TES deconvolution cookbook

Description

<<<<UNDER CONSTRUCTION>>>>

This procedure illustrates the method to deconvolve TES spectra.

Procedure

(1) Find TES Spectra in JMARS

• Open TES layer, select Add, Spectra: Warm Surface, High Quality, Clear Atmosphere

• Replace Atmosphere Adjusted Emissivity with Emissivity. In Fields, select "atm_adj_emissivity", select Delete. Next to Fields, select Add, Emissivity.

A note on JMARS atmospheric-adjusted emissivity spectra: These spectra are derived 
by deconvolving the spectra using a standard set of surface and atmosphere endmembers.
This works well for a first pass, but may remove surface features since many mineral
endmembers are not in this standard library. So, while you could use this data set for
more detailed work, it is highly recommend to redo the atmosphere removal with your
full mineral library.

• Limit spacecraft high-gain antenna (hga) and solar panel (pnl) motion. Under Selects, select Add, then:

hga_motion = 1 (min) to 1 (max).
pnl_motion = 1 (min) to 2 (max).

• Limit spacecraft ocks

ock (min) = 1583. 

This is the start of the science phase, same as orbit 0.

ock (max) = 7000.

For ocks above 7000, the TES detectors sometimes exhibit an instrumental error (the "glitch") that results in a reversal of the dust absorption near 1100 wavenumbers, creating a broad peak with random direction (peak or trough) and amplitude in the spectra centered around 1000 wn, and extending between 900-1100 wn. This is most likely caused by internal motion within the spacecraft affecting the interferometer. The glitch can be somewhat compensated for by averaging many icks from the same ock, but this isn't recommended for most applications. Bolometer/albedo data is not affected by the glitch.

• Change target_temp (min) = 260 (can be lowered for greater coverage)

• Delete best fit opacities, replace with tot_ice and tot_dust. Recommended limits (can be adjusted to higher values for more coverage):

tot_ice = (min) 0.00 (max) 0.04

tot_dust = (min) 0.00 (max) 0.15

• Submit (and save as template if you don't want to redo this in the future!)

(2) Download emissivity spectra

• Select spectra in map, highlight in spectra dialog. Save as text file.

(3) Load spectra and spectral library into Davinci

• Use split_ock to load spectra

dv> tes = split_ock("file.txt")

• View using pplot

dv> pplot(tes.ock6002avgcat,xaxis = lib.xaxis,x1 = 1300,x2 = 200)

• Load spectral library

dv> lib = load("speclib.hdf")

• Load atmospheric library

dv> atm = load("atm.hdf")

(4) Remove atmospheric component

dv> unmix1 = sma(tes.ock6002avgcat,lib,atm,wave1 = 232,wave2 = 1302,nn = 1,surface = 1,exclude = 43)

dv> endmember 43 is surface dust, remove for atm correction

dv> pplot((unmix1.rematm,unmix1.modsur),xaxis = lib.xaxis,x1 = 1300,x = 200

(5) Deconvolve surface spectrum

dv> unmix2 = sma(unmix1.rematm,lib,wave1 = 232,wave2 = 1302,nn = 1,exclude = 43)

dv> summary_sma(unmix2,1,1,group = 1)