Correcting a noisy quantum computer using a quantum computer

Fuente: arXiv
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Autor principal: Zhang, Pan
Formato: Preprint
Publicado: 2025
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author Zhang, Pan
author_facet Zhang, Pan
contents Quantum computers require error correction to achieve universal quantum computing. However, current decoding of quantum error-correcting codes relies on classical computation, which is slower than quantum operations in superconducting qubits. This discrepancy makes the practical implementation of real-time quantum error correction challenging. In this work, we propose a decoding scheme that leverages the operations of the quantum circuit itself. Given a noisy quantum circuit $A$, we train a decoding quantum circuit $B$ using syndrome measurements to identify the logical operators needed to correct errors in circuit $A$. The trained quantum circuit $B$ can be deployed on quantum devices, such as superconducting qubits, to perform real-time decoding and error correction. Our approach is applicable to general quantum codes with multiple logical qubits and operates efficiently under various noise conditions, and the decoding speed matches the speed of the quantum circuits being corrected. We have conducted numerical experiments using surface codes up to distance 7 under circuit-level noise, demonstrating performance on par with the classical minimum-weight perfect matching algorithm. Interestingly, our method reveals that the traditionally classical task of decoding error-correcting codes can be accomplished without classical devices or measurements. This insight paves the way for the development of self-correcting quantum computers.
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id arxiv_https___arxiv_org_abs_2506_08331
institution arXiv
publishDate 2025
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spellingShingle Correcting a noisy quantum computer using a quantum computer
Zhang, Pan
Quantum Physics
Disordered Systems and Neural Networks
Statistical Mechanics
Quantum computers require error correction to achieve universal quantum computing. However, current decoding of quantum error-correcting codes relies on classical computation, which is slower than quantum operations in superconducting qubits. This discrepancy makes the practical implementation of real-time quantum error correction challenging. In this work, we propose a decoding scheme that leverages the operations of the quantum circuit itself. Given a noisy quantum circuit $A$, we train a decoding quantum circuit $B$ using syndrome measurements to identify the logical operators needed to correct errors in circuit $A$. The trained quantum circuit $B$ can be deployed on quantum devices, such as superconducting qubits, to perform real-time decoding and error correction. Our approach is applicable to general quantum codes with multiple logical qubits and operates efficiently under various noise conditions, and the decoding speed matches the speed of the quantum circuits being corrected. We have conducted numerical experiments using surface codes up to distance 7 under circuit-level noise, demonstrating performance on par with the classical minimum-weight perfect matching algorithm. Interestingly, our method reveals that the traditionally classical task of decoding error-correcting codes can be accomplished without classical devices or measurements. This insight paves the way for the development of self-correcting quantum computers.
title Correcting a noisy quantum computer using a quantum computer
topic Quantum Physics
Disordered Systems and Neural Networks
Statistical Mechanics
url https://arxiv.org/abs/2506.08331