A map-based method for eliminating systematic modes from galaxy clustering power spectra with application to BOSS
B. Bahr-Kalus, W. J. Percival, D. J. Bacon, E.-M. Mueller, L., Samushia, L. Verde, A. J. Ross, J. L. Bernal

TL;DR
This paper presents a method to remove systematic errors from galaxy clustering power spectra, applied to BOSS data, revealing a large-scale power excess that persists despite systematic corrections, with implications for cosmological measurements.
Contribution
The paper introduces a map-based mode subtraction framework for systematic removal in galaxy surveys, improving unbiased power spectrum estimation over traditional weighting methods.
Findings
Systematic mode removal reduces large-scale power excess.
Large-scale power excess persists even after correction.
Implications for primordial non-Gaussianity measurements.
Abstract
We develop a practical methodology to remove modes from a galaxy survey power spectrum that are associated with systematic errors. We apply this to the BOSS CMASS sample, to see if it removes the excess power previously observed beyond the best-fit CDM model on very large scales. We consider several possible sources of data contamination, and check whether they affect the number of targets that can be observed and the power spectrum measurements. We describe a general framework for how such knowledge can be transformed into template fields. Mode subtraction can then be used to remove these systematic contaminants at least as well as applying corrective weighting to the observed galaxies, but benefits from giving an unbiased power. Even after applying templates for all known systematics, we find a large-scale power excess, but this is reduced compared with that observed using…
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