Imaging geometry through dynamics: the observable representation
Identifieur interne : 000259 ( Main/Exploration ); précédent : 000258; suivant : 000260Imaging geometry through dynamics: the observable representation
Auteurs : Bernard Gaveau [France] ; Lawrence S. Schulman [États-Unis, France] ; Leonard J. Schulman [États-Unis]Source :
- Journal of Physics A: Mathematical and General [ 0305-4470 ] ; 2006.
Abstract
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.
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DOI: 10.1088/0305-4470/39/33/004
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