LSST Cadence Optimization White Paper in Support of Observations of Unresolved Tidal Stellar Streams in Galaxies beyond the Local Group
Seppo Laine (Caltech/IPAC), David Martinez-Delgado (ARI/U., Heidelberg), Ignacio Trujillo (Instituto de Astrofisica de Canarias),, Pierre-Alain Duc (ObAS, U. Strasbourg), Carl J. Grillmair (Caltech/IPAC),, Carlos S. Frenk (U. Durham, UK), David Hendel (U. Toronto), Kathryn V.

TL;DR
This paper discusses optimizing LSST survey strategies to detect faint, unresolved stellar tidal streams in external galaxies beyond 20 Mpc, aiming to understand galaxy formation and evolution through diffuse light observations.
Contribution
It proposes using the LSST Wide-Fast-Deep survey to study unresolved tidal streams in external galaxies and compares observations with cosmological models to infer properties of stream progenitors.
Findings
Potential to detect faint tidal streams in distant galaxies
Comparison of observations with cosmological models
Strategies to minimize scattered light effects
Abstract
Deep observations of faint surface brightness stellar tidal streams in external galaxies with LSST are addressed in this White Paper contribution. We propose using the Wide--Fast--Deep survey that contains several nearby galaxies (at distances where the stars themselves are not resolved, i.e., beyond 20 Mpc). In the context of hierarchical galaxy formation, it is necessary to understand the prevalence and properties of tidal substructure around external galaxies based on integrated (i.e., unresolved) diffuse light. This requires collecting observations on much larger samples of galaxies than the Milky Way and M31. We will compare the observed structures to the predictions of cosmological models of galactic halo formation that inform us about the number and properties of streams around Milky Way-like galaxies. The insight gained from these comparisons will allow us to infer the…
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Taxonomy
TopicsGalaxies: Formation, Evolution, Phenomena · Astronomy and Astrophysical Research · CCD and CMOS Imaging Sensors
