Parallel window decoding enables scalable fault tolerant quantum computation

Area of Science:

• Quantum computing
• Quantum information science
• Error correction codes

Background:

• Quantum computers promise revolutionary computational power but are limited by qubit noise.
• Quantum Error Correction (QEC) is essential for fault-tolerant quantum computation.
• Current QEC decoders face scalability issues due to data processing bottlenecks.

Purpose of the Study:

• To address the scalability limitations of existing quantum error correction decoders.
• To develop a parallelized decoding strategy for faster and more scalable quantum computations.
• To overcome the data backlog problem in real-time QEC processing.

Main Methods:

• Implemented a parallelized decoding architecture for quantum error correction.
• Introduced delayed classical feed-forward decisions to manage computational resources.
• Numerically simulated the parallel decoder using the surface code.

Main Results:

• Achieved near-arbitrary speedup in QEC decoding through parallelization.
• Demonstrated a polynomial slowdown instead of exponential slowdown with increased problem size.
• Maintained high logical fidelity comparable to previous non-scalable decoders.

Conclusions:

• Parallelized decoding removes a critical roadblock to scalable fault-tolerant quantum computing.
• The proposed method enables faster processing of QEC data streams, crucial for superconducting quantum computers.
• This work paves the way for realizing large-scale, reliable quantum computations.