon Blyth, Manuel Böhles, Anastasia Bolshakova, Mathieu Bongrand, Matteo Borghesi , et al. (549 additional authors not shown)

Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) collaboration has completed the construction of the 20,000-ton liquid scintillator detector and the associated muon veto detector system. To meet the physics objectives, the materials used in the detector must exhibit low radioactive contamination. The single-event rate in the fiducial volume (R $<$ 17.2 m) of the scintillator is required to be… ▽ More The Jiangmen Underground Neutrino Observatory (JUNO) collaboration has completed the construction of the 20,000-ton liquid scintillator detector and the associated muon veto detector system. To meet the physics objectives, the materials used in the detector must exhibit low radioactive contamination. The single-event rate in the fiducial volume (R $<$ 17.2 m) of the scintillator is required to be approximately 7 Hz for energies above 0.7 MeV, resulting in an accidental coincidence background of about 1 event per day for reactor neutrino physics analyses. Since the beginning of the construction phase, we have screened the natural radioactivity content of thousands of materials, to select those that meet the design background budget. The radioactive impurity concentrations of the materials ultimately used in the JUNO detector are summarized in this paper. The construction of the entire detector and the subsequent filling of the liquid scintillator were completed in August 2025. From the initial data, the total count rate of natural radioactivity within the detector's fiducial volume has met the requirements and is sufficient to support the reactor antineutrino analysis. △ Less

Submitted 19 July, 2026; originally announced July 2026.

Leveraging Raman response in X-cut thin-film lithium tantalate for ultrabroadband combs and polychromatic visible light

Authors: Xin Wang, Mingkun Xiao, Min Sun, Ronghong Gao, Yuqi Chen, Zhengshun Lei, Xun Zhang, Wenfeng Zhou, Jintian Lin, Yikai Su, Xingchen Ji, Yong Zhang

Abstract: X-cut thin-film lithium tantalate (TFLT) offers a unique combination of third nonlinearity, electro-optic effects, and a high optical damage threshold. However, its strong Raman response has historically hindered broadband Kerr comb generation. Here, we leverage this inherent Raman response by engineering coupling-defined dissipation. This allows us to reconfigure the relative thresholds of Raman… ▽ More X-cut thin-film lithium tantalate (TFLT) offers a unique combination of third nonlinearity, electro-optic effects, and a high optical damage threshold. However, its strong Raman response has historically hindered broadband Kerr comb generation. Here, we leverage this inherent Raman response by engineering coupling-defined dissipation. This allows us to reconfigure the relative thresholds of Raman and Kerr processes without modifying the intrinsic microresonator dispersion. Through this coupling-engineered threshold control, we can deliberately access distinct comb states, ranging from pure Kerr combs to Raman-Kerr synergistic broadband combs. We demonstrate a Kerr comb spanning 450 nm and a Raman-Kerr comb spanning 650 nm, representing the broadest combs reported to date on X-cut TFLT platforms. Moreover, in strongly coupled devices, we show that a single near-infrared pump can generate visible emission across multiple bands (from violet to red) via cascaded second sum-frequency processes. Our work demonstrates that a strong Raman response can be transformed from a parasitic competitor into an enabling mechanism for achieving broader comb spectra and generating polychromatic visible light. This work establishes X-cut TFLT as a powerful monolithic platform for nonlinear light sources, electro-optic functions, and complex photonic systems. △ Less

Submitted 13 July, 2026; originally announced July 2026.

Excitation of non-modal perturbations in hypersonic boundary layers by free stream forcing. Part II: asymptotic theory and key mechanisms

Authors: Ming Dong, Mingze Sun, Qinyang Song, Lei Zhao

Abstract: Recently, Zhao & Dong (J. Fluid Mech. 2025, vol. 1013: A44) developed a high-efficiency, high-accuracy numerical framework, the shock-fitting harmonic linearised Navier-Stokes (SF-HLNS) approach, which enables a systematic study of the receptivity of non-modal perturbations in hypersonic blunt-body boundary layers over a wide parameter range. In this Part II, we employ a high-Reynolds-number asymp… ▽ More Recently, Zhao & Dong (J. Fluid Mech. 2025, vol. 1013: A44) developed a high-efficiency, high-accuracy numerical framework, the shock-fitting harmonic linearised Navier-Stokes (SF-HLNS) approach, which enables a systematic study of the receptivity of non-modal perturbations in hypersonic blunt-body boundary layers over a wide parameter range. In this Part II, we employ a high-Reynolds-number asymptotic analysis to elucidate the physical mechanism of the receptivity process. A distinct slow-down convection mechanism is identified in the nose region, amplifying the perturbation streamwise vorticity from the post-shock position to the boundary layer around the stagnation point by a factor of O(\sqrt{R}), where R is the Reynolds number based on nose radius. Downstream, the lift-up mechanism further leads to a transient growth of the perturbation streamwise velocity up to an amplitude of O(R). Based on these mechanisms, a reduced model is developed to predict the downstream evolution of the non-modal perturbations initiated by receptivity, whose predictions agree well with SF-HLNS calculations. This model can also be used to investigate the effects of wall temperature and nose radius on non-modal receptivity efficiency, as will be detailed in Part III of this work series. △ Less

Submitted 25 June, 2026; originally announced June 2026.

Comments: 29 pages,10 figures

Tunable Mid-Infrared Chiral Selective Absorber Based on Asymmetric V-Shaped Metasurfaces Driven by Chiral quasi-Bound State in the Continum

Authors: Yuqing Liu, Yi Wang, Ruihan Ma, Nianzhao Wang, Mengtao Sun, Yuqing Cheng

Abstract: Efficient discrimination of circularly polarized light (CPL) is of great significance in photonics. In this study, we propose a nanophotonic device based on asymmetric V-shaped metasurfaces that exhibits strong discrimination between left- and right-circularly polarized (LCP and RCP) light at the resonant wavelengths of the absorption spectra. The chiral-selective response originates from a quasi-… ▽ More Efficient discrimination of circularly polarized light (CPL) is of great significance in photonics. In this study, we propose a nanophotonic device based on asymmetric V-shaped metasurfaces that exhibits strong discrimination between left- and right-circularly polarized (LCP and RCP) light at the resonant wavelengths of the absorption spectra. The chiral-selective response originates from a quasi-bound state in the continuum (qBIC) mode enabled by controlled symmetry breaking in the V-shaped structure, which exhibits high absorption under LCP illumination while the resonance is strongly suppressed under RCP incidence, leading to a large absorption contrast between the two circular polarizations. This significant absorption difference enables highly efficient chiral discrimination. Furthermore, the resonant wavelength can be broadly tuned from 5200 to 6200 nm by scaling the structural dimensions without compromising the high absorption contrast between LCP and RCP. This work not only enables high-performance chiral detection and separation, but also offers valuable guidance for reconfigurable chiral nanodevices, with promising applications in areas such as enantiomer sensing, chiral imaging, and CPL spectroscopy. △ Less

Submitted 4 June, 2026; originally announced June 2026.

Comments: 15 pages, 8 figures

Three-dimensional density and air-rock interface reconstruction with muography: Application to the TianQin tunnel

Authors: Songran Qi, Tao Yu, Shihan Zhao, Yunsong Ning, Aiyu Bai, Yu Chen, Yi Yuan, Mingchen Sun, Zhirui Liu, Liang Xian, Hengye Xu, Hao Jiang, Zhichao Wang, Shuhang Zhang, Su Zhan, Jian Tang

Abstract: Muography is a non-invasive imaging technique that uses cosmic-ray muons, commonly divided into transmission (absorption) and scattering muography. For transmission muography, the inversion algorithm critically determines reconstruction quality. However, widely used schemes may produce smearing artifacts when measurement locations are limited and data are sparse. We develop an optimized Metropolis… ▽ More Muography is a non-invasive imaging technique that uses cosmic-ray muons, commonly divided into transmission (absorption) and scattering muography. For transmission muography, the inversion algorithm critically determines reconstruction quality. However, widely used schemes may produce smearing artifacts when measurement locations are limited and data are sparse. We develop an optimized Metropolis--Hastings (M--H) algorithm that mitigates smearing and retrieves sharper, more accurate density distributions without auxiliary data. Additionally, we implement an inverse distance weighting (IDW) approach to reconstruct the air--rock interface from muon measurements. The optimized M--H algorithm is applied in Monte Carlo simulations and applied to field data from the TianQin Tunnel experiment using the MuGrid-v2 detector. The IDW-reconstructed air--rock interface is validated against Light Detection and Ranging (LiDAR) measurements. In simulations, the optimized M--H algorithm improves high-density anomaly detection precision from $42\%$ to $100\%$ at threshold $5.1\,\mathrm{g/cm^3}$, with gains of $6\%$ to $42\%$ across other threshold and low-density scenarios, together with the TianQin Tunnel reconstructions, these results demonstrate the effectiveness of the proposed approach. △ Less

Submitted 2 June, 2026; originally announced June 2026.

Embedded underwater front-end electronics for the 3-inch photomultipliers in the JUNO experiment

Authors: Cédric Cerna, Miao He, Xiaoshan Jiang, Juan Pedro Ochoa-Ricoux, Frédéric Perrot, Angel Abusleme, Thomas Adam, Fengpeng An, Costas Andreopoulos, Giuseppe Andronico, João Pedro Athayde Marcondes de André, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Didier Auguste, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger, Svetlana Biktemerova , et al. (576 additional authors not shown)

Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) is a 20-kton liquid scintillator-based, low-radioactivity, multi-purpose neutrino detector located 693 meters (1800 m.w.e.) underground in the Guangdong province, China. To detect scintillation light produced in the target, the detector is equipped with 17,612 20-inch photomultipliers (PMTs), forming the Large PMT system (LPMT). In addition, 25,… ▽ More The Jiangmen Underground Neutrino Observatory (JUNO) is a 20-kton liquid scintillator-based, low-radioactivity, multi-purpose neutrino detector located 693 meters (1800 m.w.e.) underground in the Guangdong province, China. To detect scintillation light produced in the target, the detector is equipped with 17,612 20-inch photomultipliers (PMTs), forming the Large PMT system (LPMT). In addition, 25,600 3-inch photomultipliers (the Small Photomultiplier System or SPMT) are deployed in the gaps between the LPMTs. This paper presents the design and performance of the underwater front-end electronics developed for the SPMT system. It details the individual electronics boards and their key components, the inter-board interfaces, the system-level design, and the firmware architecture that supports data acquisition and control. It also outlines mechanical and thermal integration, board validation procedures, and system performance metrics. The readout chain includes digitization of 128 PMT channels per unit, synchronized time-stamping, charge measurement, event packaging, and bandwidth management. Comprehensive validation confirms the system's readiness to meet JUNO's stringent physics goals. The underwater electronics achieve noise levels as low as 0.04 photoelectrons with minimal crosstalk (below 0.4%) and a bandwidth of 57 MB/s, ensuring reliable single photo-electron detection and operation under high-rate conditions. The SPMT system has now been fully integrated and installed in JUNO. Its commissioning and physics performance will be reported in a future publication. △ Less

Submitted 1 June, 2026; v1 submitted 28 April, 2026; originally announced April 2026.

