Ensemble averages and nonextensivity at the edge of chaos of one-dimensional maps

Physics – Condensed Matter – Statistical Mechanics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

5 pages, 5 figures

Scientific paper

10.1103/PhysRevLett.93.020601

Ensemble averages of the sensitivity to initial conditions $\xi(t)$ and the entropy production per unit time of a {\it new} family of one-dimensional dissipative maps, $x_{t+1}=1-ae^{-1/|x_t|^z}(z>0)$, and of the known logistic-like maps, $x_{t+1}=1-a|x_t|^z(z>1)$, are numerically studied, both for {\it strong} (Lyapunov exponent $\lambda_1>0$) and {\it weak} (chaos threshold, i.e., $\lambda_1=0$) chaotic cases. In all cases we verify that (i) both $<\ln_q \xi > [\ln_q x \equiv (x^{1-q}-1)/(1-q); \ln_1 x=\ln x]$ and $ [S_q \equiv (1-\sum_i p_i^q)/(q-1); S_1=-\sum_i p_i \ln p_i]$ {\it linearly} increase with time for (and only for) a special value of $q$, $q_{sen}^{av}$, and (ii) the {\it slope} of $<\ln_q \xi>$ and that of $$ {\it coincide}, thus interestingly extending the well known Pesin theorem. For strong chaos, $q_{sen}^{av}=1$, whereas at the edge of chaos, $q_{sen}^{av}(z)<1$.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Ensemble averages and nonextensivity at the edge of chaos of one-dimensional maps does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Ensemble averages and nonextensivity at the edge of chaos of one-dimensional maps, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Ensemble averages and nonextensivity at the edge of chaos of one-dimensional maps will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-585193

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.