  We present a decoding algorithm for quantum convolutional codes that finds
the class of degenerate errors with the largest probability conditioned on a
given error syndrome. The algorithm runs in time linear with the number of
qubits. Previous decoding algorithms for quantum convolutional codes optimized
the probability over individual errors instead of classes of degenerate errors.
Using Monte Carlo simulations, we show that this modification to the decoding
algorithm results in a significantly lower block error rate.
