Zobrazeno 1 - 10
of 5 023
pro vyhledávání: '"yuan, Dong"'
Observation of quantum information collapse-and-revival in a strongly-interacting Rydberg atom array
Autor:
Xiang, De-Sheng, Zhang, Yao-Wen, Liu, Hao-Xiang, Zhou, Peng, Yuan, Dong, Zhang, Kuan, Zhang, Shun-Yao, Xu, Biao, Liu, Lu, Li, Yitong, Li, Lin
Interactions of isolated quantum many-body systems typically scramble local information into the entire system and make it unrecoverable. Ergodicity-breaking systems possess the potential to exhibit fundamentally different information scrambling dyna
Externí odkaz:
http://arxiv.org/abs/2410.15455
Publikováno v:
IEEE International Conference on Data Mining 2024
In knowledge distillation, a primary focus has been on transforming and balancing multiple distillation components. In this work, we emphasize the importance of thoroughly examining each distillation component, as we observe that not all elements are
Externí odkaz:
http://arxiv.org/abs/2410.14741
Publikováno v:
Phys. Rev. A 110, 032413 (2024)
Error-correction codes are central for fault-tolerant information processing. Here we develop a rigorous framework to describe various coding models based on quantum resource theory of superchannels. We find, by treating codings as superchannels, a h
Externí odkaz:
http://arxiv.org/abs/2409.09416
This paper introduces a novel approach to enhancing cross-view localization, focusing on the fine-grained, sequential localization of street-view images within a single known satellite image patch, a significant departure from traditional one-to-one
Externí odkaz:
http://arxiv.org/abs/2408.15569
Radio frequency (RF) signals have been proved to be flexible for human silhouette segmentation (HSS) under complex environments. Existing studies are mainly based on a one-shot approach, which lacks a coherent projection ability from the RF domain. A
Externí odkaz:
http://arxiv.org/abs/2407.19244
Federated Learning (FL) offers innovative solutions for privacy-preserving collaborative machine learning (ML). Despite its promising potential, FL is vulnerable to various attacks due to its distributed nature, affecting the entire life cycle of FL
Externí odkaz:
http://arxiv.org/abs/2407.06754
While deep learning has become a core functional module of most software systems, concerns regarding the fairness of ML predictions have emerged as a significant issue that affects prediction results due to discrimination. Intersectional bias, which
Externí odkaz:
http://arxiv.org/abs/2407.01595
Autor:
Ren, Yuchen, Chen, Zhiyuan, Qiao, Lifeng, Jing, Hongtai, Cai, Yuchen, Xu, Sheng, Ye, Peng, Ma, Xinzhu, Sun, Siqi, Yan, Hongliang, Yuan, Dong, Ouyang, Wanli, Liu, Xihui
RNA plays a pivotal role in translating genetic instructions into functional outcomes, underscoring its importance in biological processes and disease mechanisms. Despite the emergence of numerous deep learning approaches for RNA, particularly univer
Externí odkaz:
http://arxiv.org/abs/2406.10391
The security guarantee of AI-enabled software systems (particularly using deep learning techniques as a functional core) is pivotal against the adversarial attacks exploiting software vulnerabilities. However, little attention has been paid to a syst
Externí odkaz:
http://arxiv.org/abs/2406.08688
We demonstrate the existence of prethermal discrete time crystals whose sub-harmonic response is entirely localized to zero-dimensional corner modes. Within the exponentially long prethermal regime, we show that the robustness of these corner modes a
Externí odkaz:
http://arxiv.org/abs/2406.01686