Book•
Complexity, Entropy and the Physics of Information
22 Jan 1990-
TL;DR: In this article, the authors discuss the connections between quantum and classical physics, information and its transfer, computation, and their significance for the formulation of physical theories, but also consider the origins and evolution of the information-processing entities, their complexity, and the manner in which they analyze their perceptions to form models of the Universe.
Abstract: This book has emerged from a meeting held during the week of May 29 to June 2, 1989, at St. John’s College in Santa Fe under the auspices of the Santa Fe Institute. The (approximately 40) official participants as well as equally numerous “groupies” were enticed to Santa Fe by the above “manifesto.” The book—like the “Complexity, Entropy and the Physics of Information” meeting explores not only the connections between quantum and classical physics, information and its transfer, computation, and their significance for the formulation of physical theories, but it also considers the origins and evolution of the information-processing entities, their complexity, and the manner in which they analyze their perceptions to form models of the Universe. As a result, the contributions can be divided into distinct sections only with some difficulty. Indeed, I regard this degree of overlapping as a measure of the success of the meeting. It signifies consensus about the important questions and on the anticipated answers: they presumably lie somewhere in the “border territory,” where information, physics, complexity, quantum, and computation all meet.
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TL;DR: In this article, it was shown that many of the symptoms of classicality can be induced in quantum systems by their environments, which leads to environment-induced superselection or einselection, a quantum process associated with selective loss of information.
Abstract: as quantum engineering. In the past two decades it has become increasingly clear that many (perhaps all) of the symptoms of classicality can be induced in quantum systems by their environments. Thus decoherence is caused by the interaction in which the environment in effect monitors certain observables of the system, destroying coherence between the pointer states corresponding to their eigenvalues. This leads to environment-induced superselection or einselection, a quantum process associated with selective loss of information. Einselected pointer states are stable. They can retain correlations with the rest of the universe in spite of the environment. Einselection enforces classicality by imposing an effective ban on the vast majority of the Hilbert space, eliminating especially the flagrantly nonlocal ''Schrodinger-cat states.'' The classical structure of phase space emerges from the quantum Hilbert space in the appropriate macroscopic limit. Combination of einselection with dynamics leads to the idealizations of a point and of a classical trajectory. In measurements, einselection replaces quantum entanglement between the apparatus and the measured system with the classical correlation. Only the preferred pointer observable of the apparatus can store information that has predictive power. When the measured quantum system is microscopic and isolated, this restriction on the predictive utility of its correlations with the macroscopic apparatus results in the effective ''collapse of the wave packet.'' The existential interpretation implied by einselection regards observers as open quantum systems, distinguished only by their ability to acquire, store, and process information. Spreading of the correlations with the effectively classical pointer states throughout the environment allows one to understand ''classical reality'' as a property based on the relatively objective existence of the einselected states. Effectively classical pointer states can be ''found out'' without being re-prepared, e.g, by intercepting the information already present in the environment. The redundancy of the records of pointer states in the environment (which can be thought of as their ''fitness'' in the Darwinian sense) is a measure of their classicality. A new symmetry appears in this setting. Environment-assisted invariance or envariance sheds new light on the nature of ignorance of the state of the system due to quantum correlations with the environment and leads to Born's rules and to reduced density matrices, ultimately justifying basic principles of the program of decoherence and einselection.
3,499 citations
Book•
01 Jun 1996TL;DR: In this paper, a theory of consciousness and information is proposed, which is based on naturalistic dualism and the paradox of Phenomenal Judgment, and the Coherence between Consciousness and Cognition.
Abstract: I. PRELIMINARIES 1. Two Concepts of Mind 2. Supervenience and Explanation II. THE IRREDUCIBILITY OF CONSCIOUSNESS 3. Can Consciousness be Reductively Explained? 4. Naturalistic Dualism 5. The Paradox of Phenomenal Judgment III. TOWARD A THEORY OF CONSCIOUSNESS 6. The Coherence between Consciousness and Cognition 7. Absent Qualia, Fading Qualia, Dancing Qualia 8. Consciousness and Information: Some Speculation IV. APPLICATIONS 9. Strong Artificial Intelligence 10. The Interpretation of Quantum Mechanics Notes Bibliography
2,335 citations
TL;DR: In this article, a non-reductive theory based on principles of structural coherence and organizational invariance and a double-aspect theory of information is proposed to explain the complexity of the problem of consciousness.
Abstract: To make progress on the problem of consciousness, we have to confront it directly. In this paper, I first isolate the truly hard part of the problem, separating it from more tractable parts and giving an account of why it is so difficult to explain. I critique some recent work that uses reductive methods to address consciousness, and argue that such methods inevitably fail to come to grips with the hardest part of the problem. Once this failure is recognized, the door to further progress is opened. In the second half of the paper, I argue that if we move to a new kind of nonreductive explanation, a naturalistic account of consciousness can be given. I put forward my own candidate for such an account: a nonreductive theory based on principles of structural coherence and organizational invariance, and a double-aspect theory of information.
2,046 citations
Cites background from "Complexity, Entropy and the Physics..."
...Wheeler (1990) has suggested that information is fundamental to the physics of the universe....
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Book•
01 Jan 1997TL;DR: Overview: The Dynamics of Complex Systems-Examples, Questions, Methods and Concepts Introduction and Preliminaries
Abstract: Overview: The Dynamics of Complex Systems-Examples, Questions, Methods and Concepts Introduction and Preliminaries Neural Networks I: Subdivision and Hierarchy Neural Networks II: Models of Mind Protein Folding I: Size Scaling of Time Protein Folding II: Kinetic Pathways Life I: Evolution-Origin of Complex Organisms Life II: Developmental Biology-Complex by Design Human Civilization I: Defining Complexity Human Civilization II: A Complex(ity) Transition.
1,703 citations
TL;DR: A measure, called neural complexity (CN), that captures the interplay between functional segregation and functional integration in brains of higher vertebrates and may prove useful in analyzing complexity in other biological domains such as gene regulation and embryogenesis.
Abstract: In brains of higher vertebrates, the functional segregation of local areas that differ in their anatomy and physiology contrasts sharply with their global integration during perception and behavior. In this paper, we introduce a measure, called neural complexity (CN), that captures the interplay between these two fundamental aspects of brain organization. We express functional segregation within a neural system in terms of the relative statistical independence of small subsets of the system and functional integration in terms of significant deviations from independence of large subsets. CN is then obtained from estimates of the average deviation from statistical independence for subsets of increasing size. CN is shown to be high when functional segregation coexists with integration and to be low when the components of a system are either completely independent (segregated) or completely dependent (integrated). We apply this complexity measure in computer simulations of cortical areas to examine how some basic principles of neuroanatomical organization constrain brain dynamics. We show that the connectivity patterns of the cerebral cortex, such as a high density of connections, strong local connectivity organizing cells into neuronal groups, patchiness in the connectivity among neuronal groups, and prevalent reciprocal connections, are associated with high values of CN. The approach outlined here may prove useful in analyzing complexity in other biological domains such as gene regulation and embryogenesis.
1,504 citations