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38th International Cosmic Ray Conference, ICRC 2023

作者： Yang, Ci Zhou, Xunxiu Chen, Xuejian Huang, Daihui Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. School of Physical Science and Technology Southwest Jiaotong University Chengdu610031 China Key Laboratory of Particle Astrophyics Experimental Physics Division Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Physics and Astronomy Sun Yat-sen University Zhuhai519000 China School of Physics Sun Yat-sen University Guangdong Guangzhou510275 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen University Zhuhai519000 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Départeme

The Large high Altitude Air Shower Observatory (LHAASO) has three sub-arrays, KM2A, WCDA, and WFCTA. As the major array of LHAASO, KM2A has been operating stably in shower mode. To study the near-earth atmospheric electric field (AEF) effect on the trigger event rate during thunderstorms, Monte Carlo simulations are performed with CORSIKA and G4KM2A. According to the simulations, the shower rate variations are found to be strongly dependent on the strength and polarity of the AEF. The shower rates increase with the field intensity. In positive AEF (defined as the direction pointing towards the ground), the increased amplitude is less than that in negative AEF. With the same field strength 1000 V/cm, the value exceeds 12% in a negative field, and merely is up to 6% in the positive one. The dependence of the trigger rate variation on the thickness of the AEF layer is also simulated. The shower event rate increases dramatically at small thickness, and then the trend of variation slows down with the AEF layer thickness. This indicates that the AEF with larger layer thickness has more deflection effects on the development of an extensive air shower. The shower rate variations are also found to be dependent on the primary zenith angle. Our simulation results could be useful in understanding the variation of trigger rate detected by LHAASO-KM2A during thunderstorms. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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Investigation of the Ultra-high-Energy gamma-ray emission from the Northern Fermi Bubble with LHAASO-KM2A

Investigation of the Ultra-High-Energy gamma-ray emission fr...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Zhang, Yi He, Jiayin Zhang, Rui Zhao, Shiping Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences 9 Jiangsu Nanjing210023 China University of Science and Technology of China Anhui Hefei230026 China Institute of Frontier and Interdisciplinary Science Shandong University Shandong Qingdao266237 China Key Laboratory of Particle Astrophysics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays [Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University 519000 Zhuhai Guangdong Guangzhou510275 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Département de Physique Nucléaire et Cor

We analyze gamma-ray emission from the Northern Fermi bubble region at the ultra-high-energy range, using the data collected by LHAASO-KM2A from December 2019 to September 2022. Employing an improved gamma/hadron separation method, the median energy of the gamma rays is above 25 TeV. We perform the "direct integral method" in the background estimation;however, no significant excess is observed. Consequently, we present the expected upper limits for gamma-ray emissions within the Fermi bubble region at this energy range. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Gamma rays

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Pream: Enhancing HPC storage system performance with pre-allocated metadata management mechanism 21

Pream: Enhancing HPC storage system performance with pre-all...

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21st IEEE International Conference on high performance computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Li, Hongbo Cheng, Peng Chen, Zhiguang Xiao, Nong School of Data and Computer Science Sun Yat-Sen University Guangzhou China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

ISBN: (纸本)9781728120584

With the convergence of high performance computing (HPC) and big data, processing a large volume of scientific data on HPC systems is getting increased attentions. However, supporting these data-intensive workloads on HPC systems that are geared for compute-intensive workloads presents a new challenge in data management. Typical HPC systems consist of a large collection of compute nodes and use parallel file systems (PFSs) for persistent data storage. Although PFSs provide concurrent I/O bandwidth and perform well for large sequential write/read requests, its performance is bottlenecked by expensive metadata operations. Moreover, data-intensive applications with bursty I/O patterns or generate a large number of temporary files exacerbate the shortcomings. In this paper, we propose Pream, a light-weight metadata management framework that aim to address these challenges. Pream targets scenarios of supporting data-intensive workloads that generates a huge number of temporary files on diskless compute nodes. Pream pre-allocates file metadata from the metadata server, and manages these metadata locally to accelerate metadata operations. While newly created temporary files keep residing in PFSs, open/create requests of these temporary files can be handled by Pream locally without connecting with PFSs. Our evaluation demonstrates that Pream can outperform Lustre in many workloads and reduce latency of metadata operation efficiently. © 2019 IEEE.

