Description

Class:

jwst.background.BackgroundStep

Alias:

background

The background subtraction step performs image-from-image subtraction in order to accomplish subtraction of background signal. The step takes as input one target exposure, to which the subtraction will be applied, and a list of one or more background exposures. Two different approaches to background image subtraction are used, depending on the observing mode. Imaging and most spectroscopic modes use one method, while a special method is used for Wide-Field Slitless Spectroscopy (WFSS).

This type of background subtraction is just one method available within the JWST pipeline. See Background Subtraction for an overview of all the methods and to which observing modes they’re applicable.

Imaging and Non-WFSS Spectroscopic Modes

If more than one background exposure is provided, they will be averaged together before being subtracted from the target exposure. Iterative sigma clipping is applied during the averaging process, to reject sources or other outliers. The clipping is accomplished using the function astropy.stats.sigma_clip. The background step allows users to supply values for the sigma_clip parameters sigma and maxiters (see Step Arguments), in order to control the clipping operation.

For imaging mode observations, the calculation of the average background image depends on whether the background exposures are “rate” (2D) or “rateint” (3D) exposures. In the case of “rate” exposures, the average background image is produced as follows:

  1. Clip the combined SCI arrays of all background exposures. For mixtures of full chip and subarray data, only overlapping regions are used

  2. Compute the mean of the unclipped SCI values

  3. Sum in quadrature the ERR arrays of all background exposures, clipping the same input values as determined for the SCI arrays, and convert the result to an uncertainty in the mean

  4. Combine the DQ arrays of all background exposures using a bitwise OR operation

In the case of “rateint” exposures, each background exposure can have multiple integrations, so calculations are slightly more involved. The “overall” average background image is produced as follows:

  1. Clip the SCI arrays of each background exposure along its integrations

  2. Compute the mean of the unclipped SCI values to yield an average image for each background exposure

  3. Clip the means of all background exposure averages

  4. Compute the mean of the unclipped background exposure averages to yield the “overall” average background image

  5. Sum in quadrature the ERR arrays of all background exposures, clipping the same input values as determined for the SCI arrays, and convert the result to an uncertainty in the mean (This is not yet implemented)

  6. Combine the DQ arrays of all background exposures, by first using a bitwise OR operation over all integrations in each exposure, followed by doing by a bitwise OR operation over all exposures.

The average background exposure is then subtracted from the target exposure. The subtraction consists of the following operations:

  1. The SCI array of the average background is subtracted from the SCI array of the target exposure

  2. The ERR array of the target exposure is currently unchanged, until full error propagation is implemented in the entire pipeline

  3. The DQ arrays of the average background and the target exposure are combined using a bitwise OR operation

If the target exposure is a simple ImageModel, the background image is subtracted from it. If the target exposure is in the form of a 3-D CubeModel (e.g. the result of a time series exposure), the average background image is subtracted from each plane of the CubeModel.

The combined, averaged background image can be saved using the step parameter save_combined_background.

WFSS Mode

For Wide-Field Slitless Spectroscopy expsoures (NIS_WFSS and NRC_WFSS), a background reference image is subtracted from the target exposure. Before being subtracted, the background reference image is scaled to match the signal level of the WFSS image within background (source-free) regions of the image. The scaling factor is determined based on the variance-weighted mean of the science data, i.e., factor = sum(sci*bkg/var) / sum(bkg*bkg/var). This factor is equivalent to solving for the scaling constant applied to the reference background that gives the maximum likelihood of matching the science data. Outliers are rejected iteratively during determination of the scaling factor in order to avoid biasing the scaling factor based on outliers. The iterative rejection process is controlled by the wfss_outlier_percent, wfss_rms_stop, and wfss_maxiter step arguments.

The locations of source spectra are determined from a source catalog (specified by the primary header keyword SCATFILE), in conjunction with a reference file that gives the wavelength range (based on filter and grism) that is relevant to the WFSS image. All regions of the image that are free of source spectra are used for scaling the background reference image. The step argument wfss_mmag_extract can be used, if desired, to set the minimum (faintest) abmag of the source catalog objects used to define the background regions. The default is to use all source catalog entries that result in a spectrum falling within the WFSS image.

For both background methods the output results are always returned in a new data model, leaving the original input model unchanged.

Upon successful completion of the step, the S_BKDSUB keyword will be set to “COMPLETE” in the output product.