UVIS calibration update
Greg Holsclaw, Bill McClintock
Jan 7, 2008
Outline
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Detection of Spica variability by UVIS
FUV evil pixel response
FUV absolute calibration
Differences between independent
determinations of UVIS sensitivity
UVIS detection of Spica flux
variability
Introduction
• Motivation: Spica is known to be a variable
star, but the quantitative impact of this
characteristic on the systematic variation
observed with UVIS is unknown
• Approach: Search for correlation of UVISFUV photometry with Spica flux variation
models
Background on Alpha Vir (Spica)
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Spica is a non-eclipsing double-lined spectroscopic binary system
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Though not spatially resolvable, each component is detectable through
measurements of out-of-phase Doppler shifts in the constituent spectral lines
Non-eclipsing due to large apparent orbital inclination of ~70 degrees
Both stars are of a similar spectral class:
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Spica is the brightest rotating ellipsoidal variable star
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Primary: B1V
Secondary: B4V
The stars have a distorted ellipsoidal shape due to mutual gravitation effects
As the components revolve, the visible area (and thus the observed flux)
changes with orbital phase
Since this is a geometric effect, it should be roughly wavelength-independent
Orbital period is 4.01454 days
Amplitude of flux variation in V-filter ~3%
http://observatory.sfasu.edu
The primary of Spica is a Cepheid variable
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Periodic variation in the pulsating primary star is much shorter than the system’s
orbital period and about a factor of 2 less in magnitude
Period is 4.17 hours
Amplitude of flux variation in V-filter ~1.5%
This short-term variation, identified in 1968, became undetectable in the early
1970’s (but may return again due to precession of the primary’s rotation axis
relative to the orbital plane, which has a period of 200 years [Balona, 1986])
Ellipsoidal variation model
Variation in flux is given by [Shobbrook, 1969; Sterken et al, 1986]:
dE = A M2/M1 (R/D)3 (1+e cos(TA+Φ))3 (1-3cos2(TA+TA0+Φ) sin2i )
Where:
A=0.822 (wavelength dependent “photometric distortion”)
M2/M1 = 1/1.59 (ratio of masses)
R = 7.6 Rsun = 5.2858e6 km (polar radius of primary)
D = 1.92916e7 km (mean separation between stars)
e = 0.14 (orbital eccentricity)
TA = time/T0·2π (true anomaly, approx as mean)
T0 = 4.01454 days (orbital period)
TA0 = 242 degrees (apparent angle to line of apsides in
year 2005, has precession period of 133 years)
i = 65.9 degrees (orbital inclination)
Φ = empirical phase shift, a free parameter to match with data
One period of the expected variation in
flux from Spica for the year 2005
UVIS measurements
Spatial profile of a single scan
• We now have several drift observations of Spica
• This is where the spacecraft is slewed slowly, such that the star
moves along the entrance slit while many scans are acquired
UVIS measurements
Spatial profile of a single scan
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Spatial profiles of all scans in
one observation
We now have several drift scans of Spica
This is where the spacecraft is slewed slowly, such that the star moves along the
entrance slit while many scans are acquired
These plots show a spectral summation across the array, yielding a spatial profile
UVIS measurements
Total FUV signal vs. star location
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Spica is the bright UV calibration star of choice for UVIS
Many observations span over the years since launch, but there are only nine easily comparable
along-slit slew scans
There is modest variation in absolute sensitivity along the slit, so the instrument response is
averaged over the region where the star is located between rows 10 and 20
UVIS measurements
vs. time
Total FUV signal vs. star location
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Total FUV signal vs. time
Spica is the bright UV calibration star of choice for UVIS
Many observations span over the years since launch, but there are only nine easily comparable
along-slit slew scans
There is modest variation in absolute sensitivity along the slit, so the instrument response is
averaged over the region where the star is located between rows 10 and 20
Predicted and UVIS-measured
variation
measured
model
The predicted variation has a
period of only ~4 days, so the eight
UVIS observations sample this
curve sporadically.
The correlation between the
measured values and the sampled
predicted variation is good.
