Optimal dataset combining in f_nl constraints from large scale structure

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  • 1 August 2008
Abstract
We consider the problem of optimal weighting of tracers of structure for the purpose of constraining the non-Gaussianity parameter f_nl. By slicing a general sample into infinitely many samples with different biases, we derive the analytic expression for the relevant Fisher matrix element. We next consider different weighting schemes to construct two samples from a single sample of tracers with a continuously varying bias. We show that a particularly simple ansatz for weighting functions can recover all information about f_nl in a sample and that simple division into two equal samples is suboptimal at the at least 30% level when sampling of modes is good, but only marginally suboptimal in the limit where Poisson errors dominate.

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