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Towards Quantum Integrated Information Theory

Paolo Zanardi, Michael Tomka, Lorenzo Campos Venuti

arXiv Preprint Archive June 4, 2018 via arXiv

Summary

AI-generated from the abstract

Integrated Information Theory (IIT) provides a mathematical measure, Φ (phi), of how much a network's cause/effect structure is integrated—not reducible to separate parts. This work extends IIT to networks of quantum systems, identifying phases ranging from dis-integrated (Φ = 0) to holistic (where log Φ grows extensively with system size) and studying transitions between them.

Study at a glance

Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Quant-ph Quantum-consciousness Integrated-information-theory Quantum-networks Neuroscience-physics
Key finding Integrated Information Theory can be formulated for quantum networks, revealing distinct phases from dis-integrated to holistic integration.

Abstract

Integrated Information Theory (IIT) has emerged as one of the leading research lines in computational neuroscience to provide a mechanistic and mathematically well-defined description of the neural correlates of consciousness. Integrated Information ($\Phi$) quantifies how much the integrated cause/effect structure of the global neural network fails to be accounted for by any partitioned version of it. The holistic IIT approach is in principle applicable to any information-processing dynamical network regardless of its interpretation in the context of consciousness. In this paper we take the first steps towards a formulation of a general and consistent version of IIT for interacting networks of quantum systems. A variety of different phases, from the dis-integrated ($\Phi=0$) to the holistic one (extensive $\log\Phi$), can be identified and their cross-overs studied.

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