CAPS Seminars

… is essential for probing supernova progenitor physics and accurately estimating cosmological parameters, along with gaining information on many other open questions in astronomy. However, spectroscopic resources are scarce, an expected <1% will be followed up. Due to the incoming immense quantity of transient sources, we need an automated system to sort through the millions of Rubin supernovae and prioritize the most scientifically interesting for follow-up.
To maximize the SNe Ia used in a cosmology analysis, we must create a photometrically classified sample of SNe Ia, but this process is imperfect and allows contamination particularly from SNe Ib/c and SNe II. We will create an ideal, representative transient training set through active learning to obtain a pure sample of SNe Ia. We will spectroscopically observe and classify the hardest to photometrically label objects, adding these objects to our training set ensuring AI algorithms have an easier time classifying similar light curves going forward. We implement the automated system, the Recommendation System for Spectroscopic Follow-up (RESSPECT) to sort through the millions of Rubin SNe and prioritize the most cosmologically useful for followup. Preliminary results using the simulated ELAsTiCC dataset show that SNe Ia photometrically classified using a RESSPECT chosen training set leads to tighter constraints on w_0 and w_a. Type Ia cosmology is just one module of the LSST Spectroscopic recommendation system, this module can be specified for a user’s specific science case. Anomaly detection is the second metric currently integrated into the RESSPECT pipeline, and I will illustrate how a user can add their own custom metrics to find the objects they care most about. Recommendations from the pipeline can be submitted to the DESC Target and Observation Manager which will enable coordination with various spectroscopic telescopes.

… serendipitously in SDSS spectroscopy, making it difficult to determine the timescale and magnitude of the CL-AGN transition. As such, the physical mechanisms behind this transition are still unknown. I present new work measuring the timescale and magnitude of photometric variability in ZTF light curves for known CL-AGN. I find that CL-AGN transitions usually occur on timescales of about a year and can be distinguished from normal AGN variability by the change in their g-band magnitudes. I also present six Seyfert 1 AGN which are candidates for CL-AGN transitions.