Zobrazeno 1 - 10
of 1 242
pro vyhledávání: '"WANG Zhenlin"'
Autor:
Chen, Mengwen, Wang, Chenyu, Jia, Kunpeng, Tian, Xiao-Hui, Tang, Jie, Zhu, Chunxi, Gu, Xiaowen, Zhao, Zexing, Wang, Zikang, Ye, Zhilin, Tang, Ji, Zhang, Yong, Yan, Zhong, Qian, Guang, Jin, Biaobing, Wang, Zhenlin, Zhu, Shi-Ning, Xie, Zhenda
While thin film lithium niobate (TFLN) is known for efficient signal generation, on-chip signal amplification remains challenging from fully integrated optical communication circuits. Here we demonstrate the first continuous-wave-pump optical paramet
Externí odkaz:
http://arxiv.org/abs/2411.10721
Autor:
Li, Zhongfu, Li, Shiqi, Yan, Bei, Chan, Hsun-Chi, Li, Jing, Guan, Jun, Bi, Wengang, Xiang, Yuanjiang, Gao, Zhen, Zhang, Shuang, Zhan, Peng, Wang, Zhenlin, Xie, Biye
Emergent collective modes in lattices give birth to many intriguing physical phenomena in condensed matter physics. Among these collective modes, large-area modes typically feature small-level spacings, while a mode with stable frequency tends to be
Externí odkaz:
http://arxiv.org/abs/2401.10928
Autor:
Zhang, Xiaoxuan, Gupta, Tryaksh, Wang, Zhenlin, Trewartha, Amalie, Anapolsky, Abraham, Garikipati, Krishna
In this work, we present a computational framework for coupled electro-chemo-(nonlinear) mechanics at the particle scale for solid-state batteries. The framework accounts for interfacial fracture between the active particles and solid electrolyte due
Externí odkaz:
http://arxiv.org/abs/2309.13463
Autor:
Li, Chuandong, Sha, Sai, Zeng, Yangqing, Yang, Xiran, Luo, Yingwei, Wang, Xiaolin, Wang, Zhenlin
As more data-intensive tasks with large footprints are deployed in virtual machines (VMs), huge pages are widely used to eliminate the increasing address translation overhead. However, once the huge page mapping is established, all the base page regi
Externí odkaz:
http://arxiv.org/abs/2307.10618
Autor:
Lu, Yuzhe, Qin, Yilong, Zhai, Runtian, Shen, Andrew, Chen, Ketong, Wang, Zhenlin, Kolouri, Soheil, Stepputtis, Simon, Campbell, Joseph, Sycara, Katia
Out-of-distribution (OOD) data poses serious challenges in deployed machine learning models, so methods of predicting a model's performance on OOD data without labels are important for machine learning safety. While a number of methods have been prop
Externí odkaz:
http://arxiv.org/abs/2305.15640
Autor:
Li, Jing, Wang, Hongfei, Jia, Shiyin, Zhan, Peng, Lu, Minghui, Wang, Zhenlin, Chen, Yanfeng, Xie, Bi-Ye
Topological phases based on tight-binding models have been extensively studied in recent decades. By mimicking the linear combination of atomic orbitals in tight-binding models based on the evanescent couplings between resonators in classical waves,
Externí odkaz:
http://arxiv.org/abs/2304.08179
Autor:
Kinnunen, Patrick C., Srivastava, Siddhartha, Wang, Zhenlin, Ho, Kenneth K. Y., Humphries, Brock A., Chen, Siyi, Linderman, Jennifer J., Luker, Gary D., Luker, Kathryn E., Garikipati, Krishna
Targeting signaling pathways that drive cancer cell migration or proliferation is a common therapeutic approach. A popular experimental technique, the scratch assay, measures the migration and proliferation-driven cell closure of a defect in a conflu
Externí odkaz:
http://arxiv.org/abs/2302.09445
Out-of-distribution (OOD) data poses serious challenges in deployed machine learning models as even subtle changes could incur significant performance drops. Being able to estimate a model's performance on test data is important in practice as it ind
Externí odkaz:
http://arxiv.org/abs/2302.05018
Autor:
Wang, Lizheng, Xiong, Junlin, Cheng, Bin, Dai, Yudi, Wang, Fuyi, Pan, Chen, Cao, Tianjun, Liu, Xiaowei, Wang, Pengfei, Chen, Moyu, Yan, Shengnan, Liu, Zenglin, Xiao, Jingjing, Xu, Xianghan, Wang, Zhenlin, Shi, Youguo, Cheong, Sang-Wook, Zhang, Haijun, Liang, Shi-Jun, Miao, Feng
The building block of in-memory computing with spintronic devices is mainly based on the magnetic tunnel junction with perpendicular interfacial anisotropy (p-MTJ). The resulting asymmetric write and read-out operations impose challenges in downscali
Externí odkaz:
http://arxiv.org/abs/2211.06610
The memory demand of virtual machines (VMs) is increasing, while DRAM has limited capacity and high power consumption. Non-volatile memory (NVM) is an alternative to DRAM, but it has high latency and low bandwidth. We observe that the VM with heterog
Externí odkaz:
http://arxiv.org/abs/2209.13111