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The angular power spectrum is a natural tool to analyse the observed galaxynumber count fluctuations. In a standard analysis, the angular galaxydistribution is sliced into concentric redshift bins and all correlations ofits harmonic coefficients between bin pairs are considered---a procedurereferred to as `tomography'. However, the unparalleled quality of data fromoncoming spectroscopic galaxy surveys for cosmology will render this methodcomputationally unfeasible, given the increasing number of bins. Here, we putto test against synthetic data a novel method proposed in a previous study tosave computational time. According to this method, the whole galaxy redshiftdistribution is subdivided into thick bins, neglecting the cross-bincorrelations among them; each of the thick bin is, however, further subdividedinto thinner bins, considering in this case all the cross-bin correlations. Wecreate a simulated data set that we then analyse in a Bayesian framework. Weconfirm that the newly proposed method saves computational time and givesresults that surpass those of the standard approach.

Towards simulating a realistic data analysis with an optimised angular power spectrum of spectroscopic galaxy surveys