Showing 1–50 of 109 results for author: Zheng, W

Quantum Imaging via Kurtosis-Difference Weighted Covariance on 2D Camera

Authors: Zhe He, Yanli Shi, Hui Wu, Qun Cao, Weidong Zheng, Zheng Cui

Abstract: Camera-based quantum imaging detects spatially correlated photon pairs from spontaneous parametric down-conversion (SPDC). Conventional covariance methods typically require tens of thousands of frames to extract weak correlations from noise. While thick crystals can increase photon flux, they generate photon pairs from multiple emission positions within the crystal, producing multiple correlation… ▽ More Camera-based quantum imaging detects spatially correlated photon pairs from spontaneous parametric down-conversion (SPDC). Conventional covariance methods typically require tens of thousands of frames to extract weak correlations from noise. While thick crystals can increase photon flux, they generate photon pairs from multiple emission positions within the crystal, producing multiple correlation centers with complex pairing geometries. In addition, conventional covariance methods assume a single pre-selected correlation center and cannot fully exploit these distributed correlations. We demonstrate that kurtosis difference, a fourth-order statistic measuring tail similarity, effectively discriminates correlated pixel pairs even when correlation coefficients remain low. Weighting covariance by an exponential function of absolute kurtosis difference can select symmetric pixels while preserving true coincidences. This kurtosis weighting automatically identifies correlated pairs within a broad search region and accommodates multiple pairing geometries without requiring precise correlation center calibration. At 5000 frames, our method yields a contrast-to-noise ratio (CNR) exceeding 7, whereas standard covariance remains below 2. Compared with standard covariance, the method reduces the acquisition time by 40-fold and could enable practical quantum imaging in sparse correlated-photon regimes. △ Less

Submitted 29 June, 2026; originally announced June 2026.

Comments: 27 pages, 12 figures

HeteroViT: A Versatile Single-Layer Vision Transformer Concept, Co-Designed for Distributed Real-Time Data Reduction on Scientific Detectors

Authors: Abhilasha Dave, Weijian Zheng, Antonino Miceli, Dionisio Doering, Ryan Herbst, Angelo Dragone

Abstract: Next-generation X-ray detectors generate data faster than any system can affordably store or process. LCLS-II, the upgraded Linac Coherent Light Source at SLAC, produces data on the order of terabytes per second, with raw-data transfer and storage projected to be prohibitively costly, even though much of the data is not scientifically useful. This concept paper focuses on two major points. The fir… ▽ More Next-generation X-ray detectors generate data faster than any system can affordably store or process. LCLS-II, the upgraded Linac Coherent Light Source at SLAC, produces data on the order of terabytes per second, with raw-data transfer and storage projected to be prohibitively costly, even though much of the data is not scientifically useful. This concept paper focuses on two major points. The first is versatility: a deliberately tiny, single-layer Vision Transformer (ViT) is enough to serve distinct scientific quick-evaluation tasks. We demonstrate this on two very different problems: (a) a supervised hit/miss/maybe classification on the CSPAD dataset, made to resemble ePixUHR-like detector frames, and (b) a self-supervised latent space for rare-event detection in X-ray diffraction spanning two learning paradigms, two output types, and two detector modalities, with one small backbone. The second is hardware co-design: because the ViT's blocks are structurally uniform, the model maps cleanly onto the heterogeneous hardware already present in the LCLS detector pipeline (ASIC -> FPGA -> GPU) under a simple rule one ASIC is one token so the data is reduced progressively at each stage and a keep/discard decision is produced in real time at the edge. The two claims reinforce each other: versatility is precisely what justifies freezing the front-end in silicon, since a reusable front-end is only worth committing to hardware if it serves many tasks. We are explicit that this is a concept supported by early software analysis, not a hardware demonstration. The natural and primary next phase is the hardware implementation of this distributed pipeline. The decisive evidence still owed an end-to-end latency budget, ASIC feasibility of the in-sensor embedding, and the false-negative behavior that matters for a data veto defines that program. HeteroViT is our first step toward it. △ Less

Submitted 22 June, 2026; originally announced June 2026.

Comments: N/A

Experiment-free disruption prediction for new devices enabled by synthetic diagnostic data augmentation

Authors: Zhiqiang Liu, Fengming Xue, Shiwei Xue, Bihao Guo, Dalong Chen, Wei Zheng, Ping Zhu

Abstract: Deep learning based approaches have shown great promise in cross-device disruption prediction for tokamaks, however, the robustness of these models heavily relies on massive amounts of training data. For the upcoming ITER, to ensure the safety of the first plasma and subsequent operations, experimental data should be entirely unavailable initially, and disruptive discharges should be strictly avoi… ▽ More Deep learning based approaches have shown great promise in cross-device disruption prediction for tokamaks, however, the robustness of these models heavily relies on massive amounts of training data. For the upcoming ITER, to ensure the safety of the first plasma and subsequent operations, experimental data should be entirely unavailable initially, and disruptive discharges should be strictly avoided thereafter. This extreme data scarcity inherently conflicts with the data-intensive nature of deep learning algorithms. To address this challenge, we utilize synthetic diagnostic signals from the target device to supplement the experimental data from existing devices for the zero-shot disruption prediction on a new device. The detailed implementation pipeline of this scheme is presented. For experimental validation, a predictive model trained on data from the EAST tokamak is deployed for a zero-shot cross-device experiment on the J-TEXT tokamak. A synthetic diagnostic framework, configured with the diagnostic parameters of the target device, is developed to process NIMROD magnetohydrodynamic (MHD) simulation data based on the target device's magnetic configuration, thereby achieving effective data augmentation. Ultimately, the results demonstrate that by integrating the target device's synthetic diagnostic data with Fourier Domain Adaptation, the zero-shot accurate early warning rate of the model on 1,596 J-TEXT discharges is improved from 50% to 57%, while exhibiting enhanced predictive robustness. △ Less

Submitted 7 June, 2026; originally announced June 2026.

Comments: 24 pages, 6 figures

Tunable Polariton Canalization in Natural van der Waals Oxide

Authors: H. Shiravi, W. Zheng, D. A. Rhodes, L. Balicas, H. D. Zhou, G. X. Ni

Abstract: Hyperbolic phonon polaritons (HPPs) are coupled oscillations of anisotropic lattice vibrations and electromagnetic fields that confine the latter to the nanoscale, enabling novel nano-polaritonic devices. While HPPs have been identified in multiple layered materials, achieving advanced control and manipulation - particularly polariton canalization for unidirectional energy flow - often necessitate… ▽ More Hyperbolic phonon polaritons (HPPs) are coupled oscillations of anisotropic lattice vibrations and electromagnetic fields that confine the latter to the nanoscale, enabling novel nano-polaritonic devices. While HPPs have been identified in multiple layered materials, achieving advanced control and manipulation - particularly polariton canalization for unidirectional energy flow - often necessitates complex device fabrications or crystal modifications. Here we visualize and elucidate the properties of in-plane hyperbolicity in alpha-V2O5, a layered compound with a highly anisotropic permittivity tensor. We show unidirectional Poynting-vector propagation of polaritons in alpha-V2O5 without additional treatments. Combined with theoretical modeling, our infrared nano-imaging studies unveil a novel form of polariton canalization, with its dispersion contour continuously tunable by the incident light frequency. Additionally, we provide a theoretically calculated permittivity phase diagram for tailoring polaritonic wavefronts. These findings suggest that the metal-oxide alpha-V2O5 holds great promise for on-demand light canalization and control at the nanoscale. △ Less

Submitted 6 July, 2026; v1 submitted 13 April, 2026; originally announced April 2026.

Comments: The authors request withdrawal of this manuscript because one co-author does not agree with its submission in its current form. The manuscript does not reflect the authorized consensus of all contributors, and we therefore request its withdrawal pending resolution of the authorship approval

Kramers-Kronig causality in integrated photonics: The spectral tension between ultraviolet transition and mid-infrared absorption

Authors: Yue Hu, Zhenyuan Shang, Chenxi Zhang, Yuanjie Ning, Weiqin Zheng, Dengke Chen, Sanli Huang, Baoqi Shi, Zeying Zhong, Hao Tan, Wei Sun, Yi-Han Luo, Xinmao Yin, Zhi-Chuan Niu, Junqiu Liu

Abstract: Dispersion engineering via geometric confinement is essential to integrated photonics, enabling phenomena such as soliton microcombs, supercontinua, parametric oscillators, and entangled photons. However, prevailing methodologies rely on semi-empirical Sellmeier models that assume idealized material purity, neglecting the pronounced dispersion shifts induced by residual impurities like hydrogen-re… ▽ More Dispersion engineering via geometric confinement is essential to integrated photonics, enabling phenomena such as soliton microcombs, supercontinua, parametric oscillators, and entangled photons. However, prevailing methodologies rely on semi-empirical Sellmeier models that assume idealized material purity, neglecting the pronounced dispersion shifts induced by residual impurities like hydrogen-related bonds. Here, we demonstrate that these residual bonds fundamentally alter the dispersion landscape spanning from the ultraviolet (UV) to the mid-infrared (MIR) spectra. Specifically, they introduce MIR vibrational absorption while simultaneously modifying UV electronic transition, shifting the bandgap and UV pole. We show that the spectral tension between these UV and MIR modifications dictates the group velocity dispersion from the visible to the near-infrared (NIR) via the Kramers-Kronig causality. We experimentally validate this phenomenon through systematic characterization of broadband loss and dispersion in ultralow-loss silicon nitride photonic integrated circuits. By rigorously incorporating these effects, we bridge the gap between empirical fitting and predictive physical modelling. Our study resolves long-standing discrepancies in dispersion engineering, providing precision control essential for next-generation integrated photonics. △ Less

Submitted 31 March, 2026; v1 submitted 30 March, 2026; originally announced March 2026.

Comments: 11 pages, 5 figures

A validated lumped-element model for bioinspired acoustic flow sensing toward the performance limit

Authors: Wei Sun, Wanyin Zheng, Xiangyu Wei, David A. Czaplewski, Ronald N. Miles, Jian Zhou

Abstract: Flow sensing is fundamental to both biological survival and technological innovation. Inspired by biological mechanoreceptors, artificial flow sensors detect subtle fluid motion using slender, viscous-driven structures. Among these, acoustic flow sensors that mimic nature's velocity-sensitive ears have the potential to transform vector sound detection. Yet, despite their potential, understanding o… ▽ More Flow sensing is fundamental to both biological survival and technological innovation. Inspired by biological mechanoreceptors, artificial flow sensors detect subtle fluid motion using slender, viscous-driven structures. Among these, acoustic flow sensors that mimic nature's velocity-sensitive ears have the potential to transform vector sound detection. Yet, despite their potential, understanding of how design parameters determine ultimate sensor performance remains limited. To effectively guide flow sensor design, we develop and experimentally validate a lumped-element model that captures the broadband motion of slender microcantilevers immersed in fluid, combining analytical simplicity with quantitative accuracy. The model predicts flow-induced motion, thermomechanical noise, and the minimum detectable signal level, showing strong agreement with experimental measurements in air over a broad frequency range from 100 Hz to 10,000 Hz. This validated model provides a straightforward theoretical framework for designing high-performance micro- and nanomechanical sensors for flow and vector sound detection. △ Less

Submitted 13 November, 2025; originally announced November 2025.

