DEM Inversion Methods

The table below is a (probably not comprehensive) list of the different methods for computing the differential emission measure.

Name	Reference	Notes	Source code
MCMC	Vinay & Kashyap (1998)	Easily leverage many Python MCMC implementations	PINTofALE
demreg	Hannah & Kontar (2012)		https://github.com/ianan/demreg
sparse AIA	Cheung et al. (2015)		http://www.lmsal.com/~cheung/AIA/tutorial_dem/
sparse Bayesian	Warren et al. (2017)
xrt_dem_iterative2.pro		XRT DEM model. Does not seem to have a reference in literature?	SSW
Fast DEM Inversion	Plowman et al. (2012)		http://solar.physics.montana.edu/plowman/firdems.tgz
Pottasch method	Pottasch (1963)
EM loci method	see Veck et al. (1984)	Find loci of curves defined by ratio of intensity to contribution function; these are upper limits for DEM
A. Leonard Python method	Leonard and Morgan (2014)	In Python	https://github.com/SolarDrew/CoronaTemps
DeepEM	Wright et al. (2019)	NN trained on sparse basis pursuit with PyTorch	https://github.com/PaulJWright/DeepEM

Also see Aschwanden et al. (2015) for a comparison of many of these methods as well as section 7 of Del Zanna and Mason (2018) for a brief overview of some methods.