UVIS Calibration Update Greg Holsclaw, Bill McClintock Jan 6, 2009 Outline • • • • • Recent calibration observations FUV degradation and Spica variability Stellar flux comparisons with SOLSTICE The flat field for small / unresolved targets Changes in the sensitivity at Lyman alpha Recent UVIS Calibrations • The last two Spica calibrations suffered data dropouts due to DSN issues: – FUV2008_265_23_40_33_UVIS_086IC_ALPVIR001_PRIME – FUV2008_309_21_10_33_UVIS_091IC_ALPVIR001_PRIME • 2008_265 had enough data to continue the previous analysis of tracking sensitivity degradation and stellar variability Illustration of data dropouts • FUV2008_265_23_40_33_UVIS_086IC_ALPVIR001_PRIME • FUV2008_309_21_10_33_UVIS_091IC_ALPVIR001_PRIME Spica variability Background on Alpha Vir (Spica) • Spica is a non-eclipsing double-lined spectroscopic binary system – – – 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: • • • Spica is the brightest rotating ellipsoidal variable star – – – – – • 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 – – – – 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 (true anomaly) T0 = 4.01454 days (orbital period) TA0 = 150 degrees (apparent angle to line of apsides in year 2005, has precession period of 128 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 Normalized signal vs time • The left plot shows the total FUV signal vs time (normalized to the mean), with a line fit • The right plot shows the same data with this linear trend removed, along with a theoretical model of the Spica ellipsoidal variation that has been fit to the curve (optimizing only the magnitude and phase offset parameters) Stellar flux comparisons Stellar flux comparisons • We can now compare many of the stellar irradiance measurements from UVIS with those made by SOLSTICE • Background on the SOLSTICE instrument: – An FUV/MUV spectrometer onboard the SORCE spacecraft – Built at LASP – Absolutely calibrated at the NIST-SURF facility – Routinely measures stellar fluxes in order to track sensitivity degradation – Irradiance spectra reduced and calibrated by Marty Snow at LASP name canopus type F0 UVIS x SOLSTICE alp cma alp cru sirius A1 B1 x x x x alp gru alp eri alnair achernar B6 B3 x alp leo alp lyr alp pav regulus vega peacock B7 A0 B2 x x x alp peg Markab B9 alp psa alp vir fomalhaut A4 spica B1 alp car bet cen bet cma bet cru bet ori del cen del cyg mimosa rigel del sco x x x x B1 B1 B0 B8 B2 B9 x x B0 x B2 B0 B0 x x x x adara alnilam eta uma alcaid B3 x gam ori kap ori kap vel lam sco pi sco sig sgr tau sco zet cen zet oph zet ori zet pup bellatrix saiph B2 B0 B2 B2 B1 B2 B0 B2 O9 O9 O5 x x Nunki alnitak naos x x x x eps cma eps ori eps per shaula x x x x x x x x x x x x x x x x List of stars observed by UVIS and SOLSTICE • Stars must be very hot in order to produce significant flux in the FUV • Therefore, most stars observed by UVIS are of B and A spectral class • Nine stars were observed by both UVIS and SOLSTICE UVIS spectra • This shows the spectral irradiance curves as measured by UVIS • A variety of shapes (driven by spectral class) and magnitudes are seen Star parameters • We can use a catalog of stellar parameters to estimate the spectral irradiance from any star using the Kurucz model alp alp alp alp alp alp alp del eta zet name vir psa cma cru leo lyr pav sco uma cen Class B1 A3 A0 B0 B7 A0 B2 B0 B3 B2 Vmag 0.98 1.17 -1.44 0.77 1.36 0.03 1.94 NaN 1.85 NaN Temp 22387 8318 9550 24547 10965 9333 12023 NaN 11220 NaN Grav 3.67 4.19 4.27 3.57 3.77 3.98 3.48 NaN 3.78 NaN Radius 7.94 1.86 1.78 10.00 3.89 2.69 6.31 NaN 3.89 NaN Plx 12.44 130.08 379.21 10.17 42.09 128.93 17.80 NaN 32.39 NaN Temp is the effective temperature in Kelvin Radius is in units of solar radius Plx is the parallax in arcseconds as measured by Hipparcos Metallicity assumed to be zero (solar) Stellar data from: Allende Prieto C., Lambert D.L., Astron. Astrophys. 