Real-time vacuum-state quantum random number generator on a chip

Authors: Guan-Ru Qiao, Bing Bai, Zi-Xuan Weng, Han-Shen Chen, Wei Zheng, Zhi-Yuan Zheng, You-Qi Nie, Jun Zhang, Jian-Wei Pan

Abstract: Quantum random number generators (QRNGs) produce true random numbers, which are guaranteed by the fundamental principles of quantum physics. Miniaturization of QRNGs is crucial for a wide range of communication and cryptography applications. Here, we first report a fully functional QRNG chip based on vacuum-state fluctuations, with dimensions of 16.6 mm x 7.8 mm. The quantum entropy source, which… ▽ More Quantum random number generators (QRNGs) produce true random numbers, which are guaranteed by the fundamental principles of quantum physics. Miniaturization of QRNGs is crucial for a wide range of communication and cryptography applications. Here, we first report a fully functional QRNG chip based on vacuum-state fluctuations, with dimensions of 16.6 mm x 7.8 mm. The quantum entropy source, which is achieved via hybrid photonic integration with a SiO2 waveguide, generates raw quantum random numbers. The hybrid photonic and electrical components are assembled into a compact ceramic package using system-in-package technology. A microcontroller unit acquires the raw data and outputs the processed quantum random numbers via a serial peripheral interface. According to the characterization results, the QRNG chip achieves a constant real-time output rate of 5.2 Mbps across the industrial temperature range of -40°C to 85°C, making it suitable for practical applications. △ Less

Submitted 16 September, 2025; originally announced September 2025.

Comments: 8 pages, 6 figures. Accepted by Physical Review Applied

Dynamical phase evolution of Coulomb-focused electrons in strong-field ionization probed by a standing light wave

Authors: Yuan Gu, Hao Liang, Weiran Zheng, Aofan Lin, Jiaye Zhang, Zichen Li, Juan Du, Lei Ying, Peilun He, Jan-Michael Rost, Sina Jacob, Maksim Kunitski, Till Jahnke, Sebastian Eckart, Kang Lin, Reinhard Dörner

Abstract: We investigate the dynamical phase evolution of Coulomb-focused electrons in strong-field ionization. We diffract the electrons with an ultrashort standing light wave to track their time-dependent phase. Our findings show that low-energy electrons exhibit a unique chromosome-shaped diffraction pattern, distinct from higher-energy electrons. Our numerical model quantitatively reproduces the experim… ▽ More We investigate the dynamical phase evolution of Coulomb-focused electrons in strong-field ionization. We diffract the electrons with an ultrashort standing light wave to track their time-dependent phase. Our findings show that low-energy electrons exhibit a unique chromosome-shaped diffraction pattern, distinct from higher-energy electrons. Our numerical model quantitatively reproduces the experimental results, confirming this pattern maps the electron's time-dependent phase evolution as it escapes from a Coulomb potential. Our pulsed diffraction grating technique offers a new way to sense an electron's quantum phase without interfering its release mechanism. △ Less

Submitted 16 September, 2025; originally announced September 2025.

High-accuracy pointing and sub-second acquisition in a space optical communication terminal with ground-based verification method

Authors: Jianmin Wang, Zhiqian Su, Bin Li, Weiran Zheng, Haochun Gao

Abstract: This paper presents and implements a novel space optical communication terminal achieving high-precision open-loop pointing and sub-second acquisition. We further introduce a simple and accurate ground-based performance test method that enables end-to-end verification without the need for in-orbit experiments. To accurately measure open-loop pointing accuracy and acquisition characteristics, we fo… ▽ More This paper presents and implements a novel space optical communication terminal achieving high-precision open-loop pointing and sub-second acquisition. We further introduce a simple and accurate ground-based performance test method that enables end-to-end verification without the need for in-orbit experiments. To accurately measure open-loop pointing accuracy and acquisition characteristics, we formulate a comprehensive mathematical error model--covering structural misalignments, installation tolerances, and environmental effects--and estimate calibration parameters from stellar observations via a least-squares solution. Field experiments show a greater than 94% improvement in open-loop pointing accuracy, reducing the mean error from 2070.24 urad to 120.16 urad, and confirm an average acquisition time of 0.908 s with all trials completed in under 1 s. The method is generalizable to large-range, high-precision optical pointing measurements and astronomical observations. △ Less

Submitted 2 August, 2026; v1 submitted 12 August, 2025; originally announced August 2025.

Comments: 14 pages, 14 figures, 3 tables, 33 reference

Journal ref: Wang, Jianmin, et al. "High-accuracy pointing and sub-second acquisition in a space optical communication terminal with ground-based verification method." Optics & Laser Technology 193 (2026): 114313

Orbital chiral lasing in twisted bilayer metasurfaces

Authors: Mingjin Wang, Nianyuan Lv, Zixuan Zhang, Ye Chen, Jiahao Si, Jingxuan Chen, Chenyan Tang, Xuefan Yin, Zhen Liu, Dongxu Xin, Zhaozheng Yi, Wanhua Zheng, Yuri Kivshar, Chao Peng

Abstract: Chirality is a fundamental concept in physics that underpins various phenomena in nonlinear optics, quantum physics, and topological photonics. Although the spin of a photon naturally brings chirality, orbital angular momentum can also become chirally active in the structures with a broken mirror symmetry. Here, we observe orbital chiral lasing from a twisted bilayer photonic structure leveraging… ▽ More Chirality is a fundamental concept in physics that underpins various phenomena in nonlinear optics, quantum physics, and topological photonics. Although the spin of a photon naturally brings chirality, orbital angular momentum can also become chirally active in the structures with a broken mirror symmetry. Here, we observe orbital chiral lasing from a twisted bilayer photonic structure leveraging its inherent structural chirality. Specifically, we design and fabricate a Moire-type optical structure by bonding and rotating two separate semiconductor membrane metasurfaces. We achieve single-mode lasing over a broad spectral range of 250 nm by optically pumping the twisted structure. The lasing emission exhibits orbital chiral characteristics, arising from helical and non-Hermitian couplings between clockwise and counter-clockwise rotating collective guided resonances, confirmed by polarization-resolved imaging and self-interference patterns. Our results provide the first observation of orbital chiral lasing in twisted photonics, and they can contribute to diverse applications of chiral light in diagnostics, optical manipulation, and communication with light. △ Less

Submitted 25 June, 2025; originally announced June 2025.

Comments: These authors contributed equally to this work: Mingjin Wang, Nianyuan Lv, Zixuan Zhang

Topological Invariants in Nonlinear Thouless Pumping of Solitons

Authors: Fei-Fei Wu, Xian-Da Zuo, Qing-Qing Zhu, Tao Yuan, Yi-Yi Mao, Chao Zeng, Yi Jiang, Yu-Ao Chen, Jian-Wei Pan, Wei Zheng, Han-Ning Dai

Abstract: Recent explorations of quantized solitons transport in optical waveguides have thrust nonlinear topological pumping into the spotlight. In this work, we introduce a unified topological invariant applicable across both weakly and strongly nonlinear regimes. In the weak nonlinearity regime, where the nonlinear bands are wellseparated, the invariant reduces to the Abelian Chern number of the occupied… ▽ More Recent explorations of quantized solitons transport in optical waveguides have thrust nonlinear topological pumping into the spotlight. In this work, we introduce a unified topological invariant applicable across both weakly and strongly nonlinear regimes. In the weak nonlinearity regime, where the nonlinear bands are wellseparated, the invariant reduces to the Abelian Chern number of the occupied nonlinear band. Consequently, the pumped charge is quantized to an integer value. As the nonlinearity increases, the nonlinear bands start to intertwine, leading to a situation where the invariant is expressed as the non-Abelian Chern number divided by the number of interacting bands. This could result in a fractional quantization of the pumped charge. Our unified topological invariant approach not only advances the understanding of the soliton dynamics, but also provides implications for the future design of nonlinear topological systems. △ Less

Submitted 10 June, 2025; originally announced June 2025.

Comments: 9 pages, 8 figures

Solving Boolean Satisfiability Problems Using A Hypergraph-based Probabilistic Computer

Authors: Yihan He, Ming-Chun Hong, Wanli Zheng, Ching Shih, Hsin-Han Lee, Yu-Chen Hsin, Jeng-Hua Wei, Xiao Gong, Tuo-Hung Hou, Gengchiau Liang

Abstract: Boolean Satisfiability (SAT) problems are critical in fields such as artificial intelligence and cryptography, where efficient solutions are essential. Conventional probabilistic solvers often encounter scalability issues due to complex logic synthesis steps. In this work, we present a novel approach for solving the 3-SAT Boolean satisfiability problem using hypergraph-based probabilistic computer… ▽ More Boolean Satisfiability (SAT) problems are critical in fields such as artificial intelligence and cryptography, where efficient solutions are essential. Conventional probabilistic solvers often encounter scalability issues due to complex logic synthesis steps. In this work, we present a novel approach for solving the 3-SAT Boolean satisfiability problem using hypergraph-based probabilistic computers obtained through direct mapping. This method directly translates 3-SAT logical expressions into hypergraph structures, thereby circumventing conventional logic decomposition and synthesis procedures, and offering a more streamlined solver architecture. For representative uf100-430 instances, the proposed approach reduces the node count from 631 to 100 and the edge count from ~2,423 to ~1,013. Under identical simulated annealing conditions, the conventional simple undirected graph (SUG)-based solver achieves a 0% success rate across the tested instances, whereas the hypergraph-based solver attains an average success rate of ~77.6%. In addition, the hypergraph-based method reaches an average minimum energy of ~0.24, close to the theoretical ground state, while the SUG-based architecture remains trapped at substantially higher energy levels (~9.12 on average). The direct hypergraph mapping can further be extended to k-SAT formulations, providing a scalable framework for more complex satisfiability problems in probabilistic computing. △ Less

Submitted 5 July, 2026; v1 submitted 28 May, 2025; originally announced May 2025.

Comments: Main Manuscript: 20 pages, 6 figures. Supplementary Material: 7 pages, 3 supplementary figures

Twist Bilayer Photonic slab's Angle-DependentGuided Resonance Analysis based on Multiple Scattering

Authors: Wenzhu Xie, Yan Wang, Jingxuan Chen, JiaHao Si, Wei Rao, MingJin Wang, WanHua Zheng

Abstract: We present an analysis of the transmission spectra of the twisted bilayer photonic slabs using a modified rigorous coupled wave (RCWA) analysis, where the evanescent bases are replaced by bases with non-zero flux density. By utilizing the modified RCWA we demonstrate the calculation of eigenmodes, which has not been realized before. To counter for the transmission property, we propose a five-layer… ▽ More We present an analysis of the transmission spectra of the twisted bilayer photonic slabs using a modified rigorous coupled wave (RCWA) analysis, where the evanescent bases are replaced by bases with non-zero flux density. By utilizing the modified RCWA we demonstrate the calculation of eigenmodes, which has not been realized before. To counter for the transmission property, we propose a five-layer uniform slab approximation, with an accuracy around 0.04a/c, which is more straightforward and accessible for optical engineers compared to work by Lou et al. [Phys. Rev. Lett. 126, 136101]. The moiré pattern perturbation induces a split of resonance, which show great potential for engineering the band structure. Moreover, We observe two distinct transmission phases: the angle-dependent phase and Fabry-Pérot phase, which is explained by a coupled-mode theory (CMT) with expanded channels brought by the modified eigenmodes. Our work provides a theoretical framework for the design and optimization of twisted bilayer photonic devices. △ Less

Submitted 14 May, 2025; originally announced May 2025.

