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Near Infrared Camera and Multi-Object Spectrometer Instrument Handbook for Cycle 17 > Chapter 4: Imaging > 4.2 Photometry

4.2 Photometry
Ground-based near-infrared observations are limited to a set of transparent atmospheric windows, while NICMOS suffers no such restrictions. For this reason, faint flux standards with continuous, empirical spectrophotometry throughout the 0.8 μm < λ < 2.5 μm range were created using the NICMOS grism mode in combination with spectral models. The absolute flux calibration of NICMOS has been calculated using observations of stars for which reliable spectral models, normalized by ground-based photometry in the optical, are available. Two types of flux standards have been observed: pure hydrogen white dwarfs, and solar analog stars. Grism sensitivity is determined directly from flat-field corrected spectra of these stars using their known spectral energy distributions. Filter sensitivities are calculated from imaging measurements according to the synthetic photometry procedure detailed in Koornneef and Coole (1981, ApJ, 247, 860). Since the pipeline calibration cannot utilize color information, the headers of reduced data contain the calibration constant that specifies the equivalent count rate for a spectral energy distribution that is constant with wavelength. For convenience, this calibration constant appears twice, once in Jansky units and once in erg/s/cm2/Angstrom units.
4.2.1
For calibration using solar analogs, a reference spectrum of the Sun is normalized to the flux levels of the NICMOS standards at optical wavelengths. This continuous spectral model is then integrated through the total system throughput function for a given bandpass (including filter, detector, instrument and telescope optics), and the integral flux is compared to the measured count rate from the star in observations through that filter to derive the flux calibration constants. The absolute flux accuracy achieved by this method relies on two assumptions:
1.
that the calibrated reference spectrum of the Sun is known with an uncertainty of a few percent (Colina, Bohlin and Castelli, 1996; Bohlin 2007, ASPC, 364, 315), and
2.
In the past, this method was used to determine the absolute calibration of near-infrared photometry at ground-based observatories. In these cases, the absolute calibration accuracy was estimated to be at least 5%, and for some bands 2% to 3% (Campins, Rieke and Lebofsky, 1985).
Ground-based photometry by Persson et al. (1998, AJ, 116, 2475) of several solar analog stars used in the NICMOS calibration program has shown that the stars P330E and P177D (see Bohlin, Dickinson & Calzetti 2001, AJ, 112, 2118; Colina & Bohlin 1997, AJ, 113, 1138; Colina, Bohlin & Castelli 1996, AJ, 112, 307) are most closely matched to the colors of the Sun, and are thus most suitable for NICMOS photometric calibration. P330E is the primary NICMOS solar analog standard for photometric calibration.
4.2.2
Pure hydrogen white dwarfs are useful calibration standards because their spectral energy distributions can be accurately modeled from the UV through the near-IR (Bohlin, Dickinson & Calzetti 2001, AJ, 112, 2118; Bohlin 1996, AJ, 111, 1743; Bohlin, Colina & Finley 1995, AJ, 110, 1316). The star G191B2B has therefore served as a primary calibration standard for several HST instruments and was selected for NICMOS observation along with another star, GD153. Using the most up-to-date white dwarf atmosphere models, normalized to the most accurate STIS optical/UV spectra of G191B2B, Bohlin, Dickinson & Calzetti (2001) find satisfactory agreement between the white dwarf and solar analog stars for NICMOS photometric calibration.
4.2.3
During Cycle 7, NICMOS throughput (i.e. photoelectrons per second detected from a source with given flux) was generally within 20% of pre-launch expectations in all observing modes. At the new, warmer temperature under NCS operations, the detector quantum efficiency is higher at all wavelengths, with the largest improvements at shorter wavelengths. Hence, the photometric zeropoints are significantly different with the NCS in operation compared with Cycle 7. The latest zeropoints are always given at the NICMOS Photometry Web page available at:
http://www.stsci.edu/hst/nicmos/performance/photometry.
The photometric stability of NIC1 and NIC2 in Cycle 7 was monitored once a month, and more frequently near the end of the NICMOS Cryogen lifetime. Observations of the solar analog P330E were taken through a subset of filters (5 for NIC1, 6 for NIC2) covering the entire wavelength range of the NICMOS cameras, and dithered through three or four pointings. NIC3 has also been monitored in a similar fashion, although only two filters were used for part of the instrument’s lifetime. For most filters and cameras the zeropoints have been stable to within 3% throughout the lifetime of the instrument, although in Cycle 7 there was a small secular drift as the instrument temperature changed.
