Deep Multi-object Spectroscopy to Enhance Dark Energy Science from LSST
Jeffrey A. Newman, Jonathan Blazek, Nora Elisa Chisari, Douglas Clowe,, Ian Dell'Antonio, Eric Gawiser, Ren\'ee A. Hlo\v{z}ek, Alex G. Kim, Anja von, der Linden, Michelle Lochner, Rachel Mandelbaum, Elinor Medezinski, Peter, Melchior, F. Javier S\'anchez, Samuel J. Schmidt

TL;DR
Deep multi-object spectroscopy on large telescopes can significantly improve LSST cosmological measurements by refining photometric redshifts, studying galaxy evolution, and enhancing cluster and weak lensing analyses, though it requires substantial telescope time.
Contribution
This paper highlights the potential of deep multi-object spectroscopy on large telescopes to advance dark energy science from LSST by improving redshift accuracy and galaxy environment studies.
Findings
Deep spectroscopy reduces uncertainties in galaxy redshifts.
Spectroscopy constrains galaxy intrinsic alignments for weak lensing.
Cluster studies benefit from galaxy motion measurements.
Abstract
Community access to deep (i ~ 25), highly-multiplexed optical and near-infrared multi-object spectroscopy (MOS) on 8-40m telescopes would greatly improve measurements of cosmological parameters from LSST. The largest gain would come from improvements to LSST photometric redshifts, which are employed directly or indirectly for every major LSST cosmological probe; deep spectroscopic datasets will enable reduced uncertainties in the redshifts of individual objects via optimized training. Such spectroscopy will also determine the relationship of galaxy SEDs to their environments, key observables for studies of galaxy evolution. The resulting data will also constrain the impact of blending on photo-z's. Focused spectroscopic campaigns can also improve weak lensing cosmology by constraining the intrinsic alignments between the orientations of galaxies. Galaxy cluster studies can be enhanced…
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Taxonomy
TopicsAstronomy and Astrophysical Research · CCD and CMOS Imaging Sensors · Dark Matter and Cosmic Phenomena
