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arXiv · 2105.04317

Quantum Variational Learning of the Entanglement Hamiltonian

Christian Kokail·Bhuvanesh Sundar·Torsten V. Zache·Andreas Elben·Benoît Vermersch·Marcello Dalmonte·Rick van Bijnen·Peter Zoller
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Abstract

Learning the structure of the entanglement Hamiltonian (EH) is central to characterizing quantum many-body states in analog quantum simulation. We describe a protocol where spatial deformations of the many-body Hamiltonian, physically realized on the quantum device, serve as an efficient variational ansatz for a local EH. Optimal variational parameters are determined in a feedback loop, involving quench dynamics with the deformed Hamiltonian as a quantum processing step, and classical optimization. We simulate the protocol for the ground state of Fermi-Hubbard models in quasi-1D geometries, finding excellent agreement of the EH with Bisognano-Wichmann predictions. Subsequent on-device spectroscopy enables a direct measurement of the entanglement spectrum, which we illustrate for a Fermi Hubbard model in a topological phase.

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Christian Kokail, Bhuvanesh Sundar, Torsten V. Zache, Andreas Elben, Benoît Vermersch, Marcello Dalmonte, Rick van Bijnen, Peter Zoller. 2021-11-02. Quantum Variational Learning of the Entanglement Hamiltonian. https://doi.org/10.1103/physrevlett.127.170501

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