This article describes the creation of integrated emission line and averaged intensity maps. The SPEAR team created emission line maps with adaptive binning up to high resolution, while FIMS created lower-resolution emission line maps with adaptive smoothing.

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FIMS Procedure

Integrated emission line maps were produced as described in Jo et al. 2017 and Jo et al. 2019, and averaged intensity maps were obtained by averaging the hyperspectral HEALPixel maps over all wavelengths.

SPEAR Procedure

Integrated emission line maps were created using a nested adaptive binning method. For each kernel (starting at one the size of a single 13.7 arcmin HEALPixel in an Nside=256 HEALPix scheme), the team performed fits of the line emission, scattered stellar spectra, and scattered lines (see figure below). The line values from pixels where significant detection were made were transferred to the result maps. The remaining pixels were then rebinned by a scale factor of two. This process was repeated until the kernel scale factor reached 256x256 pixels. Significance limits used at each scale were set such that less than one spurious detection in a pixel would be expected at each scale.  The fits included the continuum and multiple lines, including blends.

Noisy spectrum in a 60 Angstrom range with overlayed models. There are two emission features in the best fit model, one in the blue line model, and the red line is mostly flat.

A typical 3-sigma fit to the C IV line at 1550 Å. The line at 1533 Å is the Si II* resonance line. The light grey histogram line is the data. The black line is the best fit model. The red line shows the underlying scattered stellar continuum. The blue line shows the best fit that could be made by assuming a C IV 1550Å intensity of zero. Detection significance is determined by comparing the χ2 of the fits with and without the line.

In addition to the integrated intensity, uncertainty, and detection significance, the adaptive binning maps also provide the area of the kernel with which the emission was detected in units of number of HEALPixels.  However, the size of the kernel is not the same as the number of HEALPixels used to get a significant detection.  Parts of the region could have already been found to have significant detections at smaller scales and would have already been moved to the output map.



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