Comments: Submitted to Nucl. Instrum. Methods Phys. Res. A

Facet-dependent Chemical Kinetics Governed Growth of Twisted Graphene Layers with Pre-designed Angles

Authors: Chaowu Xue, Mengzhao Sun, Zixuan Zhou, Zhuoran Yao, Li-Qun Shen, Xiao Kong, Honglong Zhao, Feng Ding, Marc Willinger, Zhongkai Liu, Zhu-Jun Wang

Abstract: Twisted graphene layers (TGLs) provide a powerful platform for investigating multiple quantum phenomena, yet their scalable deployment is hindered by the lack of reliable synthesis with precise angle. Here, benefited from a deeper understanding of the interplay between grain index and graphene growth kinetics, we report a scalable strategy to grow TGLs with pre-designed twist angles on platinum (P… ▽ More Twisted graphene layers (TGLs) provide a powerful platform for investigating multiple quantum phenomena, yet their scalable deployment is hindered by the lack of reliable synthesis with precise angle. Here, benefited from a deeper understanding of the interplay between grain index and graphene growth kinetics, we report a scalable strategy to grow TGLs with pre-designed twist angles on platinum (Pt) via chemical vapor deposition (CVD), Through a combination of complementary in situ methods, we identified the activity sequence of different Pt grains and attributed it to the area ratio of exposed (110) facets during graphene-induced surface reconstruction. Moreover, we revealed that CVD-grown graphene orientation is determined by the grain-orientation-dependent surface morphology. By leveraging the so-established correlations between grain index with both graphene growth priority and its orientation, we achieve controlled folding and tearing of graphene overlayer using a pair of adjacent grains with dramatically different catalytical activity and kink-free atomic steps. We reveal that overlayer-induced step bunching and terrace reconfiguration critically govern the domain morphology and folding direction. Building on this mechanistic insight, we demonstrate a substrate-engineering framework where specific platinum grains are rationally selected to yield TGLs with pre-designed twist angles, including magic angle with flat band dispersion. This work not only highlights fundamental kinetics of Pt catalyzed graphene CVD growth, but also offers a generalizable methodology for manipulating foldable two-dimensional materials via dynamic substrate reconstruction, exampled by programmable growth of high-quality TGLs on open surfaces. △ Less

Submitted 16 April, 2026; originally announced April 2026.

Comments: 43 pages, 6 figures. Main text only, including Methods and References

End-to-End Inverse Designed Single-Layered Metasurface for High-Compression Snapshot RGB-Achromatic Full-Stokes Polarization Imaging

Authors: Xingyu Chai, Jirong Bao, Haining Yang, Mengdi Sun

Abstract: Snapshot full-Stokes polarimetry across multiple wavelengths remains challenging because conventional architectures rely on multiplexed measurements and bulky optics. We present an end-to-end inverse designed single-layered metasurface that reconstructs RGB full-Stokes images from a snapshot sensor measurement. A metasurface modeled by a multilayer perceptron (MLP) is employed to encode the full-S… ▽ More Snapshot full-Stokes polarimetry across multiple wavelengths remains challenging because conventional architectures rely on multiplexed measurements and bulky optics. We present an end-to-end inverse designed single-layered metasurface that reconstructs RGB full-Stokes images from a snapshot sensor measurement. A metasurface modeled by a multilayer perceptron (MLP) is employed to encode the full-Stokes polarization information. The system jointly optimizes a differentiable metasurface frontend with a U-Net backend. On a real-world dataset, our design achieves a high compression ratio of 12 for snapshot RGB-achromatic polarization imaging using a single-layered metasurface. These results show that end-to-end optical-digital co-design enables high-compression snapshot full-Stokes polarization imaging with a compact footprint. △ Less

Submitted 19 June, 2026; v1 submitted 16 April, 2026; originally announced April 2026.

Comments: 14 pages, 7 figures, 3 tables

High-power-handling ultra-compact acousto-optic modulators using one-dimensional topological interface states on thin-film lithium tantalate

Authors: Yuqi Chen, Wenfeng Zhou, Min Sun, Xun Zhang, Xin Wang, Qingqing Han, Minni Qu, Yikai Su, Yong Zhang

Abstract: Recent advances in integrated photonics have enabled on-chip signal modulation and processing through localized photon-phonon interactions. For acousto-optic devices, compact footprint and high efficiency are essential for dense integration, while strong power handling is critical for stable operation in demanding applications. However, it remains challenging to achieve these features simultaneous… ▽ More Recent advances in integrated photonics have enabled on-chip signal modulation and processing through localized photon-phonon interactions. For acousto-optic devices, compact footprint and high efficiency are essential for dense integration, while strong power handling is critical for stable operation in demanding applications. However, it remains challenging to achieve these features simultaneously on existing integrated platforms. Here, we propose and experimentally demonstrate, for the first time on a thin-film lithium tantalate platform, an ultra-compact acousto-optic modulator based on topological interface states. Benefiting from the strong optical confinement of the topological boundary state, the device achieves a footprint of 0.13 by 0.12 mm2 and a half-wave voltage-length product of 0.491 Vcm. We further demonstrate stable acousto-optic modulation at an on-chip optical power of up to 28 dBm (630.9 mW), highlighting the strong power-handling capability of the thin-film lithium tantalate topological structure. This work provides a compact and high-power solution for microwave-to-photonic transduction and shows the potential of the thin-film lithium tantalate for robust integrated photonic systems. △ Less

Submitted 15 April, 2026; originally announced April 2026.

FluxMC: Rapid and High-Fidelity Inference for Space-Based Gravitational-Wave Observations

Authors: Bo Liang, Chang Liu, Hanlin Song, Tianyu Zhao, Minghui Du, He Wang, Haohao Gu, Sensen He, Yuxiang Xu, Wei-Liang Qian, Li-e Qiang, Peng Xu, Ziren Luo, Mingming Sun

Abstract: Bayesian inference in the physical sciences faces a fundamental challenge: the imperative for high-fidelity physical modeling often clashes with the intrinsic limitations of stochastic sampling algorithms. Complex, high-dimensional parameter spaces expose the universal vulnerability of conventional methods, e.g., Markov Chain Monte Carlo (MCMC), which struggle with the prohibitive costs of likelih… ▽ More Bayesian inference in the physical sciences faces a fundamental challenge: the imperative for high-fidelity physical modeling often clashes with the intrinsic limitations of stochastic sampling algorithms. Complex, high-dimensional parameter spaces expose the universal vulnerability of conventional methods, e.g., Markov Chain Monte Carlo (MCMC), which struggle with the prohibitive costs of likelihood evaluations and the risk of entrapment in local optima. To resolve this impasse, we introduce FluxMC (Flow-guided Unbiased eXploration Monte Carlo), a machine learning-enhanced framework designed to shift the inference paradigm from blind local search to globally guided transport. It integrates Flow Matching with Parallel Tempering MCMC, effectively combining the global foresight of generative AI with the rigorous asymptotic convergence and local robustness of temperature-based sampling. We showcase the efficacy of this framework through the lens of space-based gravitational-wave (GW) astronomy -- a field representing the frontier of challenging parameter inversion. In the analysis of massive black hole binaries using high-fidelity waveforms (IMRPhenomHM), FluxMC achieves robust convergence in under five hours, whereas traditional Parallel Tempering MCMC fails to converge even after hundreds of hours, yielding high Jensen-Shannon divergences (JSD) of $O(10^{-1})$. Our method reduces the distributional error by two to three orders of magnitude. Furthermore, for computationally efficient models (IMRPhenomD), it eliminates systematic biases caused by local-optima entrapment. Ultimately, FluxMC removes the necessity to compromise between model accuracy and analysis speed, establishing a new computational foundation where scientific discovery is limited only by observational data quality, not by algorithmic capacity. △ Less

Submitted 8 April, 2026; v1 submitted 3 April, 2026; originally announced April 2026.

Broadband Asymmetric Transmission with Wide Spectral Tunability based on Substrate-Embedded Silicon Nanoring Arrays

Authors: Ruihan Ma, Yuqing Cheng, Mengtao Sun

Abstract: In this work, we theoretically propose a broadband asymmetric transmission (AT) device based on periodic Si nanoring arrays embedded in a SiO2 substrate. Results indicate that the device achieves a remarkable broadband AT effect in the near-infrared region (1750-2400 nm), with forward transmissivity exceeding 0.8 (maximum of 0.98), backward transmissivity less than 0.15 (minimum of 0.015) and an i… ▽ More In this work, we theoretically propose a broadband asymmetric transmission (AT) device based on periodic Si nanoring arrays embedded in a SiO2 substrate. Results indicate that the device achieves a remarkable broadband AT effect in the near-infrared region (1750-2400 nm), with forward transmissivity exceeding 0.8 (maximum of 0.98), backward transmissivity less than 0.15 (minimum of 0.015) and an isolation ratio (IR) reaching a maximum of 17.8 dB at 2280 nm. Furthermore, the transmissivity spectrum exhibits excellent scalability and tunability through uniform scaling of the structure, allowing the operational band to be tailored across a wide spectral range, from 890 to 3300 nm. This Si-based nanostructure offers a robust and flexible platform for applications in optical isolation, multi-channel sensing, and integrated photonic circuits. △ Less

Submitted 23 March, 2026; originally announced March 2026.

