Detecting entanglement in quantum many-body systems via permutation moments
Zhenhuan Liu, Yifan Tang, Hao Dai, Pengyu Liu, Shu Chen, Xiongfeng Ma

TL;DR
This paper introduces a new framework using permutation moments to detect multipartite entanglement in quantum many-body systems, overcoming limitations of traditional methods and revealing entanglement transitions.
Contribution
The authors develop a permutation moments-based framework for entanglement detection that is experimentally feasible and applicable to complex many-body quantum systems.
Findings
Effective detection of entanglement in multi-qubit Ising models
Quantification of entanglement with physical meaning
Observation of entanglement scaling transition
Abstract
Multipartite entanglement plays an essential role in both quantum information science and many-body physics. Due to the exponentially large dimension and complex geometric structure of the state space, the detection of entanglement in many-body systems is extremely challenging in reality. Conventional means, like entanglement witness and entropy criterion, either highly depend on the prior knowledge of the studied systems or the detection capability is relatively weak. In this work, we propose a framework for designing multipartite entanglement criteria based on permutation moments, which have an effective implementation with either the generalized control-SWAP quantum circuits or the random unitary techniques. These criteria show strong detection capability in the multi-qubit Ising model with a long-range Hamiltonian. The quantities associated with these criteria have clear…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum many-body systems
