eis/hinode spectroscopic data analyses · eis/hinode spectroscopic data analyses a.k. srivastava...

EIS/Hinode Spectroscopic Data Analyses

A.K. Srivastava & Pradeep Kayshap

[A] Analyses of RASTER SCANS : Raster is generated when a slit is placedat Sun and scan the area with certain spatial step and definie exposure timeon each step.

[1] The EUV Imaging Spectrometer (EIS)/ Hinode spectral data products areobserved by 1” and 2” slits. The raw data file is the 'lo' data file, e.g.,“eis_l0_20090422_032457.fits”. This is a “Raster-Scan” observations.

[2] Initial Calibration and Cleaning of the Raw Data :

idl> file = find_file('*l0*.fits')

idl> help, file & print, file

idl> eis_prep,file,/def,/save

This routine performs the calibration and cleaning of raw zeroth level data,and corrects dark current, flat-field, as well as remove warm & dusty pixels.The cleaned data is saved in “l1' file.

[3] Reading the level-1 Data :

idl> file=find_file('*l1*.fits')

idl> print, file

eis_l1_20090422_032457.fits

idl> data=eis_getwindata(file)

idl> data=eis_getwindata(file)

% Compiled module: EIS_GETWINDATA.

% Compiled module: EIS_GETFILENAME.

% EIS_GETWINDATA: no window number input, select one . . .

% Compiled module: EIS_GET_WININFO.

% Compiled module: FXMOVE.

% Compiled module: MRD_SKIP.

% Compiled module: EIS_PIXEL_TO_WAVELENGTH.

iwin line_id wvl_min wvl_max

0 FE X 184.540 184.18 184.87

1 FE XI 188.230 187.88 188.57

2 O V 192.900 192.54 193.23

3 FE XII 195.120 194.77 195.46

4 FE XIII 202.040 201.68 202.37

5 HE II 256.320 255.97 256.66

6 SI VII 275.350 275.00 275.68

7 FE XV 284.160 283.80 284.49

Select a window to read [0...7]> 3

{Enter after choosing line ID}We have selected for example the data structure of Fe XII 195.120 A line.

[4] Structure of the Data :

idl> help, data

DATA STRUCT = -> <Anonymous> Array[1]

idl> help, data,/str

** Structure <2a4e9e8>, 26 tags, length=12684968, data length=12684911,refs=2:

FILENAME STRING 'eis_l1_20090422_032457.fits'

LINE_ID STRING 'FE XII 195.120'

INT FLOAT Array[32, 120, 400]

ERR FLOAT Array[32, 120, 400]

WVL DOUBLE Array[32]

TIME FLOAT Array[120]

TIME_CCSDS STRING Array[120]

DATA_QUALITY BYTE Array[120]

EXPOSURE_TIME FLOAT Array[120]

SOLAR_X FLOAT Array[120]

SOLAR_Y DOUBLE Array[400]

XCEN FLOAT 29.5938

YCEN DOUBLE 939.34481

NL LONG 32

NX LONG 120

NY LONG 400

SCALE DOUBLE Array[2]

UNITS STRING 'erg/cm!e2!N/s/sr/ '�

MISSING INT -100

IWIN INT 3

HDR STRUCT -> <Anonymous> Array[1]

TIME_STAMP STRING 'Sat Apr 16 16:58:41 2016'

WAVE_CORR_SET BYTE 1

WAVE_CORR DOUBLE Array[120, 400]

WAVE_CORR_TILT DOUBLE Array[400]

WAVE_CORR_T DOUBLE Array[120]

[5] Visualize the Spectra :

idl> help, data.wvl

<Expression> DOUBLE = Array[32]

idl> print, data.wvl

194.76988 194.79216 194.81445 194.83673 194.85902 194.88130 194.90359 194.92587 194.94816

194.97044 194.99272 195.01501 195.03729 195.05958195.08186 195.10415 195.12643 195.14871

195.17100 195.19328 195.21557 195.23785 195.26013195.28242 195.30470 195.32699 195.34927

195.37155 195.39384 195.41612 195.43841 195.46069

idl> Int=data.int[0:31,100,100] ; Flux at (X,Y)=(100 px,100 px)

idl> help, int

INT FLOAT = Array[32]

idl> plot, data.wvl, Int

A typical observed line profile at X=100 pixel, Y=100 pixel. Each (X,Y)pixel will have the corresponding line-profile.

