A Case for Quantum Circuit Cutting for NISQ Applications: Impact of topology, determinism, and sparsity

Fuente: arXiv
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Main Authors: Li, Zirui, Guo, Minghao, Barad, Mayank, Tang, Wei, Zhang, Eddy Z., Huang, Yipeng
Format: Preprint
Published: 2024
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author Li, Zirui
Guo, Minghao
Barad, Mayank
Tang, Wei
Zhang, Eddy Z.
Huang, Yipeng
author_facet Li, Zirui
Guo, Minghao
Barad, Mayank
Tang, Wei
Zhang, Eddy Z.
Huang, Yipeng
contents We make the case that variational algorithm ansatzes for near-term quantum computing are well-suited for the quantum circuit cutting strategy. Previous demonstrations of circuit cutting focused on the exponential execution and postprocessing costs due to the cuts needed to partition a circuit topology, leading to overly pessimistic evaluations of the approach. This work observes that the ansatz Clifford structure and variational parameter pruning significantly reduce these costs. By keeping track of the limited set of correct subcircuit initializations and measurements, we reduce the number of experiments needed by up to 16x, matching and beating the error mitigation offered by classical shadows tomography. By performing reconstruction as a sparse tensor contraction, we scale the feasible ansatzes to over 200 qubits with six ansatz layers, beyond the capability of prior work.
format Preprint
id arxiv_https___arxiv_org_abs_2412_17929
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Case for Quantum Circuit Cutting for NISQ Applications: Impact of topology, determinism, and sparsity
Li, Zirui
Guo, Minghao
Barad, Mayank
Tang, Wei
Zhang, Eddy Z.
Huang, Yipeng
Quantum Physics
We make the case that variational algorithm ansatzes for near-term quantum computing are well-suited for the quantum circuit cutting strategy. Previous demonstrations of circuit cutting focused on the exponential execution and postprocessing costs due to the cuts needed to partition a circuit topology, leading to overly pessimistic evaluations of the approach. This work observes that the ansatz Clifford structure and variational parameter pruning significantly reduce these costs. By keeping track of the limited set of correct subcircuit initializations and measurements, we reduce the number of experiments needed by up to 16x, matching and beating the error mitigation offered by classical shadows tomography. By performing reconstruction as a sparse tensor contraction, we scale the feasible ansatzes to over 200 qubits with six ansatz layers, beyond the capability of prior work.
title A Case for Quantum Circuit Cutting for NISQ Applications: Impact of topology, determinism, and sparsity
topic Quantum Physics
url https://arxiv.org/abs/2412.17929