Key papers on AIT applications to physics

Charles Bennett. Brought the idea of Landauers principle and the requirements of reversible computing into the algorithmic approach. See the following.

C. H. Bennett. Logical reversibility of computation. IBM Journal of Research and Development, 17: 525-532 (1973).

C. H. Bennett. Thermodynamics of computation- a review. International Journal of Theoretical Physics , 21(12): 905-940 (1982). Click here to download

C. H. Bennett. Notes on Landauers principle, reversible computation, and maxwells demon. Click here to download


Rolf Landauer . Landauer resolved the paradox of Maxwells demon. His argument is that irreversibility implies the loss of information with an energy cost of kTln 2 per bit lost (here k is Boltzmann's constant). The ability to apply AIT to non equilibrium systems relies on this understanding .

R. Landauer. Irreversibility and heat generation in the computing process. IBM Journal of Research and Development , 5: 183-191 (1961).

R. Landauer. "Information is physical",  In Proceedings of PhysComp 1992, pages 1-4. Los Alamitos: IEEE Computer Society Press, Oxford, 1992.  See also "Information is physical" Physics Today,  (American Institute of Physics) May 1991 page 23 .    Click here to download

See Nature News discussion on experimental evidence for Landauer's principle Nature (March 2012).  Click here to download

Wojciech Zurek The following two articles by Zurek provide the framework to apply AIT to physical systems.

W. H. Zurek, "Algorithmic Randomness and Physical Entropy I", Phys. Rev. A40, 4731--4751 (1989).

W. H. Zurek. Thermodynamics of of computation, algorithmic complexity and the information metric. Nature, 341: 119-124 (1989).

Information Distance. An article by some of the key players in AIT.

C. H. Bennett, P. Gács, M. Li, P. M. B. Vitányi, and W. H. Zurek . Information distance. IEEE Transactions on Information Theory, 44(4): 1407-1423 (1998) Click here to download

Digital physics. See Wicki discussion Click here to download .

E. Fredkin Digital mechanics. Physica D, pages 254-270 (1990)

Minimum Description Length. This interesting article links AIT with induction, the Bayesian approach to probability and with the idea that the shortest description of a data set satisfies Occams razor and Epicurus principle.

P. M. B. Vitányi and M. Li. Minimum description length induction, bayesianism, and Kolmogorov complexity. IEEE Trans. Inform. Theory, 46:446-464 (2000)

Also see Algorithmic Probability article in Scholarpedia by M. Hutter, S. Legg and P M.B. Vitányi. Click here to download

Reviews

Marcus Hutter Scholarpedia article on Algorithmic Complexity Click here to download

Peter D Grunwald and Paul M. B. Vitányi Kolmogorov Complexity and Information Theory Journal of Logic, Language and Information 12: 497-529 (2003). Click here to download.

S. D. Devine. The insights of algorithmic entropy. Entropy, 11(1): 85-110 (2009). Click here to download.