One must notice the blending of weak line (s) to the primary line. See thekey references :

EUV Emission Lines and Diagnostics Observed with Hinode/EIS, P.Young et al., 2007, PASJ, 59, 857.

Fe XII 195.120 Å has blending of Fe XII 195.180 Å

[6] Fitting of the Line-profile :

(a) Before the fitting, we need to fix the “Orbital Variation” and “Slit Tilt”.

idl> file = findfile('eis_l1**.fits')

idl>wd = eis_getwindata(file, 195.120, /refill)idl> help, wd, /str

** Structure <1a0ebf8>, 26 tags, length=12684968, data length=12684911,refs=2:












XCEN FLOAT 29.5938


NL LONG 32

NX LONG 120

NY LONG 400



MISSING INT -100

IWIN INT 3


TIME_STAMP STRING 'Sun Apr 17 08:20:37 2016'




WAVE_CORR_T DOUBLE Array[120] idl> data = eis_bin_windata(wd, xbin=2,ybin=6) ; Binning of the Data(Optional)

idl> help, data, /str

** Structure <1a34b28>, 27 tags, length=1034664, data length=1034603,refs=1:




XCEN FLOAT 29.5938


NL LONG 32

NX LONG 60

NY LONG 66



MISSING INT -100

IWIN INT 3


TIME_STAMP STRING 'Sun Apr 17 08:20:37 2016'




TIME DOUBLE Array[60]




SOLAR_Y FLOAT Array[66]

DATA_QUALITY FLOAT Array[60]

WAVE_CORR FLOAT Array[60, 66]

WAVE_CORR_TILT FLOAT Array[66]

WAVE_CORR_T FLOAT Array[60]

START_PIX INT Array[2]

The centroids of emission lines on the EIS detectors move during the satelliteorbit of 100 mins by about 2 pixels. In addition, the tilts of the EIS slits meanthat the centroid of a given line can vary by up to 2.5 pixels along the slit.This causes the offset in the line centroid.

Slit-Tilt : The EIS 1” nd 2” slits are both tilted relative to the axes of theEIS CCDs, resulting in measured line centroids varying systematically withY-position. The tilts of both slits are in the same direction, shifting linecentroids to higher pixel numbers for increasing Y-position, i.e., lines becomeincreasingly blue-shifted towards the top of the CCDs. The tilt of the 2′′ slit islarger than for the 1′′ slit.

Orbital Variation : The Hinode spacecraft is oriented such that it always

points at the Sun, and it does not rotate relative to the Sun. This means thateach side of the spacecraft receives a variable illumination from the Earth asthe spacecraft orbits the Earth. For EIS this means that in some parts of theorbit the instrument is directly illuminated by the Earth, a nd in other parts itis shadow behind SOT.

[Reference : EIS Software Notes]

==================== Visualize Some Effects==================The windata structure has an additional tag called wave corr that combinesthe spectrum drift with the EIS slit tilt (see EIS Software Note #4) to give a2D array. The wave corr array stored in the windata structure is used by theGaussian fitting routine eis auto fit.pro to perform the spectrum drift and slittilt corrections, so that the velocity map that results from the fit is free fromthese instrumental effects. This is automated computation of Kamio et al.(2010).

idl> wave=data.wave_corridl> x=data.solar_xidl>y=data.solar_yidl>plot,x, wave[0:59, 40] ; Shift at any Y-pixelidl>plot,y, wave[30, 0:65]

=======================================================

(b) MANUAL ESTIMATION :

idl>.r aks_pk_orbital_tilt.proidl> restore, 'tilt_orbit.sav', /V

(c ) Fitting of the Spectral Line Profile at Each Pixel

idl> .r aks_pk_fit_dgf.pro

Note : Switch off the second component of fitting structure if you need toperform the single Gaussian fitting. See the “EUV Emission Lines and

Diagnostics Observed with Hinode/EIS, P. Young et al., 2007, PASJ, 59,857”, and EIS Software Note 17 for blending and required number of fitcomponents.

Idl> restore, 'fit195.sav', /V

% RESTORE: Portable (XDR) SAVE/RESTORE file.

% RESTORE: Save file written by [email protected], Sun Apr 1710:01:32

2016.

% RESTORE: IDL version 7.0 (linux, x86_64).

