ACT CMB School
The intent of this course is to familiarize those new to the CMB with the basic concepts of its simulation and analysis. Topics covered include: simulation of the CMB and astrophysical sources (point sources and SZ-clusters), instrument modeling, power spectrum analysis, matched filter techniques, analysis of archival data, CMB polarization, CMB lensing, time domain simulation, maximum likelihood mapmaking, and parameter estimation.
The course is presented as a series of interactive sessions which follow Jupyter Python Notebooks which contain relevant code and text. Below you will find descriptions of each of the 10 modules and links to GitHub which will allow you to view the notebooks. If you wish to work with the code the notebooks can be downloaded from GitHub here. These notebooks run on python 3 using only standard libraries such as numpy and matplotlib. We recommend Anacond Python. We are preparing a version of this code to run online in Binder, but it is not yet ready for prime time.
The notenbooks were written by Jeff McMahon, Renee Hlozek, Mat Madhavacheril, Sigurd Naess, and Alex Van Engelen.
instructors: Jo Dunkley, Renee Hlozek, Jeff McMahon, Mat Madhavacheril, Alex van Engelen
instructors: Renee Hlozek, Jeff McMahon
La Serena 2015
instructors: Jeff McMahon (as part of the La Serena data science summer school)
In this module you will learn to simulate realizations of the CMB starting from a theoretical power spectrum.
In this module you learn to simulate maps of point sources and SZ clusters starting from statistical distributions and a cluster profile.
In this module you learn to estimate the power spectrum and its error bars starting from a map and knowledge about the instrument.
In this module you learn to find cluster and point source candidates using the matched filter technique.
In this module you simulate maps of the CMB's polarization including TE correlation, and work with B-mode estimators that minimize E-B leakage.