This package fits CCD images of atoms trapped in a magneto-optical trap (MOT) to a model based on a 2D Gaussian. This is used to evaluate the size of the atomic cloud. We take into account CCD readout noise, scattered light noise, and background nois. We find the best-fit 2D Gaussian from Bayesian estimation, using Markov Chain Monte Carlo to estimate the maximum likelihood values of the right parameters.
A series of images with different time of flights may be inputed to evalute the temperature of the trapped atoms. If different values of laser power are used, can also automatically get the temeprature of the MOT as a function of laser power.
(Repository for the Spring 2017 Harvard University Physics 201 Final Project on MOT parameters estimation)