Detecting Microscopic Chaos in a Time Series of a Macroscopic Observable

Details Detecting Microscopic Chaos in a Time Series of a Macroscopic Observable Detecting Microscopic Chaos in a Time Series of a Macroscopic Observable

2011-05-23

arxiv.org/abs/1105.4575v1

Physics

Condensed Matter

Statistical Mechanics

Main article: 4 pages, 5 figures. Supplement: 5 pages, 3 figures

Scientific paper

Extracting reliable indications of chaos from a single experimental time series is a challenging task, in particular, for systems with many degrees of freedom. The techniques available for this purpose often require unachievably long time series. In this paper, we propose a new method to discriminate chaotic from multi-periodic integrable motion for a short time series provided it is very accurately measured. The method is based on analyzing higher order time derivatives of the time series. It exploits the fact that power spectra of chaotic time series exhibit exponential high-frequency tails, while, in the integrable systems, the power spectra are normally terminated at a finite frequency. We apply the above method to analysing signals generated by integrable and non-integrable systems of many interacting classical spins.

Affiliated with

Also associated with

No associations

Rating

Detecting Microscopic Chaos in a Time Series of a Macroscopic Observable 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 Detecting Microscopic Chaos in a Time Series of a Macroscopic Observable, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Detecting Microscopic Chaos in a Time Series of a Macroscopic Observable will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-23056