352, 555 (1999), data accessed through VizieR Kurucz Stellar Models • The Kurucz model stellar irradiance at any wavelength is computed in a coarse grid of three variables: temperature, gravity, and metallicity • A convenient routine for accessing these models is available from: – IUEDAC IDL Software Libraries – http://archive.stsci.edu/iue/iuedac.html • The routine KURGET1 allows a user to specify a measured temperature, gravity, metallicity and angular size to arrive at a model spectral irradiance from any star: – – – – – Wavelength range: 9.1 nm to 106 μm Total wavelength steps: 1221 Resolution: ~1nm in the EUV, FUV, MUV Default units: [ergs/cm2/s/Angstrom] Allows linear interpolation between most model grid points UVIS, SOLSTICE, KURUCZ • Three Kurucz models show good consistency, two do not Ratio of UVIS to SOLSTICE • This plot shows the ratio of UVIS spectra (1.1nm bins) to SOLSTICE over 130-180 nm • Here, UVIS spectra were reduced using the flat-field • While the magnitude varies, a consistent shape in the ratio is apparent WITH flat-field Q - Is the discrepancy dependent on spectral type, signal level, or position on the detector? Ratio of UVIS to SOLSTICE • Normalized to a mean value of one Ratio of UVIS to SOLSTICE • This plot shows the average ratio of UVIS to SOLSTICE for all stars observed (except Alp PsA) Average of all stars Ratio of UVIS to SOLSTICE • This plot shows the average ratio of UVIS to SOLSTICE for all stars observed (except Alp PsA) • Expanded vertical scale Wavelength shift • Due to the small uncertainty in spacecraft pointing, a star image could be centered anywhere within six spectral pixels using the low-resolution slit • This is effectively an uncertainty in the wavelength scale of the spectrum • With an FUV dispersion of 0.078 nm per pixel, this translates to a potential variation of ~0.5 nm Star image UVIS detector pixels are 100 x 25 microns (H x W) UVIS-FUV Lowresolution entrance slit Low-res slit is 6 pixels wide Wavelength shift adjustment • The phase shift between the measured UVIS spectrum and SOLSTICE can be estimated by finding the peak of the cross-correlation function • This is done by the following procedure: – Shift the UVIS spectrum in one-pixel increments – Smooth the UVIS spectrum to 1 nm – Interpolate the UVIS spectrum to the SOLSTICE wavelength scale – compute the linear correlation coefficient – Find the shift value where the maximum correlation occurs • This is a small effect for 1 nm resolution spectra Cross-correlation analysis • This shows the correlation coefficient versus UVIS pixel shift • A peak in the correlation coefficient is considered a wavelength match • All matches occur within four pixels Average UVIS/SOLSTICE ratio • No wavelength shift • With individual wavelength shifts Ratio of UVIS to SOLSTICE vs SOLSTICE irradiance • • • UVIS appears to measure fluxes that are higher at lower signal levels This could be the result of a need to remove an offset, which would preferentially affect measurements of lower signal There is currently no attempt to adjust for nonlinearity due to the detector dead-time; an adjustment would have the effect of increasing the UVIS signal of brighter stars Ratio of UVIS to SOLSTICE vs surface temperature • The dimmer stars also happen to be the cooler ones Effective temperatures from: Allende Prieto C., Lambert D.L., Astron. Astrophys. 352, 555 (1999), data accessed through VizieR Stars are imaged in the star-burned rows • Flat-field corrector • Spatial distribution of stars • This plot shows the spatial distribution of light on the detector from each star, along with the inverse of the average row-torow correction from the post-burn flatfield The stars were imaged in the center of the starburned region of the detector It is here that the sensitivity correction is largest, and the spectral shape of the correction the most significant Spatial distribution of stellar flux measurements No Flat-field applied WITH Flat-field applied • These plots show the distribution of light on the FUV detector for each observation of stellar irradiance • The