Software Tools for Decoding Quantum Low-Density Parity Check Codes

Lucas Berent, Lukas Burgholzer, Robert Wille

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Quantum Error Correction (QEC) is an essential field of research towards the realization of large-scale quantum computers. On the theoretical side, a lot of effort is put into designing error-correcting codes that protect quantum data from errors, which inevitably happen due to the noisy nature of quantum hardware and quantum bits (qubits). Protecting data with an error-correcting code necessitates means to recover the original data, given a potentially corrupted data set-a task referred to as decoding. It is vital that decoding algorithms can recover error-free states in an efficient manner. While theoretical properties of recent QEC methods have been extensively studied, good techniques to analyze their performance in practically more relevant settings is still a widely unexplored area. In this work, we propose a set of software tools that allows to numerically experiment with so-called Quantum Low-Density Parity Check codes (QLDPC codes)-a broad class of codes, some of which have recently been shown to be asymptotically good. Based on that, we provide an implementation of a general decoder for QLDPC codes. On top of that, we propose an efficient heuristic decoder that tackles the runtime bottlenecks of the general QLDPC decoder while still maintaining comparable decoding performance. These tools eventually allow to confirm theoretical results around QLDPC codes in a more practical setting and showcase the value of software tools (in addition to theoretical considerations) for investigating codes for practical applications. The resulting tool, which is publicly available at this https URL under the MIT license, is meant to provide a playground for the search for "practically good" quantum codes.
Original languageEnglish
Title of host publicationAsia and South Pacific Design Automation Conference (ASP-DAC)
Number of pages6
Publication statusPublished - 2023

Fields of science

  • 102 Computer Sciences
  • 103025 Quantum mechanics
  • 202 Electrical Engineering, Electronics, Information Engineering

JKU Focus areas

  • Digital Transformation

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