Information as a physical quantity

Abstract A new physical conception of classical information in quantum mechanical systems is explicated, critically assessed, and formalized in a quantitative measure. Observer-local referential (OLR) information—a shared physical property of entities accessible to a specified observer—is defined on the joint states of composite systems, distinguished from related conceptions of information, and tested against strict criteria that would simultaneously qualify it as a physical state quantity and as a meaningful measure of classical information. It is shown specifically to satisfy these criteria in the technological context of digital computation on quantum-physical substrates, where familiar alternatives—the von Neumann entropy and quantum mutual information (or correlation entropy)— fall short. The OLR conception provides a natural foundation for the fundamental physical description of information processing in digital computing systems, both because it defines information as a physical state quantity—placing it on an equal footing with other physical quantities appearing in such descriptions—and because it captures essential features of information in computational contexts that alternative physical conceptions do not. The OLR information measure enables straightforward and thoroughly physical quantification of digital information in general quantum systems and processes, enabling unambiguous determination of bounds on physical costs of generally noisy digital computation. More generally, OLR information offers a physical foundation for information that does not require the physical to be—ontologically or metaphorically—already informational.

[1]  David Bawden,et al.  Mind the Gap: Transitions Between Concepts of Information in Varied Domains , 2014 .

[2]  A. U.S.,et al.  Predictability , Complexity , and Learning , 2002 .

[3]  Naftali Tishby,et al.  Predictability, Complexity, and Learning , 2000, Neural Computation.

[4]  Neal G. Anderson,et al.  Heat Dissipation in Nanocomputing: Lower Bounds From Physical Information Theory , 2013, IEEE Transactions on Nanotechnology.

[5]  Neal G. Anderson,et al.  Pancomputationalism and the Computational Description of Physical Systems , 2017 .

[6]  Benjamin Schumacher,et al.  Quantum Processes Systems, and Information , 2010 .

[7]  Charles H. Bennett,et al.  Logical reversibility of computation , 1973 .

[8]  Natesh Ganesh,et al.  Irreversibility and dissipation in finite-state automata , 2013 .

[9]  Tommaso Toffoli,et al.  Reversible Computing , 1980, ICALP.

[10]  M. Gell-Mann A Theory of Everything. (Book Reviews: The Quark and the Jaguar. Adventures in the Simple and the Complex.) , 1994 .

[11]  Natesh Ganesh,et al.  Toward nanoprocessor thermodynamics , 2012 .

[12]  Relation between the psychological and thermodynamic arrows of time. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Michael P. Frank,et al.  Reversibility for efficient computing , 1999 .

[14]  Neal G. Anderson Energy efficiency limits in approximate computing: A fundamental physical perspective , 2016, 2016 50th Asilomar Conference on Signals, Systems and Computers.

[15]  Neal G. Anderson,et al.  Quantifying the computational efficacy of nanocomputing channels , 2012, Nano Commun. Networks.

[16]  R. Landauer,et al.  Irreversibility and heat generation in the computing process , 1961, IBM J. Res. Dev..

[17]  Neal G. Anderson,et al.  On the physical implementation of logical transformations: Generalized L-machines , 2010, Theor. Comput. Sci..

[18]  Charles H. Bennett Notes on the history of reversible computation , 2000, IBM J. Res. Dev..

[19]  Olimpia Lombardi,et al.  What is Shannon information? , 2016, Synthese.

[20]  Gualtiero Piccinini,et al.  Physical computation : a mechanistic account , 2015 .

[21]  C. Timpson Quantum Information Theory and the Foundations of Quantum Mechanics , 2004, quant-ph/0412063.

[22]  Neal G. Anderson,et al.  Throughput-dissipation tradeoff in partially reversible nanocomputing: A case study , 2013, 2013 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH).

[23]  Maricarmen Martinez,et al.  Logic and Information , 2014 .

[24]  Natesh Ganesh,et al.  On-chip error correction with unreliable decoders: Fundamental physical limits , 2013, 2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS).

[25]  A. Kolmogorov Three approaches to the quantitative definition of information , 1968 .

[26]  James Ladyman,et al.  What does it mean to say that a physical system implements a computation? , 2009, Theor. Comput. Sci..

[27]  Gualtiero Piccinini,et al.  Information processing, computation, and cognition , 2011, Journal of biological physics.

[28]  R. Griffiths Consistent Quantum Theory , 2001 .

[29]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[30]  Gregory J. Chaitin,et al.  On the Length of Programs for Computing Finite Binary Sequences: statistical considerations , 1969, JACM.

[31]  Francesco Petruccione,et al.  The Theory of Open Quantum Systems , 2002 .

[32]  Neal G. Anderson,et al.  Overwriting information: Correlations, physical costs, and environment models , 2012 .

[33]  Alexis De Vos,et al.  Reversible Computing: Fundamentals, Quantum Computing, and Applications , 2010 .

[34]  Michael D. Westmoreland,et al.  Sending classical information via noisy quantum channels , 1997 .

[35]  I. Chuang,et al.  Quantum Computation and Quantum Information: Bibliography , 2010 .

[36]  Alexander S. Holevo,et al.  The Capacity of the Quantum Channel with General Signal States , 1996, IEEE Trans. Inf. Theory.

[37]  R. Hartley Transmission of information , 1928 .

[38]  Natesh Ganesh,et al.  Dissipation in neuromorphic computing: Fundamental bounds for feedforward networks , 2017, 2017 IEEE 17th International Conference on Nanotechnology (IEEE-NANO).

[39]  J. Smith Quantum Process , 2003, quant-ph/0307037.

[40]  Neal G. Anderson,et al.  Information Erasure in Quantum Systems , 2008 .

[41]  Susan Stepney,et al.  When does a physical system compute? , 2013, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[42]  James B. Hartle,et al.  Quantum Mechanics in the Light of Quantum Cosmology , 2018, 1803.04605.

[43]  J Clark Frank,et al.  Information Processing , 1970 .

[44]  Ray J. Solomonoff,et al.  A Formal Theory of Inductive Inference. Part II , 1964, Inf. Control..

[45]  Schumacher,et al.  Limitation on the amount of accessible information in a quantum channel. , 1996, Physical review letters.

[46]  A. Holevo Bounds for the quantity of information transmitted by a quantum communication channel , 1973 .

[47]  Neal G. Anderson Irreversible information loss: Fundamental notions and entropy costs , 2014 .