Comments: 12 pages, 5 figures

CAAL: Confidence-Aware Active Learning for Heteroscedastic Atmospheric Regression

Authors: Fei Jiang, Jiyang Xia, Junjie Yu, Mingfei Sun, Hugh Coe, David Topping, Dantong Liu, Zhenhui Jessie Li, Zhonghua Zheng

Abstract: Quantifying the impacts of air pollution on health and climate relies on key atmospheric particle properties such as toxicity and hygroscopicity. However, these properties typically require complex observational techniques or expensive particle-resolved numerical simulations, limiting the availability of labeled data. We therefore estimate these hard-to-measure particle properties from routinely a… ▽ More Quantifying the impacts of air pollution on health and climate relies on key atmospheric particle properties such as toxicity and hygroscopicity. However, these properties typically require complex observational techniques or expensive particle-resolved numerical simulations, limiting the availability of labeled data. We therefore estimate these hard-to-measure particle properties from routinely available observations (e.g., air pollutant concentrations and meteorological conditions). Because routine observations only indirectly reflect particle composition and structure, the mapping from routine observations to particle properties is noisy and input-dependent, yielding a heteroscedastic regression setting. With a limited and costly labeling budget, the central challenge is to select which samples to measure or simulate. While active learning is a natural approach, most acquisition strategies rely on predictive uncertainty. Under heteroscedastic noise, this signal conflates reducible epistemic uncertainty with irreducible aleatoric uncertainty, causing limited budgets to be wasted in noise-dominated regions. To address this challenge, we propose a confidence-aware active learning framework (CAAL) for efficient and robust sample selection in heteroscedastic settings. CAAL consists of two components: a decoupled uncertainty-aware training objective that separately optimises the predictive mean and noise level to stabilise uncertainty estimation, and a confidence-aware acquisition function that dynamically weights epistemic uncertainty using predicted aleatoric uncertainty as a reliability signal. Experiments on particle-resolved numerical simulations and real atmospheric observations show that CAAL consistently outperforms standard AL baselines. The proposed framework provides a practical and general solution for the efficient expansion of high-cost atmospheric particle property databases. △ Less

Submitted 12 February, 2026; originally announced February 2026.

Comments: 17 pages in total

Probing Internal Dynamics of Spatiotemporal Optical Vortex Strings: Spatiotemporal Attraction and Filament Stretching

Authors: Xiuyu Yao, Xuechen Gao, Ping Zhu, Jintao Fan, Jingwen Ran, Zezhao Gong, Dongjun Zhang, Xiao Liang, Xuejie Zhang, Meizhi Sun, Qiang Zhang, Lijie Cui, Hailun Zeng, Minglie Hu, Xinglong Xie, Jianqiang Zhu

Abstract: Vortex dynamics are intriguing and challenging across multiple physics fields. In optics, customized spatiotemporally structured optical fields, especially spatiotemporal optical vortices (STOV), offer the potential to tailor light via coupled space-time degrees of freedom. However, the interaction mechanisms between multiple transverse orbital angular momentum singularities within a single wave p… ▽ More Vortex dynamics are intriguing and challenging across multiple physics fields. In optics, customized spatiotemporally structured optical fields, especially spatiotemporal optical vortices (STOV), offer the potential to tailor light via coupled space-time degrees of freedom. However, the interaction mechanisms between multiple transverse orbital angular momentum singularities within a single wave packet remain elusive. This study explores the intrinsic dynamics of a STOV with three phase singularities, observing a pronounced vortex singularity oscillation phenomena by tuning the temporal dispersion. We show that these phenomena originate from the counterintuitive spatiotemporal attractive effect between vortices, which is closely related to the singularity distance. Furthermore, the stretching into filaments and annihilation behaviors is observed by introducing antivortex in the center of the wavepacket. Experimentally, we propose a Full Interferometric Retrieval of Spatiotemporal Tomography (FIRST) method that enables the complete, single-shot capture of wave packets, with excellent agreement between theoretical predictions and experimental results. To the best of our knowledge, the dynamics of transverse spatiotemporal singularities within a single wave packet are reported here for the first time. These findings confirm the existence of interesting interactions between STOV singularities, deepen our understanding of photonics and open a new direction for investigating the complex dynamics of vortex singularities in the spatiotemporal domain. △ Less

Submitted 10 February, 2026; originally announced February 2026.

An Oscillation-Free Real Fluid Quasi-Conservative Finite Volume Method for Transcritical and Phase-Change Flows

Authors: Haotong Bai, Wenjia Xie, Yixin Yang, Ping Yi, Mingbo Sun

Abstract: A new Real Fluid Quasi-Conservative (RFQC) finite volume method is developed to address the numerical simulation of real fluids involving shock waves in transcritical and phase-change flows. To eliminate the spurious pressure oscillations inherent in fully conservative schemes, we extend the classic quasi-conservative method, originally designed for two-phase flows, to real fluids governed by arbi… ▽ More A new Real Fluid Quasi-Conservative (RFQC) finite volume method is developed to address the numerical simulation of real fluids involving shock waves in transcritical and phase-change flows. To eliminate the spurious pressure oscillations inherent in fully conservative schemes, we extend the classic quasi-conservative method, originally designed for two-phase flows, to real fluids governed by arbitrary equations of state (EoS). The RFQC method locally linearizes the real fluid EoS at each grid point and time step, constructing and evolving the frozen Grüneisen coefficient $Γ$ and the linearization remainder $E_0$ via two advection equations. At the end of each time step, the evolved $Γ$ and $E_0$ are utilized to reconstruct the oscillation-free pressure field, followed by a thermodynamic re-projection applied to the conserved variables. Theoretical analysis demonstrates that, in smooth regions, the energy conservation error introduced by the RFQC method is a second-order small term dominated by the time-step. In discontinuous regions, this error is determined by the entropy increase rate, thereby maintaining consistency with the inherent truncation error of shock-capturing methods. A series of numerical tests verifies that the method can robustly simulate complex flow processes with only minor energy conservation errors, including transcritical flows, phase transitions, and shock-interface interactions. The RFQC method is proven to be both accurate and robust in capturing shock waves and phase transitions. △ Less

Submitted 22 June, 2026; v1 submitted 31 January, 2026; originally announced February 2026.

Comments: 36 pages, 15 figures

MSC Class: 76M12 ACM Class: G.1.8

Journal ref: Journal of Computational Physics, 564 (2026) 115156

Flash evaporation Riemann Problem: Formulation and its Exact Solution

Authors: Haotong Bai, Ping Yi, Yixin Yang, Guoyan Zhao, Wenjia Xie, Mingbo Sun

Abstract: Flash evaporation, a liquid-to-gas phase transition phenomenon in real fluids, is prevalent in aerospace propulsion systems. To elucidate the physical mechanisms of such complex flows and provide theoretical benchmarks for Computational Fluid Dynamics simulations, this paper formalizes the Flash evaporation Riemann problem (FeRP) characterized by the expansion branch crossing the saturation line,… ▽ More Flash evaporation, a liquid-to-gas phase transition phenomenon in real fluids, is prevalent in aerospace propulsion systems. To elucidate the physical mechanisms of such complex flows and provide theoretical benchmarks for Computational Fluid Dynamics simulations, this paper formalizes the Flash evaporation Riemann problem (FeRP) characterized by the expansion branch crossing the saturation line, within the framework of Homogeneous Equilibrium and Vapor-Liquid Equilibrium assumptions. An exact solution framework that analytically resolves all thermodynamic derivatives of equilibrium two-phase fluids is established for arbitrary two-parameter equations of state. By evaluating the Landau fundamental derivative, the non-classical wave structures arising in the FeRP are analyzed, for which a stable iterative solution strategy incorporating the Chapman-Jouguet condition as an outer constraint is proposed. Furthermore, an exact solution for the FeRP based on Wood's mechanical equilibrium speed of sound is developed, enabling a comprehensive evaluation of its thermodynamic implications. Results indicate that Wood's model alters the definition of the two-phase mixture entropy in the Euler equations, introducing an isentropic path characterized by a "density lag" effect and non-physical entropy decrease. Comparative analysis of the FeRP under typical scramjet fuel injection conditions reveals that, although Wood's model captures the general trend of the Riemann solution curve, it significantly underestimates intermediate pressure, velocity, and the extent of vaporization relative to the complete equilibrium model. △ Less

Submitted 26 January, 2026; originally announced January 2026.

Comments: 38 pages, 12 figures

MSC Class: 76T10

Journal ref: Journal of Fluid Mechanics , Volume 1038 , 10 July 2026 , A35

Broadband asymmetric transmission with tunable bilayer silicon nanoarrays: from visible to near-infrared

Authors: Ruihan Ma, Yuqing Cheng, Mengtao Sun

Abstract: A kind of asymmetric transmission (AT) device based on bilayer silicon arrays (BSA) nanostructure is theoretically explored, which achieves high forward transmissivity and suppressed backward transmissivity for broadband by simply adjusting the parameters of the structure. The structure consists of two silicon cylinder arrays, one on the SiO2 substrate and the other embedded in the substrate. Part… ▽ More A kind of asymmetric transmission (AT) device based on bilayer silicon arrays (BSA) nanostructure is theoretically explored, which achieves high forward transmissivity and suppressed backward transmissivity for broadband by simply adjusting the parameters of the structure. The structure consists of two silicon cylinder arrays, one on the SiO2 substrate and the other embedded in the substrate. Particularly, three AT devices with different configurations are designed, which exhibit broadband AT with high isolation ratios in the wavelength ranges of 685-807 nm, 866-1029 nm, and 1285-1536 nm, respectively. A comprehensive analysis of the BSA structure's performance across different array periods highlights its potential for broadband optical applications, such as optical isolation and multi-channel optical sensors. △ Less

Submitted 25 January, 2026; originally announced January 2026.

Comments: 4 figures

Muon beams towards muonium physics: progress and prospects

Authors: Siyuan Chen, Mingchen Sun, Jian Tang

Abstract: Advances in accelerator technology have led to significant improvements in the quality of muon beams over the past decades. Investigations of the muon and muonium enable precise measurements of fundamental constants, as well as searches for new physics beyond the Standard Model. Furthermore, by utilizing muon beams with high intensity and polarization, studies of the dynamics of the muon and muoni… ▽ More Advances in accelerator technology have led to significant improvements in the quality of muon beams over the past decades. Investigations of the muon and muonium enable precise measurements of fundamental constants, as well as searches for new physics beyond the Standard Model. Furthermore, by utilizing muon beams with high intensity and polarization, studies of the dynamics of the muon and muonium within atomic level can offer valuable insights into materials science. This review presents recent progress and prospects at the frontiers of muon beams and high-precision muonium physics. It also provides an overview of novel methods and detection techniques to achieve high sensitivities in different areas, including particle physics, nuclear physics, materials science and beyond. △ Less

Submitted 15 May, 2026; v1 submitted 22 January, 2026; originally announced January 2026.

