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 […]


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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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Phonon Thermal Hall Conductivity from Scattering with Collective Fluctuations

Kavli Affiliate: Leon Balents | First 5 Authors: Léo Mangeolle, Leon Balents, Lucile Savary, , | Summary: Because electrons and ions form a coupled system, it is a priori clear that the dynamics of the lattice should reflect symmetry breaking within the electronic degrees of freedom. This has been recently clearly evidenced for the case […]


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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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Shock Breakout in 3-Dimensional Red Supergiant Envelopes

Kavli Affiliate: Lars Bildsten | First 5 Authors: Jared A. Goldberg, Yan-fei Jiang, Lars Bildsten, , | Summary: Using Athena++, we perform 3D Radiation-Hydrodynamic calculations of the radiative breakout of the shock wave in the outer envelope of a red supergiant (RSG) which has suffered core collapse and will become a Type IIP supernova. The […]


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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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Minimising statistical errors in calibration of quantum-gate sets

Kavli Affiliate: David Gross | First 5 Authors: Yaiza Aragonés-Soria, René Otten, Tobias Hangleiter, Pascal Cerfontaine, David Gross | Summary: Calibration of quantum gates is a necessary hurdle to overcome on the way to a reliable quantum computer. In a recent paper, a protocol called Gate Set Calibration protocol (GSC) has been introduced and used […]


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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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APES: Articulated Part Extraction from Sprite Sheets

Kavli Affiliate: Matthew Fisher | First 5 Authors: Zhan Xu, Matthew Fisher, Yang Zhou, Deepali Aneja, Rushikesh Dudhat | Summary: Rigged puppets are one of the most prevalent representations to create 2D character animations. Creating these puppets requires partitioning characters into independently moving parts. In this work, we present a method to automatically identify such […]


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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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