Incorporating distance information to a LISA Ultra-Compact Binary data pipeline

The Laser Interferometer Space Antenna (LISA) mission is expected to detect many Ultra-Compact Binaries (UCBs) in the Milky Way. In order to link these observations to existing models of star formation and evolution, the spatial distribution of UCBs is an important target for LISA data analysis. GBMCMC is a component of the Global Lisa Analysis Software Suite (GLASS) which identifies UCBs in simulated LISA data as part of a global fit pipeline. I will present modifications to GBMCMC's trans-dimensional Markov chain Monte Carlo algorithm. These modifications incorporate a Bayesian prior on the distance to UCBs from Earth using a simple model of the Milky Way.