analysis of multitracer cosmological surveys

We present optimal quadratic estimators for the Fourier analysis of cosmological surveys that detect several different types of tracers of large-scale structure. Our estimators can be used to simultaneously fit the matter power spectrum and the biases of the tracers - as well as redshiftspace distortions (RSDs), non-Gaussianities (NGs), or any other effects that are manifested through differences between the clusterings of distinct species of tracers. Our estimators reduce to the one by Feldman, Kaiser & Peacock (FKP) in the case of a survey consisting of a single species of tracer. We show that the multitracer estimators are unbiased, and that their covariance is given by the inverse of the multitracer Fisher matrix. When the biases, RSDs and NGs are fixed to their fiducial values, and one is only interested in measuring the underlying power spectrum, our estimators are projected into the estimator found by Percival, Verde & Peacock. We have tested our estimators on simple (lognormal) simulated galaxy maps, and we show that it performs as expected, being either equivalent or superior to the FKP method in all cases we analysed. Finally, we have shown how to extend the multitracer technique to include the one-halo term of the power spectrum.