Comments: 10 pages,5 figures, with supplemental material

Extending the Low-Frequency Limit of Time-Domain Thermoreflectance via Periodic Waveform Analysis

Authors: Mingzhen Zhang, Tao Chen, Shangzhi Song, Yunjia Bao, Ruiqiang Guo, Weidong Zheng, Puqing Jiang, Ronggui Yang

Abstract: Time-domain thermoreflectance (TDTR) is a powerful technique for characterizing the thermal properties of layered materials. However, its effectiveness at modulation frequencies below 0.1 MHz is hindered by pulse accumulation effects, limiting its ability to accurately measure in-plane thermal conductivities below 6 W/(m K). Here, we present a periodic waveform analysis-based TDTR (PWA-TDTR) metho… ▽ More Time-domain thermoreflectance (TDTR) is a powerful technique for characterizing the thermal properties of layered materials. However, its effectiveness at modulation frequencies below 0.1 MHz is hindered by pulse accumulation effects, limiting its ability to accurately measure in-plane thermal conductivities below 6 W/(m K). Here, we present a periodic waveform analysis-based TDTR (PWA-TDTR) method that extends the measurable frequency range down to 50 Hz with minimal modifications to the conventional setup. This advancement greatly enhances measurement sensitivity, enabling accurate measurements of in-plane thermal conductivities as low as 0.2 W/(m K). We validate the technique by measuring polymethyl methacrylate (PMMA) and fused silica, using PWA-TDTR to obtain in-plane thermal diffusivity and conventional TDTR to measure cross-plane thermal effusivity. Together, these allow the extraction of both thermal conductivity and volumetric heat capacity, with results in excellent agreement with literature values. We further demonstrate the versatility of PWA-TDTR through (1) thermal conductivity and heat capacity measurements of thin liquid films and (2) depth-resolved thermal conductivity profiling in lithium niobate crystals, revealing point defect-induced inhomogeneities at depths up to 100 um. By overcoming frequency and sensitivity constraints, PWA-TDTR significantly expands the applicability of TDTR, enabling detailed investigations of thermal transport in materials and conditions that were previously challenging to study. △ Less

Submitted 20 April, 2025; originally announced April 2025.

Comments: 19 pages, 4 figures

Journal ref: J. Appl. Phys. 138, 055101 (2025)

JWST/MIRI Observations of Newly Formed Dust in the Cold, Dense Shell of the Type IIn SN 2005ip

Authors: Melissa Shahbandeh, Ori D. Fox, Tea Temim, Eli Dwek, Arkaprabha Sarangi, Nathan Smith, Luc Dessart, Bryony Nickson, Michael Engesser, Alexei V. Filippenko, Thomas G. Brink, Weikang Zheng, Tamás Szalai, Joel Johansson, Armin Rest, Schuyler D. Van Dyk, Jennifer Andrews, Chris Ashall, Geoffrey C. Clayton, Ilse De Looze, James M. Derkacy, Michael Dulude, Ryan J. Foley, Suvi Gezari, Sebastian Gomez , et al. (20 additional authors not shown)

Abstract: Dust from core-collapse supernovae (CCSNe), specifically Type IIP SNe, has been suggested to be a significant source of the dust observed in high-redshift galaxies. CCSNe eject large amounts of newly formed heavy elements, which can condense into dust grains in the cooling ejecta. However, infrared (IR) observations of typical CCSNe generally measure dust masses that are too small to account for t… ▽ More Dust from core-collapse supernovae (CCSNe), specifically Type IIP SNe, has been suggested to be a significant source of the dust observed in high-redshift galaxies. CCSNe eject large amounts of newly formed heavy elements, which can condense into dust grains in the cooling ejecta. However, infrared (IR) observations of typical CCSNe generally measure dust masses that are too small to account for the dust production needed at high redshifts. Type IIn SNe, classified by their dense circumstellar medium (CSM), are also known to exhibit strong IR emission from warm dust, but the dust origin and heating mechanism have generally remained unconstrained because of limited observational capabilities in the mid-IR. Here, we present a JWST/MIRI Medium Resolution Spectrograph (MRS) spectrum of the Type IIn SN 2005ip nearly 17 years post-explosion. The Type IIn SN 2005ip is one of the longest-lasting and most well-studied SNe observed to date. Combined with a Spitzer mid-IR spectrum of SN 2005ip obtained in 2008, this data set provides a rare 15-year baseline, allowing for a unique investigation of the evolution of dust. The JWST spectrum shows a new high-mass dust component ($\gtrsim0.08$ M$_{\odot}$) that is not present in the earlier Spitzer spectrum. Our analysis shows dust likely formed over the past 15 years in the cold, dense shell (CDS), between the forward and reverse shocks. There is also a smaller mass of carbonaceous dust ($\gtrsim0.005$ M$_{\odot}$) in the ejecta. These observations provide new insights into the role of SN dust production, particularly within the CDS, and its potential contribution to the rapid dust enrichment of the early Universe. △ Less

Submitted 11 October, 2024; originally announced October 2024.

Curved graphene nanoribbons derived from tetrahydropyrene-based polyphenylenes via one-pot K-region oxidation and Scholl cyclization

Authors: Sebastian Obermann, Wenhao Zheng, Jason Melidonie, Steffen Böckmann, Silvio Osella, Lenin Andrés Guerrero León, Felix Hennersdorf, David Beljonne, Jan J. Weigand, Mischa Bonn, Michael Ryan Hansen, Hai I. Wang, Ji Ma, Xinliang Feng

Abstract: Precise synthesis of graphene nanoribbons (GNRs) is of great interest to chemists and materials scientists because of their unique opto-electronic properties and potential applications in carbon-based nanoelectronics and spintronics. In addition to the tunable edge structure and width, introducing curvature in GNRs is a powerful structural feature for their chemi-physical property modification. He… ▽ More Precise synthesis of graphene nanoribbons (GNRs) is of great interest to chemists and materials scientists because of their unique opto-electronic properties and potential applications in carbon-based nanoelectronics and spintronics. In addition to the tunable edge structure and width, introducing curvature in GNRs is a powerful structural feature for their chemi-physical property modification. Here, we report an efficient solution synthesis of the first pyrene-based GNR (PyGNR) with curved geometry via one-pot K-region oxidation and Scholl cyclization of its corresponding well-soluble tetrahydropyrene-based polyphenylene precursor. The efficient A2B2-type Suzuki polymerization and subsequent Scholl reaction furnishes up to 35 nm long curved GNRs bearing cove- and armchair-edges. The construction of model compound, as a cutout of PyGNR, from a tetrahydropyrene-based oligophenylene precursor proves the concept and efficiency of the one-pot K-region oxidation and Scholl cyclization, which is clearly revealed by single crystal X-ray diffraction analysis. The structure and optical properties of PyGNR are investigated by Raman, FT-IR, solid-state NMR and UV-Vis analysis with the support of DFT calculations. PyGNR shows the absorption maximum at 680 nm, exhibiting a narrow optical bandgap of 1.4 eV, qualifying as a low-bandgap GNR. Moreover, THz spectroscopy on PyGNR estimates its macroscopic charge mobility of 3.6 cm2/Vs, outperforming other curved GNRs reported via conventional Scholl reaction. △ Less

Submitted 10 October, 2024; originally announced October 2024.

Journal ref: Chem. Sci. 2023 14, 8607-8614

Morphing median fin enhances untethered bionic robotic tuna's linear acceleration and turning maneuverability

Authors: Hongbin Huang, Zhonglu Lin, Wei Zheng, Jinhu Zhang, Zhibin Liu, Wei Zhou, Yu Zhang

Abstract: Median fins of fish-like swimmers play a crucial role in linear acceleration and maneuvering processes. However, few research focused on untethered robotic fish experiments. Imitating the behaviour of real tuna, we developed a free-swimming bionic tuna with a foldable dorsal fin. The erection of dorsal fin, at proper conditions, can reduce head heave by 50%, enhance linear acceleration by 15.7%, i… ▽ More Median fins of fish-like swimmers play a crucial role in linear acceleration and maneuvering processes. However, few research focused on untethered robotic fish experiments. Imitating the behaviour of real tuna, we developed a free-swimming bionic tuna with a foldable dorsal fin. The erection of dorsal fin, at proper conditions, can reduce head heave by 50%, enhance linear acceleration by 15.7%, increase turning angular velocity by 32.78%, and turning radius decreasing by 33.13%. Conversely, erecting the dorsal fin increases the wetted surface area, resulting in decreased maximum speed and efficiency during steady swimming phase. This finding partially explains why tuna erect their median fins during maneuvers or acceleration and fold them afterward to reduce drag. In addition, we verified that folding the median fins after acceleration does not significantly affect locomotion efficiency. This study supports the application of morphing median fins in undulating underwater robots and helps to further understand the impact of median fins on fish locomotion. △ Less

Submitted 26 July, 2024; originally announced July 2024.

Comments: 7 pages, 5 figures

Chiral emission of vortex microlasers enabled by collective modes of guided resonances

Authors: Ye Chen, Mingjin Wang, Jiahao Si, Zixuan Zhang, Xuefan Yin, Jingxuan Chen, NianYuan Lv, Chenyan Tang, Wanhua Zheng, Yuri Kivshar, Chao Peng

Abstract: Vortex lasers have attracted substantial attention in recent years owing to their wide array of applications such as micromanipulation, optical multiplexing, and quantum cryptography. In this work, we propose and demonstrate chiral emission of vortex microlaser leveraging the collective modes from omnidirectionally hybridizing the guided mode resonances (GMRs) within photonic crystal (PhC) slabs.… ▽ More Vortex lasers have attracted substantial attention in recent years owing to their wide array of applications such as micromanipulation, optical multiplexing, and quantum cryptography. In this work, we propose and demonstrate chiral emission of vortex microlaser leveraging the collective modes from omnidirectionally hybridizing the guided mode resonances (GMRs) within photonic crystal (PhC) slabs. Specifically, we encircle a central uniform PhC with a heterogeneous PhC that features a circular lateral boundary. Consequently, the bulk GMRs hybridize into a series of collective modes due to boundary scatterings, resulting in a vortex pattern in real space with a spiral phase front in its radiation. Benefiting from the long lifetime of GMRs as quasi-bound state in the continuum and using asymmetric pumping to lift the chiral symmetry, we demonstrate stable single-mode lasing oscillation with a low optical pumping threshold of $18~\mathrm{kW/cm^2}$ at room temperature. We identify the real-space vortex through polarization-resolved imaging and self-interference patterns, showing a vivid example of applying collective modes to realize compact and energy-efficient vortex microlasers. △ Less

Submitted 23 July, 2024; originally announced July 2024.