Comments: 73 pages, 32 figures, 3 tables. Review article

Swelling-Induced Stress-Assisted Transfer of Nanodiamond Arrays with a PVA Carrier Tape for Conformal Bio-Integrated Sensing and Labelling

Authors: Luyao Zhang, Lingzhi Wang, Xinhao Hu, Yip Tai Nam, Mingzhe Sun, Jixiang Jing, Lizhi Xu, Yuan Lin, Yong Hou, Zhiqin Chu

Abstract: The conformal integration of nitrogen-vacancy (NV) center nanodiamond arrays onto soft, hydrated, curvilinear biological interfaces remain a fundamental challenge for in vivo quantum sensing and imaging. Conventional transfer techniques often fail due to reliance on high temperature, corrosive chemicals, or mechanical peeling, leading to pattern damage, low fidelity, or poor biocompatibility. Here… ▽ More The conformal integration of nitrogen-vacancy (NV) center nanodiamond arrays onto soft, hydrated, curvilinear biological interfaces remain a fundamental challenge for in vivo quantum sensing and imaging. Conventional transfer techniques often fail due to reliance on high temperature, corrosive chemicals, or mechanical peeling, leading to pattern damage, low fidelity, or poor biocompatibility. Here, we report a transfer strategy utilizing polyvinyl alcohol (PVA) carrier soluble tape, enabling rapid, residue-free, high-fidelity transfer of nanodiamond patterns onto diverse biointerfaces. The success of this method is rooted in a unique "hydrate-soften-expand-self-peel" mechanism of the soluble tape with PVA backing. In situ mechanical tracking reveals non-uniform PVA swelling upon hydration generates transient local normal and shear stresses at the interface. These stresses delaminate the tape within 3 minutes at room temperature while promoting adhesion of the nanodiamond array to the substrate. In contrast, conventional water-soluble tapes with composite structures undergo passive dissolution and collapse, causing residue contamination and reduced efficiency. Leveraging this mechanism, we achieve conformal patterning on ultra-soft hydrogels (~0.6 kPa) and highly curved bio-surfaces (hair, 100 μm^-1). Additionally, we demonstrate a dual-identity verification system integrating data storage and physical unclonable functions on a hydrogel contact lens. This work provides a versatile tool for bio-interface engineering and a general framework for gentle, efficient transfer of functional nanomaterials. △ Less

Submitted 21 January, 2026; originally announced January 2026.

Comments: 36 pages, 4 figures in main texture and 14 pages in supporting information

DeepH-pack: A general-purpose neural network package for deep-learning electronic structure calculations

Authors: Yang Li, Yanzhen Wang, Boheng Zhao, Xiaoxun Gong, Yuxiang Wang, Zechen Tang, Zixu Wang, Zilong Yuan, Jialin Li, Minghui Sun, Zezhou Chen, Honggeng Tao, Baochun Wu, Yuhang Yu, He Li, Felipe H. da Jornada, Wenhui Duan, Yong Xu

Abstract: In computational physics and materials science, first-principles methods, particularly density functional theory, have become central tools for electronic structure prediction and materials design. Recently, rapid advances in artificial intelligence (AI) have begun to reshape the research landscape, giving rise to the emerging field of deep-learning electronic structure calculations. Despite numer… ▽ More In computational physics and materials science, first-principles methods, particularly density functional theory, have become central tools for electronic structure prediction and materials design. Recently, rapid advances in artificial intelligence (AI) have begun to reshape the research landscape, giving rise to the emerging field of deep-learning electronic structure calculations. Despite numerous pioneering studies, the field remains in its early stages; existing software implementations are often fragmented, lacking unified frameworks and standardized interfaces required for broad community adoption. Here we present DeepH-pack, a comprehensive and unified software package that integrates first-principles calculations with deep learning. By incorporating fundamental physical principles into neural-network design, such as the nearsightedness principle and the equivariance principle, DeepH-pack achieves robust cross-scale and cross-material generalizability. This allows models trained on small-scale structures to generalize to large-scale and previously unseen materials. The toolkit preserves first-principles accuracy while accelerating electronic structure calculations by several orders of magnitude, establishing an efficient and intelligent computational paradigm for large-scale materials simulation, high-throughput materials database construction, and AI-driven materials discovery. △ Less

Submitted 6 January, 2026; originally announced January 2026.

Comments: 19 pages, 7 figures, 1 table

Enabling Ultra-Fast Cardiovascular Imaging Across Heterogeneous Clinical Environments with A Generalist Foundation Model and Multimodal Database

Authors: Zi Wang, Mingkai Huang, Zhang Shi, Hongjie Hu, Lan Lan, Hui Zhang, Yan Li, Xi Hu, Qing Lu, Zongming Zhu, Qiong Yao, Yuxiang Dai, Fanwen Wang, Yinzhe Wu, Jun Lyu, Qianqian Gao, Guangming Xu, Zhenxuan Zhang, Haosen Zhang, Qing Li, Guangming Wang, Tianxing He, Lizhen Lan, Siyue Li, Le Xue , et al. (39 additional authors not shown)

Abstract: Multimodal cardiovascular magnetic resonance (CMR) imaging provides comprehensive and non-invasive insights into cardiovascular disease (CVD) diagnosis and underlying mechanisms. Despite decades of advancements, its widespread clinical adoption remains constrained by prolonged scan times, inconsistent image quality, and heterogeneity across medical environments. This underscores the urgent need fo… ▽ More Multimodal cardiovascular magnetic resonance (CMR) imaging provides comprehensive and non-invasive insights into cardiovascular disease (CVD) diagnosis and underlying mechanisms. Despite decades of advancements, its widespread clinical adoption remains constrained by prolonged scan times, inconsistent image quality, and heterogeneity across medical environments. This underscores the urgent need for a generalist reconstruction foundation model for ultra-fast CMR imaging, one formulated for physics-constrained inverse problems in the sensor (k-space) domain, capable of adapting across diverse imaging scenarios and serving as the essential substrate for all downstream analyses. To enable this goal, we curate MMCMR-427K, the largest and most comprehensive multimodal CMR k-space database to date, comprising 427,465 multi-coil k-space data paired with structured metadata across 13 international centers, 12 CMR modalities, 15 scanners spanning four field strengths, and 17 CVD categories in populations across three continents. Building on this unprecedented resource, we introduce CardioMM, a generalist reconstruction foundation model capable of dynamically adapting to heterogeneous fast CMR imaging scenarios. CardioMM unifies semantic contextual understanding with physics-informed data consistency to deliver robust reconstructions across varied scanners, protocols, and patient presentations. Comprehensive evaluations demonstrate that CardioMM achieves state-of-the-art performance across internal centers and exhibits strong zero-shot generalization to unseen external settings. Importantly, CardioMM supports acceleration up to 24x, providing the first evidence that such extreme acquisition speed can preserve key cardiac phenotypes, quantitative myocardial biomarkers, and diagnostic image quality without compromising clinical integrity. △ Less

Submitted 14 April, 2026; v1 submitted 25 December, 2025; originally announced December 2025.

Comments: Github: https://github.com/wangziblake/CardioMM_MMCMR-427K

Enhancing solar cell efficiency of AlxIn1-xN/Si heterojunctions using an a-Si buffer: A study of material, interface and device properties

Authors: M. Sun, R. G. Cornejo, M. de la Mata, S. I. Molina, B. Damilano, S. Valdueza-Felip, F. B. Naranjo

Abstract: This study explores the impact of an optimized amorphous silicon (a-Si) buffer layer on AlxIn1-xN-on-Si(100) heterojunction solar cells, with Al content varying from 0% (InN) to 55%. The buffer layer improves the structural quality of the AlInN layer, as evidenced by reduced full width at half maximum values in X-ray diffraction rocking curves around the AlInN (0002) peak. Atomic force microscopy… ▽ More This study explores the impact of an optimized amorphous silicon (a-Si) buffer layer on AlxIn1-xN-on-Si(100) heterojunction solar cells, with Al content varying from 0% (InN) to 55%. The buffer layer improves the structural quality of the AlInN layer, as evidenced by reduced full width at half maximum values in X-ray diffraction rocking curves around the AlInN (0002) peak. Atomic force microscopy reveals that the buffer layer does not alter surface roughness. The effectiveness of the a-Si buffer is demonstrated by an enhancement of the conversion efficiency under AM1.5G illumination from 3.3 % to 3.9 % for devices with 35 % Al. Looking at the effect of the Al content in devices with the a-Si buffer, the device with 22% Al shows the best photovoltaic performance, with a conversion efficiency of 4.1 % and a VOC of 0.42 V, JSC of 15.4 mA/cm2, and FF of 63.3%. However, performance declines for Al contents above 36% due to increased resistivity and reduced carrier concentration. These findings highlight the critical role of the novel a-Si buffer layer developed by RF-sputtering and the Al content in optimizing AlInN/Si heterojunction solar cell performance. △ Less

Submitted 3 December, 2025; originally announced December 2025.

Effect of temperature and excitation power on down-conversion process in Tb3+/Yb3+-activated silica-hafnia glass-ceramic films

Authors: S. E. Amrani, M. Sun, S. Valdueza-Felip, F. B. Naranjo, M. R. Britel, M. Ferrari, A. Bouajaj

Abstract: Transparent glass ceramics, when activated by rare earth ions, are excellent photonic materials. Regarding photonic glass-ceramics based on silicates, hafnia and silica in a binary system has proved to be an excellent matrix to incorporate rare earth ions in the hafnia nanocrystals, resulting in important luminescence enhancement and, consequently, allowing a large spectrum of critical application… ▽ More Transparent glass ceramics, when activated by rare earth ions, are excellent photonic materials. Regarding photonic glass-ceramics based on silicates, hafnia and silica in a binary system has proved to be an excellent matrix to incorporate rare earth ions in the hafnia nanocrystals, resulting in important luminescence enhancement and, consequently, allowing a large spectrum of critical applications. Here we will focus on the downconversion mechanism driven by the couple Tb3+/Yb3+, largely exploited in photovoltaic systems. The research presented here has been performed on 70SiO2-30HfO2 silica-hafnia glass-ceramic films activated with 19 % rare earth ions: [Tb + Yb]/[Si + Hf] = 19 %. Two main results will be discussed: (a) the intensity and the broadening of the Yb3+ emission band at 975 nm were found to be temperature-dependent, as shown in the figure; (b) the energy transfer mechanism Tb3+ >> Yb3+ will be discussed, referring to the mechanisms that have been proposed in the literature. In relation to the latter topic, the power dependence spectra for the luminescence of Yb3+: 2F5/2 >> 2F7/2 will be discussed. △ Less

Submitted 21 November, 2025; originally announced November 2025.

