Cosmology Without Windows: Quadratic Estimators for the Galaxy Power Spectrum

TL;DR

This paper introduces quadratic estimators to directly measure the unwindowed galaxy power spectrum, eliminating the need for window function convolution, and demonstrates their effectiveness on BOSS DR12 data.

Contribution

The work develops and implements quadratic estimators that directly estimate the unwindowed power spectrum, improving accuracy and efficiency over traditional methods.

Findings

Estimators produce consistent power spectra and parameters with traditional methods.

The approach is computationally efficient using FFTs and conjugate gradient methods.

Potential for improved measurements in dense surveys or non-Gaussian analyses.

Abstract

Conventional algorithms for galaxy power spectrum estimation measure the true spectrum convolved with a survey window function, which, for parameter inference, must be compared with a similarly convolved theory model. In this work, we directly estimate the unwindowed power spectrum multipoles using quadratic estimators akin to those introduced in the late 1990s. Under Gaussian assumptions, these are optimal and free from the leading-order effects of pixellization and non-Poissonian shot-noise. They may be straightforwardly computed given the survey data-set and a suite of simulations of known cosmology. We implement the pixel-based maximum-likelihood estimator and a simplification based on the FKP weighting scheme, both of which can be computed via FFTs and conjugate gradient descent methods. Furthermore, the estimators allow direct computation of spectrum coefficients in an arbitrary linear compression scheme, without needing to first bin the statistic. Applying the technique to a subset of the BOSS DR12 galaxies, we find that the pixel-based quadratic estimators give statistically consistent power spectra, compressed coefficients, and cosmological parameters to those obtained with the usual windowed approaches. Due to the sample's low number density and compact window function, the optimal weighting scheme gives little improvement over the simplified form; this may change for dense surveys or those focusing on primordial non-Gaussianity. The technique is shown to be efficient and robust, and shows significant potential for measuring the windowless power spectrum and bispectrum in the presence of weak non-Gaussianity.