{"title":"Operator-Projected Variational Quantum Imaginary Time Evolution","authors":"Aeishah Ameera Anuar, Francois Jamet, Fabio Gironella, Fedor Simkovic IV, Riccardo Rossi","doi":"arxiv-2409.12018","DOIUrl":null,"url":null,"abstract":"Variational Quantum Imaginary Time Evolution (VQITE) is a leading technique\nfor ground state preparation on quantum computers. A significant computational\nchallenge of VQITE is the determination of the quantum geometric tensor. We\nshow that requiring the imaginary-time evolution to be correct only when\nprojected onto a chosen set of operators allows to achieve a twofold reduction\nin circuit depth by bypassing fidelity estimations, and reduces measurement\ncomplexity from quadratic to linear in the number of parameters. We demonstrate\nby a simulation of the transverse-field Ising model that our algorithm achieves\na several orders of magnitude improvement in the number of measurements\nrequired for the same accuracy.","PeriodicalId":501226,"journal":{"name":"arXiv - PHYS - Quantum Physics","volume":"105 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Quantum Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.12018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Variational Quantum Imaginary Time Evolution (VQITE) is a leading technique
for ground state preparation on quantum computers. A significant computational
challenge of VQITE is the determination of the quantum geometric tensor. We
show that requiring the imaginary-time evolution to be correct only when
projected onto a chosen set of operators allows to achieve a twofold reduction
in circuit depth by bypassing fidelity estimations, and reduces measurement
complexity from quadratic to linear in the number of parameters. We demonstrate
by a simulation of the transverse-field Ising model that our algorithm achieves
a several orders of magnitude improvement in the number of measurements
required for the same accuracy.