Thermodynamics of computation and information distance
Charles H. Bennett, Péter Gács, et al.
STOC 1993
The observed complexity of nature is often attributed to an intrinsic propensity of matter to self-organize under certain (e.g., dissipative) conditions. In order better to understand and test this vague thesis, we define complexity as "logical depth," a notion based on algorithmic information and computational time complexity. Informally, logical depth is the number of steps in the deductive or causal path connecting a thing with its plausible origin. We then assess the effects of dissipation, noise, and spatial and other symmetries of the initial conditions and equations of motion on the asymptotic complexity-generating abilities of statistical-mechanical model systems. We concentrate on discrete, spatially-homogeneous, locally-interacting systems such as kinetic Ising models and cellular automata. © 1986 Plenum Publishing Corporation.
Charles H. Bennett, Péter Gács, et al.
STOC 1993
Charles H. Bennett, Herbert J. Bernstein, et al.
Physical Review A - AMO
Charles H. Bennett, Gilles Brassard, et al.
Natural Computing
Charles H. Bennett
International Journal of Theoretical Physics