  A novel decoding algorithm is developed for general quantum convolutional
codes. Exploiting useful ideas from classical coding theory, the new decoder
introduces two innovations that drastically reduce the decoding complexity
compared to the existing quantum Viterbi decoder. First, the new decoder uses
an efficient linear-circuits-based mechanism to map a syndrome to a candidate
vector, whereas the existing algorithm relies on a non-trivial lookup table.
Second, the new algorithm is cleverly engineered such that only one run of the
Viterbi algorithm suffices to locate the most-likely error pattern, whereas the
existing algorithm must run the Viterbi algorithm many times. The efficiency of
the proposed algorithm allows us to simulate and present the first performance
curve of a general quantum convolutional code.
