  We describe an approach to bounded-memory computation of persistent homology
and betti barcodes, in which a computational state is maintained with updates
introducing new edges to the underlying neighbourhood graph and percolating the
resulting changes into the simplex stream feeding the persistence algorithm.
  We further discuss the memory consumption and resulting speed and complexity
behaviours of the resulting algorithm.