curves are normalized to the total signal • The images are centered at about row 32 Star comparisons – TO DO • Compare spectra from measurements where the star image is located outside of the starburned rows (Alp Vir, Alp Leo, Alp PsA, others?) • Look into getting extended SOLSTICE spectra (>180nm) from Marty • Check other catalogs to see if the effective temperatures are consistent • How are the stellar parameters of temperature, gravity, and metallicity derived? How accurately are they known? • Include flux from secondary companion stars • Compare the flux from UVIS using Don’s FUV sensitivity curve Flat-fielding for small targets Use of the flat-field corrector for small sources • The flat-field is meant to correct the highfrequency pixel-to-pixel sensitivity nonuniformity • It is derived from the along-slit slew scans of Spica, which approximates a uniform extended source • However, it has been noticed that there could be an issue with using the corrector for small (unresolved) targets Effect of the flat-field on an extended source • • This approximates the spatial distribution of a uniform extended source Sum of all scans, sum in the spectral dimension • • • This demonstrates the effect of applying a flat-field to a uniform extended source Sum of all scans, flat field applied, and sum in the spectral dimension Overcorrection in the starburned rows Effect of the flat-field on a point source • • • Total signal vs star position Evil pixels interpolated across No flat-field applied • Total signal vs star position • Flat-field applied to each frame Sensitivity at Lyman-alpha IPH data reduction • Identify all UVIS observations which are: – – – – – FUV Low-resolution Unbinned Unwindowed IPHSURVEY • Average all records in each observation • Mark all evil pixels as NaNs • Average all remaining ‘good’ pixels in each column (row 3 to 60) to form a single spectrum Filtering IPH data • All selected LISM spectra in the DAPS database • All LISM spectra which meet a filtering criteria to exclude contamination by stars and data dropouts Filtering IPH data • Select all observations prior to the year 2000 • Select all observations after the year 2000 with an average (between pixel 300 and 1023) signal in the range 0.0005±0.00001 Normalizing to a fixed LISM signal • All filtered spectra, with the offset subtracted (mean of signal between pixels 990 – 1010) • Need to remove LISM signal variation due to distance from the Sun and pointing. • Normalize each spectrum to the signal between pixel ranges 100-110 and 150-160 Signal normalized spectra • Spectra are normalized to the signal in the shaded regions Ratio to an early spectrum • This shows the ratio of all spectra to an early spectrum • This should show the fractional change in sensitivity Ratio to an early spectrum • Look at the change as a function of time for a few pixels Pixel value vs time • • • • This shows the count rate vs time for three spectral columns Each curve is normalized to the mean of the values before 2000 The variation is much larger than the random uncertainty in the detected counts Ideas: – Colors here denote different pixels – Due to a small mislocation in the position of the slit? This is a known effect. Incomplete removal of stellar spectra? Poor background subtraction? • Raw spectra (counts/second) • Seems unlikely that some pixels decline more than others. More likely that the background subtraction was poor. • After subtraction of an estimate of the background (mean of pixels 990-1010) Summary • There is a small, approximately linear decline in FUV sensitivity • The ellipsoidal variation of Spica continues • Comparisons of UVIS measurements of absolute stellar fluxes with SOLSTICE show that there is a variation in absolute magnitude on the order of 30%, and a systematic shape difference • The flat-field should be used with caution for small targets • There is a measurable decrease in sensitivity at Lyman alpha as a function of time, but the shape is difficult to determine