% RESTORE: Restored variable: FIT.

idl> help, fit, /str

** Structure <1baa308>, 33 tags, length=1651968, data length=1651950,refs=1:

EXP_START_TIMES DOUBLE Array[60]

MISSING INT -100

XRANGE LONG Array[2]

YRANGE LONG Array[2]

NGAUSS INT 2

REFWVL DOUBLE Array[2]

NX LONG 60

NY LONG 66

INT_ARR FLOAT Array[32, 60, 66]

ERR_ARR FLOAT Array[32, 60, 66]

OFFSET_ARR FLOAT Array[60, 66]

AA FLOAT Array[8, 60, 66]

SIGMAA FLOAT Array[8, 60, 66]

YFIT_ARR FLOAT Array[16, 60, 66]


INTERR FLOAT Array[2, 60, 66]

CHI2 FLOAT Array[60, 66]

X_BG1 FLOAT Array[60, 66]

X_BG2 FLOAT Array[60, 66]

SLIT_IND LONG 2

YBIN DOUBLE 6.0000000

WD_NX LONG 120

WD_NY LONG 400

RASTER INT 1

START_PIX INT Array[2]

YIP LONG 362

BAD_PIX BYTE Array[60, 66]

DATE_OBS STRING '2009-04-22T03:24:57.000'

XCEN FLOAT 29.5938



TIME_STAMP STRING ''

INSTRUME STRING 'EIS'

View the Fitted Profiles :

idl> .r fit_profiles_view ; You can Make Your Own Program. This is just a ;demo !!

Black : Fe XII 195.12 line profile; Blue : Fitted Profile

[7] Plot Intensity, Velocity, and FWHM Maps

idl> .r int_map.proidl> .r vel_map.proidl> .r wid_map.pro

Note : You can Make Your Own Program. This is just ademo !!

These maps will look like as follows :

Intensity (left), Doppler Velocity (middle), and FWHM (right) maps[binned].

[8] Estimation of Reference Wavelength for Doppler Velocity :

The data which has “solar limb” included in the FOV, can provide a veryspecific opportunity to derive reference wavelength of the particular EIS line.It should be noted that EIS has no specific wavelength calibration. Forexample, in the considered data set, we have norh-polar limb. We select a boxat the very quiet part of the limb. It is assumed that upward and downwardflow at the limb cancel each other, so the plasma is approximately at the“rest”. We derive spectra from the chosen “box”, integrate them, and fitappropriately. The fitted profile results into the line centroid, and its valuegive us the reference wavelength.

Idl>.r aks_pk_ref_wvl.pro

It prints 195.128 Å.

It should be noted that if the limb isnot present in the FOV, then we needto use the average value of thecentroid while selecting the mostquiet-Sun region on-disk, derivingand fitting its spectra. However, thiswill not give very reliable restwavelength.

[9] Density Diagnostics :

We use the following data set to demo such measurement :

eis_l1_20070207_165100; eis_er_20070207_165100

We need to fit the density sensitive lines separately likewisepreviously we have performed. We choose Fe XII 195.120 and Fe XII186.88 A lines.

Idl> .r aks_pk_orbital_tilt.pro

Idl> .r aks_pk_fit_dgf_195.12.pro

Idl> .r aks_pk_fit_dgf_186.88.pro

Idl> .r aks_pk_dens_cal.pro

Density Map (based on line ratio; left); Some density variations alongvarious paths chosen off the limb (right)

The two narrow spaced lines : If one is allowed and other forbidden, or bothare forbidden (but with different transition rates), then the line intensity ratiodepends upon some power of the density, and it shows density dependence.

[B] Analyses of Sit-n-Stae : This is generated when a slit is placed at Sun andtrack the same location in time.

[1] Data set : We take the following data set for the demo analyses.

eis_l1_20070208_071610.fits eis_er_20070208_071610.fits

[2] Reading the Data and Its Structure :

idl>IDL> file = findfile('eis_l1**.fits') idl> data = eis_getwindata(file)

% EIS_GETWINDATA: no window number input, select one . . .

