Minkowski Functionals of SDSS-III BOSS : Hints of Possible Anisotropy in the Density Field?
Stephen Appleby, Changbom Park, Pratyush Pranav, Sungwook E. Hong, Ho, Seong Hwang, Juhan Kim, Thomas Buchert

TL;DR
This study measures Minkowski functionals from SDSS-III BOSS galaxy data to investigate potential anisotropies in the cosmic density field, finding hints of systematic differences between sky regions that could suggest anisotropy or data systematics.
Contribution
It introduces a methodology for unbiased Minkowski functional measurement from masked survey data and applies it to BOSS data, revealing possible anisotropic features in the density field.
Findings
Lower shape parameter $a_0$ in LOWZ-South compared to LOWZ-North
Constraints on cosmological parameters consistent with Planck results
Potential indication of anisotropy or systematics in the data
Abstract
We present measurements of the Minkowski functionals extracted from the SDSS-III BOSS catalogs. After defining the Minkowski functionals, we describe how an unbiased reconstruction of these statistics can be obtained from a field with masked regions and survey boundaries, validating our methodology with Gaussian random fields and mock galaxy snapshot data. From the BOSS galaxy data we generate a set of four density fields in three dimensions corresponding to the northern and southern skies of LOWZ and CMASS catalogs, smoothing over large scales such that the field is perturbatively non-Gaussian. We extract the Minkowski functionals from each data set separately, and measure their shapes and amplitudes by fitting a Hermite polynomial expansion. For the shape parameter of the Minkowski functional curves , that is related to the bispectrum of the field, we find that the LOWZ-South…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
