The NICMOS "Pedestal" Effect This memo describes our current understanding of the "pedestal" effect in NICMOS images. Observers are encouraged to read the on-line image anomalies page at the STScI NICMOS web site. Questions about anomalies in general should be addressed to your contact scientist. Questions specific to the software may be addressed to the authors of the programs. Work on the "pedestal" effect is ongoing, and we hope that within the next year or so we'll have a definitive solution to this problem. At that time we'll pull together a full Instrument Science Report (ISR) (which will be available on the web) and circulate a notice through the ST Analysis News- letter (STAN) which NICMOS observers get monthly via email. I. WHAT IS IT? A big problem in reducing NICMOS images is the removal of the "DC pedestal", a time varying bias level which appears in all NICMOS images. The pedestal is also quadrant-dependent. Due to its random nature, it cannot be removed by current pipeline processing, but must be removed at the data-analysis level. Quadrant-dependent means that the 4 quadrants of a NICMOS camera will have different levels (which usually shows as a different degree of "darkness" of each quadrant in a science image); the levels change from exposure to exposure. The most obvious effect of the pedestal is to leave a residual flat-field signature in the science images, because the image processing is applying flat-fields to a component which does not follow the quantum efficiency variations of the pixels. The pedestal, therefore, compromises photometry, isophotal studies, etc. This problem was much more severe in the early months of NICMOS operation. A change in the instrument software that took effect on Aug. 21, 1997 has minimized (but not eliminated) this effect. Another effect that looks like pedestal is "residual shading". This is a bias effect; like the pedestal, it is a noiseless component, but, unlike the pedestal, the shading varies ACROSS each quadrant. This is why none of the "pedestal removal" techniques described below can detect it. The residual shading is due to a temperature-dependent change of the bias level of NICMOS; thus sun-angles, seasons, level of detector activity, SAA, all affect the shading level. There is also a secular component which the NICMOS group is now characterizing and, hopefully, at the end of the NICMOS lifetime we will have time-flagged calibration darks to reduce the images. Luckily, the residual shading is generally a small effect, and although its presence leaves residual flat-field fluctuations, these are much smaller than the fluctuations given by the pedestal. Thus there is usually more than one thing going on in the data that needs fixing. In addition, recently acquired data when processed with old dark reference files has residual shading (because the shading is changing with time/temp). This leaves a *non-constant* and *non-linear* signal across quadrants and through a MultiAccum sequence. You should not ignore this and simply try to compute and subtract a constant from the end of your exposure. Some investigators have had some success with a separate shading fit and removal before doing the more common pedestal fit and removal. Hopefully we may be able to ease the situation by soon coming up with time- dependent darks in which the shading matches the science images. Then if you reprocess using the newer darks, all that should be left to worry about is the normal pedestal. A final complication is that much of what routines like those described below are probably measuring is *not* bona fide pedestal, but rather a signature of a mismatch between the flatfielding lamp and the sky. It may be possible in the future to make some "super-sky" images in at least the most popular filters, but this has not been done yet. II. PEDESTAL REMOVAL: One of the best methods available for removing the pedestal in a semi-automatic way is to use the code developed by Roeland Van der Marel; both code and instructions are available from the Web: http://sol.stsci.edu/~marel/software.html Roeland's program (unpedestal) is packaged for UNIX workstations. It takes as input IRAF format (.imh and .pix pairs) although the NICMOS group has a cl script to translate the .fits files for use by this program, and to translate the products back into fits. This program works iteratively, by using unsharp masking to remove large diffuse objects from the field and then measuring and subtracting a constant (per quadrant) times the flat field image until the residual is minimized. This works well on diffuse sources but can give non-optimal results on images with lots of point sources. Another removal code has been written by Mark Dickenson (med@stsci.edu). Mark may be able to provide the IRAF script to run this code on request. This program (pedsky) starts with the _raw.fits data and interfaces directly with calnica, again iteratively solving for the sky. This program is very good at eliminating point sources