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

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

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

Submitted 10 July, 2024; originally announced July 2024.

Highly sensitive AuNCs@GSH/Ch-PtNPs metal nanoprobes for fluorescent and colorimetric dual-mode detection of ascorbic acid in drink

Authors: Wei Zheng

Abstract: Fluorescence detection is a commonly used analytical method with the advantages of fast response, good selectivity and low destructiveness. However, fluorescence detection, a single-mode detection method, has some limitations, such as background interference that affects the accuracy of the fluorescence signal, lack of visualization of the detection results, and low sensitivity for detecting low-c… ▽ More Fluorescence detection is a commonly used analytical method with the advantages of fast response, good selectivity and low destructiveness. However, fluorescence detection, a single-mode detection method, has some limitations, such as background interference that affects the accuracy of the fluorescence signal, lack of visualization of the detection results, and low sensitivity for detecting low-concentration samples. In order to overcome the shortcomings of fluorescence single-mode detection, we used the dual-mode method of fluorescence and colorimetry to detect ascorbic acid. The dual-mode detection of AA by fluorescence and colorimetry in the probe system enhances the specificity and accuracy of the detection. This bimodal detection method solved the problem of low detection sensitivity in the low concentration range of the analytes to be tested, and was linear in the lower (0-50 μM) and higher (50-350 μM) concentration ranges, respectively, and had a lower detection limit (0.034 μM). This glutathione-based gold cluster assay is characterized by simplicity, rapidity and accuracy, and provides a new way for the quantitative analysis of ascorbic acid. In addition, the method was validated during the determination of AA in beverages, which has the advantages of high sensitivity and fast response time. △ Less

Submitted 5 June, 2024; originally announced June 2024.

Probing Berry phase effect in topological surface states

Authors: Ya Bai, Yang Jiang, Wenyang Zheng, Jiayin Chen, Shuo Wang, Candong Liu, Ruxin Li, Peng Liu

Abstract: We have observed the Berry phase effect associated with interband coherence in topological surface states (TSSs) using two-color high-harmonic spectroscopy. This Berry phase accumulates along the evolution path of strong field-driven election-hole quasiparticles in electronic bands with strong spin-orbit coupling. By introducing a secondary weak field, we perturb the evolution of Dirac fermions in… ▽ More We have observed the Berry phase effect associated with interband coherence in topological surface states (TSSs) using two-color high-harmonic spectroscopy. This Berry phase accumulates along the evolution path of strong field-driven election-hole quasiparticles in electronic bands with strong spin-orbit coupling. By introducing a secondary weak field, we perturb the evolution of Dirac fermions in TSSs and thus provide access to the Berry phase. We observe a significant shift in the oscillation phase of the even-order harmonics from the spectral interferogram. We reveal that such a modulation feature is linked to the geometric phase acquired in the nonperturbative dynamics of TSSs. Furthermore, we show that the overwhelming Berry phase effect can significantly deform the quantum paths of electron-hole pairs, thus enhancing the ability to harness electron spin using lightwaves in quantum materials with strong spin-orbit interactions. △ Less

Submitted 9 April, 2024; originally announced April 2024.

Comments: 16 pages, 4 figures,

Broadband NIR photon upconversion generates NIR persistent luminescence for bioimaging

Authors: Shuting Yang, Bing Qi, Mingzi Sun, Wenjing Dai, Ziyun Miao, Wei Zheng, Bolong Huang, Jie Wang

Abstract: Upconversion persistent luminescence (UCPL) phosphors that can be directly charged by near-infrared (NIR) light have gained considerable attention due to their promising applications ranging from photonics to biomedicine. However, current lanthanide-based UCPL phosphors show small absorption cross-sections and low upconversion charging efficiency. The development of UCPL phosphors faces challenges… ▽ More Upconversion persistent luminescence (UCPL) phosphors that can be directly charged by near-infrared (NIR) light have gained considerable attention due to their promising applications ranging from photonics to biomedicine. However, current lanthanide-based UCPL phosphors show small absorption cross-sections and low upconversion charging efficiency. The development of UCPL phosphors faces challenges of lacking flexible upconversion charging pathways and poor design flexibility. Herein, we discovered a new lattice defect-mediated broadband photon upconversion process and the accompanied NIR-to-NIR UCPL in Cr-doped zinc gallate nanoparticles. The zinc gallate nanoparticles can be directly activated by broadband NIR light in the 700-1000 nm range to produce persistent luminescence at about 700 nm, which is also readily enhanced by rationally tailoring the lattice defects in the phosphors. This proposed UCPL phosphors achieved a signal-to-background ratio of over 200 in bioimaging by efficiently avoiding interference from autofluorescence and light scattering. Our findings reported the lattice defect-mediated photon upconversion for the first time, which significantly expanded the horizons for the flexible design of NIR-to-NIR UCPL phosphors toward broad applications. △ Less

Submitted 14 March, 2024; originally announced March 2024.

Metasurface spectrometers beyond resolution-sensitivity constraints

Authors: Feng Tang, Jingjun Wu, Tom Albrow-Owen, Hanxiao Cui, Fujia Chen, Yaqi Shi, Lan Zou, Jun Chen, Xuhan Guo, Yijun Sun, Jikui Luo, Bingfeng Ju, Jing Huang, Shuangli Liu, Bo Li, Liming Yang, Eric Anthony Munro, Wanguo Zheng, Hannah J. Joyce, Hongsheng Chen, Lufeng Che, Shurong Dong, Tawfique Hasan, Xin Ye, Yihao Yang , et al. (1 additional authors not shown)

Abstract: Optical spectroscopy plays an essential role across scientific research and industry for non-contact materials analysis1-3, increasingly through in-situ or portable platforms4-6. However, when considering low-light-level applications, conventional spectrometer designs necessitate a compromise between their resolution and sensitivity7,8, especially as device and detector dimensions are scaled down.… ▽ More Optical spectroscopy plays an essential role across scientific research and industry for non-contact materials analysis1-3, increasingly through in-situ or portable platforms4-6. However, when considering low-light-level applications, conventional spectrometer designs necessitate a compromise between their resolution and sensitivity7,8, especially as device and detector dimensions are scaled down. Here, we report on a miniaturizable spectrometer platform where light throughput onto the detector is instead enhanced as the resolution is increased. This planar, CMOS-compatible platform is based around metasurface encoders designed to exhibit photonic bound states in the continuum9, where operational range can be altered or extended simply through adjusting geometric parameters. This system can enhance photon collection efficiency by up to two orders of magnitude versus conventional designs; we demonstrate this sensitivity advantage through ultra-low-intensity fluorescent and astrophotonic spectroscopy. This work represents a step forward for the practical utility of spectrometers, affording a route to integrated, chip-based devices that maintain high resolution and SNR without requiring prohibitively long integration times. △ Less

Submitted 1 March, 2024; v1 submitted 29 February, 2024; originally announced February 2024.

Helmholtz decomposition based windowed Green function methods for elastic scattering problems on a half-space

Authors: Tao Yin, Lu Zhang, Weiying Zheng, Xiaopeng Zhu

Abstract: This paper proposes a new Helmholtz decomposition based windowed Green function (HD-WGF) method for solving the time-harmonic elastic scattering problems on a half-space with Dirichlet boundary conditions in both 2D and 3D. The Helmholtz decomposition is applied to separate the pressure and shear waves, which satisfy the Helmholtz and Helmholtz/Maxwell equations, respectively, and the correspondin… ▽ More This paper proposes a new Helmholtz decomposition based windowed Green function (HD-WGF) method for solving the time-harmonic elastic scattering problems on a half-space with Dirichlet boundary conditions in both 2D and 3D. The Helmholtz decomposition is applied to separate the pressure and shear waves, which satisfy the Helmholtz and Helmholtz/Maxwell equations, respectively, and the corresponding boundary integral equations of type $(\mathbb{I}+\mathbb{T})\bsφ=\bs f$, that couple these two waves on the unbounded surface, are derived based on the free-space fundamental solution of Helmholtz equation. This approach avoids the treatment of the complex elastic displacement tensor and traction operator that involved in the classical integral equation method for elastic problems. Then a smooth ``slow-rise'' windowing function is introduced to truncate the boundary integral equations and a ``correction'' strategy is proposed to ensure the uniformly fast convergence for all incident angles of plane incidence. Numerical experiments for both two and three dimensional problems are presented to demonstrate the accuracy and efficiency of the proposed method. △ Less

Submitted 23 December, 2023; originally announced December 2023.

Comments: 20 pages, 5 figures

Nano-Imaging of Landau-Phonon Polaritons in Dirac Heterostructures

Authors: Lukas Wehmeier, Suheng Xu, Rafael A. Mayer, Brian Vermilyea, Makoto Tsuneto, Michael Dapolito, Rui Pu, Zengyi Du, Xinzhong Chen, Wenjun Zheng, Ran Jing, Zijian Zhou, Kenji Watanabe, Takashi Taniguchi, Adrian Gozar, Qiang Li, Alexey B. Kuzmenko, G. Lawrence Carr, Xu Du, Michael M. Fogler, D. N. Basov, Mengkun Liu

Abstract: Polaritons are light-matter quasiparticles that govern the optical response of quantum materials and enable their nanophotonic applications. We have studied a new type of polaritons arising in magnetized graphene encapsulated in hexagonal boron nitride (hBN). These polaritons stem from hybridization of Dirac magnetoexciton modes of graphene with waveguide phonon modes of hBN crystals. We refer to… ▽ More Polaritons are light-matter quasiparticles that govern the optical response of quantum materials and enable their nanophotonic applications. We have studied a new type of polaritons arising in magnetized graphene encapsulated in hexagonal boron nitride (hBN). These polaritons stem from hybridization of Dirac magnetoexciton modes of graphene with waveguide phonon modes of hBN crystals. We refer to these quasiparticles as the Landau-phonon polaritons (LPPs). Using infrared magneto nanoscopy, we imaged LPPs and controlled their real-space propagation by varying the magnetic field. These LLPs have large in-plane momenta and are not bound by the conventional optical selection rules, granting us access to the "forbidden" inter-Landau level transitions (ILTs). We observed avoided crossings in the LPP dispersion - a hallmark of the strong coupling regime - occurring when the magnetoexciton and hBN phonon frequencies matched. Our LPP-based nanoscopy also enabled us to resolve two fundamental many-body effects: the graphene Fermi velocity renormalization and ILT-dependent magnetoexciton binding energies. These results indicate that magnetic-field-tuned Dirac heterostructures are promising platforms for precise nanoscale control and sensing of light-matter interaction. △ Less

Submitted 21 December, 2023; originally announced December 2023.

