Optimization of Quantum Error Correcting Code under Temporal Variation of Qubit Quality

TL;DR

This paper presents an adaptive quantum error correction method that dynamically adjusts code distances based on daily qubit error rates, significantly reducing resource overhead while maintaining qubit usability on IBM's NISQ devices.

Contribution

It introduces a practical adaptive QEC approach that accounts for temporal qubit error variations, optimizing resource use and qubit utility in real-world quantum hardware.

Findings

Reduces physical qubit overhead by over 50% on ibm_kyiv

Achieves up to 71% resource savings on other devices

Maintains 85-100% qubit usability across tested devices

Abstract

Error rates in current noisy quantum hardware are not static; they vary over time and across qubits. This temporal and spatial variation challenges the effectiveness of fixed-distance quantum error correction (QEC) codes. In this paper, we analyze 12 days of calibration data from IBM's 127-qubit device (ibm_kyiv), showing the fluctuation of Pauli-X and CNOT gate error rates. We demonstrate that fixed-distance QEC can either underperform or lead to excessive overhead, depending on the selected qubit and the error rate of the day. We then propose a simple adaptive QEC approach that selects an appropriate code distance per qubit, based on daily error rates. Using logical error rate modeling, we identify qubits that cannot be used and qubits that can be recovered with minimal resources. Our method avoids unnecessary resource overhead by excluding outlier qubits and tailoring code distances. Across 12 calibration days on ibm_kyiv, our adaptive strategy reduces physical qubit overhead by over 50% per logical qubit while maintaining access to 85-100% of usable qubits. To further validate the method, we repeat the experiment on two additional 127-qubit devices, ibm_brisbane and ibm_sherbrooke, where the overhead savings reach up to 71% while still preserving over 80% qubit usability. This approach offers a practical and efficient path forward for Noisy Intermediate-Scale Quantum (NISQ)-era QEC strategies.