Update analysis_idacs.tex

analysis_idacs.tex

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-\textbf{I-100}
-\textbf{I-200}
-\textbf{I-300}
+\textbf{I-201} Retrieve PSF cutouts from coadd images (e.g., using the Notebook Aspect of the RSP) to derive parameters of PSF models. Use these parameters to train machine-learning-based algorithms for galaxy classification using GPU resources at IDACs.
+\textbf{I-202}: Find galaxy clusters in LSST data using Rubin APIs and notebooks for exploratory analysis. Download data to NERSC and run cluster-finding algorithms developed by LSST DESC, incorporating data from precursor surveys such as DECam and HSC.
+\textbf{I-301} Using direct access to a copy of the coadd and shear catalogs at NERSC or other supercomputing facilities (which will require many iterations through the entire coadd catalogs with high I/O demands), measure weak lensing and galaxy clustering two-point correlation functions to estimate cosmological parameters and constrain cosmological models. Analyze tomographic data, perform photo-z calibrations, and compute covariances using parallelized HPC pipelines and Rubin APIs