Red-shift effect on the zero field splitting for negatively charged nitrogen-vacancy centers in diamond

Authors: Wang Zheng, Zhang Jintao, Feng Xiaojuan, Xing Li

Abstract: The zero field splitting (ZFS) quantifies the energy difference for the ground electron spin-triplet of a nitrogen-vacancy center in the absence of external fields. The values of the ZFS play a key role in determining the Larmor precession of the Bloch sphere and the Rabi oscillation of a spin system. The ZFS is generally detected using coherent spin manipulation by sweeping microwaves (MWs) at fr… ▽ More The zero field splitting (ZFS) quantifies the energy difference for the ground electron spin-triplet of a nitrogen-vacancy center in the absence of external fields. The values of the ZFS play a key role in determining the Larmor precession of the Bloch sphere and the Rabi oscillation of a spin system. The ZFS is generally detected using coherent spin manipulation by sweeping microwaves (MWs) at frequencies close to resonance with the ZFS. In this letter, we report our experimental observations of the red-shift effect on the ZFS as a function of the MW power for two different thermal environments of a sample. We find an asymptotic property of the red shifts of the ZFS. Given the identical initial thermal equilibrium states of the sample, the differences in the raw values of the ZFS between the two cases randomly vary from 47 kHz to 1505 kHz over the entire experimental range. According to the asymptotic approximation, the differences are reduced to 29-166 kHz with a standard deviation of 49 kHz, suggesting a significant elimination of the red-shift effect. To the best of our knowledge, no other study has addressed the quantification and elimination of the red shift-effect of the MW field dependence using the asymptotic approximation. △ Less

Submitted 1 February, 2024; v1 submitted 13 December, 2023; originally announced December 2023.

Rapid detection of rare events from in situ X-ray diffraction data using machine learning

Authors: Weijian Zheng, Jun-Sang Park, Peter Kenesei, Ahsan Ali, Zhengchun Liu, Ian T. Foster, Nicholas Schwarz, Rajkumar Kettimuthu, Antonino Miceli, Hemant Sharma

Abstract: High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots over time of the evolving microstructure and attributes. However, the extreme data volumes and the high costs o… ▽ More High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots over time of the evolving microstructure and attributes. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. Here we present a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. Our technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to 9 times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data into compact, semantic-rich representations of visually salient characteristics (e.g., peak shapes). These characteristics can be a rapid indicator of anomalous events such as changes in diffraction peak shapes. We anticipate that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods that span many decades of length scales. △ Less

Submitted 6 December, 2023; originally announced December 2023.

Cross-Tokamak Deployment Study of Plasma Disruption Predictors Based on Convolutional Autoencoder

Authors: Xinkun Ai, Wei Zheng, Ming Zhang, Yonghua Ding, Dalong Chen, Zhongyong Chen, Chengshuo Shen, Bihao Guo, Nengchao Wang, Zhoujun Yang, Zhipeng Chen, Yuan Pan, Biao Shen, Binjia Xiao, J-TEXT team

Abstract: In the initial stages of operation for future tokamak, facing limited data availability, deploying data-driven disruption predictors requires optimal performance with minimal use of new device data. This paper studies the issue of data utilization in data-driven disruption predictor during cross tokamak deployment. Current predictors primarily employ supervised learning methods and require a large… ▽ More In the initial stages of operation for future tokamak, facing limited data availability, deploying data-driven disruption predictors requires optimal performance with minimal use of new device data. This paper studies the issue of data utilization in data-driven disruption predictor during cross tokamak deployment. Current predictors primarily employ supervised learning methods and require a large number of disruption and non-disruption shots for training. However, the scarcity and high cost of obtaining disruption shots for future tokamaks result in imbalanced training datasets, reducing the performance of supervised learning predictors. To solve this problem, we propose the Enhanced Convolutional Autoencoder Anomaly Detection (E-CAAD) predictor. E-CAAD can be only trained by normal samples from non-disruption shots and can also be trained by disruption precursor samples when disruption shots occur. This model not only overcomes the sample imbalance in supervised learning predictors, but also overcomes the inefficient dataset utilization faced by traditional anomaly detection predictors that cannot use disruption precursor samples for training, making it more suitable for the unpredictable datasets of future tokamaks. Compared to traditional anomaly detection predictor, the E-CAAD predictor performs better in disruption prediction and is deployed faster on new devices. Additionally, we explore strategies to accelerate deployment of E-CAAD predictor on the new device by using data from existing devices. Two deployment strategies are presented: mixing data from existing devices and fine-tuning the predictor trained on existing devices. Our comparisons indicate that the data from existing device can accelerate the deployment of predictor on new device. Notably, the fine-tuning strategy yields the fastest deployment on new device among the designed strategies. △ Less

Submitted 4 January, 2024; v1 submitted 17 November, 2023; originally announced November 2023.

Comments: 19 pages, 8 figures

How Biomimetic Morphing Dorsal Fin Affects the Swimming Performance of a Free-swimming Tuna Robot

Authors: Hongbing Huang, Zhonglu Lin, Wei Zheng, Jinhu Zhang, Wei Zhou, Yu Zhang

Abstract: It is well known that tuna fish in the ocean can dynamically morph their median fins to achieve optimal hydrodynamic performance, e.g. linear acceleration and maneuverability. In this study, based on the previous studies about the median fin's hydrodynamic effects focusing on tethered conditions, we continue to explore the hydrodynamic function of tuna morphing dorsal fin in free swimming conditio… ▽ More It is well known that tuna fish in the ocean can dynamically morph their median fins to achieve optimal hydrodynamic performance, e.g. linear acceleration and maneuverability. In this study, based on the previous studies about the median fin's hydrodynamic effects focusing on tethered conditions, we continue to explore the hydrodynamic function of tuna morphing dorsal fin in free swimming conditions for better approaching real-life situations.Here, we developed a tuna-inspired robotic fish platform that can swim independently in three dimensions, equipped with a biomimetic morphing dorsal fin magnetically attached to the robotic fish. Based on the free-swimming robotic fish platform, we investigated how the erected dorsal fin affects the speed, cost of transport (COT), and robotic fish's yaw angle at different frequencies and amplitudes. The erected dorsal fin plays a positive role in improving the yaw stability of robotic fish. However, it shows little influence on the speed and COT in our test. This remains to be further investigated in the future. △ Less

Submitted 19 October, 2023; originally announced October 2023.

Comments: 10 pages, 5 figures, 2 tables

Performance of FPGA controller in ISAC-1 accelerator chain

Authors: K. Fong, X. Fu, Q. W. Zheng, T. Au, R. Leewe, TRIUMF, V6T2A3, Vancouver, Canada

Abstract: The LLRF of five of TRIUMF's ISAC-1 accelerator cavities have been replaced by 3 similar FPGA based system with different operating frequencies. These LLRF use internal digital phase locked loops for frequency generation and synchronization, feedback control using Amplitude/Phase regulations. These FPGAs also have internal stepper motor controller for resonance control. Various modes of resonance… ▽ More The LLRF of five of TRIUMF's ISAC-1 accelerator cavities have been replaced by 3 similar FPGA based system with different operating frequencies. These LLRF use internal digital phase locked loops for frequency generation and synchronization, feedback control using Amplitude/Phase regulations. These FPGAs also have internal stepper motor controller for resonance control. Various modes of resonance control are possible, including phase comparison and minimum seeking slide-mode control. Operational performances including frequency generation and synchronization, amplitude and phase noises, tuning speeds, compatibility to original remote controls, are reported. △ Less

Submitted 19 October, 2023; v1 submitted 18 October, 2023; originally announced October 2023.

Comments: Poster presented at LLRF Workshop 2023 (LLRF2023, arXiv: 2310.03199)

Report number: LLRF2023/16

Health diagnosis and recuperation of aged Li-ion batteries with data analytics and equivalent circuit modeling

Authors: Riko I Made, Jing Lin, Jintao Zhang, Yu Zhang, Lionel C. H. Moh, Zhaolin Liu, Ning Ding, Sing Yang Chiam, Edwin Khoo, Xuesong Yin, Guangyuan Wesley Zheng

Abstract: Battery health assessment and recuperation play a crucial role in the utilization of second-life Li-ion batteries. However, due to ambiguous aging mechanisms and lack of correlations between the recovery effects and operational states, it is challenging to accurately estimate battery health and devise a clear strategy for cell rejuvenation. This paper presents aging and reconditioning experiments… ▽ More Battery health assessment and recuperation play a crucial role in the utilization of second-life Li-ion batteries. However, due to ambiguous aging mechanisms and lack of correlations between the recovery effects and operational states, it is challenging to accurately estimate battery health and devise a clear strategy for cell rejuvenation. This paper presents aging and reconditioning experiments of 62 commercial high-energy type lithium iron phosphate (LFP) cells, which supplement existing datasets of high-power LFP cells. The relatively large-scale data allow us to use machine learning models to predict cycle life and identify important indicators of recoverable capacity. Considering cell-to-cell inconsistencies, an average test error of $16.84\% \pm 1.87\%$ (mean absolute percentage error) for cycle life prediction is achieved by gradient boosting regressor given information from the first 80 cycles. In addition, it is found that some of the recoverable lost capacity is attributed to the lateral lithium non-uniformity within the electrodes. An equivalent circuit model is built and experimentally validated to demonstrate how such non-uniformity can be accumulated, and how it can give rise to recoverable capacity loss. SHapley Additive exPlanations (SHAP) analysis also reveals that battery operation history significantly affects the capacity recovery. △ Less

Submitted 21 September, 2023; originally announced October 2023.

Comments: 20 pages, 5 figures, 1 table

Journal ref: iScience (2024)

Breaking Through the Plasma Wavelength Barrier to Extend the Transparency Range of Ultrathin Indium Tin Oxide Films into the Far Infrared

Authors: Ran Bi, Chuantao Zheng, William W. Yu, Weitao Zheng, Dingdi Wang

Abstract: Indium tin oxide (ITO) film, which is the most commonly used transparent conductive film (TCF), has traditionally been believed to be transparent in the visible spectrum but to reflect infrared (IR) light beyond the plasma wavelength ($λ_p$). However, our theoretical analysis challenges this notion by demonstrating that an ultrathin ITO TCF that is thinner than the light's penetration depth, can o… ▽ More Indium tin oxide (ITO) film, which is the most commonly used transparent conductive film (TCF), has traditionally been believed to be transparent in the visible spectrum but to reflect infrared (IR) light beyond the plasma wavelength ($λ_p$). However, our theoretical analysis challenges this notion by demonstrating that an ultrathin ITO TCF that is thinner than the light's penetration depth, can overcome the transmission barrier at $λ_p$. To validate the theoretical modeling, we have successfully fabricated ITO films that, despite having $λ_p \approx$ 1 $μ$m, remain transparent from 400 nm to 20 $μ$m. This represents the broadest transparency range ever reported for any In$_2$O$_3$-based TCF. The 10-nm-thick ITO TCFs have high visible transmittance (91.0% at 550 nm), low resistivity (5 $\times$ 10$^{-4}$ $Ω\cdot$ cm), and good IR transmittance (averaging 60% over 1.35 $\unicode{x2013}$ 18.35 $μ$m). Their IR transparency facilitates radiative cooling of the underlying circuitry. When an operational resistor is enclosed by commercial ITO TCFs that are 140 nm thick, its temperature increases. However, using 10-nm-thick ITO TCFs instead of the commercial ones can completely avoid this temperature rise. Moreover, attaching a silver grid to a 10-nm-thick ITO TCF can reduce the effective sheet resistance to ~10 $Ω/\square$ at the expense of only ~3% transmittance. This development paves the way for large-scale applications that require low sheet resistance and far-IR transparency. △ Less

Submitted 2 October, 2023; originally announced October 2023.

