Efficient preparation of the AKLT State with Measurement-based Imaginary Time Evolution
Tianqi Chen, Tim Byrnes

TL;DR
This paper introduces a measurement-based imaginary time evolution method to efficiently prepare the AKLT ground state, achieving exponential speedup and compatibility with qubit-based simulators.
Contribution
It presents a novel deterministic approach for AKLT state preparation using MITE, significantly reducing resource requirements compared to traditional methods.
Findings
Constant scaling with the number of AKLT sites
Exponential improvement over naive convergence estimates
Compatible with qubit-based quantum simulators
Abstract
Quantum state preparation plays a crucial role in several areas of quantum information science, in applications such as quantum simulation, quantum metrology and quantum computing. However, typically state preparation requires resources that scale exponentially with the problem size, due to their probabilistic nature or otherwise, making studying such models challenging. In this article, we propose a method to prepare the ground state of the Affleck-Lieb-Kennedy-Tasaki (AKLT) model deterministically using a measurement-based imaginary time evolution (MITE) approach. By taking advantage of the special properties of the AKLT state, we show that it can be prepared efficiently using the MITE approach. Estimates based on the convergence of a sequence of local projections, as well as direct evolution of the MITE algorithm suggest a constant scaling with respect to the number of AKLT sites,…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Neural Networks and Reservoir Computing