before removing the pedestal, but doesn't do as good a job on extended sources. A third script (which calls IDL) has been written by Eddie Bergeron. This program runs well at STScI but is not intended for use at other institutions. Eddie's programs (pedmed, for images with minimal thermal contribution) and pedtherm (for images with a thermal component) measures and subtracts the median of each quadrant before the flatfielding step. This program is very sensitive to the amount of real signal in the images, and so works best with sparse fields. You may want to try this program if you visit STScI to reduce your data. It may be possible to remove the pedestal unambiguously as part of the calnica processing. Development of this technique, and/or incorporation of one or more of the above techniques into STSDAS, is a major goal of NICMOS software development over the next year. As you can imagine, the major complication arises when the NICMOS frames contain extended objects or crowded fields; in this case the identification and subsequent removal of the pedestal level can be tricky. Roeland's code has provisions for both cases (in addition to the "easy" one of sparsely populated fields). Many attempts at removing pedestal are not very successful. Eddie's programs work ok at the short wavelengths, but the thermal wavelengths are often more difficult because they were being affected by the thermal back- ground, so it is harder to get the pedestal level just right. Roeland's code works fine for sparse fields or images with low gradients but you have to deal with each case individually. There seems to be no optimal set of parameters that always do the job, at least for the case of one extended, dominant source that almost fills the chip. III. OTHER WORKAROUNDS If you have data that has contemporaneous background measurements (generally recommended for observations at "thermal" wavelengths) the background and pedestal can be removed almost completely in the standard background sub- traction process. This may be because although the pedestal is time variable, the time constant is rather long and object/sky pairs have approximately the same effect. Another way to minimize pedestal (and dark) problems is to reduce your data using the first or second read as the "zeroth" read. You will lose some integration time but this should not be a concern for longer exposures. Note that if you do this you will have to massage your darks in a similar way (i.e. shift all the multiaccum images "down" by a place or two). This method does not work in every case and is difficult to implement-- you will probably only want to try this as a last resort. IV. BASIC STEPS for the cleaning and stacking of the NICMOS images using Roeland's code. The application of the code is not necessarily straightforward to observations of crowded fields; sometimes the presence of the extended target/multiple objects confuses the algorithm which is supposed to identify the pedestal and you end up with a final image which looks like junk. Of course, the jumbling is not automatic and sometimes the code works well even in the presence of such "confusing" objects. It is worth trying the code directly on the images the first time; you may be lucky and, if it works, will save some time. If the code doesn't work, the best way is to create a mask to mask away the object(s). So the general approach looks like the following: 1. Make sure you have the *_cal.fits images produced by the pipeline; Roeland's software works on those (after they have been translated into IRAF *.imh images). 2. Create mask images for the objects in the field. 3. Feed both *_cal.imh and the flatfield images and the masks to Roeland's software. As you will see from the instructions, there are other input parameters which must be set up; this will be an exercise of trial/error, but one thing that you want to input is the correction done with the "pedestal multiplied by the flatfield". 4. Once you get the outputs, there is one more step: you want to use the IRAF task "background" to remove the residual shading; you want to set up the task to remove the background along columns for NIC2 (axis=2) or rows for NIC1 (axis=1) with a low order polynomial (a straight line is what you want). 5. Finally, now you can use your most loved programs for registration and stacking of the images. The final images obtained with the 5 steps above should be science-grade ones. A few general remarks can be made: - Often the "best" method to bring the quadrants to a common level using Roeland's code (i.e. the method that makes the result look nicest, without edges at the quadrant borders) is a simple linear interpolation over just a few columns/rows. That is to say, set MORCONT=-1, ix0=2, and ix1=3 or 4. That is especially true if the galaxy nucleus with its steep brightness gradient sits close to a quadrant border. This seems a little frustrating, but we could not find any other set of parameters that has a similar success rate....
