The convergence time of parallel dynamics is compared analytically with that of random sequential dynamics. In parallel dynamics all elements are updated simultaneously, whereas in random sequential dynamics the elements are updated only on average at the same speed. One-dimensional and infinite-range interactions are studied. The relevance of the results to neural networks and Monte Carlo simulations is discussed.
Bibliographical noteFunding Information:
I would like to thank P.W. Anderson and D.S. Fisher for numerous stimulating discussions. The work is supported by a Weizmann Fellowship and also in part by the NSF Grant No. 8719523.