Time-Symmetric Physics: A Radical Approach to the Decoherence Problem
arXiv:1501.00027
Abstract
The most powerful form of quantum learning system possible would somehow learn the parameters W of a quantum system f(X, W), for f representing the largest, most powerful set of possible input-output relations. This paper addresses the issue of how to enlarge the set represented by f, by using a new formulation of time-symmetric physics to model analog quantum computers based on spin and by exploring possible sources of backwards-time free energy so as to address problems of decoherence and dissipation.
5 pages, 2 figures. Invited keynote talk for Quantum Computing workshop at Pacific Rim AI (PRICAI) conference, December 2014. Simple summary and link to the slides and audio of the talk posted at http://www.werbos.com/quantum.htm