Using Photometric Redshifts to Identify Host Galaxies in the Rubin Data Preview

Redshift is an important tool used by physicists to determine many properties of distant objects, and to determine the luminosity of transients, if they can be associated with a host galaxy. For large scale photometric surveys, such as the Legacy Survey of Space and Time (LSST), spectral data is not readily available to determine true redshift calculations so an estimation must be made. Using Rubin DP02 data, we estimate the PhotoZ of galaxies, and use this to associate transients with a likely host galaxy. In the first part of this project, a Color Match Nearest Neighbor (CMNN) PhotoZ redshift estimator was made to predict true redshift given only photometric data. The magnitude of each color filter of a test set of 10,000 galaxies was compared to a training set of 100,000 galaxies with known spectral redshift values to determine the most likely match. The test galaxies are then assigned a redshift estimation from this match. Using the CMNN estimator, ~73% of test galaxies were assigned a redshift estimate with 12.4% of those being outliers (|trueZ-testZ|>1.5). The standard deviation of these estimates was 0.1167. In the second part of this project, the Photoz estimator is used to identify host galaxies for Type 1a Supernovas (SN) detected by LSST. Second, we use these redshifts to associate simulated supernova with host galaxies. Using the right ascension (RA) and declination (DEC), the angular separation between the SN and potential host galaxies is found. Using the redshift estimation, we can determine the horizontal offset distance if the SN is at that redshift. For Type 1a SN, the luminosity distance for the SN is determined using the Standard Candle model. We use this to find an approximate line-of-sight distance between the SN and potential host galaxies. Using both the angular and line-of-sight separations, potential host galaxies are ranked based on apparent distance. These candidates will then be compared to the true host galaxy to do determine accuracy. Overall, both these tools will be extremely useful for future science for galaxies and SN's detected by LSST.