Predicted and UVIS-measured
variation
measured
model
The predicted variation has a
period of only ~4 days, so the eight
UVIS observations sample this
curve sporadically.
The correlation between the
measured values and the sampled
predicted variation is good.
Predicted and UVIS-measured
variation
measured
model
The predicted variation has a
period of only ~4 days, so the nine
UVIS observations sample this
curve sporadically.
The correlation between the
measured values and the sampled
predicted variation is good.
Dividing out the predicted
variation leaves a more
obvious slow decline in
sensitivity with time, which is
not surprising.
Predicted and UVIS-measured
variation
time modulo T0
This view shows how well a single
period of the ellipsoidal variation curve
has been sampled by UVIS so far.
Predicted and UVIS-measured
variation
time modulo T0
This view shows how well a single
period of the ellipsoidal variation curve
has been sampled by UVIS so far.
Predicted vs measured relative values
shows a high correlation.
Dividing out the slow linear decline
improves the r value to 0.86.
Conclusion
• In spite of the challenges of the UVIS-FUV detector, fewpercent photometric variations in the flux from Spica are
detectable
• Removing this systematic trend from the data will enable
more accurate tracking of the relative instrument
sensitivity
• Residual discrepancies from the model could be due to:
– contribution from the high frequency (~4 hr) Cepheid variation
– spectral variability in the magnitude of the ellipsoidal fluctuation
Continued Work
• Future routine calibration observations of Spica will provide better
sampling of the ellipsoidal variation
• A search for the transient Cepheid variation of the Spica primary
could be conducted with the HSP or FUV channel
– For the HSP this would require staring at the star for an entire period of
4 hours, resulting in a well-sampled light curve.
– For the FUV, in order to avoid starburn, we could perform multiple
along-slit slew zigzag scans across half the slit length. The typical
duration of a single along-slit slew scan is ~1 hour. This method would
acquire eight samples across the 4 hour period.
• Validation of these results as well as an independent search for the
Cepheid variation can be gained by analyzing the observations of
Spica by the Cassini Imaging Science Subsystem (ISS)
References
• Balona, On the amplitude decrease of the beta Cephei stars SPICA
and 16 Lacertae, Royal Astronomical Society, Monthly Notices, vol.
217, Nov. 15, 1985, p. 17P-21P
• Shobbrook et al, Light variations in Spica, Monthly Notices of the
Royal Astronomical Society, Vol. 145, p.131 (1969)
• Sterken et al, The variability of Spica, Astronomy and Astrophysics,
vol. 169, no. 1-2, Nov. 1986, p. 166-170
Evil pixel characterization
Evil pixel definition
• Evil pixels are those FUV detector elements which
exhibit an anomalously low response relative to their
immediate neighbors
• Evil pixels have been identified by smoothing an image
where all pixels are illuminated (such as a LISM scan)
and setting a statistical threshold below this mean local
value; pixels below this value are considered ‘evil’
• This threshold is somewhat arbitrary (different UVIS
team members have chosen a variety of defendable
values - 3 sigma, 5 sigma, etc low) and therefore evil
pixel identification is not unique
Example of evil pixels
• This plot shows a
single column
from a aggregate
(summed) image
of Spica as it was
slewed along the
entrance slit
• Evil pixels are
seen to have a
significantly lower
response than
“good” pixels
Distribution of evil pixels
Evil pixels
comprise ~15%
of the detector
Fraction of evil pixels per
column is highly variable
Fraction of evil pixels per row is
fairly constant
FUV evil pixel characterization
• It remains unknown if the low-response ‘evil’ pixels
present any useful information
• One test is to see if they respond linearly to a change in
incident flux
• We have many observations of several UV bright stars
• However, to do this experiment properly, the star should
be slewed along the slit, thereby illuminating each
column uniformly
Comparison of FUV stellar fluxes
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These plots show
the spectra of all
the stars
observed thus far
The comparison
star should fill
most of the
detector, be of a
significantly
different flux level
than Spica, but
not be too dim
Comparison of FUV stellar fluxes
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Plot of the total count
rate from each star,