Low-to-mid Al content ($x\sim$ 0-0.56) Al$_x$In$_{1-x}$N layers deposited on Si(100) by radio-frequency sputtering

Authors: R. Blasco, S. Valdueza-Felip, D. Montero, M. Sun, J. Olea, F. B. Naranjo

Abstract: Radio-frequency (RF) sputtering is a low-cost technique for the deposition of large-area single-phase AlInN on silicon layers with application in photovoltaic devices. Here, the effect of the Al mole fraction x from 0 to 0.56 on the structural, morphological, electrical, and optical properties of $n$ Al$_x$In$_{1-x}$N layers deposited at 550 $^\circ$C on p-Si(100) by RF sputtering is studied. X-ra… ▽ More Radio-frequency (RF) sputtering is a low-cost technique for the deposition of large-area single-phase AlInN on silicon layers with application in photovoltaic devices. Here, the effect of the Al mole fraction x from 0 to 0.56 on the structural, morphological, electrical, and optical properties of $n$ Al$_x$In$_{1-x}$N layers deposited at 550 $^\circ$C on p-Si(100) by RF sputtering is studied. X-ray diffraction data show a wurtzite structure oriented along the c-axis in all samples, where the full width at half maximum of the rocking curve around the InN (0002) diffraction peak decreases from $\sim 9^\circ$ to $\sim 3^\circ$ while incorporating Al to the AlInN layer. The rootmean-square surface roughness, estimated from atomic force microscopy, evolves from 20 nm for InN to 1.5 nm for Al$_{0.56}$In$_{0.44}$N. Low-temperature photoluminescence spectra show a blueshift of the emission energy from 1.59 eV (779 nm) for InN to 1.82 eV (681 nm) for Al$_{0.35}$In$_{0.65}$N according to the Al content rise. Hall effect measurements of Al$_x$In$_{1-x}$N ($0<x <0.35$) on sapphire samples grown simultaneously point to a residual n-type carrier concentration in the 1021 cm$^{-3}$ range. The developed n-AlInN/p-Si junctions present promising material properties to explore their performance operating as solar cell devices. △ Less

Submitted 21 November, 2025; originally announced November 2025.

InN nanowire solar cells on Si with amorphous Si interlayer deposited by sputtering

Authors: M. Sun, R. Gómez, B. Damilano, J. M. Asensi, F. B. Naranjo, S. Valdueza-Felip

Abstract: Here, we report the first experimental demonstration of InN nanowire solar cells deposited by RF sputtering with a bandgap energy of 1.78 eV. By adding an amorphous Si (a-Si) buffer to the n-InN/p-Si structure, we have improved the photovoltaic performance of the resulting devices while maintaining their material quality. We have firstly optimized the deposition of Si on Si(100) by DC sputtering,… ▽ More Here, we report the first experimental demonstration of InN nanowire solar cells deposited by RF sputtering with a bandgap energy of 1.78 eV. By adding an amorphous Si (a-Si) buffer to the n-InN/p-Si structure, we have improved the photovoltaic performance of the resulting devices while maintaining their material quality. We have firstly optimized the deposition of Si on Si(100) by DC sputtering, obtaining an amorphous material with bandgap energy of 1.39 eV. Then we have studied the influence of the thickness of the a-Si buffer layer (0-25 nm) on the structural, morphological, electrical, and optical properties of InN nanowires on Si (100) substrates. With the use of a 15-nm buffer, n-InN/a-Si/p-Si nanowire heterojunction solar cells exhibit a promising short-circuit current density of 17 mA/cm2, open circuit voltage of 0.37 V and fill factor of 35.5%, pointing to a power-conversion efficiency of 2.3% under 1-sun (AM 1.5G) illumination. These work demonstrated that the combination of in-situ sputtered a-Si, which could serve as potential passivation layer, and the light trapping enhancement by the nanostructured active layer leads to an improvement of the photovoltaic efficiency of sputtered III-nitride devices. △ Less

Submitted 21 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

Dual-Mode Asymmetric Transmission based on Asymmetric and Orthogonal Gratings: Polarization-Dependent and -Independent Modes

Authors: Ruihan Ma, Yuqing Cheng, Mengtao Sun

Abstract: A dual-mode asymmetric transmission (AT) nanodevice based on the asymmetric and orthogonal grating-film-grating (AO-GFG) structure is proposed and systematically investigated theoretically. The device supports two distinct localized surface plasmon resonance (LSPR) modes for forward transmission, corresponding to the polarization-dependent (M1) and the polarization-independent (M2) resonances, res… ▽ More A dual-mode asymmetric transmission (AT) nanodevice based on the asymmetric and orthogonal grating-film-grating (AO-GFG) structure is proposed and systematically investigated theoretically. The device supports two distinct localized surface plasmon resonance (LSPR) modes for forward transmission, corresponding to the polarization-dependent (M1) and the polarization-independent (M2) resonances, respectively. This results in the fact that when x-polarized light is incident, only M2 exists; when y-polarized light is incident, both M1 and M2 exist. Besides, both modes yield the maximum isolation ratio of more than 10 dB. The electric field distributions further indicate that M2 exhibits strong confinement and efficient tunneling through the metallic film, while M1 shows weaker but more polarization-sensitive hybridization. The coexistence and tunability of these two modes constitute the physical basis of dual-mode AT, highlighting the AO-GFG structure as a promising platform for high-isolation and polarization-tunable plasmonic devices in the visible and near-infrared regions. △ Less

Submitted 16 November, 2025; originally announced November 2025.

Comments: 15 pages, 7 figures

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

Extend the waveband of high isolation ratio and narrow band asymmetric transmission based on grating-film-grating nanostructure

Authors: Ruihan Ma, Yuqing Cheng, Mengtao Sun

Abstract: A serial asymmetric transmission (AT) nanodevices based on the grating-film-grating (G-F-G) structure are proposed and studied. By showing the results of three different nanodevices as examples, it is proved that this kind of G-F-G nanostructure can achieve high isolation ratio AT at arbitrary wavelength within a certain range by designing the parameters of the structure. These three nanodevices c… ▽ More A serial asymmetric transmission (AT) nanodevices based on the grating-film-grating (G-F-G) structure are proposed and studied. By showing the results of three different nanodevices as examples, it is proved that this kind of G-F-G nanostructure can achieve high isolation ratio AT at arbitrary wavelength within a certain range by designing the parameters of the structure. These three nanodevices can achieve high forward transmittivities of 0.69, 0.71, and 0.87 at the wavelengths of 714, 810, and 905 nm, respectively, and the isolation ratio between forward and backward transmittivities are all more than 10 dB. In addition, the effects of the incidence angle and lateral displacement of upper gratings on device performance were also investigated, revealing that optimal AT is achieved under normal incidence and zero displacement. The proposed G-F-G structure provides a solution for passive and easy to manufacture optical isolators with potential applications in optical communication and sensing systems. △ Less

Submitted 6 November, 2025; originally announced November 2025.

Comments: 16pages, 7 figures

Ultrafast Reconfigurable Topological Photonic Processing Accelerator

Authors: Wenfeng Zhou, Xin Wang, Xun Zhang, Yuqi Chen, Min Sun, Jingchi Li, Xiong Ni, Yahui Zhu, Qingqing Han, Jungan Wang, Chen Yang, Bin Li, Feng Qiu, Yikai Su, Yong Zhang

Abstract: The rise of artificial intelligence has triggered exponential growth in data volume, demanding rapid and efficient processing. High-speed, energy-efficient, and parallel-scalable computing hardware is thus increasingly critical. We demonstrate a wafer-scale non-volatile topological photonic computing chip using topological modulators. Leveraging the GHz-speed electro-optic response and nonvolatili… ▽ More The rise of artificial intelligence has triggered exponential growth in data volume, demanding rapid and efficient processing. High-speed, energy-efficient, and parallel-scalable computing hardware is thus increasingly critical. We demonstrate a wafer-scale non-volatile topological photonic computing chip using topological modulators. Leveraging the GHz-speed electro-optic response and nonvolatility of ferroelectric lead zirconate titanate (PZT) thin films via topological photonic confinement, Our chip enables thousand-fold faster reconfiguration, zero-static-power operation, and a computational density of 266 trillion operations per second per square millimeter . This density surpasses that of silicon photonic reconfigurable computing chips by two orders of magnitude and thin-film lithium niobate platforms by four orders of magnitude. A 16-channel wavelength-space multiplexed chip delivers 1.92 TOPS throughput with 95.64% digit-recognition accuracy and 94.5% precision for solving time-varying partial differential equations. Additionally, the chip supports functional reconfiguration for high bandwidth density optical I/O. This work establishes ferroelectric topological photonics for efficient high-speed photonic tensor processing. △ Less

Submitted 5 November, 2025; originally announced November 2025.

Longwave-transparent low-emissivity material

Authors: Yue Zhang, Longnan Li, Junyan Dai, Xiaowen Zhang, Qunyan Zhou, Naiqin Yi, Ruizhe Jian, Fei Zhu, Xiaopeng Li, Mengke Sun, Jiazheng Wu, Xinfeng Li, Xiangtong Kong, Ziai Liu, Yinwei Li, Qiang Cheng, Yiming Zhu, Tie Jun Cui, Wei Li

Abstract: Low emissivity (low-e) materials are crucial for conserving thermal energy in buildings, cold chain logistics and transportation by minimizing unwanted radiative heat loss or gain. However, their metallic nature intrinsically causes severe longwave attenuation, hindering their broad applications. Here, we introduce, for the first time, an all-dielectric longwave-transparent low-emissivity material… ▽ More Low emissivity (low-e) materials are crucial for conserving thermal energy in buildings, cold chain logistics and transportation by minimizing unwanted radiative heat loss or gain. However, their metallic nature intrinsically causes severe longwave attenuation, hindering their broad applications. Here, we introduce, for the first time, an all-dielectric longwave-transparent low-emissivity material (LLM) with ultra-broadband, high transmittance spanning 9 orders of magnitude, from terahertz to kilohertz frequencies. This meter-scale LLM not only achieves energy savings of up to 41.1% over commercial white paint and 10.2% over traditional low-e materials, but also unlocks various fundamentally new capabilities including high-speed wireless communication in energy-efficient buildings, wireless energy transfer with radiative thermal insulation, as well as non-invasive terahertz security screening and radio frequency identification in cold chain logistics. Our approach represents a new photonic solution towards carbon neutrality and smart city development, paving the way for a more sustainable and interconnected future. △ Less

Submitted 18 October, 2025; originally announced October 2025.

