Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Zhang, Shengzhi"'
Autor:
Lee, Sangyun, Zhang, Shengzhi, Thomas, S. M., Pressley, L., Bridges, C. A., Choi, Eun Sang, Zapf, Vivien S., Winter, Stephen M., Lee, Minseong
BaCo$_2$(AsO$_4$)$_2$ (BCAO), a honeycomb cobaltate, is considered a promising candidate for materials displaying the Kitaev quantum spin liquid state. This assumption is based on the distinctive characteristics of Co$^{2+}$ ions (3$d^7$) within an o
Externí odkaz:
http://arxiv.org/abs/2408.00622
Autor:
Zhang, Shengzhi, Lee, Sangyun, Brosha, Eric, Huang, Qing, Zhou, Haidong, Zapf, Vivien S., Lee, Minseong
We have investigated the magnetic properties and mapped out the phase diagram of the honeycomb magnet Na2Co2TeO6 with Co 3d7 in out-of-plane magnetic fields. This material has previously been proposed to show nearest-neighbor Kitaev interactions betw
Externí odkaz:
http://arxiv.org/abs/2405.13935
Autor:
Lee, Sangyun, Woods, Andrew J., Lee, Minseong, Zhang, Shengzhi, Choi, Eun Sang, Scheie, A. O., Tennant, D. A., Xing, J., Sefat, A. S., Movshovich, R.
A quantum spin liquid (QSL) is a state of matter characterized by fractionalized quasiparticle excitations, quantum entanglement, and a lack of long-range magnetic order. However, QSLs have evaded definitive experimental observation. Several Yb$^{3+}
Externí odkaz:
http://arxiv.org/abs/2402.06788
Autor:
Lv, Peizhuo, Ma, Hualong, Chen, Kai, Zhou, Jiachen, Zhang, Shengzhi, Liang, Ruigang, Zhu, Shenchen, Li, Pan, Zhang, Yingjun
Recently, numerous highly-valuable Deep Neural Networks (DNNs) have been trained using deep learning algorithms. To protect the Intellectual Property (IP) of the original owners over such DNN models, backdoor-based watermarks have been extensively st
Externí odkaz:
http://arxiv.org/abs/2401.15239
Autor:
Yao, Weiliang, Huang, Qing, Xie, Tao, Podlesnyak, Andrey, Brassington, Alexander, Xing, Chengkun, Mudiyanselage, Ranuri S. Dissanayaka, Xie, Weiwei, Zhang, Shengzhi, Lee, Minseong, Zapf, Vivien S., Bai, Xiaojian, Tennant, D. Alan, Liu, Jian, Zhou, Haidong
Continuous spin excitations are widely recognized as one of the hallmarks of novel spin states in quantum magnets, such as quantum spin liquids (QSLs). Here, we report the observation of such kind of excitations in K2Ni2(SO4)3, which consists of two
Externí odkaz:
http://arxiv.org/abs/2303.16384
Autor:
Zhang, Shengzhi, Lee, Sangyun, Woods, Andrew J., Peria, William, Thomas, Sean M., Movshovich, Roman, Brosha, Eric, Huang, Qing, Zhou, Haidong, Zapf, Vivien S., Lee, Minseong
The 3$d^7$ Co$^{2+}$-based insulating magnet \NCTO{} has recently been reported to have strong Kitaev interactions on a honeycomb lattice, and is thus being considered as a Kitaev quantum spin liquid candidate. However, due to the existence of other
Externí odkaz:
http://arxiv.org/abs/2212.03849
Autor:
Lv, Peizhuo, Li, Pan, Zhu, Shenchen, Zhang, Shengzhi, Chen, Kai, Liang, Ruigang, Yue, Chang, Xiang, Fan, Cai, Yuling, Ma, Hualong, Zhang, Yingjun, Meng, Guozhu
Recent years have witnessed tremendous success in Self-Supervised Learning (SSL), which has been widely utilized to facilitate various downstream tasks in Computer Vision (CV) and Natural Language Processing (NLP) domains. However, attackers may stea
Externí odkaz:
http://arxiv.org/abs/2209.03563
Autor:
Zhou, Qihang, Cao, Wenzhuo, Jia, Xiaoqi, Zhang, Shengzhi, Chen, Jiayun, Jiang, Nan, Zhang, Weijuan, Du, Haichao, Song, Zhenyu, Huang, Qingjia
Publikováno v:
In Computers & Security September 2024 144
Autor:
Lv, Peizhuo, Ma, Hualong, Zhou, Jiachen, Liang, Ruigang, Chen, Kai, Zhang, Shengzhi, Yang, Yunfei
Recently, transformer architecture has demonstrated its significance in both Natural Language Processing (NLP) and Computer Vision (CV) tasks. Though other network models are known to be vulnerable to the backdoor attack, which embeds triggers in the
Externí odkaz:
http://arxiv.org/abs/2111.11870
Due to the wide use of highly-valuable and large-scale deep neural networks (DNNs), it becomes crucial to protect the intellectual property of DNNs so that the ownership of disputed or stolen DNNs can be verified. Most existing solutions embed backdo
Externí odkaz:
http://arxiv.org/abs/2103.13628