The PAU Survey: Spectral features and galaxy clustering using simulated narrow-band photometry
This article has been accepted for publication in MNRAS ©: 2018 The Autor(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved. ; We present a mock catalogue for the Physics of the Accelerating Universe Survey (PAUS) and use it to quantify the competitiveness of narrow-band imaging for measuring spectral features and galaxy clustering. The mock agrees with observed number count and redshift distribution data. We demonstrate the importance of including emission lines in the narrow-band fluxes. We show that PAUCam has sufficient resolution to measure the strength of the 4000 Å break to the nominal PAUS depth. We predict the evolution of a narrow-band luminosity function and show how this can be affected by the OII emission line. We introduce new rest-frame broad-bands (UV and blue) that can be derived directly from the narrow-band fluxes. We use these bands along with D4000 and redshift to define galaxy samples and provide predictions for galaxy clustering measurements. We show that systematic errors in the recovery of the projected clustering due to photometric redshift errors in PAUS are significantly smaller than the expected statistical errors. The galaxy clustering on two halo scales can be recovered quantitatively without correction, and all qualitative trends seen in the one halo term are recovered. In this analysis, mixing between samples reduces the expected contrast between the one halo clustering of red and blue galaxies and demonstrates the importance of a mock catalogue for interpreting galaxy clustering results. The mock catalogue is available on request at https://cosmohub.pic.es/home. ; This work was supported by the Science and Technol- ogy Facilities Council [ST/J501013/1, ST/L00075X/1]. PN acknowledges the support of the Royal Society through the award of a University Research Fellowship and the Euro- pean Research Council, through receipt of a Starting Grant (DEGAS-259586). We acknowledge support from the Royal Society international exchange programme. This work used the DiRAC Data Centric system at Durham University, operated by the Institute for Computational Cosmology on behalf of the STFC DiRAC HPC Facility www.dirac. ac.uk. This equipment was funded by BIS National E- infrastructure cap- ital grant ST/K00042X/1, STFC capital grant ST/H008519/1, and STFC DiRAC Operations grant ST/K003267/1 and Durham University. DiRAC is part of the National E-Infrastructure. Funding for PAUS has been provided by Durham Uni- versity (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scienti c Research (NWO) Vici grant 639.043.512) and University College London. The PAUS participants from Spanish institutions are par- tially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2015-88861, FPA2015-68048, SEV- 2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IEEC and IFAE are partially funded by the CERCA program of the Generalitat de Catalunya.Funding for PAUS has been provided by Durham Uni- versity (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scienti c Research (NWO) Vici grant 639.043.512) and University College London. The PAUS participants from Spanish institutions are par- tially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2015-88861, FPA2015-68048, SEV- 2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IEEC and IFAE are partially funded by the CERCA program of the Generalitat de Catalunya. Funding for PAUS has been provided by Durham Uni- versity (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scienti c Research (NWO) Vici grant 639.043.512) and University College London. The PAUS participants from Spanish institutions are par- tially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2015-88861, FPA2015-68048, SEV- 2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union