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.

Comparing Machine Learning and Physics-Based Nanoparticle Geometry Determinations Using Far-Field Spectral Properties

Authors: Mengqi Sun, Zixu Huang, Muammer Y. Yaman, Maxim Ziatdinov, Sergei V. Kalinin, David S. Ginger

Abstract: Anisotropic metal nanostructures exhibit polarization-dependent light scattering. This property has been widely exploited to determine geometries of subwavelength structures using far-field microscopy. Here, we explore the use of variational autoencoders (VAEs) to determine the geometries of gold nanorods (NRs) such as in-plane orientation and aspect ratio under linearly polarized dark-field illum… ▽ More Anisotropic metal nanostructures exhibit polarization-dependent light scattering. This property has been widely exploited to determine geometries of subwavelength structures using far-field microscopy. Here, we explore the use of variational autoencoders (VAEs) to determine the geometries of gold nanorods (NRs) such as in-plane orientation and aspect ratio under linearly polarized dark-field illumination in an optical microscope. We input polarized dark-field scattering spectra and electron microscopy images into a dual-branch multimodal VAE with a single shared latent space trained on paired spectra-image data, using a learnable linear adapter. We achieve prediction of Au NRs using only polarized dark-field scattering spectra input. We determine geometrical parameters of orientational angle and aspect ratio quantitatively via both dual-VAE and physics-based analysis. We show that orientational angle prediction by dual-VAE performs well with only a small (300 particle) training set, yielding a mean absolute error (MAE) of 14.4 and a concordance correlation coefficient (CCC) of 0.95. This performance is only marginally worse than the physics-based cos(2theta) fitting approach between the scattering intensity and the polarizing angle, which achieves MAE of 8.78 and CCC of 0.99. Aspect ratio determination is also similar for the dual-VAE and physics-based fitting comparison (MAE of 0.21 vs. 0.23 and CCC of 0.53 vs. 0.68). By learning a shared latent manifold linking spectra and morphology, the model can generate NR images with accurate orientation and aspect ratio with spectra-only input in the small-data regime (300 particles), suggesting a general recipe for inverse nano-optical problems requiring both structure and orientation information. △ Less

Submitted 9 September, 2025; originally announced September 2025.

Toward Efficient and Accurate EMRI Parameter Estimation: A Machine Learning-Enhanced MCMC Framework

Authors: Bo Liang, Chang Liu, Hanlin Song, Zhenwei Lyu, Minghui Du, Peng Xu, Ziren Luo, Sensen He, Haohao Gu, Tianyu Zhao, Manjia Liang, Yuxiang Xu, Li-e Qiang, Mingming Sun, Wei-Liang Qian

Abstract: The detection of gravitational waves from extreme-mass-ratio inspirals (EMRIs) in space-based antennas like Taiji and Laser Interferometer Space Antenna promises deep insights into strong-field gravity and black hole physics. However, the complex, highly degenerate, and nonconvex likelihood landscapes characteristic of EMRI parameter spaces pose severe challenges for conventional Markov chain Mont… ▽ More The detection of gravitational waves from extreme-mass-ratio inspirals (EMRIs) in space-based antennas like Taiji and Laser Interferometer Space Antenna promises deep insights into strong-field gravity and black hole physics. However, the complex, highly degenerate, and nonconvex likelihood landscapes characteristic of EMRI parameter spaces pose severe challenges for conventional Markov chain Monte Carlo (MCMC) methods. Under realistic instrumental noise and broad priors, these methods demand impractical computational costs but are prone to becoming trapped in local maxima, leading to biased and unreliable parameter estimates. To address these challenges, we introduce flow-matching MCMC (FM-MCMC), a novel Bayesian framework that integrates continuous normalizing flows (CNFs) with parallel tempering MCMC (PTMCMC). By generating high-likelihood regions via CNFs and refining them through PTMCMC, FM-MCMC enables robust exploration of the nontrivial parameter spaces, achieves orders-of-magnitude improvement in computational efficiency, and, more importantly, ensures statistically unbiased inference. By enabling real-time, unbiased parameter inference, FM-MCMC could unlock the full scientific potential of EMRI observations, and would serve as a scalable pipeline for precision gravitational-wave astronomy. △ Less

Submitted 18 August, 2026; v1 submitted 1 August, 2025; originally announced August 2025.

Journal ref: Research 9, 1055 (2026)

General-Purpose Models for the Chemical Sciences: LLMs and Beyond

Authors: Nawaf Alampara, Anagha Aneesh, Martiño Ríos-García, Adrian Mirza, Mara Schilling-Wilhelmi, Ali Asghar Aghajani, Meiling Sun, Gordan Prastalo, Kevin Maik Jablonka

Abstract: Data-driven techniques have a large potential to transform and accelerate the chemical sciences. However, chemical sciences also pose the unique challenge of very diverse, small, fuzzy datasets that are difficult to leverage in conventional machine learning approaches. A new class of models, which can be summarized under the term general-purpose models (GPMs) such as large language models, has sho… ▽ More Data-driven techniques have a large potential to transform and accelerate the chemical sciences. However, chemical sciences also pose the unique challenge of very diverse, small, fuzzy datasets that are difficult to leverage in conventional machine learning approaches. A new class of models, which can be summarized under the term general-purpose models (GPMs) such as large language models, has shown the ability to solve tasks they have not been directly trained on, and to flexibly operate with low amounts of data in different formats. In this review, we discuss fundamental building principles of GPMs and review recent and emerging applications of those models in the chemical sciences across the entire scientific process. While many of these applications are still in the prototype phase, we expect that the increasing interest in GPMs will make many of them mature in the coming years. △ Less

Submitted 24 November, 2025; v1 submitted 10 July, 2025; originally announced July 2025.

Electrochemistry-Enhanced Dynamic Paths Sampling Unveiling Nuclear Quantum Effects in Electrocatalysis

Authors: Li Fu, Yifan Li, Menglin Sun, Xiaolong Yang, Bin Jin, Shenzhen Xu

Abstract: Proton-coupled electron transfers (PCET) are elementary steps in electrocatalysis. However, accurate calculations of PCET rates remain challenging, especially considering nuclear quantum effects (NQEs) under a constant potential condition. Statistical sampling of reaction paths is an ideal approach for rate calculations, however, is always limited by the rare-event issue. Here we develop an electr… ▽ More Proton-coupled electron transfers (PCET) are elementary steps in electrocatalysis. However, accurate calculations of PCET rates remain challenging, especially considering nuclear quantum effects (NQEs) under a constant potential condition. Statistical sampling of reaction paths is an ideal approach for rate calculations, however, is always limited by the rare-event issue. Here we develop an electrochemistry-driven quantum dynamics approach enabling realistic enhanced paths sampling under constant potentials without a priori defined reaction coordinates. We apply the method in modeling the Volmer step of the hydrogen evolution reaction, and demonstrate that the NQEs exhibit more than one order of magnitude impact on the computed rate constant, indicating an essential role of NQEs in electrochemistry. △ Less

Submitted 20 June, 2025; originally announced June 2025.

MuGrid-v2: A novel scintillator detector for multidisciplinary applications

Authors: Tao Yu, Yunsong Ning, Yi Yuan, Shihan Zhao, Songran Qi, Minchen Sun, Yuye Li, Zhirui Liu, Aiyu Bai, Hesheng Liu, Yibo Lin, Geng Tuo, Ting On Chan, Zhou Zhou, Yu Chen, Yu Chen, Jian Tang

Abstract: Muography, traditionally recognized as a potent instrument for imaging the internal structure of gigantic objects, has initialized various interdisciplinary applications. As the financial and labor costs of muography detector development hinder their massive applications, we develop a novel muon detector called MuGrid by coupling a monolithic plastic scintillator with the light guide array in orde… ▽ More Muography, traditionally recognized as a potent instrument for imaging the internal structure of gigantic objects, has initialized various interdisciplinary applications. As the financial and labor costs of muography detector development hinder their massive applications, we develop a novel muon detector called MuGrid by coupling a monolithic plastic scintillator with the light guide array in order to achieve competitive spatial resolution while substantially reducing production costs. For a prototype detector in 30 cm $\times$ 30 cm, the intrinsic spatial resolution has been optimized toward a millimeter scale. An outdoor field muography experiment was conducted to monitor two buildings for validation purposes. The test successfully resolved the geometric influence of architectural features based on the attenuation of muon flux in a good agreement between experimental results and the simulation prediction. △ Less

Submitted 26 May, 2025; originally announced May 2025.

Journal ref: J. Appl. Phys. 138, 024501 (2025)

Single-shot 3D characterization the spatiotemporal optical vortex via a spatiotemporal wavefront sensor (STWFS)

Authors: Xiuyu Yao, Ping Zhu, Youjian Yi, Zezhao Gong, Dongjun Zhang, Ailin Guo, Fucai Ding, Xiao Liang, Xuejie Zhang, Meizhi Sun, Qiang Zhang, Miaoyan Tong, Lijie Cui, Hailun Zen, Xinglong Xie, Jianqiang Zhu

Abstract: The advent of spatiotemporal wave packets (STWPs), represented by spatiotemporal optical vortices (STOVs), has paved the way for the exploration in optics and photonics. To date, despite considerable efforts, a comprehensive and efficient practical means to characterizing wave packets with such complex structures is still lacking. In this study, we introduced a new method designed to achieve high-… ▽ More The advent of spatiotemporal wave packets (STWPs), represented by spatiotemporal optical vortices (STOVs), has paved the way for the exploration in optics and photonics. To date, despite considerable efforts, a comprehensive and efficient practical means to characterizing wave packets with such complex structures is still lacking. In this study, we introduced a new method designed to achieve high-precision and high-throughput spatiotemporal wave packet measurements using a user-friendly set up. This method is based on a quadriwave lateral shearing interferometric wavefront sensor that utilizes wavelength division multiplexing, termed the "spatiotemporal wavefront sensor (STWFS)." Using this method, we have fabricated a compact prototype with 295 * 295 spatial pixels * 36 wavelength channels of 0.5 nm spectral resolution in a single frame. This STWFS enabled, for the first time, single-shot self-referenced spatiotemporal three-dimensional (3D) optical field characterizations of STOV pulses with transverse orbital angular momenta L of 1 and 2, and obtained the dynamic visualization of the focused propagation of STOV pulses. Furthermore, the STWFS provides a 1.87 nm (0.95%) root mean square (RMS) absolute accuracy for spatiotemporal phase reconstruction. This achievement represents the highest performance compared with other three-dimensional spatiotemporal metrology methods. As a spatiotemporal optical field characterization method, the STWFS offers ultrafast 3D diagnostics, contributing to spatiotemporal photonics and broader applications across different fields, such as light-matter interactions and optical communications. △ Less

Submitted 22 May, 2025; originally announced May 2025.

