  In this paper, we develop an in-depth analysis of non-reversible Markov
chains on denumerable state space from a similarity orbit perspective. In
particular, we study the class of Markov chains whose transition kernel is in
the similarity orbit of a normal transition kernel, such as the one of
birth-death chains or reversible Markov chains. We start by identifying a set
of sufficient conditions for a Markov chain to belong to the similarity orbit
of a birth-death one. As by-products, we obtain a spectral representation in
terms of non-self-adjoint resolutions of identity in the sense of Dunford [21]
and offer a detailed analysis on the convergence rate, separation cutoff and
${\rm{L}}^2$-cutoff of this class of non-reversible Markov chains. We also look
into the problem of estimating the integral functionals from discrete
observations for this class. In the last part of this paper, we investigate a
particular similarity orbit of reversible Markov kernels, that we call the pure
birth orbit, and analyze various possibly non-reversible variants of classical
birth-death processes in this orbit.
