2006/07/17 by Bernard Gaveau, Lawrence S. Schulman, Lawrence S Schulman +2 · 1 citation
Mathematics · Physics and Astronomy · #Markov Chains and Monte Carlo Methods #Quantum Mechanics and Applications #Theoretical and Computational Physics #cond-mat.other #cond-mat.stat-mech
paper · pdf · doi:10.1088/0305-4470/39/33/004
published as J. Phys. A: Math. Gen. 39 10307-10321 (2006)
arxiv created 2006/07/17 · openalex publication_date 2006/08/02 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/30
For many stochastic processes there is an underlying coordinate space, V , with the process moving from point to point in V or on variables (such as spin configurations) defined with respect to V . There is a matrix of transition probabilities (whether between points in V or between variables defined on V ) and we focus on its 'slow' eigenvectors, those with eigenvalues closest to that of the stationary eigenvector. These eigenvectors are the 'observables', and can be used to recover geometrical features of V .