normalized and sorted
Choose three
candidate stars, ~4x
lower in irradiance
than Spica
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Alp Pav
Del Sco
Eta UMa
Comparison with
absolute irradiance
measurements by
SORCE-SOLSTICE
will provide an
additional path to
validating the
calibration
Selected data for analysis
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Spica:
Eta Uma:
We now have identical
along-slit slews of Alpha Vir
(Spica) and Eta UMa
This plot shows the total
counts acquired from both
stars
Alp Vir spectral class: B1III
Eta Uma spectral class:
B3V
As the stars are not the
same spectral class, we
cannot expect the spectral
ratio to be a flat
multiplicative factor (though
Spica is roughly 4.3x
brighter)
In addition, the stars exist in
different directions in the
sky and are located at
different distances, thus the
scattering and absorption
effects by the interstellar
medium are not shared
FUV2007_140_16_20_53_UVIS_045IC_ALPVIR001_PRIME
FUV2007_192_02_04_18_UVIS_048IC_ETAUMA001_PRIME
Analysis procedure
• Assume the star was slewed in a direction parallel to the entrance
slit
• Sum the images where the star is located comfortably on the
detector
• Ratio the summed image from Eta Uma (Eta Ursae Majoris, Alcaid)
to the summed image from Alp Vir (Alpha Virginis, Spica)
• Assume all pixels in a column should exhibit the same flux ratio (i.e.
the absolute irradiance spectrum from either star need not be
known)
• Normalize each column vector in the ratio image to the mean of the
good pixels in that column
• Overplot every normalized column vector
– We expect good pixels to be distributed about 1, with a spread
determined by the residual flat field and counting statistics
– Are the evil pixels also distributed about 1, or are they consistently
higher or lower?
Image sums and ratio
Eta UMa
Alp Vir
Image sums and ratio
Eta UMa
Alp Vir
Eta UMa divided by
Alp Vir
Relative pixel response
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This plot shows the
ratio of the pixel
values in a single
column to the goodpixel average
Evil pixel values
seem to be
somewhat lower on
the average
In order to bring out a
trend, overplot
columns normalized
in the same way on
one plot
Relative pixel response
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Evil pixel values (blue) have been shifted 0.5 pixels to
the right for clarity
This plot shows the ratio
of each column to the
column good-pixel
average
If both good and evil
pixels respond the same
to a multiplicative
change in flux, both ratio
values should be
centered about 1
Good pixels are seen to
be distributed about 1,
while evil pixels are
distributed about 0.8
To see this a different
way, try computing a
histogram for the good
and evil pixels
separately
Relative pixel response
• Another useful
view of this data is
to calculate a
histogram for the
good and evil pixel
ratio values
• Here the evil pixel
mode (most
frequent value) is
seen to be about
20% lower than
the good-pixel
mode
Relative pixel response
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Normalizing the
histograms to the
peak value shows
that there is a much
wider distribution of
evil pixel values
If Eta Uma is exactly
4x fainter than
Spica, the evil pixels
would show it to be
~4.8x fainter
Relative pixel response across
detector
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Evil pixels
This is a plot of the
average value of
each column (in
the ratio image) for
good and evil
pixels, normalized
to the good pixel
average
Evil pixel averages
are seen to be
consistently lower
Conclusion
• Evil pixels are defined to be anomalously low-response
detector elements
• This investigation has shown that these pixels respond
to a change in incident flux differently than “good” pixels
• If we assume that good pixels are linear, then the evil
pixels can be considered to exhibit a nonlinear response
• This provides additional motivation for the exclusion of
evil pixels in the analysis of UVIS-FUV data
Absolute calibration of the
FUV channel
Introduction
• Given the inherent difficulty in calibrating FUV spectrometers,
previous measurements of stellar sources are of uncertain utility for
use as a reference for UVIS
• SOLSTICE is a UV monochromator onboard the SORCE spacecraft,
and was developed at LASP under the direction of Bill McClintock
• It’s objective is to measure the absolute spectral irradiance of the
Sun in the FUV and MUV, and tracks degradation through the
measurement of stellar irradiance
• SOLSTICE was rigorously calibrated on the ground using a stable
