From transiting exoplanets to variable quasars, transient phenomena have rich scientific potential. Although the LSST will allow astronomers to see 18,000 $deg^2$ of the southern sky, allowing for the long-term tracking of billions of objects over its 10 year lifetime, the regular observing cadence is not optimal to find exoplanets. However, LSST will be spending 10\% of their observing time on ``deep drilling fields" and other mini-surveys, which might be advantageous for serendipitous exoplanet recovery with the help of period-recovering algorithms. Also, despite DES's large observing area ($5000 deg^2$), no catalog of variability of quasars and other variable objects has been created for this survey.
In this work, I present a realistic LSST light curve creation pipeline, which is used to rigorously test exoplanet transit search algorithms and see how different cadence models impact these search algorithms, as well as a code framework for DES that will identify and characterize variability. I will discuss my work in ascertaining the likelihood that LSST will be able to find earth- and super earth- sized planets around M6 dwarfs with the Box-Least Squares method. Additionally, I will present my current success in applying the variability code to DES supernova fields, as well as fixing incorrect error bars. Finally, I will propose my future work of using deep learning to recover exoplanet signals from LSST light curves, my intent to create a multi-planet light curve simulator as well as my intent to modify my current BLS code to recover multi-planet systems, and my plan to create a multi-band catalog of variability for DES.
