  Different algorithms can be used for clustering purposes with data sets. On
of these algorithms, uses topological features extracted from the data set to
base the clusters on. The complexity of this algorithm is however exponential
in the number of data points. Recently a quantum algorithm was proposed by
Lloyd Garnerone and Zanardi with claimed polynomial complexity, hence an
exponential improved over classical algorithms. However, we show that this
algorithm in general cannot be used to compute these topological features in
any dimension but the zeroth. We also give pointers on how to still use the
algorithm for clustering purposes.
