Bardeen, Bond, Kaiser - PowerPoint PPT Presentation

1 / 23
About This Presentation
Title:

Bardeen, Bond, Kaiser

Description:

1. Bardeen, Bond, Kaiser & Szalay (1986) 'The Statistics of Peaks in Gaussian Random Fields' ... Isotropy makes this P(k) Rigorous multivariate definition: 8 ... – PowerPoint PPT presentation

Number of Views:72
Avg rating:3.0/5.0
Slides: 24
Provided by: tri5104
Category:

less

Transcript and Presenter's Notes

Title: Bardeen, Bond, Kaiser


1
Bardeen, Bond, Kaiser Szalay (1986)The
Statistics of Peaks in Gaussian Random Fields
  • Edwin Sirko
  • 2004-11-22

2
(No Transcript)
3
(No Transcript)
4
Outline
5
(No Transcript)
6
Gaussian random fields what they are
  • Central limit theorem
  • Random-phase assumption of independent Fourier
    modes
  • White noise field
  • Convolved with square root of correlation
    function



Bertschinger (2001) ApJS 137, 1
7
Gaussian random fields useful things
  • Randomly selected point has a Gaussian
    distribution
  • Derivatives, integrals, linear functions of F are
    also Gaussian
  • Characterized completely by power spectrum P(k)
  • Isotropy makes this P(k)
  • Rigorous multivariate definition

8
Gaussian fields why they are important
  • Predicted by inflation
  • The density field is our Gaussian random field

Gaussian fields what they are not
  • Topological defect models
  • Anything with a nonzero three-point correlation
    function (bispectrum) the nonlinear universe

9
Gaussian fields what else they are
  • CMB
  • Ocean waves
  • Quasar light curves
  • Accuracy in clocks
  • Flow of Nile over last 2000 years
  • Music

Press (1978) ComAp 7, 103 http//map.gsfc.nasa.gov
/
10
More comments on noise
  • Their noise is our signal
  • f0 white noise, Johnson noise in electrical
    circuits
  • f-1 pink noise, flicker noise, 1/f noise,
    scale-invariant
  • f-2 brown noise, random walk
  • f-3

http//astronomy.swin.edu.au/pbourke/fractals/noi
se/
11
Gaussian random fields definitions
12
Smoothing
  • Physical
  • Silk damping, free streaming
  • Artificial
  • To study difference between clusters and galaxies

13
The spectral parameters
  • g
  • depends on
  • P(k) which depends on cosmology
  • RF smoothing
  • Approaches 1 if the power spectrum is a shell in
    k-space
  • Less than 1 if the power spectrum is broad
  • R
  • Measure of coherence scale

14
Peak density
  • Strategy evaluate
  • This will depend on spectral parameters g and R

15
Biasing
  • Bias the mass correlation function and galaxy
    (or cluster) correlation function differ
  • In other words, galaxies dont trace mass
  • Explained naturally if bright galaxies form
    preferentially at high peaks

16
Peak enhancement by background field
  • Assume galaxies form at peaks with F gt Ft
  • Superimpose field Fb
  • Enhancement factor in local density of peaks
  • In other words, a modest overdensity on some
    large mass scale can lead to a strong enhancement
    in the local density of galaxies.

17
Correlation functions of peaks
18
Profiles
http//mathworld.wolfram.com/Spheroid.html
19
Borgani et al. 1992
Naselsky et al. 2004
Thoul Weinberg 1996
Pudritz 2002
Van de Weygaert Icke 1989
Turner et al. 1993
McDonald Miralda-Escude 1999
Zhang et al 1997
Kaufmann Straumann 2000
Castro 2003
Suginohara Suto 1991
Ma Shu 2001
Theuns et al. 1998
20
Transfer function / Power spectrum
21
Conclusions
  • Inflation predicts the density perturbation field
    to be a Gaussian random field
  • Gaussianity is also simple because it can be
    described by just the power spectrum
  • BBKS derived peak density, correlation function,
    and profiles
  • These things depend only on two parameters of the
    power spectrum
  • BBKS is mostly cited because of their fit to the
    transfer function

22
(No Transcript)
23
(No Transcript)
Write a Comment
User Comments (0)
About PowerShow.com