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  <titleInfo>
    <title>Information Theory for Complex Systems</title>
    <subTitle>An Information Perspective on Complexity in Dynamical Systems and Statistical Mechanics</subTitle>
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    <namePart>Lindgren, Kristian.</namePart>
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    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
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    <extent>XI, 153 p. 70 illus., 16 illus. in color. online resource.</extent>
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  <abstract>This book introduces a comprehensive framework tailored for dissecting complex systems across diverse disciplines. What defines a complex system? How can we harness information to quantify its order, structure, and intricacy? Delving into phenomena from the intricate processes in physical systems to the dynamic behaviours in cellular automata and pattern formation, readers will uncover the profound interplay between physics and information theory. This intricate relationship provides fresh insight into physical phenomena, reimagining them through the lens of information. Notably, the book demystifies how seemingly opposing forces—rising order and increasing disorder—coexist, ultimately shedding light on the second law of thermodynamics as an outcome of deterministic, reversible dynamics beneath the surface. Geared towards graduate students, this book presumes an undergraduate foundation in mathematics and physics, ensuring a deep, engaging exploration for its readers.</abstract>
  <tableOfContents>Introduction -- Information theory -- Information theory for lattice systems -- Cellular automata -- Physics and information theory -- Geometric information theory -- Pattern formation in chemical systems -- Chaos and information -- Appendix -- References.</tableOfContents>
  <note type="statement of responsibility">by Kristian Lindgren.</note>
  <subject authority="lcsh">
    <topic>System theory</topic>
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  <subject authority="lcsh">
    <topic>Dynamical systems</topic>
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  <subject authority="lcsh">
    <topic>Statistical Mechanics</topic>
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  <subject authority="lcsh">
    <topic>Thermodynamics</topic>
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  <subject authority="lcsh">
    <topic>Data structures (Computer science)</topic>
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  <subject authority="lcsh">
    <topic>Information theory</topic>
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  <subject>
    <topic>Complex Systems</topic>
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  <subject>
    <topic>Dynamical Systems</topic>
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  <subject>
    <topic>Statistical Mechanics</topic>
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  <subject>
    <topic>Thermodynamics</topic>
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  <subject>
    <topic>Data Structures and Information Theory</topic>
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  <classification authority="lcc">Q295</classification>
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      <title>Understanding Complex Systems</title>
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  <identifier type="isbn">9783662682142</identifier>
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