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  • Letter
  • Open Access

Efficient adiabatic preparation of tensor network states

Zhi-Yuan Wei, Daniel Malz, and J. Ignacio Cirac

  • Max-Planck-Institut für Quantenoptik, Hans-Kopfermann-Straße 1, D-85748 Garching, Germany and Munich Center for Quantum Science and Technology (MCQST), Schellingstraße 4, D-80799 München, Germany

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Phys. Rev. Research 5, L022037 – Published 22 May, 2023

DOI: https://doi.org/10.1103/PhysRevResearch.5.L022037

Abstract

We propose and study a specific adiabatic path to prepare those tensor network states that are unique ground states of few-body parent Hamiltonians in finite lattices, which include normal tensor network states, as well as other relevant nonnormal states. This path guarantees a gap for finite systems and allows for efficient numerical simulation. In one dimension, we numerically investigate the preparation of a family of states with varying correlation lengths and the one-dimensional Affleck-Kennedy-Lieb-Tasaki (AKLT) state and show that adiabatic preparation can be much faster than standard methods based on sequential preparation. We also apply the method to the two-dimensonal AKLT state on the hexagonal lattice, for which no method based on sequential preparation is known, and show that it can be prepared very efficiently for relatively large lattices.

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Outline

Information

Phys. Rev. Research 5, L022037– Published 22 May, 2023
  • Received 26 September 2022
  • Revised 19 January 2023
  • Accepted 18 April 2023
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Open access publication funded by the Max Planck Society.

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