  We present an elementary way to transform an expander graph into a simplicial
complex where all high order random walks have a constant spectral gap, i.e.,
they converge rapidly to the stationary distribution. As an upshot, we obtain
new constructions, as well as a natural probabilistic model to sample constant
degree high-dimensional expanders.
  In particular, we show that given an expander graph $G$, adding self loops to
$G$ and taking the tensor product of the modified graph with a high-dimensional
expander produces a new high-dimensional expander. Our proof of rapid mixing of
high order random walks is based on the decomposable Markov chains framework
introduced by Jerrum et al.
