  Coupled cluster theory is a vital cornerstone of electronic structure theory
and is being applied to ever-larger systems. Stochastic approaches to quantum
chemistry have grown in importance and offer compelling advantages over
traditional deterministic algorithms in terms of computational demands,
theoretical flexibility or lower scaling with system size. We present a highly
parallelizable algorithm of the coupled cluster Monte Carlo method involving
sampling of clusters of excitors over multiple time steps. The behaviour of the
algorithm is investigated on the uniform electron gas and the water dimer at
CCSD, CCSDT and CCSDTQ levels. We also describe two improvements to the
original sampling algorithm, full non-composite and multi-spawn sampling. A
stochastic approach to coupled cluster results in an efficient and scalable
implementation at arbitrary truncation levels in the coupled cluster expansion.
