# Cosmic Variance Calculator: Short Description - README v1.0

## Purpose

####
The CosmicVarianceCalculator estimates the one sigma fractional
uncertainty on the galaxy number counts for high-redshift surveys. It
takes into account fluctuations in the counts due to large scale
structure ("cosmic variance") as well as due to Poisson noise.

## Method

####
Cosmic variance is computed by first integrating the two points
correlation function of dark matter (computed in linear theory) over
the pencil beam volume and then by multiplying it for the average bias
of the galaxy sample, estimated using extended Press-Schechter
formalism from the input number density and average halo occupation
fraction.

For optimal browsing performance, the web edition v1.0 of this
calculator has a precomputed two point correlation function xi(r)
based on our standard cosmological model. This is done over a grid
with n=30000 points equally spaced points, from 0.005Mpc/h to
150Mpc/h. Within the grid a nearest point lookup in the table is used
to access stored data, while xi(r) is set to 0 for r>150Mc/h.

The pencil beam is a parallelepiped with base given by the input field
of view transformed from angular to comoving size using the angular
diameter distance evaluated at the input mean redshift of the
survey. The length of the pencil beam is given by the line of sight
comoving distance between the input minimum and maximum redshifts for
the selection window.

The two point correlation function is then integrated over the volume
V of the survey to obtain the dark matter variance: sigma_DM = \int_V
\int_V xi(|r1-r2|)d^3r1d^3r2 / \int_V \int_V d^3r1d^3r2. Integration
is carried out using the GSL Plain Multidimensional Monte Carlo
Integration (gsl_monte_plain) with 200000 points.

The average bias (b) of the sample is computed from the input comoving
density of objects using extended Press-Schecter modeling. The cosmic
variance is given by sigma^2_CV = b^2*sigma^2_DM.

Finally the total uncertainty on the number counts is computed combining the contribution from cosmic variance and from Poisson noise.

## Input

####
The input data required are divided into three blocks:

* Pencil beam properties, that is geometry of the field of view for the
survey, average redshift of the galaxy population and redshift width
of the selection window.

* Galaxy sample properties, that is the intrinsic number of objects
the survey is expected to observe, the average halo occupation
fraction and the completeness of the observation.

* Cosmology, currently (in version 1.0) restricted for cpu limitation
on the web-server to a flat LCDM universe with OmegaM=0.26,
OmegaL=0.74, h=70km/s/Mpc and ns=1. Free parameters are Sigma8 and the
choice between classic Press-Schechter or Sheth-Tormen bias calculation.

## Output

####
The main output is the one sigma fractional uncertainty on the number
counts. This is also translated into the error on the observed counts
for easy and immediate use.

In addition the code provides output information about the number
density of the sample, the average bias, the minimum mass of dark
matter halos that host the galaxies in the sample and the bias at this
minimum mass. The pencil beam geometry is also summarized.

Finally the input parameters provided are mirrored, just to make sure
that the answer you get is really what you asked.

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