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The most powerful form of quantum learning system possible would somehowlearn the parameters W of a quantum system f(X, W), for f representing thelargest, most powerful set of possible input-output relations. This paperaddresses the issue of how to enlarge the set represented by f, by using a newformulation of time-symmetric physics to model analog quantum computers basedon spin and by exploring possible sources of backwards-time free energy so asto address problems of decoherence and dissipation.

Time-Symmetric Physics: A Radical Approach to the Decoherence Problem