Entanglement diagnostics for efficient VQA optimization

Joonho Kim, Yaron Oz

Research output: Contribution to journalArticlepeer-review

Abstract

We consider information spreading measures in randomly initialized variational quantum circuits and introduce entanglement diagnostics for efficient variational quantum/classical computations. We establish a robust connection between entanglement measures and optimization accuracy by solving two eigensolver problems for Ising Hamiltonians with nearest-neighbor and long-range spin interactions. As the circuit depth affects the average entanglement of random circuit states, the entanglement diagnostics can identify a high-performing depth range for optimization tasks encoded in local Hamiltonians. We argue, based on an eigensolver problem for the Sachdev-Ye-Kitaev model, that entanglement alone is insufficient as a diagnostic to the approximation of volume-law entangled target states and that a large number of circuit parameters is needed for such an optimization task.

Original languageEnglish
Article number073101
JournalJournal of Statistical Mechanics: Theory and Experiment
Volume2022
Issue number7
DOIs
StatePublished - 1 Jul 2022

Keywords

  • entanglement entropies
  • quantum computation
  • quantum information

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