English

Characterizing maximally many-body entangled fermionic states by using $M$-body density matrix

Quantum Physics 2025-06-25 v2

Abstract

Fermionic Hamiltonians play a critical role in quantum chemistry, one of the most promising use cases for near-term quantum computers. However, since encoding nonlocal fermionic statistics using conventional qubits results in significant computational overhead, fermionic quantum hardware, such as fermion atom arrays, were proposed as a more efficient platform. In this context, we here study the many-body entanglement structure of fermionic NN-particle states by concentrating on MM-body reduced density matrices (DMs) across various bipartitions in Fock space. The von Neumann entropy of the reduced DM is a basis independent entanglement measure which generalizes the traditional quantum chemistry concept of the one-particle DM entanglement, which characterizes how a single fermion is entangled with the rest. We carefully examine upper bounds on the MM-body entanglement, which are analogous to the volume law of conventional entanglement measures. To this end we establish a connection between MM-body reduced DM and the mathematical structure of hypergraphs. Specifically, we show that a special class of hypergraphs, known as tt-designs, corresponds to maximally entangled fermionic states. Finally, we explore fermionic many-body entanglement in random states. We semianalytically demonstrate that the distribution of reduced DMs associated with random fermionic states corresponds to the trace-fixed Wishart-Laguerre random matrix ensemble. In the limit of large single-particle dimension DD and a non-zero filling fraction, random states asymptotically become absolutely maximally entangled.

Keywords

Cite

@article{arxiv.2412.09576,
  title  = {Characterizing maximally many-body entangled fermionic states by using $M$-body density matrix},
  author = {Irakli Giorgadze and Haixuan Huang and Jordan Gaines and Elio J. König and Jukka I. Väyrynen},
  journal= {arXiv preprint arXiv:2412.09576},
  year   = {2025}
}

Comments

21 + 3 pages, 5 figures

R2 v1 2026-06-28T20:32:58.274Z