INVESTIGADORES
PAZ Dante Javier
artículos
Título:
Non-fiducial cosmological test from geometrical and dynamical distortions around voids
Autor/es:
CORREA, CARLOS M; PAZ, DANTE J; PADILLA, NELSON D; RUIZ, ANDRÉS N; ANGULO, RAÚL E; SÁNCHEZ, ARIEL G
Revista:
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Editorial:
WILEY-BLACKWELL PUBLISHING, INC
Referencias:
Lugar: Londres; Año: 2019 vol. 485 p. 5761 - 5772
ISSN:
0035-8711
Resumen:
We present a new cosmological test using the distribution of galaxiesaround cosmic voids without assuming a fiducial cosmology. The test isbased on a physical model for the void-galaxy cross-correlation functionprojected along and perpendicular to the line of sight. We treatcorrelations in terms of void-centric angular distances and redshiftdifferences between void-galaxy pairs, hence it is not necessary toassume a fiducial cosmology. This model reproduces the coupled dynamical(Kaiser effect, RSD) and geometrical (Alcock-Paczynski effect, GD)distortions that affect the correlation measurements. It also takes intoaccount the scale mixing due to the projection ranges in bothdirections. The model is general, so it can be applied to an arbitrarycylindrical binning scheme, not only in the case of the projectedcorrelations. It primarily depends on two cosmological parameters:Ωm, the matter fraction of the Universe today(sensitive to GD), and β, the ratio between the growth rate factorof density perturbations and the tracer bias (sensitive to RSD). In thecontext of the new generation of galaxy spectroscopic surveys, wecalibrated the test using the Millennium XXL simulation for differentredshifts. The method successfully recovers the cosmological parameters.We studied the effect of measuring with different projection ranges,finding robust results up to wide ranges. The resulting data covariancematrices are relatively small, which reduces the noise in the Gaussianlikelihood analysis and will allow the usage of a smaller number of mockcatalogues. The performance evaluated in this work indicates that thedeveloped method is a promising test to be applied on real data.