- Pinon, M;
- de Mattia, A;
- McDonald, P;
- Burtin, E;
- Ruhlmann-Kleider, V;
- White, M;
- Bianchi, D;
- Ross, AJ;
- Aguilar, J;
- Ahlen, S;
- Brooks, D;
- Cahn, RN;
- Chaussidon, E;
- Claybaugh, T;
- Cole, S;
- de la Macorra, A;
- Dey, B;
- Doel, P;
- Fanning, K;
- Forero-Romero, JE;
- Gaztañaga, E;
- Gontcho, S Gontcho A;
- Howlett, C;
- Kirkby, D;
- Kisner, T;
- Kremin, A;
- Lambert, A;
- Landriau, M;
- Lasker, J;
- Le Guillou, L;
- Levi, ME;
- Manera, M;
- Martini, P;
- Meisner, A;
- Miquel, R;
- Moustakas, J;
- Myers, AD;
- Niz, G;
- Palanque-Delabrouille, N;
- Percival, WJ;
- Poppett, C;
- Rossi, G;
- Sanchez, E;
- Schlegel, D;
- Schubnell, M;
- Seo, H;
- Sprayberry, D;
- Tarlé, G;
- Vargas-Magaña, M;
- Weaver, BA;
- Zarrouk, P;
- Zhou, R;
- Zou, H
Abstract:
We present a method to mitigate the effects of fiber assignment incompleteness in
two-point power spectrum and correlation function measurements from galaxy spectroscopic surveys,
by truncating small angular scales from estimators. We derive the corresponding modified
correlation function and power spectrum windows to account for the small angular scale truncation
in the theory prediction. We validate this approach on simulations reproducing the Dark Energy
Spectroscopic Instrument (DESI) Data Release 1 (DR1) with and without fiber assignment. We show
that we recover unbiased cosmological constraints using small angular scale truncated estimators
from simulations with fiber assignment incompleteness, with respect to standard estimators from
complete simulations. Additionally, we present an approach to remove the sensitivity of the fits
to high k modes in the theoretical power spectrum, by applying a transformation to the data
vector and window matrix. We find that our method efficiently mitigates the effect of fiber
assignment incompleteness in two-point correlation function and power spectrum measurements, at
low computational cost and with little statistical loss.