Multi-Particle Tunneling Transport at Strongly-Correlated Interfaces

Kavli Affiliate: Mamoru Matsuo | First 5 Authors: Hiroyuki Tajima, Daigo Oue, Mamoru Matsuo, , | Summary: We elucidate the multi-particle transport of pair- and spin-tunnelings in strongly correlated interfaces. Not only usual single-particle tunneling but also interaction-induced multi-particle tunneling processes naturally arise from a conventional microscopic model without any empirical parameters, through the overlap […]


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Valley transport driven by dynamic lattice distortion

Kavli Affiliate: Mamoru Matsuo | First 5 Authors: Yuya Ominato, Daigo Oue, Mamoru Matsuo, , | Summary: Angular momentum conversion between mechanical rotation and the valley degree of freedom in 2D Dirac materials is investigated theoretically. Coupling between the valley and vorticity of dynamic lattice distortions is derived by applying the k.p method to 2D […]


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Charge order and superconductivity in a minimal two-band model for infinite-layer nickelates

Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Hong-Chen Jiang, Brian Moritz, Thomas P. Devereaux, Chunjing Jia | Summary: The recent discovery of superconductivity in infinite-layer nickelates has drawn considerable attention; however, a consensus on the fundamental building blocks and common ingredients necessary to understand and describe their ground states and emergent properties […]


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Finding Local Minimax Points via (Stochastic) Cubic-Regularized GDA: Global Convergence and Complexity

Kavli Affiliate: Yi Zhou | First 5 Authors: Ziyi Chen, Qunwei Li, Yi Zhou, , | Summary: Standard gradient descent-ascent (GDA)-type algorithms can only find stationary points in nonconvex minimax optimization, which are far more sub-optimal than local minimax points. In this work, we develop GDA-type algorithms that globally converge to local minimax points in […]


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Assisted Learning for Organizations with Limited Data

Kavli Affiliate: Yi Zhou | First 5 Authors: Cheng Chen, Jiaying Zhou, Jie Ding, Yi Zhou, | Summary: We develop an assisted learning framework for assisting organization-level learners to improve their learning performance with limited and imbalanced data. In particular, learners at the organization level usually have sufficient computation resource, but are subject to stringent […]


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Assisted Learning for Organizations with Limited Imbalanced Data

Kavli Affiliate: Yi Zhou | First 5 Authors: Cheng Chen, Jiaying Zhou, Jie Ding, Yi Zhou, | Summary: In the era of big data, many big organizations are integrating machine learning into their work pipelines to facilitate data analysis. However, the performance of their trained models is often restricted by limited and imbalanced data available […]


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Subregion Spectrum Form Factor via Pseudo Entropy

Kavli Affiliate: Masahiro Nozaki | First 5 Authors: Kanato Goto, Masahiro Nozaki, Kotaro Tamaoka, , | Summary: We introduce a subsystem generalization of the spectral form factor via pseudo entropy, the von-Neumann entropy for the reduced transition matrix. We consider a transition matrix between the thermofield double state and its time-evolved state in two-dimensional conformal […]


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A comparative study of model approximation methods applied to economic MPC

Kavli Affiliate: Biao Huang | First 5 Authors: Zhiyinan Huang, Qinyao Liu, Jinfeng Liu, Biao Huang, | Summary: Economic model predictive control (EMPC) has attracted significant attention in recent years and is recognized as a promising advanced process control method for the next generation smart manufacturing. It can lead to improving economic performance but at […]


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