Comments: This article has been accepted by the Journal of Applied Physics

Visualizing moiré ferroelectricity via plasmons and nano-photocurrent in graphene/twisted-WSe2 structures

Authors: Shuai Zhang, Yang Liu, Zhiyuan Sun, Xinzhong Chen, Baichang Li, S. L. Moore, Song Liu, Zhiying Wang, S. E. Rossi, Ran Jing, Jordan Fonseca, Birui Yang, Yinming Shao, Chun-Ying Huang, Taketo Handa, Lin Xiong, Matthew Fu, Tsai-Chun Pan, Dorri Halbertal, Xinyi Xu, Wenjun Zheng, P. J. Schuck, A. N. Pasupathy, C. R. Dean, Xiaoyang Zhu , et al. (6 additional authors not shown)

Abstract: Ferroelectricity, a spontaneous and reversible electric polarization, is found in certain classes of van der Waals (vdW) material heterostructures. The discovery of ferroelectricity in twisted vdW layers provides new opportunities to engineer spatially dependent electric and optical properties associated with the configuration of moiré superlattice domains and the network of domain walls. Here, we… ▽ More Ferroelectricity, a spontaneous and reversible electric polarization, is found in certain classes of van der Waals (vdW) material heterostructures. The discovery of ferroelectricity in twisted vdW layers provides new opportunities to engineer spatially dependent electric and optical properties associated with the configuration of moiré superlattice domains and the network of domain walls. Here, we employ near-field infrared nano-imaging and nano-photocurrent measurements to study ferroelectricity in minimally twisted WSe2. The ferroelectric domains are visualized through the imaging of the plasmonic response in a graphene monolayer adjacent to the moiré WSe2 bilayers. Specifically, we find that the ferroelectric polarization in moiré domains is imprinted on the plasmonic response of the graphene. Complementary nano-photocurrent measurements demonstrate that the optoelectronic properties of graphene are also modulated by the proximal ferroelectric domains. Our approach represents an alternative strategy for studying moiré ferroelectricity at native length scales and opens promising prospects for (opto)electronic devices. △ Less

Submitted 12 September, 2023; originally announced September 2023.

Comments: 19 pages, 3 figures

Journal ref: Nature Communications 14, 6200 (2023)

Cross-tokamak Disruption Prediction based on Physics-Guided Feature Extraction and domain adaptation

Authors: Chengshuo Shen, Wei Zheng, Bihao Guo, Yonghua Ding, Dalong Chen, Xinkun Ai, Fengming Xue, Yu Zhong, Nengchao Wang, Biao Shen, Binjia Xiao, Zhongyong Chen, Yuan Pan, J-TEXT team

Abstract: The high acquisition cost and the significant demand for disruptive discharges for data-driven disruption prediction models in future tokamaks pose an inherent contradiction in disruption prediction research. In this paper, we demonstrated a novel approach to predict disruption in a future tokamak using only a few discharges. The first step is to use the existing understanding of physics to extrac… ▽ More The high acquisition cost and the significant demand for disruptive discharges for data-driven disruption prediction models in future tokamaks pose an inherent contradiction in disruption prediction research. In this paper, we demonstrated a novel approach to predict disruption in a future tokamak using only a few discharges. The first step is to use the existing understanding of physics to extract physics-guided features from the diagnostic signals of each tokamak, called physics-guided feature extraction (PGFE). The second step is to align a few data from the future tokamak (target domain) and a large amount of data from existing tokamak (source domain) based on a domain adaptation algorithm called CORrelation ALignment (CORAL). It is the first attempt at applying domain adaptation in the task of disruption prediction. PGFE has been successfully applied in J-TEXT to predict disruption with excellent performance. PGFE can also reduce the data volume requirements due to extracting the less device-specific features, thereby establishing a solid foundation for cross-tokamak disruption prediction. We have further improved CORAL (supervised CORAL, S-CORAL) to enhance its appropriateness in feature alignment for the disruption prediction task. To simulate the existing and future tokamak case, we selected J-TEXT as the existing tokamak and EAST as the future tokamak, which has a large gap in the ranges of plasma parameters. The utilization of the S-CORAL improves the disruption prediction performance on future tokamak. Through interpretable analysis, we discovered that the learned knowledge of the disruption prediction model through this approach exhibits more similarities to the model trained on large data volumes of future tokamak. △ Less

Submitted 1 November, 2023; v1 submitted 11 September, 2023; originally announced September 2023.

Comments: 17 pages, 9 figures

Observation of microscopic confinement dynamics by a tunable topological $θ$-angle

Authors: Wei-Yong Zhang, Ying Liu, Yanting Cheng, Ming-Gen He, Han-Yi Wang, Tian-Yi Wang, Zi-Hang Zhu, Guo-Xian Su, Zhao-Yu Zhou, Yong-Guang Zheng, Hui Sun, Bing Yang, Philipp Hauke, Wei Zheng, Jad C. Halimeh, Zhen-Sheng Yuan, Jian-Wei Pan

Abstract: The topological $θ$-angle is central to the understanding of a plethora of phenomena in condensed matter and high-energy physics such as the strong CP problem, dynamical quantum topological phase transitions, and the confinement--deconfinement transition. Difficulties arise when probing the effects of the topological $θ$-angle using classical methods, in particular through the appearance of a sign… ▽ More The topological $θ$-angle is central to the understanding of a plethora of phenomena in condensed matter and high-energy physics such as the strong CP problem, dynamical quantum topological phase transitions, and the confinement--deconfinement transition. Difficulties arise when probing the effects of the topological $θ$-angle using classical methods, in particular through the appearance of a sign problem in numerical simulations. Quantum simulators offer a powerful alternate venue for realizing the $θ$-angle, which has hitherto remained an outstanding challenge due to the difficulty of introducing a dynamical electric field in the experiment. Here, we report on the experimental realization of a tunable topological $θ$-angle in a Bose--Hubbard gauge-theory quantum simulator, implemented through a tilted superlattice potential that induces an effective background electric field. We demonstrate the rich physics due to this angle by the direct observation of the confinement--deconfinement transition of $(1+1)$-dimensional quantum electrodynamics. Using an atomic-precision quantum gas microscope, we distinguish between the confined and deconfined phases by monitoring the real-time evolution of particle--antiparticle pairs, which exhibit constrained (ballistic) propagation for a finite (vanishing) deviation of the $θ$-angle from $π$. Our work provides a major step forward in the realization of topological terms on modern quantum simulators, and the exploration of rich physics they have been theorized to entail. △ Less

Submitted 20 June, 2023; originally announced June 2023.

Comments: $7+7$ pages, $4+7$ figures, $1+0$ table

Photonic Integrated Neuro-Synaptic Core for Convolutional Spiking Neural Network

Authors: Shuiying Xiang, Yuechun Shi, Yahui Zhang, Xingxing Guo, Ling Zheng, Yanan Han, Yuna Zhang, Ziwei Song, Dianzhuang Zheng, Tao Zhang, Hailing Wang, Xiaojun Zhu, Xiangfei Chen, Min Qiu, Yichen Shen, Wanhua Zheng, Yue Hao

Abstract: Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture. Linear weighting and nonlinear spiking activation are two fundamental functions of a photonic spiking neural network (PSNN). However, they are separately implemented with different photonic materials and devices, hindering the large-scale integration of PSNN.… ▽ More Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture. Linear weighting and nonlinear spiking activation are two fundamental functions of a photonic spiking neural network (PSNN). However, they are separately implemented with different photonic materials and devices, hindering the large-scale integration of PSNN. Here, we propose, fabricate and experimentally demonstrate a photonic neuro-synaptic chip enabling the simultaneous implementation of linear weighting and nonlinear spiking activation based on a distributed feedback (DFB) laser with a saturable absorber (DFB-SA). A prototypical system is experimentally constructed to demonstrate the parallel weighted function and nonlinear spike activation. Furthermore, a four-channel DFB-SA array is fabricated for realizing matrix convolution of a spiking convolutional neural network, achieving a recognition accuracy of 87% for the MNIST dataset. The fabricated neuro-synaptic chip offers a fundamental building block to construct the large-scale integrated PSNN chip. △ Less

Submitted 5 June, 2023; originally announced June 2023.

Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection

Authors: Xinkun Ai, Wei Zheng, Ming Zhang, Dalong Chen, Chengshuo Shen, Bihao Guo, Bingjia Xiao, Yu Zhong, Nengchao Wang, Zhoujun Yang, Zhipeng Chen, Zhongyong Chen, Yonghua Ding, Yuan Pan, J-TEXT team

Abstract: The full understanding of plasma disruption in tokamaks is currently lacking, and data-driven methods are extensively used for disruption prediction. However, most existing data-driven disruption predictors employ supervised learning techniques, which require labeled training data. The manual labeling of disruption precursors is a tedious and challenging task, as some precursors are difficult to a… ▽ More The full understanding of plasma disruption in tokamaks is currently lacking, and data-driven methods are extensively used for disruption prediction. However, most existing data-driven disruption predictors employ supervised learning techniques, which require labeled training data. The manual labeling of disruption precursors is a tedious and challenging task, as some precursors are difficult to accurately identify, limiting the potential of machine learning models. To address this issue, commonly used labeling methods assume that the precursor onset occurs at a fixed time before the disruption, which may not be consistent for different types of disruptions or even the same type of disruption, due to the different speeds at which plasma instabilities escalate. This leads to mislabeled samples and suboptimal performance of the supervised learning predictor. In this paper, we present a disruption prediction method based on anomaly detection that overcomes the drawbacks of unbalanced positive and negative data samples and inaccurately labeled disruption precursor samples. We demonstrate the effectiveness and reliability of anomaly detection predictors based on different algorithms on J-TEXT and EAST to evaluate the reliability of the precursor onset time inferred by the anomaly detection predictor. The precursor onset times inferred by these predictors reveal that the labeling methods have room for improvement as the onset times of different shots are not necessarily the same. Finally, we optimize precursor labeling using the onset times inferred by the anomaly detection predictor and test the optimized labels on supervised learning disruption predictors. The results on J-TEXT and EAST show that the models trained on the optimized labels outperform those trained on fixed onset time labels. △ Less

Submitted 27 March, 2023; originally announced March 2023.

