A Hamiltonian-Entropy Production Connection in the Skew-symmetric Part of a Stochastic Dynamics
arXiv:1205.6552
Abstract
The infinitesimal transition probability operator for a continuous-time discrete-state Markov process, , can be decomposed into a symmetric and a skew-symmetric parts. As recently shown for the case of diffusion processes, while the symmetric part corresponding to a gradient system stands for a reversible Markov process, the skew-symmetric part, $\frac{d}{dt}u(t)=\mcA u$, is mathematically equivalent to a linear Hamiltonian dynamics with Hamiltonian $H=1/2u^T\big(\mcA^T\mcA)^{1/2}u$. It can also be transformed into a Schrödinger-like equation where the "Hamiltonian" operator $\mathcal{H}=-i\mcA$ is Hermitian. In fact, these two representations of a skew-symmetric dynamics emerge natually through singular-value and eigen-value decompositions, respectively. The stationary probability of the Markov process can be expressed as . The motion can be viewed as "harmonic" since where with being a constant. More interestingly, we discover that $\textrm{Tr}(\mcA^T\mcA)=\sum_{j,\ell=1}^n \frac{(q_{j\ell}π_\ell-q_{\ell j}π_j)^2}{π_jπ_{\ell}}$, whose right-hand-side is intimately related to the entropy production rate of the Markov process in a nonequilibrium steady state with stationary distribution . The physical implication of this intriguing connection between conservative Hamiltonian dynamics and dissipative entropy production remains to be further explored.
18 pages
References in corpus (4)
- Stochastic Dynamical Structure (SDS) of Nonequilibrium Processes in the Absence of Detailed Balance. IV: Emerging of Stochastic Dynamical Equalities and Steady State Thermodynamics from Darwinian Dynamics
- Steady state statistics of driven diffusions
- A Decomposition of Irreversible Diffusion Processes Without Detailed Balance
- Relation of a New Interpretation of Stochastic Differential Equations to Ito Process