Scheduling of syndrome measurements with a few ancillary qubits

TL;DR

This paper introduces a framework for designing efficient syndrome measurement circuits in quantum error correction that use fewer ancillary qubits, reducing overhead and improving logical error rates in quantum computing.

Contribution

It proposes a novel method to minimize the number of physical qubits needed for syndrome measurements in CSS codes, especially surface codes, under practical constraints.

Findings

Balanced qubit counts lower logical error rates

Fewer ancillary qubits than stabilizers can be effective

Method applies to surface codes and general settings

Abstract

Quantum error-correcting codes are a vital technology for demonstrating reliable quantum computation. They require data qubits for encoding quantum information and ancillary qubits for taking error syndromes necessary for error correction. The need for a large number of ancillary qubits is an overhead specific to quantum computing, and it prevents the scaling of quantum computers to a useful size. In this work, we propose a framework for generating efficient syndrome measurement circuits with a few ancillary qubits in CSS codes and provide a method to minimize the total number of physical qubits in general settings. We demonstrated our proposal by applying it to surface codes, and we generated syndrome measurement circuits under several constraints of total qubit count. As a result, we find that balanced data and ancillary qubit counts achieve the lower logical error rates under a fixed total number of physical qubits. This result indicates that using fewer ancillary qubits than the number of stabilizers can be effective for reducing logical error rates in a practical noise model.