The monitoring program continued in Cycle 11 and beyond after the NCS was installed. Four filters in each of the cameras were monitored using solar analog P330E. With the switch to Two Gyro Mode in Cycle 14 the white dwarf standard G191B2B was added to the monitoring program to ensure year-round coverage. In the five years since the NCS installation in 2002, there has been a decrease on the order of 1% in sensitivity in NIC2 for all filters. For the other cameras, a similar effect may be present, but this is hard to confirm due to the larger noise in photometry for these cameras. Evidence that this effect involves all three cameras is, however, given by the flat-field monitoring (see Section 7.2.3). No satisfactory explanation has yet been found for this decrease in sensitivity. However, the change in sensitivity is consistent with a drift in detector temperature with time (see Dahlen, NICMOS ISR-2007-002).
4.2.4
The NICMOS team has determined that NICMOS has a significant count rate dependent non-linearity that also depends on wavelength. This is a different nonlinearity from the well-known total count dependent non-linearity. The non-linearity amounts to a 0.050.10 mag/dex offset in incident flux for the shortest wavelength (F090M and F110W), about 0.03 mag/dex at F160W and less than that at longer wavelengths (see Figure 4.4). Objects fainter than the NICMOS standard stars of about 12th magnitude will be measured too faint, objects that are brighter than our standards will seem too bright. The effect depends entirely on the incoming flux rate, so any objects fainter than the night sky (or on top of a bright object) will have a non-linearity offset determined by the background flux (Shaw, NICMOS ISR-2008-003). This means that the maximum offsets on dark sky backgrounds at F110W are about 0.25 mag in NIC1 and NIC2, and about 0.16 mag in NIC3 (de Jong, NICMOS-ISR 2006-001). Software has been developed to linearize the counts in imaging observations (de Jong, NICMOS ISR-2006-003). More details on the effect and how to correct for it can be found at:
http://www.stsci.edu/hst/nicmos/performance/anomalies/nonlinearity.html.
Figure 4.4: Wavelength dependent non-linearity amounts for all three cameras.
4.2.5
The response of a pixel in the NICMOS detectors to light from an unresolved source varies with the positioning of the source within the pixel due to low sensitivity at the pixel’s edges and dead zones between pixels. The interpixel sensitivity was found to be an important effect and it varies by as much as 30%. This effect has no impact on observations of resolved sources, and little effect on well-sampled point sources (e.g. observations with NIC1 and NIC2 through most filters). However in NIC3, point sources are badly under-sampled, especially at short wavelengths where the telescope diffraction limit is much smaller than the NIC3 pixel size. Therefore, object counts may vary by as much as 30% depending on the wavelength positioning of a star within a pixel. Well-dithered exposures will average out this effect, but NIC3 observations of stars with few dither positions can have significant uncertainties which may limit the achievable quality of point source photometry.
The intrapixel sensitivity in Cycle 7 and possible post-processing solutions are discussed in Storrs et al. (NICMOS ISR-99-005) and Lauer (1999, PASP, 111, 1434). This was also investigated for NIC3 in Cycle 11, after the installation of cryo-cooler (Xu, NICMOS ISR-2003-009).
Compared to Cycle 7, the intrapixel sensitivity after installation of the NCS in Cycle 11 is found to decrease by 27% for both F110W and F160W filters. This is likely due to the increase in the detector temperature (and electron mobility) in Cycle 11 and beyond, leading to a higher rate of electrons absorption by diodes.
4.2.6
Sources with Extreme Colors
We have carried out tests to establish the likely impact on photometric observations of sources of extreme colors induced by the wavelength-dependent flat field. This contributes at most a 3% photometric error for sources with unknown colors.