and well-known UV source at a NIST facility (SURF), and may be
the best calibrated spaceborne FUV spectrometer
• Spica is one of the brightest FUV sources in the sky, and has been
observed often by both UVIS and SOLSTICE
• Recent access to the SOLSTICE stellar data allows for a new
validation of the UVIS-FUV absolute sensitivity
Aggregation of various measurements
of the FUV irradiance from Spica
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This plot shows the
calibrated spectral
irradiance of Spica
from several previous
investigations
Most measurements
agree fairly well above
~140nm
The minimum
wavelength for
SOLSTICE stellar
irradiance is
~130nm, due to
contamination by
Lyman-alpha
emission from the
Earth’s geocorona
SOLSTICE, Rocket, and UVIS
comparison
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A rocket measurement by Brune et al (1979) has been previously used as the Spica irradiance
standard
Rocket and SOLSTICE data are 1nm resolution, so UVIS has been smoothed to 1nm
On the average, we find that UVIS-FUV is within ~10% of the SOLSTICE spectrum
SOLSTICE, Rocket, and UVIS
comparison
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A rocket measurement by Brune et al (1979) has been previously used as the Spica irradiance
standard
Rocket and SOLSTICE data are 1nm resolution, so UVIS has been smoothed to 1nm
On the average, we find that UVIS-FUV is within ~10% of the SOLSTICE spectrum
Conclusion
• The current FUV absolute calibration is
consistent to within ~10% of the best
measurement to date of the stellar flux of
Spica
Continued Work
• Compare other UVIS-measured FUV
stellar fluxes with the SOLSTICE
measurements
Comparison of Independently
derived FUV sensitivities
Introduction
• At the June 2007 team meeting in Goslar, it was
noted that inconsistent FUV results were
obtained when combining calibration tools
provided by Don and LASP
• The origin of this problem lies in the details of
how the two independent instrument calibrations
were derived
Objectives
• Quantitatively compare the two independently derived
FUV calibrations
• Understand the differences between the derivation
techniques
• Later:
– Highlight the strengths and weaknesses of the two approaches
– Determine through team discussion if the disagreement can be
resolved through:
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A new perspective
new laboratory results
a re-analysis of the original data
new observations
– Reach a team consensus on the instrument calibration
FUV Calibration comparison
between Don and LASP
Lores,
filled slit
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The 1999 LASP sensitivity is based on the laboratory measurements
Don’s sensitivity corresponds to an independent derivation based on the
laboratory measurements and modified by lunar results
Significant shape differences are present, on the order of 20 – 30%
Largest discrepancies at 115nm, 135nm, 170nm
Adjustment of absolute magnitude
of Don’s calibration
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The LASP 1999 curve
refers to the state of the
on-ground laboratory
calibration
Don’s calibration has
been adjusted for results
from the Moon, and so
involves a red-response
correction (significant
above ~173nm)
Increasing the magnitude
of Don’s calibration curve
by 9% will equate the
areas between the LASP
1999 lab cal and Don’s
curve within the
wavelengths of 114 and
173nm
This will minimize the
relative deviation from the
LASP calibrated results.
Fundamental differences between
the two calibration approaches
• The LASP calibration is based on the measured instrument
sensitivity using standard detectors. These values were validated
through a comparison of the UVIS measurements of H2 and N2
emission with Joe Ajello’s laboratory measurements of H2 and N2
with a known excitation source
• Don’s calibration is based on a comparison of the same UVIS
measurements of H2 with a theoretical model of the H2 emission
• These two different references produce significant differences in the
derived calibration using the same laboratory dataset
Conclusions
• Significant differences between the two
independently derived FUV calibrations have
been known since at least 2000
– Spectral variations of 20 – 30%
• Fundamental differences in interpretation of the
laboratory calibration results have led to the two
disparate calibration vectors
Continued Work
• Produce absolute stellar fluxes using
Don’s calibration, adjusted for time
variations in the sensitivity, and compare
with SOLSTICE