关键词： Metadata

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Ionic Hydrogen Bond-Assisted Catalytic Construction of Nitrogen Stereogenic Center via Formal Desymmetrization of Remote Diols

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Angewandte Chemie 2024年第31期136卷

作者： Zhongfu Luo Minghong Liao Wei Li Sha Zhao Kun Tang Prof. Pengcheng Zheng Prof. Dr. Yonggui Robin Chi Dr. Xinglong Zhang Prof. Dr. Xingxing Wu National Key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural Bioengineering Ministry of Education Guizhou University Huaxi District Guiyang 550025 China School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637371 Singapore Institute of High Performance Computing (IHPC) A*STAR Singapore 138632 Singapore

The control of noncarbon stereogenic centers is of profound importance owing to their enormous interest in bioactive compounds and chiral catalyst or ligand design for enantioselective synthesis. Despite various elegant approaches have been achieved for construction of S-, P-, Si- and B-stereocenters over the past decades, the catalyst-controlled strategies to govern the formation of N -stereogenic compounds have garnered less attention. Here, we disclose the first organocatalytic approach for efficient access to a wide range of nitrogen-stereogenic compounds through a desymmetrization approach. Intriguingly, the pro-chiral remote diols, which are previously not well addressed with enantiocontrol, are well differentiated by potent chiral carbene-bound acyl azolium intermediates. Preliminary studies shed insights on the critical importance of the ionic hydrogen bond (IHB) formed between the dimer aggregate of diols to afford the chiral N-oxide products that feature a tetrahedral nitrogen as the sole stereogenic element with good yields and excellent enantioselectivities. Notably, the chiral N-oxide products could offer an attractive strategy for chiral ligand design and discovery of potential antibacterial agrochemicals.

关键词： nitrogen-stereogenicity organocatalysis N-heterocyclic carbene desymmetrization chiral N-oxides

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CNN Feature Boosted SeqSLAM for Real-Time Loop Closure Detection

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Chinese Journal of Electronics 2018年第3期27卷 488-499页

作者： BAI Dongdong WANG Chaoqun ZHANG Bo YI Xiaodong YANG Xuejun College of Computer National University of Defense Technology State Key Laboratory of High Performance Computing National University of Defense Technology National Institute of Defense Technology Innovation

This paper proposes an efficient and robust Loop closure detection(LCD) method based on Convolutional neural network(CNN) feature. The primary method is called SeqCNNSLAM, in which both the outputs of the intermediate layer of a pre-trained CNN and the outputs of traditional sequence-based matching procedure are incorporated, making it possible to handle the viewpoint and condition variance properly. An acceleration algorithm for SeqCNNSLAM is developed to reduce the search range for the current image, resulting in a new LCD method called A-SeqCNNSLAM. To improve the applicability of A-SeqCNNSLAM to new environments, O-SeqCNNSLAM is proposed for online parameters adjustment in A-SeqCNNSLAM. In addition to the above work, we further put forward a promising idea to enhance Seq SLAM by integrating the both CNN features and VLAD's advantages called patch based Seq CNNSLAM(P-SeqCNNSLAM), and provide some preliminary experimental results to reveal its performance.

