Anthropic prediction for a large multi-jump landscape

Physics – High Energy Physics – High Energy Physics - Theory

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

33 pages, 7 figures Minor revisions made and references added

Scientific paper

10.1088/1475-7516/2008/10/009

The assumption of a flat prior distribution plays a critical role in the anthropic prediction of the cosmological constant. In a previous paper we analytically calculated the distribution for the cosmological constant, including the prior and anthropic selection effects, in a large toy ``single-jump'' landscape model. We showed that it is possible for the fractal prior distribution we found to behave as an effectively flat distribution in a wide class of landscapes, but only if the single jump size is large enough. We extend this work here by investigating a large ($N \sim 10^{500}$) toy ``multi-jump'' landscape model. The jump sizes range over three orders of magnitude and an overall free parameter $c$ determines the absolute size of the jumps. We will show that for ``large'' $c$ the distribution of probabilities of vacua in the anthropic range is effectively flat, and thus the successful anthropic prediction is validated. However, we argue that for small $c$, the distribution may not be smooth.

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

Anthropic prediction for a large multi-jump landscape 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 Anthropic prediction for a large multi-jump landscape, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Anthropic prediction for a large multi-jump landscape will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-500070

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