An expert survey presenting GPTs as generalized probability theory through Foulis-Randall test spaces and their linearized ordered-vector-space form.
A Royal Road to Quantum Theory (or Thereabouts)
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
This paper fails to derive quantum mechanics from a few simple postulates. But it gets very close --- and it does so without much exertion. More exactly, I obtain a representation of finite-dimensional probabilistic systems in terms of euclidean Jordan algebras, in a strikingly easy way, from simple assumptions. This provides a framework within which real, complex and quaternionic QM can play happily together, and allows some --- but not too much --- room for more exotic alternatives. (This is a leisurely summary, based on recent lectures, of material from the papers arXiv:1206:2897 and arXiv:1507.06278, the latter joint work with Howard Barnum and Matthew Graydon. Some further ideas are also explored.)
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Generalized Probability Theory: notes for a short course
An expert survey presenting GPTs as generalized probability theory through Foulis-Randall test spaces and their linearized ordered-vector-space form.