关键词： Simultaneous localization and mapping(SLAM) Loop closure detection(LCD) Convolutional neural network(CNN) SeqSLAM SeqCNNSLAM A-SeqCNNSLAM O-SeqCNNSLAM P-SeqCNNSLAM

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Loophole-free test of macroscopic realism via high-order correlations of measurement

arXiv

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arXiv 2024年

作者： Wang, Ping Chen, Chong Liao, Hao Vorobyov, Vadim V. Wrachtrup, Jörg Liu, Ren-Bao College of Education for the Future Beijing Normal University Zhuhai519087 China Department of Physics The Chinese University of Hong Kong New Territories Shatin Hong Kong Centre for Quantum Coherence The Chinese University of Hong Kong New Territories Shatin Hong Kong The Hong Kong Institute of Quantum Information Science and Technology The Chinese University of Hong Kong New Territories Shatin Hong Kong National Engineering Laboratory on Big Data System Computing Technology Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China 3rd Institute of Physics Research Center SCoPE and IQST University of Stuttgart Stuttgart70569 Germany New Cornerstone Science Laboratory The Chinese University of Hong Kong New Territories Shatin Hong Kong

Test of macroscopic realism (MR) is key to understanding the foundation of quantum mechanics. Due to the existence of the non-invasive measurability loophole and other interpretation loopholes, however, such test remains an open question. Here we propose a general inequality based on high-order correlations of measurements for a loophole-free test of MR at the weak signal limit. Importantly, the inequality is established using the statistics of raw data recorded by classical devices, without requiring a specific model for the measurement process, so its violation would falsify MR without the interpretation loophole. The non-invasive measurability loophole is also closed, since the weak signal limit can be verified solely by measurement data (using the relative scaling behaviors of different orders of correlations). We demonstrate that the inequality can be broken by a quantum spin model. The inequality proposed here provides an unambiguous test of the MR principle and is also useful to characterizing quantum coherence. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum theory

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Robust second-order correlation of twin parametric beams generated by amplified spontaneous parametric down-conversion

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Chinese Optics Letters 2020年第12期18卷 63-67页

作者： Kunpeng Jia Xiaohan Wang Xinjie LV Ping Xu Zhenlin Wang ZhiWei Wuang Gang Zhao Yan-Xiao Gong Zhenda Xie Shining Zhu National Laboratory of Solid State Microstructures School of PhysicsSchool of Electronic Science and EngineeringCollege of Engineering and Applied Sciencesand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China Institute for Quantum Information and State Key Laboratory of High Performance Computing.College of Computing National University of Defense TechnologyChangsha 410073China Mesoscopic Optics and Quantum Electronics Laboratory University of California Los AngelesCciliforniaCA 90095USA

We report an observation of the second-order correlation between twin beams generated by amplified spontaneous parametric down-conversion operating above threshold with kilowatt-level peak power, from a periodically poled Li Ta O3 crystal via a single-pass scheme. Photocurrent correlation was measured because of the bright photon streams, with raw visibility of 37.9% or 97.3% after electronic filtering. As expected in our theory, this correlation is robust and insensitive to parametric gain and detection loss, enabling important applications in optical communications, precision measurement, and nonlocal imaging.

关键词： amplified spontaneous parametric down-con version robust second-order correlation high-gain twin beams

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O2iJoin： An Efficient Index-Based Algorithm for Overlap Interval Join

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Journal of Computer Science & technology 2018年第5期33卷 1023-1038页

作者： Ji-Zhou Luo Sheng-Fei Shi Guang Yang Hong-Zhi Wang Jian-Zhong Li School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China Guangdong Key Laboratory of Popular High Performance Computers Key Laboratory of Service Computing and Application Shenzhen 518000 China

Time intervals are often associated with tuples to represent their valid time in temporal relations, where overlap join is crucial for various kinds of queries. Many existing overlap join algorithms use indices based on tree structures such as quad-tree, B＋-tree and interval tree. These algorithms usually have high CPU cost since deep path traversals are unavoidable, which makes them not so competitive as data-partition or plane-sweep based algorithms. This paper proposes an efficient overlap join algorithm based on a new two-layer flat index named as Overlap Interval Inverted Index （i.e., O2i Index）. It uses an array to record the end points of intervals and approximates the nesting structures of intervals via two functions in the first layer, and the second layer uses inverted lists to trace all intervals satisfying the approximated nesting structures. With the help of the new index, the join algorithm only visits the must-be-scanned lists and skips all others. Analyses and experiments on both real and synthetic datasets show that the proposed algorithm is as competitive as the state-of-the-art algorithms.

