1. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory What does eis_prep do? Dr Peter Young Dr Peter Young Rutherford Appleton Laboratory, UK

2. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory eis_prep eis_prep takes a level-0 EIS FITS file and calibrates iteis_prep takes a level-0 EIS FITS file and calibrates it The output is a level-1 EIS FITS fileThe output is a level-1 EIS FITS file Pixel intensities are stored in data number (DN) units in the level-0 filePixel intensities are stored in data number (DN) units in the level-0 file In the level-1 FITS file they are stored as erg cm -2 s -1 sr -1 Å -1In the level-1 FITS file they are stored as erg cm -2 s -1 sr -1 Å -1 In addition to the level-1 file, an additional error file is createdIn addition to the level-1 file, an additional error file is created The error file contains 1σ errors on the intensitiesThe error file contains 1σ errors on the intensities

3. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory ‘Missing’ data Some pixels in the data should not be used for analysis, e.g.,Some pixels in the data should not be used for analysis, e.g., –saturated pixels –defective pixels –cosmic rays These pixels are flagged by eis_prep by giving them the value -100 in the error FITS file (not the level-1 file)These pixels are flagged by eis_prep by giving them the value -100 in the error FITS file (not the level-1 file)

4. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory eis_prep: Step 1 The first thing eis_prep does is flag any saturated pixels as missing dataThe first thing eis_prep does is flag any saturated pixels as missing data Saturated pixels have a value of 16,383 DN (2 14 -1)Saturated pixels have a value of 16,383 DN (2 14 -1)

5. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory eis_prep: Step 2 The CCD pedestal and dark current are removedThe CCD pedestal and dark current are removed For most data-sets the method is as follows:For most data-sets the method is as follows: –take specified 3D window array –find 2 % of pixels with the lowest DN values –find the median value of these 2 % pixels –subtract this value from every pixel Around 1 % of pixels will end up with a negative DN value after this processAround 1 % of pixels will end up with a negative DN value after this process –these pixels will be flagged as missing

6. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory Warm and hot pixels The EIS detectors exhibit a number of pixels that yield anomalously high DN valuesThe EIS detectors exhibit a number of pixels that yield anomalously high DN values The brightest of such pixels are termed “hot pixels”The brightest of such pixels are termed “hot pixels” All others are referred to as “warm pixels”All others are referred to as “warm pixels” These pixels can have different characteristics:These pixels can have different characteristics: –some are permanent –some last for several weeks and then disappear –some flicker

7. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory Warm and hot pixels, and cosmic rays The EIS cosmic ray removal routine (eis_despike) flags most of the warm and hot pixelsThe EIS cosmic ray removal routine (eis_despike) flags most of the warm and hot pixels Cosmic ray Hot pixel Warm pixels Image cleaned with eis_despike Raw data

8. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory Warm and hot pixels, and cosmic rays Warm and hot pixels lying within a line profile are often not flagged by eis_despikeWarm and hot pixels lying within a line profile are often not flagged by eis_despike For these, it is necessary to flag them by using warm and hot pixel mapsFor these, it is necessary to flag them by using warm and hot pixel maps The maps are created using engineering studies and stored in SolarsoftThe maps are created using engineering studies and stored in Solarsoft Hot pixel maps:Hot pixel maps: –$SSW/hinode/eis/data/cal/hp Warm pixel maps:Warm pixel maps: –not implemented yet

9. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory Step 3: HPs, WPs and CRs Step 3a:Step 3a: –use hot pixel map to flag hot pixels Step 3b (not implemented yet):Step 3b (not implemented yet): –use warm pixel map to flag warm pixels Step 3c:Step 3c: –flag cosmic rays using eis_despike –(note: eis_despike calls the CDS routine new_spike) All flagged pixels are marked as missingAll flagged pixels are marked as missing

10. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory Warm pixels and hot pixels The numbers of WPs and HPs on the CCDs are increasing with timeThe numbers of WPs and HPs on the CCDs are increasing with time There are many more WPs then HPsThere are many more WPs then HPs Currently (Oct 2007) around 4 % of the CCD pixels are WPsCurrently (Oct 2007) around 4 % of the CCD pixels are WPs In two years time predicted to be 12-15 %In two years time predicted to be 12-15 % Louise Bradley, MSSL

11. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory Step 4: calibrated intensities DN values are converted first to photonsDN values are converted first to photons Photons converted to erg cm -2 s -1 sr -1 Å -1 using EIS effective area curvesPhotons converted to erg cm -2 s -1 sr -1 Å -1 using EIS effective area curves Curves derived before launch in lab. calibrationCurves derived before launch in lab. calibration Curves available in:Curves available in: –$SSW/hinode/eis/response

12. Hinode / EIS Hinode Data Analysis Workshop, Paris, Nov 2007 Dr Peter Young, Rutherford Appleton Laboratory Step 5: errors on intensity Fractional errors given by:Fractional errors given by: 2.5 is an estimate of the CCD read noise2.5 is an estimate of the CCD read noise [ (Photons) + (2.5) 2 ] 1/2 / Photons