iwin line_id wvl_min wvl_max

0 O VI 184.020 183.74 184.26

1 FE X 184.540 184.28 184.79

2 FE XII 186.880 186.62 187.13

3 FE XXI 187.700 187.42 187.94

4 FE XI 188.230 187.96 188.47

5 CA XVII 192.820 192.55 193.06

6 FE XII 195.120 194.84 195.36

7 FE VIII 195.970 195.69 196.20

8 FE XIII 202.040 201.77 202.29

9 FE XIII 203.830 203.56 204.07

10 HE II 256.320 256.04 256.55

11 SI IX 257.930 257.67 258.18

12 SI X 258.460 258.20 258.71

13 SI X 261.040 260.78 261.30

14 FE XVI 262.980 262.72 263.23

15 FE XIV 264.780 264.52 265.04

16 MG VI 269.000 268.73 269.24

17 FE XIV 270.510 270.24 270.75

18 FE XIV 274.200 273.93 274.45

19 SI VII 275.350 275.09 275.60

20 MG VII 276.150 275.89 276.40

21 MG VII 276.990 276.71 277.23

22 O IV 280.050 279.78 280.30

23 FE XV 284.160 283.90 284.41

Select a window to read [0...23]> 6

% EIS_GETWINDATA: RETURNING BUFFERED DATA

idl> help, data,/str

** Structure <255e468>, 26 tags, length=6156456, data length=6156401,refs=2:












XCEN FLOAT 962.623

YCEN DOUBLE -90.346964

NL LONG 24

NX LONG 60

NY LONG 512



MISSING INT -100

IWIN INT 6


TIME_STAMP STRING 'Mon Apr 18 13:40:32 2016'




WAVE_CORR_T DOUBLE Array[60]

idl> print, data.wvl

194.84478 194.86706 194.88934 194.91163 194.93391

194.95620 194.97848 195.00076 195.02305 195.04533

195.06762 195.08990 195.11218 195.13447 195.15675

195.17903 195.20132 195.22360 195.24589 195.26817

195.29045 195.31274 195.33502 195.35730

idl> print, data.time

0.00000 61.8301 123.701 185.533 247.592 309.430

371.277 433.107 494.953 556.818 618.939 680.797

742.645 804.557 866.646 928.494 990.338 1052.19

1114.07 1175.91 1237.93 1299.80 1361.64 1423.48

1485.34 1547.40 1609.28 1671.11 1732.96 1794.85

1856.97 1918.89 1980.87 2042.74 2104.64 2166.52

2228.38 2290.37 2352.21 2414.10 2475.98 2537.86

2599.70 2661.54 2723.40 2785.27 2847.37 2909.20

2971.06 3032.89 3094.83 3156.83 3218.66 3280.56

3342.38 3404.28 3466.14 3528.29 3590.15 3651.98

idl> print, data.solar_x

963.123 963.200 963.162 963.200 963.162 963.200

963.239 963.200 963.200 963.123 963.123 963.162

963.123 963.200 963.123 963.200 963.123 963.200

963.123 963.200 963.162 963.239 963.200 963.239

963.200 963.200 963.162 963.162 963.162 963.123

963.200 963.162 963.200 963.200 963.123 963.277

963.046 963.200 963.200 963.123 963.200 963.123

963.123 963.200 963.162 963.162 963.200 963.200

963.200 963.162 963.162 963.200 963.200 963.200

963.123 963.200 963.123 963.200 963.123 963.200

idl> plot, data.time, data.solar_x, yrange=[963,963.5]

idl> print, data.solar_x[30]-data.data.solar_x[29]

0.0772705 (Subarcsec Jitter; It can be ignored ! Examine every data set.)

idl>.r aks_pk_ss_offset.pro ; Generate the Orbital Variation and Tilt Array

idl> file='eis_l1_20070208_071610.fits'

idl> aks_pk_ss_dgf, file, bin=[2,2] ; Fit the spectra with bin=[2,2]

Example fit at t=1897 ss

Summary :

[1] Spectroscopy is a very rich tool to constrain the physical properties of the emitting region.

[2] Spectroscopic data must be dealt by caution both on technical and basic atomic physics point of views.

[3] Line formation, blending, asymmetry must be taken into account.

[4] Fitting must be done accurately to derive correct information.

[5] Each spectroscopic data set is a unique dataset. Therefore, one should examine it thoroughly instead analyzing using general/automated routines.

[6] Better to check the details of (on display and print both) each spectral profile in the data set, and examine them very carefully.

Note : The users may utilize these routines on their own responsibility based on thescientific problems and chosen EIS/Hinode slit observations. The use of the routines canbe acknowledged appropriately.

eis/hinode spectroscopic data analyses · eis/hinode spectroscopic data analyses a.k. srivastava...

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