Measuring multipartite quantum correlations by thermodynamic work extraction
ORAL
Abstract
While bipartite quantum correlations have been extensively studied, multipartite quantum correlations in many-body systems remain elusive due to their complex structure. In particular, a primary challenge lies in the fact that the calculation of multipartite quantum correlation measure often requires exponential cost. In this work, we tackle this problem by adopting a thermodynamic approach; we introduce a measure of multipartite quantum correlations based on the difference in extractable thermodynamic work by global operations and local operations and classical communication (LOCC). This can be regarded as a multipartite generalization of the work deficit, which has attracted attention as a thermodynamic measure of bipartite quantum correlation. Importantly, we develop an efficient calculation method of the multipartite work deficit. This efficient method works for a class of quantum many-body systems described by matrix product states (MPS), where the numerical cost is shown to be proportional to the system size, significantly reducing the exponential cost required for the direct calculations. We demonstrate this efficient method in the AKLT state and the cluster state, and analytically obtain the exact values of this measure. We further show that a quantum phase transition described by MPS is well captured by the multipartite work deficit.
*T.Y. is supported by World-leading Inno- vative Graduate Study Program for Materials Research, Information, and Technology (MERIT-WINGS) of the University of Tokyo. T.Y. is also supported by JSPS KAKENHI Grant No. JP23KJ0672. N.Y. wishes to thank JST PRESTO No. JPMJPR2119, JST Grant Number JPMJPF2221, JST CREST Grant Number JP- MJCR23I4, IBM Quantum, and JST ERATO Grant Number JPMJER2302, Japan. T.S. is supported by JST ERATO-FS Grant Number JPMJER2204, JST ERATO Grant Number JPMJER2302, Japan, JSPS KAKENHI Grant Number JP19H05796, and JST CREST Grant Number JPMJCR20C1. N.Y. and T.S. are also sup- ported by Institute of AI and Beyond of the University of Tokyo.
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Publication:T. Yada, N. Yoshioka, and T. Sagawa, arXiv:2407.04058 (2024).
Presenters
Toshihiro Yada
University of Tokyo
Authors
Toshihiro Yada
University of Tokyo
Nobuyuki Yoshioka
University of Tokyo
Takahiro Sagawa
Univ of Tokyo
University of Tokyo
The University of Tokyo
Department of Applied Physics, The University of Tokyo