2018
DOI: 10.1016/j.nuclphysb.2017.12.008
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Information transport in classical statistical systems

Abstract: For "static memory materials" the bulk properties depend on boundary conditions. Such materials can be realized by classical statistical systems which admit no unique equilibrium state. We describe the propagation of information from the boundary to the bulk by classical wave functions. The dependence of wave functions on the location of hypersurfaces in the bulk is governed by a linear evolution equation that can be viewed as a generalized Schrödinger equation. Classical wave functions obey the superposition … Show more

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Cited by 13 publications
(53 citation statements)
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“…11 in particular in the presence of interactions. 1,9,10,11,24,25 Which motivates the study of the model of Section 3.…”
Section: Matters Of Language -Distinguishing Ontological Classical Amentioning
confidence: 92%
See 1 more Smart Citation
“…11 in particular in the presence of interactions. 1,9,10,11,24,25 Which motivates the study of the model of Section 3.…”
Section: Matters Of Language -Distinguishing Ontological Classical Amentioning
confidence: 92%
“…1,4,10,11 for further discussions, as well as to other related attempts. 12,13,14,15,16,17,18,19,20,21,22,23,24,25 It may be useful to distinguish here between going beyond, as indicated, and recent reconstructions from various alternative sets of axioms, without changing the contents of quantum theory, see, e.g., Refs. 26,27,28,29 .…”
Section: Introductionmentioning
confidence: 99%
“…The possible relevance of Ising models for the understanding of Bell's theorem and statistical issues in quantum theory, other than serving as our model for the evolution of OS, has recently also been discussed [4,5,6,7].…”
Section: Introductionmentioning
confidence: 99%
“…The appropriate theoretical framework for the transport of probabilistic information is the quantum formalism for classical statistics [28,29]. It can be based on the "classical density matrix" ρ (t), whose diagonal elements are the "local" probabilities p(t) at t. In contrast to the local probabilities, the change from ρ (t) to a neighboring layer ρ (t + ) obeys a simple linear evolution law ρ (t + ) = S(t) ρ (t) S −1 (t) .…”
Section: Introductionmentioning
confidence: 99%
“…Here S(t) is the step evolution operator at t, which corresponds to a particular normalization of the transfer matrix [31][32][33]. In the occupation number basis the step evolution operator for generalized Ising models is a real non-negative matrix [28,29]. This restriction may be removed for more general forms of probabilistic computing.…”
Section: Introductionmentioning
confidence: 99%