Transcript Hinode XRT Intro to MSU Solar Group

3 high-performance telescopes
Solar Optical Telescope (SOT)
High resolution observations of
magnetic and velocity fields at
the photosphere
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EUV Imaging Spectrometer
(EIS)
 Diagnostics of the coronal
thermal properties and
dynamics
X-Ray Telescope (XRT)
High resolution imaging of
the corona
Coordinated observations among three telescopes
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Hinode Fields of View
800arcsec
360arcsec
320arcsec
512arcsec
160arcsec
SOT
EIS
2000arcsec
Maximum size of FOV is shown here.
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XRT
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Optical Path
X-Ray Mirror
Shutter & filter wheels
Visible Light Optic
Focus Mechanism
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Focal Plane Filter Wheels
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Observational Constraints
Three basic types of XRT observations, which must be optimized
subject to our data rate (~ 0.5 Gbyte/day)
• Thermal structure & energetics
– 3-7 filters used per target region
– May limit cadence or FOV to stay within the data rate.
• Dynamics
– Fast cadence with 1 or 2 filters
– May limit context images or FOV to stay within the data rate
• Morphology / Topology
– Large FOV, combine long and short exposures
– May limit number of filters, cadence or FOV
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What kind of images will you find?
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Full-Sun synoptic images, 2-4 times per day, several filters
Partial-Sun images, throughout the day
• Field of view 384x384, 512x512, and some 1024x384
• Active regions, coronal holes, quiet sun, variety of targets
• Sometimes a single filter at high cadence
• Sometimes many filters for temperatures, DEMs
• And with occasional full-Sun images for context
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What format? What level of preparation?
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FITS format, with time/date/filter/pointing info in the header
Level-0 data have complete header info, but no preparation
• No corrections for dark current, exposure time, jitter: They’re
Raw.
• Preparation software are available in SolarSoft
• Typically available a few days after the image was made.
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Finding the Data: VSO
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VSO
• http://sdac.virtualsolar.org/cgi-bin/search
• Check ‘Instrument/Source/Provider’ and select ‘Generate
VSO Search Form’
• Select date & time interval
• Check ‘SAO’ (for now) and ‘XRT’ and hit ‘Search’
• Use the checkboxes to choose the data you want
• The “All above” or “All below” options may be useful.
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Finding the Data: SOT website
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SOT website at LMSAL
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http://sot.lmsal.com/sot-data
Choose ‘Planned’ for a link to what’s planned in the next day or so.
Descriptive, but the data aren’t there.
Choose ‘Recent’ for a link to recently acquired data.
Select ‘XRT’
Click on an image for a link to more data from that set.
These are automatically generated, so the results of this method are
hard to predict. I haven’t had much luck with them, but I’m
impatient.
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Finding the Data: xrt_cat
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xrt_cat in SolarSoft
Take advantage of MSU’s data archive
On jefferson:
IDL> t0 = '2007-03-26T17:00:00'
IDL> t1 = '2007-03-26T18:10:00'
IDL> xrt_cat, t0, t1, catx, ofiles
IDL> help, catx
CATX
STRUCT = -> <Anonymous> Array[126]
IDL> help, ofiles
OFILES
STRING = Array[126]
IDL> print, ofiles(0:1)
/disk/data/HINODE/xrt/level0/2007/03/26//H1700/XRT20070326_170036.9.fits
/disk/data/HINODE/xrt/level0/2007/03/26//H1700/XRT20070326_170050.1.fits
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Reading the Data on jefferson
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Two choices
IDL> mreadfits, ofiles, index, data
IDL> read_xrt, ofiles, index, data, /force
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Example of selecting only images of a certain size
IDL> ss = where(catx.naxis1 eq 512 and catx.naxis2 eq 512)
IDL> read_xrt, ofiles(ss), index, data
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Prepping the Data on jefferson
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An example
IDL> ss = where(catx.naxis1 eq 512 and catx.naxis2 eq 512)
IDL> read_xrt, ofiles(ss), index, data
IDL> xrt_prep, index, data index_out, data_out, /norm, /float
[or]
IDL> xrt_prep, ofiles, ss, index_out, data_out, /norm, /float
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Advanced Topics
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Removing spacecraft jitter
IDL> xrt_prep, index_in, data_in, index_prep, data_prep, /norm, /float
IDL> ssw_path, '/ssw/hinode/xrt/idl/util/jitter'
IDL> xrt_jitter, index_prep, jitter_offset
IDL> data_out = image_translate(data_prep, jitter_offset, /interp)
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Removing CCD contamination spots
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End Presentation
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