Always Finite Entropy and Lyapunov exponents of two-dimensional cellular automata

Given a new definition for the entropy of a cellular automata acting on a two-dimensional space, we propose an inequality between the entropy of the shift on a two-dimensional lattice and some angular analog of Lyapunov exponents.Comment: 20 Fevrier 200

Density of periodic points, invariant measures and almost equicontinuous points of cellular automata

Revisiting the notion of m-almost equicontinuous cellular automata introduced by R. Gilman, we show that the sequence of image measures of a shift ergodic measure m by iterations of a m-almost equicontinuous automata F, converges in Cesaro mean to an invariant measure mc. If the initial measure m is a Bernouilli measure, we prove that the Cesaro mean limit measure mc is shift mixing. Therefore we also show that for any shift ergodic and F-invariant measure m, the existence of m-almost equicontinuous points implies that the set of periodic points is dense in the topological support S(m) of the invariant measure m. Finally we give a non trivial example of a couple (m-equicontinuous cellular automata F, shift ergodic and F-invariant measure m) which has no equicontinuous point in S(m)

Some properties of cellular automata with equicontinuity points

We investigate topological and ergodic properties of cellular automata having equicontinuity points. In this class surjectivity on a transitive SFT implies existence of a dense set of periodic points. Our main result is that under the action of such an automaton any shift ergodic measure converges in Cesaro Mean

Entropy rate of higher-dimensional cellular automata

We introduce the entropy rate of multidimensional cellular automata. This number is invariant under shift-commuting isomorphisms; as opposed to the entropy of such CA, it is always finite. The invariance property and the finiteness of the entropy rate result from basic results about the entropy of partitions of multidimensional cellular automata. We prove several results that show that entropy rate of 2-dimensional automata preserve similar properties of the entropy of one dimensional cellular automata. In particular we establish an inequality which involves the entropy rate, the radius of the cellular automaton and the entropy of the d-dimensional shift. We also compute the entropy rate of permutative bi-dimensional cellular automata and show that the finite value of the entropy rate (like the standard entropy of for one-dimensional CA) depends on the number of permutative sites. Finally we define the topological entropy rate and prove that it is an invariant for topological shift-commuting conjugacy and establish some relations between topological and measure-theoretic entropy rates

On a zero speed sensitive cellular automaton

Using an unusual, yet natural invariant measure we show that there exists a sensitive cellular automaton whose perturbations propagate at asymptotically null speed for almost all configurations. More specifically, we prove that Lyapunov Exponents measuring pointwise or average linear speeds of the faster perturbations are equal to zero. We show that this implies the nullity of the measurable entropy. The measure m we consider gives the m-expansiveness property to the automaton. It is constructed with respect to a factor dynamical system based on simple "counter dynamics". As a counterpart, we prove that in the case of positively expansive automata, the perturbations move at positive linear speed over all the configurations

A Bilateral version of Shannon-Breiman-McMillan Theorem

We give a new version of the Shannon-McMillan-Breiman theorem in the case of a bijective action. We illustrate this new result with an exampl

Cellular automata and Lyapunov exponents

In this article we give a new definition of some analog of Lyapunov exponents for cellular automata .Then for a shift ergodic and cellular automaton invariant probability measure we establish an inequality between the entropy of the automaton, the entropy of the shift and the Lyapunov exponent

Developement of simulation tools for the analysis of variability in advanced semiconductor electron devices

The progressive down-scaling has been the driving force behind the integrated circuit (IC) industry for several decades, continuously delivering higher component densities and greater chip functionality, while reducing the cost per function from one CMOS technology generation to the next. Moore’s law boosts IC industry profits by constantly releasing high-quality and inexpensive electronic applications into the market using new technologies. From the 1 m gate lengths of the eighties to the 35 nm gate lengths of contemporary 22 nm technology, the industry successfully achieved its scaling goals, not only miniaturizing devices but also improving device performance