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基本説明
Brings under one cover thirty-two reprints - more than half of which are new. Included are seminal works by James Clerk Maxwell and William Thomson; historical reviews by Martin Klein and Edward Daub, and more.
Full Description
Over 130 years ago, James Clerk Maxwell introduced his hypothetical "demon" as a challenge to the scope of the second law of thermodynamics. Fascination with the demon persisted throughout the development of statistical and quantum physics, information theory, and computer science, and links have been established between Maxwell's demon and each of these disciplines. The demon's seductive quality makes it appealing to physical scientists, engineers, computer scientists, biologists, psychologists, and historians and philosophers of science.
Since the publication of Maxwell's Demon: Entropy, Information, Computing in 1990, Maxwell's demon has been the subject of renewed and increased interest by numerous researchers in the fields mentioned above. Updated and expanded, Maxwell's Demon 2: Entropy, Classical and Quantum Information, Computing retains many of the seminal papers that appeared in the first edition, including the original thoughts of James Clerk Maxwell and William Thomson; a historical review by Martin Klein; and key articles by Leo Szilard, Leon Brillouin, Rolf Landauer, and Charles Bennett that led to new branches of research on the demon. This second edition contains newer articles by Landauer, Bennett, and others, related to Landauer's principle; connections with quantum mechanics; algorithmic information; and the thermodynamics and limits of computation. The book also includes two separate bibliographies: an alphabetical listing by author and a chronological bibliography that is annotated by the editors and contains selected quotes from the books and articles listed. The bibliography has more than doubled in size since publication of the first edition and now contains over 570 entries.
Contents
Overview. Early History and Philosophical Considerations. Smoluchowski Trap Doors and Information Acquisition. Information Erasure: Landauer's Principle. Quantum Nuances. Algorithmic Information. Computation: Thermodynamics and Limits.
