Invention:
This technology is an advanced message-passing decoder called the Min-Sum with Past Influence (MS-PI) decoder, specifically designed for Quantum Low-Density Parity-Check (QLDPC) codes. The MS-PI decoder addresses critical challenges in quantum error correction by leveraging oscillatory message dynamics to enhance decoding performance, particularly for degenerate codes. Unlike conventional approaches, MS-PI achieves superior reliability without relying on complex serial scheduling or post-processing techniques, making it both efficient and scalable for real-world applications. Simulation results from the inventors demonstrate that MS-PI can significantly surpass nMS decoding performance and closely approach the performance of more complex decoders, such as Belief-Propagation with Ordered Statistics Decoding (BP-OSD), within a limited number of iterations.
Background:
Quantum error correction is critical for the advancement of quantum computing, as quantum systems are highly susceptible to errors. Existing solutions, such as normalized min-sum (nMS) and belief propagation (BP), often fail in decoding highly degenerate quantum codes due to symmetrical stabilizers and oscillatory message dynamics, resulting in inefficiencies and inaccuracies. Current post-processing techniques or modified scheduling approaches introduce additional latency and complexity. The MS-PI decoder addresses these challenges by breaking symmetries and exploiting message dynamics, ensuring higher reliability and faster convergence without the need for complex post-processing.
Applications:
- Quantum computing
- Quantum communication systems
- Cryptographic systems
- Fault-tolerant quantum memory
Advantages:
- Outperforms traditional decoders like normalized min-sum (nMS) and belief propagation (BP) in highly degenerate scenarios
- Maintains linear computational complexity for scalability
- Reduces latency by avoiding complex post-processing techniques
- Enhances reliability in quantum error correction for complex quantum codes
- Optimized for parallel scheduling and practical implementation
- Demonstrated performance in simulations
