Predicting Star Formation Rates Using SDSS Data

With the latest public data release from the SDSS MaNGA program, we are attempting to find a possible correlation between the fluxes from SDSS imaging of optical bands from galaxies to their Star Formation Rates (SFR). We aggregated our data from both SDSS and WISE survey databases. This full dataset contained over 7000 galaxies. With this data, we could calculate the H-alpha luminosities, distance, and SFR. We then used WISE data to correct for the effects of dust obscuration, similar to Kennicutt et al. 2009. We are in the process of using the SDSS flux data and calculated SFR to train a machine learning model so we can apply this correlation to a much larger catalog. When this correlation is found and applied, one would only need the SDSS band fluxes to predict the SFR for a galaxy.

Theme – Machine Learning, Statistics, and Algorithms