A Brownian Motor is a nanoscale or molecular device that combines the effects of thermal noise, spatial or temporal asymmetry, and directionless input energy to drive directed motion. Because of the input energy, Brownian motors function away from thermodynamic equilibrium and concepts such as linear response theory, fluctuation dissipation relations, and detailed balance do not apply. The generalized fluctuation-dissipation relation, however, states that even under strongly thermodynamically non-equilibrium conditions the ratio of the probability of a transition to the probability of the time-reverse of that transition is the exponential of the change in the internal energy of the system due to the transition. Here, we derive an extension of the generalized fluctuation dissipation theorem for a Brownian motor for the ratio between the probability for the motor to take a forward step and the probability to take a backward step.PACS numbers: 87.16.Uv, A Brownian Motor is a nanoscale or molecular device that combines the effects of thermal noise, spatial or temporal asymmetry, and directionless input energy to drive directed motion [1,2,3]. Many biological motile systems may be driven by Brownian motors [4], and chemists have been able to synthesize molecules that function as Brownian motors [5,6]. In solution, viscous drag and thermal noise dominate the inertial forces that drive macroscopic machines. Because of the strong viscous drag, the motion of such a Brownian motor is over-damped and in one dimension can be described by the simple equation [7] Rα − X = ǫ(t)where ǫ(t) is Gaussian noise with mean µ = 0 and variance σ 2 = 2Rk B T /dt, and R is the coefficient of viscous friction. In the following we use units where the thermal energy k B T = 1. The generalized force X = X(α, ψ(t)) can be written as the gradient of a scalar potential X = −∂H/∂α whereis the sum of an intrinsic potential due to chemical interactions and any external load and an external time dependent forcing term that is the product of canonically conjugate intensive and extensive thermodynamic parameters z(α) and ψ(t), respectively [8]. The conjugate parameters include, e.g., molecular volume and pressure, entropy and temperature, or dipole moment and field. The underlying system is typically spatially periodic (possibly with a homogeneous force or load F ) so that U (α + L) = U (α) + ∆U , where ∆U = F L, and z(α + L) = z(α).For any fixed value of ψ detailed balance requireswhere P (α i +L, T | · · · |α i , 0) is the conditional probability density that a particle starting at position α i at time 0 goes to position α i +L at time T by the specific trajectory (sequence of positions and times) denoted by · · · , andis the conditional probability to follow the reverse of that process. The ratio depends only on the difference in energy between the initial and final points. It further holds thatwhere the net probability P (L, T |0,is the integral over all trajectories from (0, 0) to (L, T ). A time dependent modulation, ψ(t), causes dissipation an...