Bridging quantum many-body scar and quantum integrability in Ising chains with transverse and longitudinal fields

Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Xiaoling Cui, , , | Summary: Quantum many-body scar (QMBS) and quantum integrability(QI) have been recognized as two distinct mechanisms for the breakdown of eigenstate thermalization hypothesis(ETH) in an isolated system. In this work, we reveal a smooth route to connect these two ETH-breaking mechanisms […]


Continue.. Bridging quantum many-body scar and quantum integrability in Ising chains with transverse and longitudinal fields

Bridging quantum many-body scar and quantum integrability in Ising chains with transverse and longitudinal fields

Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Xiaoling Cui, , , | Summary: Quantum many-body scar (QMBS) and quantum integrability(QI) have been recognized as two distinct mechanisms for the breakdown of eigenstate thermalization hypothesis(ETH) in an isolated system. In this work, we reveal a smooth route to connect these two ETH-breaking mechanisms […]


Continue.. Bridging quantum many-body scar and quantum integrability in Ising chains with transverse and longitudinal fields

Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search

Kavli Affiliate: Zheng Zhu | First 5 Authors: Han Xiao, Ziwei Wang, Zheng Zhu, Jie Zhou, Jiwen Lu | Summary: In this paper, we propose a Shapley value based method to evaluate operation contribution (Shapley-NAS) for neural architecture search. Differentiable architecture search (DARTS) acquires the optimal architectures by optimizing the architecture parameters with gradient descent, […]


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Spin Pumping into Anisotropic Dirac Electrons

Kavli Affiliate: Mamoru Matsuo | First 5 Authors: Takumi Funato, Takeo Kato, Mamoru Matsuo, , | Summary: We study spin pumping into an anisotropic Dirac electron system induced by microwave irradiation to an adjacent ferromagnetic insulator theoretically. We formulate the Gilbert damping enhancement due to the spin current flowing into the Dirac electron system using […]


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Enhanced superconductivity by near-neighbor attraction in the doped Hubbard model

Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Yao Wang, Jiajia Wen, Young Lee, Thomas Devereaux | Summary: Recent experiment has unveiled an anomalously strong electron-electron attraction in one-dimensional copper-oxide chain Ba$_{2-x}$Sr$_x$CuO$_{3+delta}$. While the near-neighbor electron attraction $V$ in the one-dimensional extended Hubbard chain has been examined recently, its effect in the Hubbard […]


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OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression

Kavli Affiliate: Zheng Zhu | First 5 Authors: Wanhua Li, Xiaoke Huang, Zheng Zhu, Yansong Tang, Xiu Li | Summary: This paper presents a language-powered paradigm for ordinal regression. Existing methods usually treat each rank as a category and employ a set of weights to learn these concepts. These methods are easy to overfit and […]


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NeMF: Neural Motion Fields for Kinematic Animation

Kavli Affiliate: Yi Zhou | First 5 Authors: Chengan He, Jun Saito, James Zachary, Holly Rushmeier, Yi Zhou | Summary: We present an implicit neural representation to learn the spatio-temporal space of kinematic motions. Unlike previous work that represents motion as discrete sequential samples, we propose to express the vast motion space as a continuous […]


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Collective effects in an incompressible electronic liquid

Kavli Affiliate: Yi Zhou | First 5 Authors: Jian-Jian Miao, Hui-Ke Jin, Yi Zhou, , | Summary: Starting from the Landau’s kinetic equation, we show that an electronic liquid in $d=2,3$ dimensions depicted by a Landau type effective theory will become incompressible on condition that the Landau parameters satisfy either (i) $1+F_{1}^{s}/d=0$ or (ii) $F_{0}^{s}to{}+infty$. […]


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Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors

Kavli Affiliate: Zheng Zhu | First 5 Authors: Jianfei Yang, Xiangyu Peng, Kai Wang, Zheng Zhu, Jiashi Feng | Summary: Domain Adaptation of Black-box Predictors (DABP) aims to learn a model on an unlabeled target domain supervised by a black-box predictor trained on a source domain. It does not require access to both the source-domain […]


Continue.. Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors