Decoding 3D color codes with boundaries
Authors:
Preprint
Abstract
Practical large-scale quantum computation requires both efficient error correction and robust implementation of logical operations. Three-dimensional (3D) color codes are a promising candidate for fault-tolerant quantum computation due to their transversal non-Clifford gates, but efficient decoding remains challenging. In this work, we extend previous decoders for two-dimensional color codes [1], which are based on the restriction of the decoding problem to a subset of the qubit lattice, to three dimensions. Including boundaries of 3D color codes, we demonstrate that the 3D restriction decoder achieves optimal scaling of the logical error rate and a threshold value of 1.55(6)% for code-capacity bit- and phase-flip noise, which is almost a factor of two higher than previously reported for this family of codes [2, 3]. We furthermore present qCodePlot3D, a Python package for visualizing 2D and 3D color codes, error configurations, and decoding paths, which supports the development and analysis of such decoders. These advancements contribute to making 3D color codes a more practical option for exploring fault-tolerant quantum computation.Keywords
All Related Versions
- Version 1, 2025-12-15, ArXiv
- Version 2, 2025-12-22, ArXiv
- Published version: Physical Review A, 113 (4).
This publication has 61 references indexed in Scilit:
- Fault-tolerant operation and materials science with neutral atom logical qubitsnpj Quantum Information, 2025
- Experimental fault-tolerant code switchingNature Physics, 2025
- Encoding a magic state with beyond break-even fidelityNature, 2024
- Logical quantum processor based on reconfigurable atom arraysNature, 2023
- Demonstration of fault-tolerant universal quantum gate operationsNature, 2022
- Realizing repeated quantum error correction in a distance-three surface codeNature, 2022
- Visualization toolkit softwareWIREs Computational Statistics, 2012
- Quantum Computation and Quantum Information2012
- Rare Event Simulation using Monte Carlo Methods2009
- Fault-tolerant quantum computation by anyonsAnnals of Physics, 2003