The language of lattice random walks or hopping models is widely used to describe different kinetic and transport processes in physics, chemistry, and biology. Examples range from hopping transport in semiconductors to single-molecule enzyme kinetics and intracellular transport by molecular motors. 1-10 When (1) the random walk occurs on a periodic lattice and (2) the observation time is sufficiently long so that a typical displacement exceeds the lattice period, one can use a coarse-grained description of the motion. In this description, all information about the underlying random walk is packed into the effective drift velocity, V eff , and diffusion coefficient, D eff . The goal of the theory is to establish the relation between V eff and D eff and the parameters of the underlying random walk.For a Markovian nearest-neighbor random walk in one dimension,where α n and β n are the rate constants for transitions from site n to sites n + 1 and n − 1, respectively, which are assumed to be periodic functions of n with period N, α n + N = α n , and β n + N = β n , such a theory was developed by Derrida 11 (see also the analysis of a special case in Ref. 12). In the absence of the effective drift velocity, V eff = 0, the Derrida (D) formula for D eff takes the form (see Eqs. (46), (47), and (50) from Ref. 11),whereandIn this Note we show that the Derrida formula, Eq. (2), can be interpreted as a discretized version of the LifsonJackson formula for the effective diffusion coefficient. 13 The latter provides the effective diffusion coefficient for a particle diffusing in an arbitrary one-dimensional periodic potential Here the angular brackets denote averaging over the period,, where k B and T are the Boltzmann constant and absolute temperature. It is convenient to introduce the equilibrium probability density, p eq (x), normalized to unity on the period L,Using this probability density we can write D (LJ ) eff in Eq. (5) asTo transform the Derrida formula, Eq. (2), to the form similar to that of the Lifson-Jackson formula, Eq. (7), we introduce the equilibrium distribution function, P eq n , for the hopping dynamics, Eq. (1), normalized to unity on the period N,This distribution function is periodic, P eq n+N = P eq n , and satisfies the detailed balance condition, α n P eq n = β n+1 P eq n+1 .Using Eqs. (8) and (9) we find that r n and u n are given by