  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
https://github.com/lucasberent/qecc under the MIT license, is meant to provide
a playground for the search for "practically good" quantum codes.
