Measuring multipartite quantum correlations by thermodynamic work extraction
While bipartite quantum correlations have been extensively studied across various fields, the role of multipartite quantum correlations in many-body systems remains elusive due to their complex structure. A primary challenge lies in the fact that the calculation of multipartite quantum correlation measure often requires an exponential cost with respect to the system size. In this work, we address this problem by adopting a thermodynamic approach: We introduce a measure of multipartite quantum correlations based on the difference in extractable thermodynamic work between global operations and LOCC (local operations and classical communication). This can be regarded as a multipartite generalization of the bipartite work deficit, which has attracted attention as a thermodynamic measure of bipartite quantum correlation. Importantly, we develop an efficient method for computing the multipartite work deficit in a special class of quantum many-body systems described by matrix product states (MPS). The numerical cost of this method scales linearly with system size, significantly reducing the exponential overhead required for direct calculations. We apply this method to an MPS family and show that a quantum phase transition is well captured by the multipartite work deficit, which exhibits singular behavior at the transition point. Our work shows that the multipartite work deficit not only highlights the fundamental connection between multipartite quantum correlations and quantum thermodynamics, but also serves as an efficiently computable probe of the structures of quantum many-body systems.
Authors
- Karl J. Friston
Institutions
- RIKEN (JP)
- Judd Systems Technologies (United States) (US)
- The University of Tokyo (JP)
Publication Details
- Journal
- Physical Review Research
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1103/s8h3-5ptz
- Citations
- 2
- Primary Topic
- Advanced Thermodynamics and Statistical Mechanics
- Type
- article
- Field-Weighted Citation Impact
- 2.65