Path integral methods for primordial density perturbations - Sampling of constrained Gaussian random fields

Statistics – Computation

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

75

Cosmology, Galactic Evolution, Mass Distribution, Algorithms, Computational Astrophysics, Dark Matter, Density Distribution, Monte Carlo Method, Random Processes, Statistical Distributions

Scientific paper

Path integrals may be used to describe the statistical properties of a random field such as the primordial density perturbation field. In this framework the probability distribution is given for a Gaussian random field subjected to constraints such as the presence of a protovoid or supercluster at a specific location in the initial conditions. An algorithm has been constructed for generating samples of a constrained Gaussian random field on a lattice using Monte Carlo techniques. The method makes possible a systematic study of the density field around peaks or other constrained regions in the biased galaxy formation scenario, and it is effective for generating initial conditions for N-body simulations with rare objects in the computational volume.

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

Path integral methods for primordial density perturbations - Sampling of constrained Gaussian random fields 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 Path integral methods for primordial density perturbations - Sampling of constrained Gaussian random fields, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Path integral methods for primordial density perturbations - Sampling of constrained Gaussian random fields will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-901342

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