Local clustering decoder as a fast and adaptive hardware decoder for the surface code

Area of Science:

• Quantum Information Science
• Computer Engineering

Background:

• Fault-tolerant quantum computation requires efficient decoding to manage errors.
• Current decoding methods face trade-offs between speed and accuracy, hindering practical quantum computing.

Purpose of the Study:

• To introduce a novel decoding system that meets both accuracy and speed requirements for real-time quantum error correction.
• To reduce the overheads associated with fault-tolerant quantum computation.

Main Methods:

• Implementation of the Local Clustering Decoder on Field-Programmable Gate Arrays (FPGAs).
• Exploitation of hardware parallelism and an adaptivity engine for real-time updates.
• Testing under a circuit-level noise model with leakage as a primary error source.

Main Results:

• The Local Clustering Decoder achieves high accuracy and speed, decoding in under 1 microsecond per round.
• Enables one million error-free quantum operations using 4x fewer physical qubits compared to standard non-adaptive decoders.
• Demonstrates efficient performance with modest FPGA resources.

Conclusions:

• The Local Clustering Decoder provides a viable solution for real-time decoding in fault-tolerant quantum computation.
• This advancement significantly reduces qubit overhead, paving the way for scalable quantum computers.
• The adaptive nature of the decoder enhances its robustness against dominant error sources like leakage.