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20152026
most citedMore Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

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quant-ph2024★ 5 cited

Flow-Based Sampling for Entanglement Entropy and the Machine Learning of Defects

Andrea Bulgarelli, Elia Cellini, Karl Jansen +5

We introduce a novel technique to numerically calculate Rényi entanglement entropies in lattice quantum field theory using generative models. We describe how flow-based approaches…

quant-ph2021★ 6 cited

Reinforcement Learning Approach to Shortcuts between Thermodynamic States with Extra Constraints

Rongxing Xu

We propose a systematic method based on reinforcement learning (RL) techniques to find the optimal path that can minimize the total entropy production between two equilibrium state…

quant-ph2021★ 21 cited

Exponential clustering of bipartite quantum entanglement at arbitrary temperatures

Tomotaka Kuwahara, Keiji Saito

Macroscopic quantum effects play central roles in the appearance of inexplicable phenomena in low-temperature quantum many-body physics. Such macroscopic quantumness is often evalu…

quant-ph2021★ 149 cited

Fate of measurement-induced phase transition in long-range interactions

Takaaki Minato, Koudai Sugimoto, Tomotaka Kuwahara +1

We consider quantum many-body dynamics under quantum measurements, where the measurement-induced phase transitions (MIPs) occur when changing the frequency of the measurement. In t…

quant-ph2021★ 41 cited

Lieb-Robinson bound and almost-linear light-cone in interacting boson systems

Tomotaka Kuwahara, Keiji Saito

In this work, we investigate how quickly local perturbations propagate in interacting boson systems with Bose-Hubbard-type Hamiltonians. In general, these systems have unbounded lo…

quant-ph2020★ 59 cited

Absence of fast scrambling in thermodynamically stable long-range interacting systems

Tomotaka Kuwahara, Keiji Saito

In this study, we investigate out-of-time-order correlators (OTOCs) in systems with power-law decaying interactions such as , where is the distance. In such systems, th…