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  Efficient Adiabatic Preparation of Tensor Network States

Wei, Z., Malz, D., & Cirac, J. I. (2023). Efficient Adiabatic Preparation of Tensor Network States. Physical Review Research, 5: L022037. doi:10.1103/PhysRevResearch.5.L022037.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000B-37D0-C Version Permalink: https://hdl.handle.net/21.11116/0000-000F-80D8-C
Genre: Journal Article

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 Creators:
Wei, Zhiyuan1, 2, 3, Author           
Malz, Daniel1, 2, Author           
Cirac, J. Ignacio1, 2, Author           
Affiliations:
1Theory, Max Planck Institute of Quantum Optics, Max Planck Society, ou_1445571              
2MCQST - Munich Center for Quantum Science and Technology, External Organizations, ou_3330166              
3IMPRS (International Max Planck Research School), Max Planck Institute of Quantum Optics, Max Planck Society, ou_3164443              

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Free keywords: Quantum Physics, quant-ph
 Abstract: We propose and study a specific adiabatic path to prepare a family of 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 non-normal states. This path guarantees a gap and allows for efficient
numerical simulation. In 1D we numerically investigate the preparation of a
family of states with varying correlation lengths and the 1D 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 2D 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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Language(s): eng - English
 Dates: 2022-09-022023-04-182023-05-22
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: arXiv: 2209.01230v1
DOI: 10.1103/PhysRevResearch.5.L022037
Other: 6434
 Degree: -

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Project name : Hightech Agenda Bayern Plus
Grant ID : -
Funding program : -
Funding organization : Bavarian state government
Project name : ERC Advanced Grant QUENOCOBA
Grant ID : 742102
Funding program : EU Horizon 2020 program
Funding organization : European Commission (EC)
Project name : -
Grant ID : 899354 (FET Open SuperQuLAN)
Funding program : European Union’s Horizon 2020 research and innovation program
Funding organization : European Commission (EC)

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Title: Physical Review Research
Source Genre: Journal
 Creator(s):
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Publ. Info: College Park, Maryland, United States : American Physical Society (APS)
Pages: - Volume / Issue: 5 Sequence Number: L022037 Start / End Page: - Identifier: ISSN: 2643-1564
CoNE: https://pure.mpg.de/cone/journals/resource/2643-1564