Comments: 21 pages, 11 figures

Report number: S1738-5733(23)00556-9

Journal ref: Nuclear Engineering and Technology 2023

Anomalously high supercurrent density in a two-dimensional topological material

Authors: Qi Zhang, Md Shafayat Hossain, Brian Casas, Wenkai Zheng, Zi-Jia Cheng, Zhuangchai Lai, Yi-Hsin Tu, Guoqing Chang, Yao Yao, Siyuan Li, Yu-Xiao Jiang, Sougata Mardanya, Tay-Rong Chang, Jing-Yang You, Yuan-Ping Feng, Guangming Cheng, Jia-Xin Yin, Nana Shumiya, Tyler A. Cochran, Xian P. Yang, Maksim Litskevich, Nan Yao, Kenji Watanabe, Takashi Taniguchi, Hua Zhang , et al. (2 additional authors not shown)

Abstract: Ongoing advances in superconductors continue to revolutionize technology thanks to the increasingly versatile and robust availability of lossless supercurrent. In particular high supercurrent density can lead to more efficient and compact power transmission lines, high-field magnets, as well as high-performance nanoscale radiation detectors and superconducting spintronics. Here, we report the disc… ▽ More Ongoing advances in superconductors continue to revolutionize technology thanks to the increasingly versatile and robust availability of lossless supercurrent. In particular high supercurrent density can lead to more efficient and compact power transmission lines, high-field magnets, as well as high-performance nanoscale radiation detectors and superconducting spintronics. Here, we report the discovery of an unprecedentedly high superconducting critical current density (17 MA/cm2 at 0 T and 7 MA/cm2 at 8 T) in 1T'-WS2, exceeding those of all reported two-dimensional superconductors to date. 1T'-WS2 features a strongly anisotropic (both in- and out-of-plane) superconducting state that violates the Pauli paramagnetic limit signaling the presence of unconventional superconductivity. Spectroscopic imaging of the vortices further substantiates the anisotropic nature of the superconducting state. More intriguingly, the normal state of 1T'-WS2 carries topological properties. The band structure obtained via angle-resolved photoemission spectroscopy and first-principles calculations points to a Z2 topological invariant. The concomitance of topology and superconductivity in 1T'-WS2 establishes it as a topological superconductor candidate, which is promising for the development of quantum computing technology. △ Less

Submitted 26 January, 2023; originally announced January 2023.

Journal ref: Phys. Rev. Materials 7, L071801 (2023)

How wavelength affects the hydrodynamic performance of two accelerating mirror-symmetric slender swimmers

Authors: Zhonglu Lin, Dongfang Liang, Amneet Pal Singh Bhalla, Ahmed A. Sheikh Al-Shabab, Martin Skote, Wei Zheng, Yu Zhang

Abstract: Fish schools are capable of simultaneous linear acceleration. To reveal the underlying hydrodynamic mechanism, we numerically investigate how Reynolds number $ Re = 1000 - 2000 $, Strouhal number $ St = 0.2 - 0.7 $ and wavelength $ λ= 0.5 - 2 $ affect the mean net thrust and net propulsive efficiency of two side-by-side hydrofoils undulating in anti-phase. In total, $ 550 $ cases are simulated usi… ▽ More Fish schools are capable of simultaneous linear acceleration. To reveal the underlying hydrodynamic mechanism, we numerically investigate how Reynolds number $ Re = 1000 - 2000 $, Strouhal number $ St = 0.2 - 0.7 $ and wavelength $ λ= 0.5 - 2 $ affect the mean net thrust and net propulsive efficiency of two side-by-side hydrofoils undulating in anti-phase. In total, $ 550 $ cases are simulated using immersed boundary method. The thrust increases significantly with wavelength and Strouhal number, yet only slightly with the Reynolds number. We apply a symbolic regression algorithm to formulate this relationship. Furthermore, we find that mirror-symmetric schooling can achieve a \textit{net} thrust more than ten times that of a single swimmer, especially at low Reynolds numbers. The highest efficiency is obtained at $ St = 0.5 $ and $ λ= 1.2 $, where $ St $ is consistent with that observed in the linear-accelerating natural swimmers, \eg Crevalle jack. Six distinct flow structures are identified. The highest thrust corresponds to an asymmetric flow pattern, whereas the highest efficiency occurs when the flow is symmetric with converging vortex streets. △ Less

Submitted 22 July, 2023; v1 submitted 21 December, 2022; originally announced December 2022.

Comments: This paper has been accepted by Physics of Fluids. This is the accepted version

Active beam steering enabled by photonic crystal surface emitting laser

Authors: Mingjin Wang, Zihao Chen, Yuanbo Xu, Jingxuan Chen, Jiahao Si, Zheng Zhang Chao Peng, Wanhua Zheng

Abstract: Emitting light towards on-demand directions is important for various optoelectronic applications, such as optical communication, displaying, and ranging. However, almost all existing directional emitters are assemblies of passive optical antennae and external light sources, which are usually bulky, fragile, and with unendurable loss of light power. Here we theoretically propose and experimentally… ▽ More Emitting light towards on-demand directions is important for various optoelectronic applications, such as optical communication, displaying, and ranging. However, almost all existing directional emitters are assemblies of passive optical antennae and external light sources, which are usually bulky, fragile, and with unendurable loss of light power. Here we theoretically propose and experimentally demonstrate a new conceptual design of directional emitter, by using a single surface-emitting laser source itself to achieve dynamically controlled beam steering. The laser is built on photonic crystals that operates near the band edges in the continuum. By shrinking laser sizes into tens-of-wavelength, the optical modes quantize in three-dimensional momentum space, and each of them directionally radiates towards the far-field. Further utilizing the luminescence spectrum shifting effect under current injection, we consecutively select a sequence of modes into lasing action and show the laser maintaining in single mode operation with linewidths at a minimum of $1.8$ MHz and emitting power of $\sim$ ten milliwatts, and we demonstrate fast beam steering across a range of $3.2^\circ \times 4^\circ$ in a time scale of $500$ nanoseconds. Our work proposes a novel method for on-chip active beam steering, which could pave the way for the development of automotive, industrial, and robotic applications. △ Less

Submitted 7 October, 2022; originally announced October 2022.

Comments: 23 pages, 5 figures

Entanglement-enhanced magnetic induction tomography

Authors: Wenqiang Zheng, Hengyan Wang, Rebecca Schmieg, Alan Oesterle, Eugene S. Polzik

Abstract: Magnetic induction tomography (MIT) is a sensing protocol, exploring conductive objects via their response to radio-frequency magnetic fields. MIT is used in nondestructive testing ranging from geophysics to medical applications. Atomic magnetometers, employed as MIT sensors, allow for significant improvement of the MIT sensitivity and for exploring its quantum limits. Here we report entanglement-… ▽ More Magnetic induction tomography (MIT) is a sensing protocol, exploring conductive objects via their response to radio-frequency magnetic fields. MIT is used in nondestructive testing ranging from geophysics to medical applications. Atomic magnetometers, employed as MIT sensors, allow for significant improvement of the MIT sensitivity and for exploring its quantum limits. Here we report entanglement-enhanced MIT with an atomic magnetometer used as the sensing element. We generate an entangled and spin squeezed state of atoms of the sensor by stroboscopic quantum non-demolition measurement. We then utilize this spin state to demonstrate the improvement of one-dimensional MIT sensitivity beyond the standard quantum limit. △ Less

Submitted 4 February, 2023; v1 submitted 5 September, 2022; originally announced September 2022.

IDP-PGFE: An Interpretable Disruption Predictor based on Physics-Guided Feature Extraction

Authors: Chengshuo Shen, Wei Zheng, Yonghua Ding, Xinkun Ai, Fengming Xue, Yu Zhong, Nengchao Wang, Li Gao, Zhipeng Chen, Zhoujun Yang, Zhongyong Chen, Yuan Pan, J-TEXT team

Abstract: Disruption prediction has made rapid progress in recent years, especially in machine learning (ML)-based methods. Understanding why a predictor makes a certain prediction can be as crucial as the prediction's accuracy for future tokamak disruption predictors. The purpose of most disruption predictors is accuracy or cross-machine capability. However, if a disruption prediction model can be interpre… ▽ More Disruption prediction has made rapid progress in recent years, especially in machine learning (ML)-based methods. Understanding why a predictor makes a certain prediction can be as crucial as the prediction's accuracy for future tokamak disruption predictors. The purpose of most disruption predictors is accuracy or cross-machine capability. However, if a disruption prediction model can be interpreted, it can tell why certain samples are classified as disruption precursors. This allows us to tell the types of incoming disruption and gives us insight into the mechanism of disruption. This paper designs a disruption predictor called Interpretable Disruption Predictor based On Physics-guided feature extraction (IDP-PGFE) on J-TEXT. The prediction performance of the model is effectively improved by extracting physics-guided features. A high-performance model is required to ensure the validity of the interpretation results. The interpretability study of IDP-PGFE provides an understanding of J-TEXT disruption and is generally consistent with existing comprehension of disruption. IDP-PGFE has been applied to the disruption due to continuously increasing density towards density limit experiments on J-TEXT. The time evolution of the PGFE features contribution demonstrates that the application of ECRH triggers radiation-caused disruption, which lowers the density at disruption. While the application of RMP indeed raises the density limit in J-TEXT. The interpretability study guides intuition on the physical mechanisms of density limit disruption that RMPs affect not only the MHD instabilities but also the radiation profile, which delays density limit disruption. △ Less

Submitted 26 September, 2024; v1 submitted 28 August, 2022; originally announced August 2022.

Comments: 17 pages, 13 figures

Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor

Authors: Wei Zheng, Fengming Xue, Ming Zhang, Zhongyong Chen, Chengshuo Shen, Xinkun Ai, Nengchao Wang, Dalong Chen, Bihao Guo, Yonghua Ding, Zhipeng Chen, Zhoujun Yang, Biao Shen, Bingjia Xiao, Yuan Pan

Abstract: Predicting disruptions across different tokamaks is a great obstacle to overcome. Future tokamaks can hardly tolerate disruptions at high performance discharge. Few disruption discharges at high performance can hardly compose an abundant training set, which makes it difficult for current data-driven methods to obtain an acceptable result. A machine learning method capable of transferring a disrupt… ▽ More Predicting disruptions across different tokamaks is a great obstacle to overcome. Future tokamaks can hardly tolerate disruptions at high performance discharge. Few disruption discharges at high performance can hardly compose an abundant training set, which makes it difficult for current data-driven methods to obtain an acceptable result. A machine learning method capable of transferring a disruption prediction model trained on one tokamak to another is required to solve the problem. The key is a disruption prediction model containing a feature extractor that is able to extract common disruption precursor traces in tokamak diagnostic data, and a transferable disruption classifier. Based on the concerns above, the paper first presents a deep fusion feature extractor designed specifically for extracting disruption precursor features from common diagnostics on tokamaks according to currently known precursors of disruption, providing a promising foundation for transferable models. The fusion feature extractor is proved by comparing with manual feature extraction on J-TEXT. Based on the feature extractor trained on J-TEXT, the disruption prediction model was transferred to EAST data with mere 20 discharges from EAST experiment. The performance is comparable with a model trained with 1896 discharges from EAST. From the comparison among other model training scenarios, transfer learning showed its potential in predicting disruptions across different tokamaks. △ Less

Submitted 19 August, 2022; originally announced August 2022.

