IBEXMagnetospheric ENA Foreground:

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IBEX--Magnetospheric ENA Foreground Lessons
Learned from IMAGE/HENA Edmond C. Roelof Johns
Hopkins University/Applied Physics
Laboratory Laurel, MD 20723-6099 IBEX Science
Team Meeting 8 November 2006, Oxnard CA Finding
ENA from the Heliosphere, R. DeMajistre, E.
Roelof, P. Brandt, and D. Mitchell,
IMAGE/HENA,September, 2002.
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Basic Task

• Search for a heliospheric signal in the HENA data
  that is not due to
• Magnetospheric ENA
• Ion contamination
• Sun/Background UV contamination
• This will be our cleanest estimate of an upper
  bound on heliospheric ENA
• VERY low count rate (a few/hour)

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Approach
Select sky pixels for averaging
Select data at apogee
Preliminary geometric restrictions
Estimate and subtract accidentals
Solar particle/ Geomagnetic activity restrictions
Bin filtered data in sky pixels
Final geometric restrictions
Final spectrum/images
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Initial data selection

• All low energy MCP data extracted from UDF where
  IMAGE position gt 97 of apoapsis (3 hour
  segments).
• Save all pixels looking gt 90 degrees from the
  sun, gt 90 degrees from earth and with a minimum L
  along the LOS gt 20

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Data selection

• Restrict data to
• AP lt 10
• ACE/EPAM P2 channel reading lt 8x104
• Number of valid points in orbit gt 1000
• Accidental estimation lt actual count rate

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Proton activity selection
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Final geometric restrictions

• Pixels additionally restricted
• Sun angle gt 120 deg
• Earth angle gt 120 deg
• Minimum L gt 40
• These restrictions were based on viewing data
  binned in GSE and ECI coordinates with the
  preliminary restrictions

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Sky binning

• Regular grid on sky set out 10 degree bins
• Count rate shared with nearest 4 points
• Both exposure and count grids accumulated

X
X
X
X
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Accidental rate estimation

• Accidentals estimated from start and stop
  accumulator data
• Accounts for dead time, sequential windows and
  software selection
• Estimated rate exceeds actual rate only in the
  lowest energy bin (longest TOF)

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Binning in GSE
Raw Data Relative scale
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Binning in GSE
Accidental Estimation Relative scale
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Binning in GSE
Accidental subtracted Relative scale
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Binning in GECI
Accidental subtracted Relative scale
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Binning in Apex Coordinates
Accidental subtracted Relative scale
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• Summary
• Lessons to be learned from IMAGE/HENA search for
• Heliospheric ENAs
• Quantify instrumental backgrounds, e.g.,
  accidentals
• 2. Excise data contaminated by SEPs, large ap
  storms
• 3. Exclude regions of magnetospheric ENA
  emission
• ring current, plasma sheet, cusp, etc.
• 4. Bin data (and quantified backgrounds)
  properly in sky
• nearest-point accumulations of counts
• nearest-point accumulation occupation time
• corrections for scanning duty cycle
• Bin data in multiple coordinate systems in order
  to
• identify possible contamination sources
• e.g., GSE,GECI,Upwind