Journal ref: Optica 12, 1884-1894 (2025)

Reinforcement Learning (RL) Meets Urban Climate Modeling: Investigating the Efficacy and Impacts of RL-Based HVAC Control

Authors: Junjie Yu, John S. Schreck, David John Gagne, Keith W. Oleson, Jie Li, Yongtu Liang, Qi Liao, Mingfei Sun, David O. Topping, Zhonghua Zheng

Abstract: Reinforcement learning (RL)-based heating, ventilation, and air conditioning (HVAC) control has emerged as a promising technology for reducing building energy consumption while maintaining indoor thermal comfort. However, the efficacy of such strategies is influenced by the background climate and their implementation may potentially alter both the indoor climate and local urban climate. This study… ▽ More Reinforcement learning (RL)-based heating, ventilation, and air conditioning (HVAC) control has emerged as a promising technology for reducing building energy consumption while maintaining indoor thermal comfort. However, the efficacy of such strategies is influenced by the background climate and their implementation may potentially alter both the indoor climate and local urban climate. This study proposes an integrated framework combining RL with an urban climate model that incorporates a building energy model, aiming to evaluate the efficacy of RL-based HVAC control across different background climates, impacts of RL strategies on indoor climate and local urban climate, and the transferability of RL strategies across cities. Our findings reveal that the reward (defined as a weighted combination of energy consumption and thermal comfort) and the impacts of RL strategies on indoor climate and local urban climate exhibit marked variability across cities with different background climates. The sensitivity of reward weights and the transferability of RL strategies are also strongly influenced by the background climate. Cities in hot climates tend to achieve higher rewards across most reward weight configurations that balance energy consumption and thermal comfort, and those cities with more varying atmospheric temperatures demonstrate greater RL strategy transferability. These findings underscore the importance of thoroughly evaluating RL-based HVAC control strategies in diverse climatic contexts. This study also provides a new insight that city-to-city learning will potentially aid the deployment of RL-based HVAC control. △ Less

Submitted 11 May, 2025; originally announced May 2025.

Development of portable cosmic-ray muon detector array for muography

Authors: Yunsong Ning, Yi Yuan, Tao Yu, Hongyu Chen, Chengyan Xie, Hui Jiang, Hesheng Liu, Guihao Lu, Mingchen Sun, Yu Chen, Jian Tang

Abstract: As the multidisciplinary applications of cosmic-ray muons expand to large-scale and wide-area scenarios, the construction of cosmic-ray muon detector arrays has become a key solution to overcome the hardware limitations of individual detector. For muography, the array-based detector design enables fast-scanning of large target objects, allowing for rapid identification of density variation regions… ▽ More As the multidisciplinary applications of cosmic-ray muons expand to large-scale and wide-area scenarios, the construction of cosmic-ray muon detector arrays has become a key solution to overcome the hardware limitations of individual detector. For muography, the array-based detector design enables fast-scanning of large target objects, allowing for rapid identification of density variation regions, which can improve the efficiency of tomography. This paper integrates scintillator detector technology with Internet of things (IoT) technology, proposing a novel array networking model for nationwide deployment. The model enables long-distance data collection and distribution, laying the foundation for future multidisciplinary applications such as muography and other fields. △ Less

Submitted 1 April, 2025; v1 submitted 24 March, 2025; originally announced March 2025.

Comments: 7 pages, 8 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

Scalable freeform optimization of wide-aperture 3D metalenses by zoned discrete axisymmetry

Authors: Mengdi Sun, Ata Shakeri, Arvin Keshvari, Dimitrios Giannakopoulos, Qing Wang, Wei Ting Chen, Steven G. Johnson, Zin Lin

Abstract: We introduce a novel framework for design and optimization of 3D freeform metalenses that attains nearly linear scaling of computational cost with diameter, by breaking the lens into a sequence of radial "zones" with $n$-fold discrete axisymmetry, where $n$ increases with radius. This allows vastly more design freedom than imposing continuous axisymmetry, while avoiding the compromises of the loca… ▽ More We introduce a novel framework for design and optimization of 3D freeform metalenses that attains nearly linear scaling of computational cost with diameter, by breaking the lens into a sequence of radial "zones" with $n$-fold discrete axisymmetry, where $n$ increases with radius. This allows vastly more design freedom than imposing continuous axisymmetry, while avoiding the compromises of the locally periodic approximation (LPA) or scalar diffraction theory. Using a GPU-accelerated finite-difference time-domain (FDTD) solver in cylindrical coordinates, we perform full-wave simulation and topology optimization within each supra-wavelength zone. We validate our approach by designing millimeter and centimeter-scale, poly-achromatic, 3D freeform metalenses which outperform the state of the art. By demonstrating the scalability and resulting optical performance enabled by our "zoned discrete axisymmetry" (ZDA) and supra-wavelength domain decomposition, we highlight the potential of our framework to advance large-scale meta-optics and next-generation photonic technologies. △ Less

Submitted 21 May, 2025; v1 submitted 14 January, 2025; originally announced January 2025.

Comments: 15 pages, 8 figures

Evaluating authorship disambiguation quality through anomaly analysis on researchers' career transition

Authors: Huaxia Zhou, Mengyi Sun

Abstract: Authorship disambiguation is crucial for advancing studies in science of science. However, assessing the quality of authorship disambiguation in large-scale databases remains challenging since it is difficult to manually curate a gold-standard dataset that contains disambiguated authors. Through estimating the timing of when 5.8 million biomedical researchers became independent Principal Investiga… ▽ More Authorship disambiguation is crucial for advancing studies in science of science. However, assessing the quality of authorship disambiguation in large-scale databases remains challenging since it is difficult to manually curate a gold-standard dataset that contains disambiguated authors. Through estimating the timing of when 5.8 million biomedical researchers became independent Principal Investigators (PIs) with authorship metadata extracted from the OpenAlex -- the largest open-source bibliometric database -- we unexpectedly discovered an anomaly: over 60% of researchers appeared as the last authors in their first career year. We hypothesized that this improbable finding results from poor name disambiguation, suggesting that such an anomaly may serve as an indicator of low-quality authorship disambiguation. Our findings indicated that authors who lack affiliation information, which makes it more difficult to disambiguate, were far more likely to exhibit this anomaly compared to those who included their affiliation information. In contrast, authors with Open Researcher and Contributor ID (ORCID) -- expected to have higher quality disambiguation -- showed significantly lower anomaly rates. We further applied this approach to examine the authorship disambiguation quality by gender over time, and we found that the quality of disambiguation for female authors was lower than that for male authors before 2010, suggesting that gender disparity findings based on pre-2010 data may require careful reexamination. Our results provide a framework for systematically evaluating authorship disambiguation quality in various contexts, facilitating future improvements in efforts to authorship disambiguation. △ Less

Submitted 24 December, 2024; originally announced December 2024.

Proposal for Superconducting Photodiode

Authors: A. V. Parafilo, Meng Sun, K. Sonowal, V. M. Kovalev, I. G. Savenko

Abstract: We propose a concept of a superconducting photodiode - a device that transforms the energy and `spin' of an external electromagnetic field into the rectified steady-state supercurrent and develop a microscopic theory describing its properties. For this, we consider a two-dimensional thin film cooled down below the temperature of superconducting transition with the injected dc supercurrent and expo… ▽ More We propose a concept of a superconducting photodiode - a device that transforms the energy and `spin' of an external electromagnetic field into the rectified steady-state supercurrent and develop a microscopic theory describing its properties. For this, we consider a two-dimensional thin film cooled down below the temperature of superconducting transition with the injected dc supercurrent and exposed to an external electromagnetic field with a frequency smaller than the superconducting gap. As a result, we predict the emergence of a photoexcited quasiparticle current, and, as a consequence, oppositely oriented stationary flow of Cooper pairs. The strength and direction of this photoinduced supercurrent depend on (i) such material properties as the effective impurity scattering time and the nonequilibrium quasiparticles' energy relaxation time and (ii) such electromagnetic field properties as its frequency and polarization. △ Less

Submitted 4 December, 2024; originally announced December 2024.

Comments: Published in 2D Materials (Letters)

Journal ref: https://iopscience.iop.org/article/10.1088/2053-1583/ad9596

Two-Stage Pretraining for Molecular Property Prediction in the Wild

Authors: Kevin Tirta Wijaya, Minghao Guo, Michael Sun, Hans-Peter Seidel, Wojciech Matusik, Vahid Babaei

Abstract: Molecular deep learning models have achieved remarkable success in property prediction, but they often require large amounts of labeled data. The challenge is that, in real-world applications, labels are extremely scarce, as obtaining them through laboratory experimentation is both expensive and time-consuming. In this work, we introduce MoleVers, a versatile pretrained molecular model designed fo… ▽ More Molecular deep learning models have achieved remarkable success in property prediction, but they often require large amounts of labeled data. The challenge is that, in real-world applications, labels are extremely scarce, as obtaining them through laboratory experimentation is both expensive and time-consuming. In this work, we introduce MoleVers, a versatile pretrained molecular model designed for various types of molecular property prediction in the wild, i.e., where experimentally-validated labels are scarce. MoleVers employs a two-stage pretraining strategy. In the first stage, it learns molecular representations from unlabeled data through masked atom prediction and extreme denoising, a novel task enabled by our newly introduced branching encoder architecture and dynamic noise scale sampling. In the second stage, the model refines these representations through predictions of auxiliary properties derived from computational methods, such as the density functional theory or large language models. Evaluation on 22 small, experimentally-validated datasets demonstrates that MoleVers achieves state-of-the-art performance, highlighting the effectiveness of its two-stage framework in producing generalizable molecular representations for diverse downstream properties. △ Less

Submitted 18 July, 2025; v1 submitted 5 November, 2024; originally announced November 2024.