Elastic turbulence homogenizes fluid transport in stratified porous media

Authors: Christopher A. Browne, Richard B. Huang, Callie W. Zheng, Sujit S. Datta

Abstract: Many key environmental, industrial, and energy processes rely on controlling fluid transport within subsurface porous media. These media are typically structurally heterogeneous, often with vertically-layered strata of distinct permeabilities -- leading to uneven partitioning of flow across strata, which can be undesirable. Here, using direct in situ visualization, we demonstrate that polymer addi… ▽ More Many key environmental, industrial, and energy processes rely on controlling fluid transport within subsurface porous media. These media are typically structurally heterogeneous, often with vertically-layered strata of distinct permeabilities -- leading to uneven partitioning of flow across strata, which can be undesirable. Here, using direct in situ visualization, we demonstrate that polymer additives can homogenize this flow by inducing a purely-elastic flow instability that generates random spatiotemporal fluctuations and excess flow resistance in individual strata. In particular, we find that this instability arises at smaller imposed flow rates in higher-permeability strata, diverting flow towards lower-permeability strata and helping to homogenize the flow. Guided by the experiments, we develop a parallel-resistor model that quantitatively predicts the flow rate at which this homogenization is optimized for a given stratified medium. Thus, our work provides a new approach to homogenizing fluid and passive scalar transport in heterogeneous porous media. △ Less

Submitted 12 July, 2022; originally announced July 2022.

Hardware-algorithm collaborative computing with photonic spiking neuron chip based on integrated Fabry-Pérot laser with saturable absorber

Authors: Shuiying Xiang, Yuechun Shi, Xingxing Guo, Yahui Zhang, Hongji Wang, Dianzhuang Zheng, Ziwei Song, Yanan Han, Shuang Gao, Shihao Zhao, Biling Gu, Hailing Wang, Xiaojun Zhu, Lianping Hou, Xiangfei Chen, Wanhua Zheng, Xiaohua Ma, Yue Hao

Abstract: Photonic neuromorphic computing has emerged as a promising avenue toward building a low-latency and energy-efficient non-von-Neuman computing system. Photonic spiking neural network (PSNN) exploits brain-like spatiotemporal processing to realize high-performance neuromorphic computing. However, the nonlinear computation of PSNN remains a significant challenging. Here, we proposed and fabricated a… ▽ More Photonic neuromorphic computing has emerged as a promising avenue toward building a low-latency and energy-efficient non-von-Neuman computing system. Photonic spiking neural network (PSNN) exploits brain-like spatiotemporal processing to realize high-performance neuromorphic computing. However, the nonlinear computation of PSNN remains a significant challenging. Here, we proposed and fabricated a photonic spiking neuron chip based on an integrated Fabry-Pérot laser with a saturable absorber (FP-SA) for the first time. The nonlinear neuron-like dynamics including temporal integration, threshold and spike generation, refractory period, and cascadability were experimentally demonstrated, which offers an indispensable fundamental building block to construct the PSNN hardware. Furthermore, we proposed time-multiplexed spike encoding to realize functional PSNN far beyond the hardware integration scale limit. PSNNs with single/cascaded photonic spiking neurons were experimentally demonstrated to realize hardware-algorithm collaborative computing, showing capability in performing classification tasks with supervised learning algorithm, which paves the way for multi-layer PSNN for solving complex tasks. △ Less

Submitted 18 April, 2022; originally announced April 2022.

Comments: 10 pages, 8 figures

Non-equilibrium Phonon Thermal Resistance at MoS2/Oxide and Graphene/Oxide Interfaces

Authors: Weidong Zheng, Connor J. McClellan, Eric Pop, Yee Kan Koh

Abstract: Accurate measurements and physical understanding of thermal boundary resistance (R) of two-dimensional (2D) materials are imperative for effective thermal management of 2D electronics and photonics. In previous studies, heat dissipation from 2D material devices was presumed to be dominated by phonon transport across the interfaces. In this study, we find that in addition to phonon transport, therm… ▽ More Accurate measurements and physical understanding of thermal boundary resistance (R) of two-dimensional (2D) materials are imperative for effective thermal management of 2D electronics and photonics. In previous studies, heat dissipation from 2D material devices was presumed to be dominated by phonon transport across the interfaces. In this study, we find that in addition to phonon transport, thermal resistance between non-equilibrium phonons in the 2D materials could play a critical role too when the 2D material devices are internally self-heated, either optically or electrically. We accurately measure R of oxide/MoS2/oxide and oxide/graphene/oxide interfaces for three oxides (SiO2, HfO2, Al2O3) by differential time-domain thermoreflectance (TDTR). Our measurements of R across these interfaces with external heating are 2-to-4 times lower than previously reported R of the similar interfaces measured by Raman thermometry with internal self-heating. Using a simple model, we show that the observed discrepancy can be explained by an additional internal thermal resistance (Rint) between non-equilibrium phonons present during Raman measurements. We subsequently estimate that for MoS2 and graphene, Rint is about 31 and 22 m2 K/GW, respectively. The values are comparable to the thermal resistance due to finite phonon transmission across interfaces of 2D materials and thus cannot be ignored in the design of 2D material devices. Moreover, the non-equilibrium phonons also lead to a different temperature dependence than that by phonon transport. As such, our work provides important insights into physical understanding of heat dissipation in 2D material devices. △ Less

Submitted 14 April, 2022; originally announced April 2022.

Reconfigurable optical logic operations through scattering media with wavefront shaping

Authors: Zhipeng Yu, Yuchen Song, Tianting Zhong, Huanhao Li, Wei Zheng, Puxiang Lai

Abstract: Optical logic gates are fundamental blocks of optical computing to accelerate information processing. While significant progress has been achieved in recent years, existing implementations typically rely on dedicated structures that are predesigned to modulate the phases and intensities of optical beams accurately for specific logic functions. Thus, these optical gates usually lack reconfigurabili… ▽ More Optical logic gates are fundamental blocks of optical computing to accelerate information processing. While significant progress has been achieved in recent years, existing implementations typically rely on dedicated structures that are predesigned to modulate the phases and intensities of optical beams accurately for specific logic functions. Thus, these optical gates usually lack reconfigurability and are incapable within or through dynamic complex media/environment, such as fog and turbid water. In this work, as a conceptual demonstration, we propose reconfigurable optical logic operations through scattering media with transmission matrix-based wavefront shaping. A light beam is reflected by a spatial light modulator divided into several subregions functioning as logic units, with each displayed with predetermined wavefronts via transmission matrix-based wavefront shaping. Each modulated wavefront transmits through the scattering medium to form a desired light field. The interference of these light fields generates bright optical focus at pre-assigned locations, representing different logic states. As a proof of concept, we experimentally demonstrate five basic logic functions (AND, OR, NOT, NAND, NOR). As the transmission matrix of the scattering medium/system can be measured instantly to adapt to environment perturbation, the method, if further engineered, opens new venues towards reconfigurable optical logic computing in a dynamically complex environment. △ Less

Submitted 27 August, 2022; v1 submitted 19 January, 2022; originally announced January 2022.

Comments: 26 pages,12 figures

Semi-supervised Impedance Inversion by Bayesian Neural Network Based on 2-d CNN Pre-training

Authors: Muyang Ge, Wenlong Wang, Wangxiangming Zheng

Abstract: Seismic impedance inversion can be performed with a semi-supervised learning algorithm, which only needs a few logs as labels and is less likely to get overfitted. However, classical semi-supervised learning algorithm usually leads to artifacts on the predicted impedance image. In this artical, we improve the semi-supervised learning from two aspects. First, by replacing 1-d convolutional neural n… ▽ More Seismic impedance inversion can be performed with a semi-supervised learning algorithm, which only needs a few logs as labels and is less likely to get overfitted. However, classical semi-supervised learning algorithm usually leads to artifacts on the predicted impedance image. In this artical, we improve the semi-supervised learning from two aspects. First, by replacing 1-d convolutional neural network (CNN) layers in deep learning structure with 2-d CNN layers and 2-d maxpooling layers, the prediction accuracy is improved. Second, prediction uncertainty can also be estimated by embedding the network into a Bayesian inference framework. Local reparameterization trick is used during forward propagation of the network to reduce sampling cost. Tests with Marmousi2 model and SEAM model validate the feasibility of the proposed strategy. △ Less

Submitted 20 November, 2021; originally announced November 2021.

Controlling higher-orbital quantum phases of ultracold atoms via coupling to optical cavities

Authors: Hui Tan, Jinsen Han, Wei Zheng, Jianmin Yuan, Yongqiang Li

Abstract: Orbital degree of freedom plays an important role in understanding exotic phenomena of strongly correlated materials. We study strongly correlated ultracold bosonic gases coupled to a high-finesse cavity, pumped by a blue-detuned laser in the transverse direction. Based on an extended Bose-Hubbard model with parameters adapted to recent experiments, we find that by tuning the reflection of pump la… ▽ More Orbital degree of freedom plays an important role in understanding exotic phenomena of strongly correlated materials. We study strongly correlated ultracold bosonic gases coupled to a high-finesse cavity, pumped by a blue-detuned laser in the transverse direction. Based on an extended Bose-Hubbard model with parameters adapted to recent experiments, we find that by tuning the reflection of pump laser, atoms can be selectively transferred to the odd-parity $p$-orbital, or to even-parity $d$-orbital band of a two-dimensional square lattice, accompanied with cavity-photon excitations. By interacting with cavity field, atoms self-organize to form stable higher-orbital superfluid and Mott-insulating phases with orbital-density waves, as a result of cavity induced orbital-flip processes. Our study opens the route to manipulate orbital degrees of freedom in strongly correlated quantum gases via coupling to optical cavities. △ Less

Submitted 28 August, 2021; v1 submitted 23 August, 2021; originally announced August 2021.

Comments: 6 pages, 4 figures, with supplementary materials

Highly Efficient Ultrathin Light Emitting Diodes based on Perovskite Nanocrystals

Authors: Qun Wan, Weilin Zheng, Chen Zoub, Francesco Carulli, Congyang Zhang, Haili Song, Mingming Liu, Qinggang Zhang, Lih Y. Lin, Long Kong, Liang Li, Sergio Brovelli

Abstract: Light-emitting diodes based on perovskite nanocrystals (PNCs-LEDs) have gained great interest for next-generation display and lighting technologies prized for their color purity, high brightness and luminous efficiency approaching the intrinsic limit imposed by extraction of electroluminescence from the device structure. Although the time is ripe for the development of effective light outcoupling… ▽ More Light-emitting diodes based on perovskite nanocrystals (PNCs-LEDs) have gained great interest for next-generation display and lighting technologies prized for their color purity, high brightness and luminous efficiency approaching the intrinsic limit imposed by extraction of electroluminescence from the device structure. Although the time is ripe for the development of effective light outcoupling strategies to further boost the device performance, this technologically relevant aspect of PNC-LEDs is still without a definitive solution. Here, following theoretical guidelines and without the integration of complex photonic structures, we realize stable PNC-LEDs with EQE as high as 29.2% (average EQE=24.7%), which substantially break the outcoupling limit of common PNC-LEDs and systematically surpass any previous perovskite-based device. Key to such unprecedented performance is channeling the recombination zone in PNC emissive layers as thin as 10 nm, which we achieve by finely balancing the electron and hole transport using CsPbBr3 PNCs resurfaced with a nickel oxide layer. The ultra-thin approach general and, in principle, applicable to other perovskite nanostructures for fabricating highly efficient, color tunable transparent LEDs ideal for unobtrusive screens and displays and is compatible with the integration of photonic components for further enhanced performance. △ Less

Submitted 3 June, 2021; originally announced June 2021.