Day 1229

Wednesday.

1703.02070
Unbiased clustering estimation in the presence of missing observations
Bianchi, Percival

In order to be efficient, spectroscopic galaxy redshift surveys do not obtain redshifts for all galaxies in the population targeted.  The missing galaxies are often clustered, commonly leading to a lower proportion of successful observations in dense regions.  One example is the close-pair issue for SDSS spectroscopic galaxy surveys, which have a deficit of pairs of observed galaxies with angular separation closer than the hardware limit on placing neighboring fibers.  Spatially clustered missing observations will exist in the next generations of surveys.  Various schemes have previously been suggested to mitigate these effects, but none works for all situations.  Argue that the solution is to link the missing galaxies to those observed with statistically equivalent clustering properties, and that the best way to do this is to rerun the targeting algorithm, varying the angular position of the observations.  Provided that every pair has a non-zero probability of being observed in one realization of the algorithm, then a pair-unweighting scheme linking targets to successful observations, can correct these issues.  Present such a scheme, and demonstrate its validity using realizations of an idealized simple survey strategy.


1703.02071
Using angular pair unweighting to improve 3D clustering measurements
Percival, Bianchi

Analysis of mocks suggests that, if an angular clustering measurement is available over twice the area covered spectroscopically, weighting gives a ~10-20% reduction of the variance of the monopole correction function on the BAO scale.