Simulation of the five-qubit quantum error correction code on superconducting qubits

TL;DR

This paper demonstrates a minimal five-qubit quantum error correction code implemented on superconducting qubits, showing improved logical error rates over larger codes through simulation and neural network decoding.

Contribution

It introduces a minimal distance-3 QEC circuit with fewer qubits, and evaluates its performance using density-matrix simulation and neural network-based decoding.

Findings

Lower logical error rate than Surface-17 at similar physical error rates

Effective neural network decoder trained on experimental data

Feasible implementation with reduced qubit footprint

Abstract

Experimental realization of stabilizer-based quantum error correction (QEC) codes that would yield superior logical qubit performance is one of the formidable task for state-of-the-art quantum processors. A major obstacle towards realizing this goal is the large footprint of QEC codes, even those with a small distance. We propose a circuit based on the minimal distance-3 QEC code, which requires only 5 data qubits and 5 ancilla qubits, connected in a ring with iSWAP gates implemented between neighboring qubits. Using a density-matrix simulation, we show that, thanks to its smaller footprint, the proposed code has a lower logical error rate than Surface-17 for similar physical error rates. We also estimate the performance of a neural network-based error decoder, which can be trained to accommodate the error statistics of a specific quantum processor by training on experimental data.