Quantum subspace verification for error correction codes
Junjie Chen, Pei Zeng, Qi Zhao, Xiongfeng Ma, and You Zhou

TL;DR
This paper introduces a quantum subspace verification framework that efficiently assesses quantum error correction codes and magic states, significantly reducing measurement and sample complexities for practical fault-tolerant quantum computing.
Contribution
It develops a novel verification method leveraging code subspace knowledge, with efficient local measurements and reduced sample complexity, applicable to stabilizer and QLDPC codes.
Findings
Sample complexity is $O(n-k)$ for stabilizer codes.
Sample complexity is $O((n-k)^2)$ for generic QLDPC codes.
Verification protocol for magic states has exponentially smaller sample complexity.
Abstract
Benchmarking the performance of quantum error correction codes in physical systems is crucial for achieving fault-tolerant quantum computing. Current methodologies, such as (shadow) tomography or direct fidelity estimation, fall short in efficiency due to the neglect of possible prior knowledge about quantum states. To address the challenge, we introduce a framework of quantum subspace verification, employing the knowledge of quantum error correction code subspaces to reduce the potential measurement budgets. Specifically, we give the sample complexity to estimate the fidelity to the target subspace under some confidence level. Building on the framework, verification operators are developed, which can be implemented with experiment-friendly local measurements for stabilizer codes and quantum low-density parity-check (QLDPC) codes. Our constructions require local measurement…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Advanced Data Storage Technologies · Quantum Information and Cryptography
