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Predictions for the Detectability of Milky Way Satellite Galaxies and Outer-Halo Star Clusters

Kabelo Tsiane (kabelo@umich.edu)

Rubin Science Assembly 05/29/25

Vera C. Rubin Observatory | Agency Quarterly Status | 12-07-2025

Acronyms & Glossary

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Motivation

  • Current census of Milky Way satellites is incomplete
  • Ultra-Faint Dwarfs allow us to probe:
    • Galaxy formation
    • Reionization
    • Properties of dark matter
  • The goal of our work is to predict the detectability of Milky Way satellite galaxies and outer-halo star clusters with the Vera C. Rubin Observatory using simulated satellite systems

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Reionization Redshift

  • UV heating after reionization suppresses gas accretion below a time-dependent mass scale
  • Faint end of luminosity function probes this

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From Manwadkar & Kravtsov 2022

Vera C. Rubin Observatory | Agency Quarterly Status | 12-07-2025

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Constraints on Dark Matter Properties

  • Non-CDM physics suppresses the linear matter power spectrum on small scales (left), leading to an underabundance of subhalos (middle) and faint MW-satellites (right)

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From Nadler+ 2021

Vera C. Rubin Observatory | Agency Quarterly Status | 12-07-2025

Acronyms & Glossary

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Dataset

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Vera C. Rubin Observatory | Agency Quarterly Status | 12-07-2025

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Simulated Satellites

  • Key photometric properties of the DC2 catalog (photometric uncertainty, detection probability, star/galaxy classification efficiency) used to generate consistent catalog-level simulations of satellite galaxies

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Acronyms & Glossary

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Simulated Satellites

  • For photometric uncertainties we used the measured magnitude uncertainties of stars in combination with 𝑆/𝑁 = 5 magnitude limit depth maps generated from the input images

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Simulated Satellites

  • 105 Milky Way satellites are generated at catalog level
  • Spatial distributions of stars are sampled from a Plummer profile
  • Simulated LSST bandpasses used for DC2 were integrated into the Padova CMD interface to generate photometry consistent with DC2
  • Stellar initial masses are drawn from a Chabrier IMF πŸ‘ͺ used to assign current absolute magnitudes from a Marigo + 2017 isochrone

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Analysis

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Injection, Selection and Rejection

For each satellite:

  • Query the Rubin Table Access Protocol (TAP) service for DC2 catalog objects that were located ≀ 2 deg from the centroid of the satellite
  • Select objects with magnitude error in the 𝑔 and π‘Ÿ bands of 𝜎 < 0.2 (S/N ≳ 5)
  • Select objects with g < 26 mag, r < 26 mag due to drop in stellar classification efficiency

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Acronyms & Glossary

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Search Algorithm -- simple

  • Creates an annulus around a region of interest and applies an isochrone filter in color–magnitude space
  • Identifies local density peaks with density thresholds
  • Expected number of stars calculated at peak, then observed stars recorded
  • Outputs Poisson detection significance (SIG) [0, 37.5]
  • Detection flagged for SIG β‰₯ 5.5

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Star/Galaxy Classification

  • Our analysis is split into two configurations
    • Measured (using object EXTENDEDNESS)
    • Idealized (truth information)
  • Measured configuration β‰ˆ 22.4% false positives
  • Idealized configuration β‰ˆ 2.3% false positives

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Results

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Observational Selection Function

  • The probability that a satellite will be detected (SIG > 5.5) as a function of its heliocentric distance (𝐷), absolute 𝑉-band magnitude (𝑀𝑉 ), and azimuthally averaged projected physical half-light radius (π‘Ÿ1/2)
  • A useful parameterization of the OSF is the 50% detection efficiency contour
  • Gradient-boosted decision tree classifier fully characterizes the OSF parameter space

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DES (black dashed)

Measured star/galaxy classification SIG > 8.4 (red dotted)

Measured star/galaxy classification SIG > 5.5 (red dot-dash)

Perfect star/galaxy classification SIG > 5.5 (red dashed)

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Vera C. Rubin Observatory | Agency Quarterly Status | 12-07-2025

Acronyms & Glossary

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Depth and Coverage of 10-year LSST WFD

  • We estimate the coverage and depth of the 10-year LSST WFD program using the baseline v4.0 operations simulation
  • Masked regions of the sky with interstellar dust, bright stars, globular clusters and Magellanic Clouds
  • The resulting footprint has an area of ∼ 18,300 deg2

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Galaxy-Halo Model

  • Parameterizes the relationship between satellite and subhalo properties, and the effects of baryonic physics on subhalo populations
  • We sample from the posteriors of the galaxy–halo model parameters that were derived by fitting to data from DES and PS1

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Nadler+2020

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Galaxy-Halo Model

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Nadler+2020

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Acronyms & Glossary

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Luminosity Function

  • Combine OSF, predictions for depth and coverage of 10-year LSST WFD and MW GH model to predict satellite population properties
  • We focus on faint (MV < 0) and compact (r1/2 > 10 pc) systems that LSST will detect within the virial radius of the Milky Way halo (∼300 kpc) as a function of satellite luminosity

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Luminosity Function

  • The galaxy–halo model from Nadler et al. (2020) predicts that the Milky Way has 220 Β± 50 satellite galaxies
  • 10-year LSST predictions (mean Β± 1 𝜎):
    • 89 Β± 20 assuming perfect star/galaxy separation – 53 discoveries
    • 83 Β± 18 assuming measured star/galaxy separation – 47 discoveries
    • 67 Β± 14 assuming measured and corrected star/galaxy separation – 31 discoveries

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LSST Predictions

  • Properties of Milky Way satellite dwarf galaxies detectable with LSST
  • Currently known candidate (open circles) and confirmed (filled circles) Milky Way satellite dwarf galaxies

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END

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Overflow – DC2

  • DC2 simulates 5 years of LSST observations
  • Six optical bands ugrizy
  • 300 deg2 of LSST WFD footprint (19,600 deg2)
  • 1 deg2 of LSST DDF
  • Median S/N = 5 magnitude limits for point-like sources in DC2 are 𝑔 = 27.0 mag and π‘Ÿ = 26.8

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Overflow – ML model OSF

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Vera C. Rubin Observatory | Agency Quarterly Status | 12-07-2025

Acronyms & Glossary