Update analysis_brokers.tex

lsst · Jan 21, 2025 · 2289608 · 2289608
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-\textbf{B-101} Identify Tidal Disruption Events (TDEs) and extreme AGN by constructing long-term light curves from difference images using forced photometry.  Combine host galaxy properties (e.g., mass, Start Formation Rate, etc) with TDE candidates to build a comprehensive classification.
-\textbf{B-201}  Detect and characterize microlensing events by analyzing DIA images. Model light curves and assess crowding effects to estimate baseline magnitudes and object properties. 
-\textbf{B-202} Classify periodic variable stars using a neural network. Improve classification algorithms with DR1 data and develop labeled datasets for future analyses.
+\textbf{B-201} Identify Tidal Disruption Events (TDEs) and extreme AGN by constructing long-term light curves from difference images using forced photometry.
+Combine host galaxy properties (e.g., mass, Start Formation Rate, etc) with TDE candidates to build a comprehensive classification.
+
+\textbf{B-202} Detect and characterize microlensing events by analyzing DIA images.
+Model light curves and assess crowding effects to estimate baseline magnitudes and object properties.
+
+\textbf{B-203} Classify periodic variable stars using a neural network.
+Improve classification algorithms with DR1 data and develop labeled datasets for future analyses.