Syndrome-Based Min-Sum vs OSD-0 Decoders: FPGA Implementation and Analysis for Quantum LDPC Codes

Javier Valls, Francisco Garcia-Herrero, Nithin Raveendran, Bane Vasić

Research output: Contribution to journalArticlepeer-review

Abstract

Quantum processors need to improve their reliability to scale up the number of qubits and increase the number of algorithms that can execute. To reduce the logical error rate of the quantum systems, the use of error correction codes and decoders has been established as a low-cost and feasible approach, with good results from a theoretical perspective, for mid and long-term architectures. While most of the authors are focused on the algorithms to improve the correction capability of quantum computers, without taking into account a fundamental implementation aspect for their deployment in a real system, i.e., their latency must be bounded to avoid the qubit decoherence, only a few propose hardware architectures and they just include time estimations of their decoding latency. However, a real implementation has not been shown yet. In this work, we analyze from the point of view of hardware implementation two algorithmic options based on quantum low-density parity-check (QLDPC) codes: a) belief propagation min-sum decoders combined with codes with good error-floor behavior and b) belief propagation min-sum decoders concatenated with ordered statistics decoders (OSDs) for codes with early error-floor. The bounds for the maximum clock frequency required by the decoders to decode within the qubit coherence time are established as a parameter to show if a practical implementation is possible with the present or near future FPGA technology. Furthermore, real implementation results for a Xilinx FPGA device are provided, showing that some solutions can meet the timing constraints set up by the state-of-the-art quantum processors.

Original languageEnglish (US)
Pages (from-to)138734-138743
Number of pages10
JournalIEEE Access
Volume9
DOIs
StatePublished - 2021

Keywords

  • FPGA devices
  • ordered statistics
  • Quantum error correction
  • syndrome based decoding

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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