关键词： overlap interval join temporal relation overlap inverted index join algorithm

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Light Weight Automatic Modulation Classification for Edge Devices in Spectrum Sensing Wireless Networks

Light Weight Automatic Modulation Classification for Edge De...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Wanli Ma Bo Zhang Yuli Zhang Sudan Han Jianchao Zheng Jinlin Peng Yuhua Tang National Innovation Institute of Defense Technology P. R. China State Key Laboratory of High Performance Computing National University of Defense Technology P. R. China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

With the aid of software-defined radio (SDR) technologies, the recent progress in automatic modulation classification of high accuracy using deep neural networks (DNNs) may play an increasingly important role in spectrum monitoring. However, the computational demand brought by the stochastic gradient descent method in the training process is unbearable in edge devices. In this paper, we proposed a lightweight trained neural network for an Internet of thing (IoT) chip by separating the learning process from the inference process. Besides, we analyzed the influence of the size of the convolution kernel and the length of the sampling samples on the calculation and memory usage of the neural network Experimental results on actual datasets show that the proposed network occupies about 700kb of memory, and requires a single sample floating-point operation per second (FLOPs) of about 400k, while achieving high accuracy of 95.58% at a signal-to-noise ratio (SNR) from -10 to 19dB.

关键词： Convolution Neural networks Training Modulation Kernel Feature extraction Signal to noise ratio

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Superconductivity in pressurized trilayer La4Ni3O10-δ single crystals

arXiv

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arXiv 2023年

作者： Zhu, Yinghao Peng, Di Zhang, Enkang Pan, Bingying Chen, Xu Chen, Lixing Ren, Huifen Liu, Feiyang Hao, Yiqing Li, Nana Xing, Zhenfang Lan, Fujun Han, Jiyuan Wang, Junjie Jia, Donghan Wo, Hongliang Gu, Yiqing Gu, Yimeng Ji, Li Wang, Wenbin Gou, Huiyang Shen, Yao Ying, Tianping Chen, Xiaolong Yang, Wenge Cao, Huibo Zheng, Changlin Zeng, Qiaoshi Guo, Jiangang Zhao, Jun State Key Laboratory of Surface Physics Department of Physics Fudan University Shanghai200433 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Shanghai201203 China College of Physics and Optoelectronic Engineering Ocean University of China Shandong Qingdao266100 China Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China Neutron Scattering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Center for High Pressure Science and Technology Advanced Research Shanghai201203 China School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China Center for High Pressure Science and Technology Advanced Research Beijing100094 China State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China Institute of Nanoelectronics and Quantum Computing Fudan University Shanghai200433 China Shanghai Branch Hefei National Laboratory Shanghai201315 China

The pursuit of discovering new high-temperature superconductors that diverge from the copper-based paradigm1-3 carries profound implications for elucidating mechanisms behind superconductivity and may also enable new applications4-8. Here, our investigation reveals that application of pressure effectively suppresses the spin and charge order in trilayer nickelate La4Ni3O10-δ single crystals, leading to the emergence of superconductivity with a maximum critical temperature (Tc) of around 30 K at 69.0 GPa. The DC susceptibility measurements confirm a substantial diamagnetic response below Tc, indicating the presence of bulk superconductivity with a volume fraction exceeding 80%. In the normal state, we observe a "strange metal" behavior, characterized by a linear temperature-dependent resistance extending up to 300 K. Furthermore, the layer-dependent superconductivity observed hints at a unique interlayer coupling mechanism specific to nickelates, setting them apart from cuprates in this regard. Our findings provide crucial insights into the fundamental mechanisms underpinning superconductivity, while also introducing a new material platform to explore the intricate interplay between the spin/charge order, flat band structures, interlayer coupling, strange metal behavior and high-temperature superconductivity. © 2023, CC BY-NC-ND.

关键词： Single crystals

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