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Clustering Discussion Session. Understanding LAE - Heidelberg 09/oct/08 Chair: Harold Francke, U. de Chile. Why do we care?. Clustering measurements allows the testing of DM hosting halos (of LAEs) Masses, number densities Can constrain evolution of LAE

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Clustering discussion session

Clustering Discussion Session

Understanding LAE - Heidelberg 09/oct/08

Chair: Harold Francke, U. de Chile


Why do we care
Why do we care?

  • Clustering measurements allows the testing of DM hosting halos (of LAEs)

    • Masses, number densities

  • Can constrain evolution of LAE

    • Evolution of DM halos is known in CDM cosmology.

  • Gives clean measurement of the occupation fraction of LAE on their hosting halos

  • Using LAEs as tracers of LSS, we can constrain cosmological parameters

Talks by Ouchi san & Gawiser san

Talk by Blanc kun in the morning…


Basics
Basics

  • Two-point autocorrelation function:

    P=n2(1 + (12))d1d2 (angular)

    P=2(1 + (r12))dV1dV2 (spatial)

    Corresponds to excess probability of finding two points in areas (volumes) d1 and d2 (dV1 and dV2) separated by 12 (r12).

  • Correlation lengthr0 , slope : (r) = ( r / r0 )-


What does this look like
What does this look like?

  • Real galaxies show a power law correlation function



Halo mass and clustering
Halo Mass and clustering

Dark matter halos are biased tracers of the matter field.

Autocorrelation function in a numerical simulation…





From 2d into 3d
From 2D into 3D… the DM halos hosting our galaxies…

dist

observer

SPATIAL correlation function

ANGULAR correlation function

Beware of narrow redshift distributions! (Simon 2006)

distance distribution


Cosmic variance
Cosmic variance? the DM halos hosting our galaxies…

  • If in a survey we detect N galaxies with angular corr. (), the variance in this number is:

  • LAE surveys are spatially thin

    • there are less projection effects

    • () is considerable


From statistics to halos
From statistics to halos the DM halos hosting our galaxies…

  • Bias factor: relates halos to mass

    • At large scales, the bias is a constant (linear regime)

    • Short scales (~Rvir) non-linear collapse and non-gravitational effects play a role


From statistics to halos1
From statistics to halos the DM halos hosting our galaxies…

  • bias(M) can be calculated from theoretical prediction for halo collapse (Mo&White ‘96 and revisions)

  • Number densities can be calculated from the halo mass function (Press&Schechter ‘74 and revisions by Sheth&Tormen, 1999-2002)


  • From statistics to halos2
    From statistics to halos the DM halos hosting our galaxies…

    • Having a simulation at hand (semianalytical or hydro), you can compare (r) directly and measure masses and number densities in the simulation.

      (C. Lacey’s & A. Orsi’s talks yesterday)

    These models should also reproduce the clustering measurements that exist!!


    Lae clustering issues
    LAE clustering issues the DM halos hosting our galaxies…

    • What are the masses of the halos containing them?

    • How many halos are occupied?

    • How does LAE clustering relate to Lya and continuum luminosity?

    • How do LAEs at redshift X relate to galaxy type Y at redshift Z?


    Lae clustering issues1
    LAE clustering issues the DM halos hosting our galaxies…

    • How do LAEs at redshift X relate to galaxy type Y at redshift Z?

      New samples:

      at z~3: McLinden poster

      at z~2: talks by Nilsson, Reddy)