For each filter, we used two sources with different colors assuming the spectral energy distributions to have black-body functions. The first case had a color temperature of 10,000K, and thus is typical of stellar photospheres and the resultant color is representative of the bluer of the sources that will be seen with NICMOS. (It is worth noting that for reflection nebulae illuminated by hot stars, a significantly bluer spectrum is often seen.) The second source had a color temperature of 700K which in ground-based terms corresponds to [J–K] = 5, a typical color encountered for embedded sources, such as Young Stellar Objects (YSOs). Again, there are sources which are known to be redder. The Becklin-Neugebauer object, for example, has no published photometry at J, but has [H–K] = 4.1, and the massive YSO AFGL2591 has [J–K] = 6.0. YSOs with [J–K] = 7 are known, although not in large numbers.
An example of a pair of simulated spectra is shown Figure 4.5, for the F110W filter. In this filter an image of a very red source will be dominated by the flat field response in the 1.2 to 1.4 micron interval, while for a blue source the most important contribution will come from the 0.8 to 1.0 micron interval. The results of our study for the most affected filters are shown in Table 4.4. The other filters are better.
Even for the broadest NICMOS filters the wavelength dependence of the flat field response generates only small photometric errors, typically less than 3% for sources of unknown color. Not surprisingly, the largest errors arise in the 3 broadband filters whose bandpass include some part of the regions where the flat field response changes most rapidly.
The same results hold true even for filters at the most extreme wavelengths (e.g., F090M, F222M and F240M) because of their small bandwidth.
It will probably be difficult to obtain photometry to better than the limits shown in Table 4.4 for the F090M, F110W, F140W, F205W and F240M filters, and observers requiring higher accuracy should contact the Help Desk at STScI for guidance.
These errors can probably be corrected if more accurate photometry is needed, by taking multi-wavelength observations and using an iterative correction technique.
For observers requiring high precision photometry, these represent non-trivial limits beyond which it will not be possible to venture without obtaining multi-wavelength images. In order to obtain 1% precision using the F110W filter, for instance, observers should observe at least in another wavelength. The color information derived from the pair (or group) of images could then be used to construct a more appropriate flat field image, which could then be applied to improve the color information.
Figure 4.5: Detected Source Spectrum. These are for sources with color temperatures of 700K (solid line) and 10,000K (dashed line). It is easy to see that the detected image will be dominated by the flat field response in the 1.2-1.4 μm region for a 700K source, while for a 10,000K source the detected image will be affected by the flat field response throughout the filter bandpass.
Extended Sources with Extreme Spatial Color
Variations
So far, the analysis has been limited to point sources, but some mention should be made of the situation for extended objects. A good example is the YSO AFGL2591. This has an extremely red core of [J–K] = 6, and is entirely undetected optically. However, it also has a large IR nebula which is quite prominent at J and K, and in the red visual region, but much fainter at L, and which is probably a reflection nebula. Spatially, the nebula has highly variable color, some parts of it having fairly neutral or even slightly blue colors in the NICMOS waveband, while other parts are extremely red. Obtaining very accurate measurements of the color of such a source requires the use of images at more than one wavelength and an iterative tool of the kind described earlier. A further example of this kind of complicated object is the prototypical post-AGB object CRL2688, the Cygnus Egg Nebula, which has an extremely blue bipolar reflection nebula surrounding an extremely red core. Techniques which require very accurate measurements of the surface brightness of extended objects, such as the brightness fluctuation technique for distant galaxies, will need to be applied with care given to the photometric uncertainties such as those discussed here.
Creating Color-Dependent Flat Fields
NICMOS ISR-99-002 describes two methods for creating color-dependent flat fields. We have included programs and calibration files for making these flat fields in the software part of the Web site. One way of approaching the problem is to make monochromatic flats by doing a linear least squares fit to several narrowband (and, if necessary for increased wavelength coverage) medium band flats, for each pixel. The slope and intercept images that result from such a fit can be used to determine the detector response to a monochromatic source. This method works best if the desired wavelength is within the range covered by the observed flats; extrapolation with this method gives questionable results.
If the source spectrum is known, a composite flat made from the weighted sum of the narrowband flats in the passband of the observed image can be made. The IRAF script, interflat.cl, uses an input spectrum and the calibration database in STSDAS to compute composite flats. This script is downloadable from:
http://www.stsci.edu/hst/nicmos/tools/colorflat_intro.html.
If you have a variety of sources in your image you may want to make several flat fields and apply them to regions defined by some criterion, like color as defined by a couple of narrowband images on either side of the broadband image.

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