Quantum Circuit Distillation and Compression

Fuente: arXiv
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Bibliographic Details
Main Authors: Daimon, Shunsuke, Tsunekawa, Kakeru, Takeuchi, Ryoto, Sagawa, Takahiro, Yamamoto, Naoki, Saitoh, Eiji
Format: Preprint
Published: 2023
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author Daimon, Shunsuke
Tsunekawa, Kakeru
Takeuchi, Ryoto
Sagawa, Takahiro
Yamamoto, Naoki
Saitoh, Eiji
author_facet Daimon, Shunsuke
Tsunekawa, Kakeru
Takeuchi, Ryoto
Sagawa, Takahiro
Yamamoto, Naoki
Saitoh, Eiji
contents Quantum coherence in a qubit is vulnerable to environmental noise. When long quantum calculation is run on a quantum processor without error correction, the noise often causes fatal errors and messes up the calculation. Here, we propose quantum-circuit distillation to generate quantum circuits that are short but have enough functions to produce an output almost identical to that of the original circuits. The distilled circuits are less sensitive to the noise and can complete calculation before the quantum coherence is broken in the qubits. We created a quantum-circuit distillator by building a reinforcement learning model, and applied it to the inverse quantum Fourier transform (IQFT) and Shor's quantum prime factorization. The obtained distilled circuit allows correct calculation on IBM-Quantum processors. By working with the quantum-circuit distillator, we also found a general rule to generate quantum circuits approximating the general $n$-qubit IQFTs. The quantum-circuit distillator offers a new approach to improve performance of noisy quantum processors.
format Preprint
id arxiv_https___arxiv_org_abs_2309_01911
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Quantum Circuit Distillation and Compression
Daimon, Shunsuke
Tsunekawa, Kakeru
Takeuchi, Ryoto
Sagawa, Takahiro
Yamamoto, Naoki
Saitoh, Eiji
Quantum Physics
Quantum coherence in a qubit is vulnerable to environmental noise. When long quantum calculation is run on a quantum processor without error correction, the noise often causes fatal errors and messes up the calculation. Here, we propose quantum-circuit distillation to generate quantum circuits that are short but have enough functions to produce an output almost identical to that of the original circuits. The distilled circuits are less sensitive to the noise and can complete calculation before the quantum coherence is broken in the qubits. We created a quantum-circuit distillator by building a reinforcement learning model, and applied it to the inverse quantum Fourier transform (IQFT) and Shor's quantum prime factorization. The obtained distilled circuit allows correct calculation on IBM-Quantum processors. By working with the quantum-circuit distillator, we also found a general rule to generate quantum circuits approximating the general $n$-qubit IQFTs. The quantum-circuit distillator offers a new approach to improve performance of noisy quantum processors.
title Quantum Circuit Distillation and Compression
topic Quantum Physics
url https://arxiv.org/abs/2309.01911