Search Results for author: W. Zhang

Found 8 papers, 3 papers with code

Machine Learning for UAV Propeller Fault Detection based on a Hybrid Data Generation Model

no code implementations3 Feb 2023 J. J. Tong, W. Zhang, F. Liao, C. F. Li, Y. F. Zhang

This paper describes the development of an on-board data-driven system that can monitor and localize the fault in a quadrotor unmanned aerial vehicle (UAV) and at the same time, evaluate the degree of damage of the fault under real scenarios.

Fault Detection

Porting WarpX to GPU-accelerated platforms

1 code implementation28 Jan 2021 A. Myers, A. Almgren, L. D. Amorim, J. Bell, L. Fedeli, L. Ge, K. Gott, D. P. Grote, M. Hogan, A. Huebl, R. Jambunathan, R. Lehe, C. Ng, M. Rowan, O. Shapoval, M. Thévenet, J. -L. Vay, H. Vincenti, E. Yang, N. Zaïm, W. Zhang, Y. Zhao, E. Zoni

WarpX is a general purpose electromagnetic particle-in-cell code that was originally designed to run on many-core CPU architectures.

Computational Physics Distributed, Parallel, and Cluster Computing Accelerator Physics

Insight-HXMT observations of Swift J0243.6+6124: the evolution of RMS pulse fractions at super-Eddington luminosity

no code implementations24 Dec 2020 P. J. Wang, L. D. Kong, S. Zhang, Y. P. Chen, S. N. Zhang, J. L. Qu, L. Ji, L. Tao, M. Y. Ge, F. J. Lu, L. Chen, L. M. Song, T. P. Li, Y. P. Xu, X. L. Cao, Y. Chen, C. Z. Liu, Q. C. Bu, C. Cai, Z. Chang, G. Chen, T. X. Chen, Y. B. Chen, W. Cui, W. W. Cui, J. K. Deng, Y. W. Dong, Y. Y. Du, M. X. Fu, G. H. Gao, H. Gao, M. Gao, Y. D. Gu, J. Guan, C. C. Guo, D. W. Han, Y. Huang, J. Huo, S. M. Jia, L. H. Jiang, W. C. Jiang, J. Jin, Y. J. Jin, B. Li, C. K. Li, G. Li, M. S. Li, W. Li, X. Li, X. B. Li, X. F. Li, Y. G. Li, Z. W. Li, X. H. Liang, J. Y. Liao, B. S. Liu, G. Q. Liu, H. W. Liu, X. J. Liu, Y. N. Liu, B. Lu, X. F. Lu, Q. Luo, T. Luo, X. Ma, B. Meng, Y. Nang, J. Y. Nie, G. Ou, N. Sai, R. C. Shang, X. Y. Song, L. Sun, Y. Tan, Y. L. Tuo, C. Wang, G. F. Wang, J. Wang, L. J. Wang, W. S. Wang, Y. S. Wang, X. Y. Wen, B. Y. Wu, B. B. Wu, M. Wu, G. C. Xiao, S. Xiao, S. L. Xiong, J. W. Yang, S. Yang, Yan Ji Yang, Yi Jung Yang, Q. B. Yi, Q. Q. Yin, Y. You, A. M. Zhang, C. M. Zhang, F. Zhang, H. M. Zhang, J. Zhang, T. Zhang, W. C. Zhang, W. Zhang, W. Z. Zhang, Y. F. Zhang, Y. J. Zhang, Y. Zhang, Zhao Zhang, Zhi Zhang, Z. L. Zhang, H. S. Zhao, X. F. Zhao, S. J. Zheng, Y. G. Zheng, D. K. Zhou, J. F. Zhou, Y. X. Zhu, Y. Zhu, R. L. Zhuang

The results show a general trend of the pulse fraction increasing with luminosity and energy at super-critical luminosity.

High Energy Astrophysical Phenomena

A Multi-task Two-stream Spatiotemporal Convolutional Neural Network for Convective Storm Nowcasting

no code implementations27 Oct 2020 W. Zhang, H. Liu, P. Li, L. Han

Second, we employ a concise two-stream convolutional neural network to extract spatial and temporal cues for nowcasting.

Multi-Task Learning

Improved Coupling of Hydrodynamics and Nuclear Reactions via Spectral Deferred Corrections

1 code implementation10 Aug 2019 M. Zingale, M. P. Katz, J. B. BelL, M. L. Minion, A. J. Nonaka, W. Zhang

Simulations in stellar astrophysics involve the coupling of hydrodynamics and nuclear reactions under a wide variety of conditions, from simmering convective flows to explosive nucleosynthesis.

Computational Physics Instrumentation and Methods for Astrophysics

Challenging local realism with human choices

1 code implementation11 May 2018 The BIG Bell Test Collaboration, C. Abellán, A. Acín, A. Alarcón, O. Alibart, C. K. Andersen, F. Andreoli, A. Beckert, F. A. Beduini, A. Bendersky, M. Bentivegna, P. Bierhorst, D. Burchardt, A. Cabello, J. Cariñe, S. Carrasco, G. Carvacho, D. Cavalcanti, R. Chaves, J. Cortés-Vega, A. Cuevas, A. Delgado, H. de Riedmatten, C. Eichler, P. Farrera, J. Fuenzalida, M. García-Matos, R. Garthoff, S. Gasparinetti, T. Gerrits, F. Ghafari Jouneghani, S. Glancy, E. S. Gómez, P. González, J. -Y. Guan, J. Handsteiner, J. Heinsoo, G. Heinze, A. Hirschmann, O. Jiménez, F. Kaiser, E. Knill, L. T. Knoll, S. Krinner, P. Kurpiers, M. A. Larotonda, J. -Å. Larsson, A. Lenhard, H. Li, M. -H. Li, G. Lima, B. Liu, Y. Liu, I. H. López Grande, T. Lunghi, X. Ma, O. S. Magaña-Loaiza, P. Magnard, A. Magnoni, M. Martí-Prieto, D. Martínez, P. Mataloni, A. Mattar, M. Mazzera, R. P. Mirin, M. W. Mitchell, S. Nam, M. Oppliger, J. -W. Pan, R. B. Patel, G. J. Pryde, D. Rauch, K. Redeker, D. Rieländer, M. Ringbauer, T. Roberson, W. Rosenfeld, Y. Salathé, L. Santodonato, G. Sauder, T. Scheidl, C. T. Schmiegelow, F. Sciarrino, A. Seri, L. K. Shalm, S. -C. Shi, S. Slussarenko, M. J. Stevens, S. Tanzilli, F. Toledo, J. Tura, R. Ursin, P. Vergyris, V. B. Verma, T. Walter, A. Wallraff, Z. Wang, H. Weinfurter, M. M. Weston, A. G. White, C. Wu, G. B. Xavier, L. You, X. Yuan, A. Zeilinger, Q. Zhang, W. Zhang, J. Zhong

A Bell test requires spatially distributed entanglement, fast and high-efficiency detection and unpredictable measurement settings.

Quantum Physics

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