Quantum Error Mitigation Relying on Permutation Filtering

Abstract

Quantum error mitigation (QEM) is a class of promising techniques capable of reducing the computational error of variational quantum algorithms tailored for current noisy intermediate-scale quantum computers. The recently proposed permutation-based methods are practically attractive, since they do not rely on any a priori information concerning the quantum channels. In this treatise, we propose a general framework termed as permutation filters, which includes the existing permutation-based methods as special cases. In particular, we show that the proposed filter design algorithm always converge to the global optimum, and that the optimal filters can provide substantial improvements over the existing permutation-based methods in the presence of narrowband quantum noise, corresponding to large-depth, high-error-rate quantum circuits.

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Cited by in corpus (12)

• Fundamental limits of quantum error mitigation
• Near-Term Quantum Computing Techniques: Variational Quantum Algorithms, Error Mitigation, Circuit Compilation, Benchmarking and Classical Simulation
• Generalized quantum subspace expansion
• Shadow Distillation: Quantum Error Mitigation with Classical Shadows for Near-Term Quantum Processors
• Universal Sampling Lower Bounds for Quantum Error Mitigation
• Unifying and benchmarking state-of-the-art quantum error mitigation techniques
• Resource-efficient Purification-based Quantum Error Mitigation
• Mitigating Quantum Errors via Truncated Neumann Series
• Virtual distillation with noise dilution
• Improving the efficiency of learning-based error mitigation
• Circuit-Noise-Resilient Virtual Distillation
• Error analysis of quantum operators written as a linear combination of permutations