Here we briefly revisit entanglement in bipartite quantum systems and mention issues to its extension to multipartite situations. Finally, we indicate the role of entanglement in the description of many-body systems through matrix product states.
Quantum information theory has considerably helped in the understanding of quantum many-body systems. The role of quantum correlations and in particular, bipartite entanglement, has become crucial to characterise, classify and simulate quantum many body systems. Furthermore, the scaling of entanglement has inspired modifications to numerical techniques for the simulation of many-body systems leading to the, now established, area of tensor networks. However, the notions and methods brought by quantum information do not end with bipartite entanglement. There are other forms of correlations embedded in the ground, excited and thermal states of quantum many-body systems that also need to be explored and might be utilised as potential resources for quantum technologies. The aim of this work is to review the most recent developments regarding correlations in quantum many-body systems focussing on multipartite entanglement, quantum nonlocality, quantum discord, mutual information but also other non classical measures of correlations based on quantum coherence. Moreover, we also discuss applications of quantum metrology in quantum many-body systems.
These notes provide an introduction to tensor-network methods in quantum many-body physics, with an emphasis on matrix-product states (MPS). They develop the basic tensor-network language, including graphical notation, virtual indices, bond dimensions, gauge freedom, canonical forms, QR and singular-value decompositions, and the role of entanglement in controlling the efficiency of the representation. The main MPS algorithms are then introduced, including contractions, correlation functions, matrix-product operators, DMRG, and time-evolution methods. The notes also briefly discuss projected entangled-pair states (PEPS) as a higher-dimensional generalization of MPS, together with the basic ideas behind approximate PEPS contraction. Finally, tensor-network representations of mixed states, quantum channels, and Lindblad dynamics are presented, with applications to thermal states and open quantum systems. The presentation is accompanied by short Julia code examples based on ITensor, ITensorMPS, and TensorMixedStates. These notes were written for the 9th Les Houches Summer School on Computational Physics: Open Quantum Systems, held in June 2026.
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.