1. UVIS Calibration Update
Greg Holsclaw
July 10, 2006

2. Outline FUV Calibration history
Approach to deriving a time variable sensitivity
Spica variation
Fomalhaut variation
Spica vs. Fomalhaut
Continued work

3. Calibration History 1997 – original ground calibration
1999 – update reflecting improved lab measurements of PMT reference detectors and initial Spica observations
2004 – update of 1999 calibration to match the spectral shape of the lunar albedo from SOLSTICE observations
2005 – (red patch) update of 1999 calibration to match observed change of Spica observations from Jan 1999 to Oct 2005

4. Approach to Deriving a Time Variable Sensitivity
Need to find consistent observations of the same target over a broad time range
Several rows should be illuminated to avoid row-to-row variations
Selected all Spica observations using the occultation slit (Jan – Jan. 2005):
filename Fslit nx ny nz int odcid x1 x2 y1 y2
FUV1999_016_19_47_
FUV1999_016_22_46_
FUV1999_016_23_16_
FUV2001_093_08_35_
FUV2001_093_16_52_
FUV2001_299_19_41_
FUV2002_155_18_10_03_UVIS_C32ST_DECON001_ISS
FUV2005_029_12_55_04_UVIS_00CST_ALPVIR001_PRIME
FUV2005_029_13_16_34_UVIS_00CST_ALPVIR001_PRIME

5. Spica Spectra Average count rate, summed over central 16 rows (24-39)
Each spectrum shifted to match wavelength scales
Increase in response above ~155nm, decrease below

6. Spica Spectral Ratios No offset corrections, which would include:
RTG background
Scattered light

7. Spica Curve Fit
Fit an exponential curve to each pixel of the form:

8. Fomalhaut Spectra
Fomalhaut observations provide an independent dataset in which to validate the sensitivity variation derived from Spica
Different spectral distribution and lower count rate

9. Fomalhaut Spectral Ratios
Fomalhaut spectra show a change in response similar to that from Spica

10. Fomalhaut Curve Fit
Fomalhaut spectra show a change in response similar to that from Spica

11. Spica and Fomalhaut Spectra
Spica is much brighter across the entire FUV wavelength range
Increased Spica signal toward shorter wavelengths contributes scattered light to long wavelengths
Fomalhaut long wavelengths less sensitive to scattered light but more sensitive to Lyman-alpha and RTG background

12. Spica and Fomalhaut Fit
To place both datasets on the same scale, multiply Fomalhaut curves by the Spica fractional change at the initial Fomalhaut observation
Fomalhaut spectra show a faster rate of change than that expected from Spica
Discrepancy thought be due to neglect of offset subtraction

13. Lyman alpha estimation
Lyman alpha can be estimated by scaling an IPH scan
This shows that the contribution is large at shorter wavelengths, but fractionally small at longer wavelengths for Fomalhaut

14. Continued work PSF estimation for scattered light removal
Lyman alpha, RTG background estimation
Backgound and scattered light subtraction will increase the current values of the sensitivity at long wavelengths
Consider datasets without the occultation lens
Goal: Time variation of the 2D calibration