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Complexity, Entropy and the Physics of Information

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TLDR
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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Journal ArticleDOI

An Information-Theoretic Link Between Spacetime Symmetries and Quantum Linearity

TL;DR: In this article, a nonlinear generalisation of Schrodinger's equation is obtained using information-theoretic arguments and the nonlinearities are controlled by an intrinsic length scale and involve derivatives to all orders thus making the equation mildly nonlocal.
Book

Crystalline computation

TL;DR: In 1981, Richard Feynman gave a talk at a conference hosted by the MIT Information Mechanics Group, entitled "Simulating Physics with Computers," and is reproduced in this volume.
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The simplicity of metazoan cell lineages

TL;DR: A measure of biological complexity based on the similarity between developmental and computer programs is introduced and it is proposed that selection for decreased complexity has played a major role in moulding metazoan cell lineages.
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On the dynamic nature of hydrological similarity

TL;DR: This study subdivides a mesoscale catchment into 105 hillslopes and represents each by a two-dimensional numerical hillslope model, and finds that the concept of hydrological similarity is not necessarily time invariant.
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Correspondence and Independence of Numerical Evaluations of Algorithmic Information Measures

TL;DR: K_m proves to be a finer-grained measure and a potential alternative approach to lossless compression algorithms for small entities, where compression fails, and a first Beta version of an Online Algorithmic Complexity Calculator (OACC) is announced, based on a combination of theoretical concepts and numerical calculations.