The raw data from Bolocam contains noise components from the atmosphere and instrument in addition to the astrophysical signal. To remove the atmospheric noise, an iterative approach was required.

1. The median across all bolometers is subtracted
2. A set number of principle components are subtracted. The principle components are the most correlated components between bolometers. In this process both the atmosphere above the telescope - which is assumed to be constant across the field of view - and any large-scale astrophysical structure are removed.
3. The timestream data is mapped into the plane of the sky. Data points are mapped to the nearest pixel. 7.2" pixels are used so that sampling is better than Nyquist.
4. The map is deconvolved using a maximum entropy deconvolution algorithm ( Based on paper by Hollis, Dorband, Yusef-Zadeh, Ap.J. Feb.1992, written by Frank Varosi at NASA/GSFC 1992)
5. The deconvolved map is returned to a timestream and subtracted from the original to yield a noise-only timestream.
6. Power spectral densities are calculated for each scan in the noise timestream, and weights are calculated from these. [At the moment, the weights are actually inverse-variance]
7. The deconvolved map timestream is subtracted from the raw timestream, and then steps 1-6 are repeated on that timestream to recover flux that was oversubtracted in the first iteration.

Convergence takes ???? iterations.... ??? PCA components are subtracted [default 13]...