Purification and correction of quantum channels by commutation-derived quantum filters

TL;DR

This paper introduces quantum filters that combine error correction and mitigation techniques to reduce errors in quantum circuits efficiently, without significant overhead, and demonstrates their effectiveness through simulations.

Contribution

It presents a novel quantum filtering scheme capable of correcting arbitrary noise in Clifford circuits and partially purifying non-Clifford gates, reducing errors with minimal ancilla resources.

Findings

Corrects arbitrary noise in Clifford circuits with 2n ancillas

Partially purifies non-Clifford gates like T and CCZ

Achieves quadratic infidelity reduction with two ancillas

Abstract

Reducing errors is essential for reliable quantum computation. Quantum error mitigation (QEM) and quantum error correction (QEC) are two leading approaches for this task, each with challenges: QEM suffers from high sampling costs and cannot recover states, while QEC incurs large qubit and gate overheads. We combine ideas from both and introduce an information-theoretic device called a quantum filter that can purify or correct quantum channels. We present an explicit construction capable of correcting arbitrary noise in an n-qubit Clifford circuit using 2n ancillary qubits through a commutation-derived error-detection circuit. This scheme can also partially purify noise in non-Clifford gates such as T and CCZ. Unlike QEC, it achieves deterministic error reduction without encoding the input state. Under the assumption of clean ancillas, it overcomes the exponential sampling overhead in QEM using a single query to the channel. We also propose an ancilla-efficient Pauli filter that removes nearly all low-weight erroneous Pauli components in noisy Clifford circuits using only two ancillas. For local depolarizing noise, it achieves a quadratic reduction in average infidelity. Beyond existing QEM methods, our approach enables systematic error correction as the infidelity can be exponentially reduced with each added ancilla. Through numerical simulations under ancilla noise, we identify regimes where quantum filters outperform other techniques, demonstrating their effectiveness as a scalable error-reduction tool for quantum information processing.