Conceptual Design of the Muonium-to-Antimuonium Conversion Experiment (MACE)

Authors: Ai-Yu Bai, Hanjie Cai, Chang-Lin Chen, Siyuan Chen, Xurong Chen, Yu Chen, Weibin Cheng, Ling-Yun Dai, Rui-Rui Fan, Li Gong, Zihao Guo, Yuan He, Zhilong Hou, Yinyuan Huang, Huan Jia, Hao Jiang, Han-Tao Jing, Xiaoshen Kang, Hai-Bo Li, Jincheng Li, Yang Li, Daming Liu, Shulin Liu, Guihao Lu, Han Miao , et al. (27 additional authors not shown)

Abstract: The spontaneous conversion of muonium to antimuonium is one of the interesting charged lepton flavor violation phenomena offering a sensitive probe of potential new physics and serving as a tool to constrain the parameter space beyond the Standard Model. The Muonium-to-Antimuonium Conversion Experiment (MACE) is designed to utilize a high-intensity muon beam, a Michel electron magnetic spectromete… ▽ More The spontaneous conversion of muonium to antimuonium is one of the interesting charged lepton flavor violation phenomena offering a sensitive probe of potential new physics and serving as a tool to constrain the parameter space beyond the Standard Model. The Muonium-to-Antimuonium Conversion Experiment (MACE) is designed to utilize a high-intensity muon beam, a Michel electron magnetic spectrometer, a positron transport system, and a positron detection system, to either discover or constrain this rare process with a conversion probability of $\mathcal{O}(10^{-13})$. This article presents an overview of the theoretical framework as well as a detailed description of the experimental design for the search for muonium-to-antimuonium conversion. △ Less

Submitted 21 November, 2025; v1 submitted 24 October, 2024; originally announced October 2024.

Comments: 45 pages, 51 figures, 14 tables. Accepted by Nuclear Science and Techniques

Journal ref: Nuclear Science and Techniques, volume 37, article number 57, (2026)

Simplified radar architecture based on information metasurface

Authors: Si Ran Wang, Zhan Ye Chen, Shao Nan Chen, Jun Yan Dai, Jun Wei Zhang, Zhen Jie Qi, Li Jie Wu, Meng Ke Sun, Qun Yan Zhou, Hui Dong Li, Zhang Jie Luo, Qiang Cheng, Tie Jun Cui

Abstract: Modern radar typically employs a chain architecture that consists of radio-frequency (RF) and intermediate frequency (IF) units, baseband digital signal processor, and information display. However, this architecture often results in high costs, significant hardware demands, and integration challenges. Here we propose a simplified radar architecture based on space-time-coding (STC) information meta… ▽ More Modern radar typically employs a chain architecture that consists of radio-frequency (RF) and intermediate frequency (IF) units, baseband digital signal processor, and information display. However, this architecture often results in high costs, significant hardware demands, and integration challenges. Here we propose a simplified radar architecture based on space-time-coding (STC) information metasurfaces. With their powerful capabilities to generate multiple harmonic frequencies and customize their phases, the STC metasurfaces play a key role in chirp signal generation, transmission, and echo reception. Remarkably, the receiving STC metasurface can implement dechirp processing directly on the RF level and realize the digital information outputs, which are beneficial to lower the hardware requirement at the receiving end while potentially shortening the time needed for conventional digital processing. As a proof of concept, the proposed metasurface radar is tested in a series of experiments for target detection and range/speed measurement, yielding results comparable to those obtained by conventional methods. This study provides valuable inspiration for a new radar system paradigm to combine the RF front ends and signal processors on the information metasurface platform that offers essential functionalities while significantly reducing the system complexity and cost. △ Less

Submitted 9 October, 2024; originally announced October 2024.

Comments: 25 pages, 10 figures

Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning

Authors: Gang Liu, Michael Sun, Wojciech Matusik, Meng Jiang, Jie Chen

Abstract: While large language models (LLMs) have integrated images, adapting them to graphs remains challenging, limiting their applications in materials and drug design. This difficulty stems from the need for coherent autoregressive generation across texts and graphs. To address this, we introduce Llamole, the first multimodal LLM capable of interleaved text and graph generation, enabling molecular inver… ▽ More While large language models (LLMs) have integrated images, adapting them to graphs remains challenging, limiting their applications in materials and drug design. This difficulty stems from the need for coherent autoregressive generation across texts and graphs. To address this, we introduce Llamole, the first multimodal LLM capable of interleaved text and graph generation, enabling molecular inverse design with retrosynthetic planning. Llamole integrates a base LLM with the Graph Diffusion Transformer and Graph Neural Networks for multi-conditional molecular generation and reaction inference within texts, while the LLM, with enhanced molecular understanding, flexibly controls activation among the different graph modules. Additionally, Llamole integrates A* search with LLM-based cost functions for efficient retrosynthetic planning. We create benchmarking datasets and conduct extensive experiments to evaluate Llamole against in-context learning and supervised fine-tuning. Llamole significantly outperforms 14 adapted LLMs across 12 metrics for controllable molecular design and retrosynthetic planning. △ Less

Submitted 5 October, 2024; originally announced October 2024.

Comments: 27 pages, 11 figures, 4 tables

Procedural Synthesis of Synthesizable Molecules

Authors: Michael Sun, Alston Lo, Minghao Guo, Jie Chen, Connor Coley, Wojciech Matusik

Abstract: Designing synthetically accessible molecules and recommending analogs to unsynthesizable molecules are important problems for accelerating molecular discovery. We reconceptualize both problems using ideas from program synthesis. Drawing inspiration from syntax-guided synthesis approaches, we decouple the syntactic skeleton from the semantics of a synthetic tree to create a bilevel framework for re… ▽ More Designing synthetically accessible molecules and recommending analogs to unsynthesizable molecules are important problems for accelerating molecular discovery. We reconceptualize both problems using ideas from program synthesis. Drawing inspiration from syntax-guided synthesis approaches, we decouple the syntactic skeleton from the semantics of a synthetic tree to create a bilevel framework for reasoning about the combinatorial space of synthesis pathways. Given a molecule we aim to generate analogs for, we iteratively refine its skeletal characteristics via Markov Chain Monte Carlo simulations over the space of syntactic skeletons. Given a black-box oracle to optimize, we formulate a joint design space over syntactic templates and molecular descriptors and introduce evolutionary algorithms that optimize both syntactic and semantic dimensions synergistically. Our key insight is that once the syntactic skeleton is set, we can amortize over the search complexity of deriving the program's semantics by training policies to fully utilize the fixed horizon Markov Decision Process imposed by the syntactic template. We demonstrate performance advantages of our bilevel framework for synthesizable analog generation and synthesizable molecule design. Notably, our approach offers the user explicit control over the resources required to perform synthesis and biases the design space towards simpler solutions, making it particularly promising for autonomous synthesis platforms. Code is at https://github.com/shiningsunnyday/SynthesisNet. △ Less

Submitted 28 February, 2025; v1 submitted 24 August, 2024; originally announced September 2024.

Comments: ICLR 2025

Coupling Between Local and Global Oscillations in Palladium-Catalysed Methane Oxidation

Authors: Yuxiong Hu, Jianyu Hu, Mengzhao Sun, Aowen Li, Shucheng Shi, P. J. Hu, Wu Zhou, Marc-Georg Willinger, Dan Zhou, Zhi Liu, Xi Liu, Wei-Xue Li, Zhu-Jun Wang

Abstract: The interplay between order and disorder is crucial across various fields, especially in understanding oscillatory phenomena. Periodic oscillations are frequently observed in heterogeneous catalysis, yet their underlying mechanisms need deeper exploration. Here, we investigate how periodic oscillations arise during methane oxidation catalysed by palladium nanoparticles (Pd NPs), utilizing a suite… ▽ More The interplay between order and disorder is crucial across various fields, especially in understanding oscillatory phenomena. Periodic oscillations are frequently observed in heterogeneous catalysis, yet their underlying mechanisms need deeper exploration. Here, we investigate how periodic oscillations arise during methane oxidation catalysed by palladium nanoparticles (Pd NPs), utilizing a suite of complementary operando techniques across various spatial scales. We found that reaction intensity and collective dynamic modes can be tuned by the reactant gas-flow rate. At lower gas-flow rates, we observed periodic facet reconstruction of Pd NPs correlated with repeated bubbling behaviour at the Pd/PdO interface, without evident global oscillatory responses. Conversely, at higher gas-flow rates, Pd NPs undergo chaotic transformations between metallic and oxidized states, resulting in overall oscillation. Integrating our observations at different gas-flow rates, we attributed the emergence of global oscillation to thermal coupling regulated by gas flow and connected local and global dynamics through a weak synchronization mechanism. This work demonstrates the correlations between open surfaces and interfaces, chaos and regularity, and dissipative processes and coupling behaviour. Our findings offer critical insights into the complexity behind catalytic oscillations and provide guidance for modulating oscillatory behaviours in catalytic processes, with significant implications for both science and industry. △ Less

Submitted 14 August, 2024; originally announced August 2024.

Deep learning density functional theory Hamiltonian in real space

Authors: Zilong Yuan, Zechen Tang, Honggeng Tao, Xiaoxun Gong, Zezhou Chen, Yuxiang Wang, He Li, Yang Li, Zhiming Xu, Minghui Sun, Boheng Zhao, Chong Wang, Wenhui Duan, Yong Xu

Abstract: Deep learning electronic structures from ab initio calculations holds great potential to revolutionize computational materials studies. While existing methods proved success in deep-learning density functional theory (DFT) Hamiltonian matrices, they are limited to DFT programs using localized atomic-like bases and heavily depend on the form of the bases. Here, we propose the DeepH-r method for dee… ▽ More Deep learning electronic structures from ab initio calculations holds great potential to revolutionize computational materials studies. While existing methods proved success in deep-learning density functional theory (DFT) Hamiltonian matrices, they are limited to DFT programs using localized atomic-like bases and heavily depend on the form of the bases. Here, we propose the DeepH-r method for deep-learning DFT Hamiltonians in real space, facilitating the prediction of DFT Hamiltonian in a basis-independent manner. An equivariant neural network architecture for modeling the real-space DFT potential is developed, targeting a more fundamental quantity in DFT. The real-space potential exhibits simplified principles of equivariance and enhanced nearsightedness, further boosting the performance of deep learning. When applied to evaluate the Hamiltonian matrix, this method significantly improved in accuracy, as exemplified in multiple case studies. Given the abundance of data in the real-space potential, this work may pave a novel pathway for establishing a ``large materials model" with increased accuracy. △ Less

Submitted 19 July, 2024; originally announced July 2024.