Analytical marginalisation over photometric redshift uncertainties in cosmic shear analyses

Understand

As the statistical power of imaging surveys grows, it is crucial to account for all systematic uncertainties.

• This is normally done by constructing a model of these uncertainties and then marginalizing over the additional model parameters.
• The resulting high dimensionality of the total parameter spaces makes inferring the cosmological parameters significantly more costly using traditional Monte-Carlo sampling methods.
• A particularly relevant example is the redshift distribution, $p(z)$, of the source samples, which may require tens of parameters to describe fully.