tokens: assumed to be single Gaussians, using photographic density , and solving for , and c from these lines. Then, I was solved at neighboring wavelengths for the Fe x transitions. This procedure slightly reduced the lower intensity values at the base of the lines, without changing the results significantly. We do not know widths of Fe x lines that are unblended, nor do we know the precise wavelength of Fe x lines on the wavelength scale above. Therefore, the unresolved FS can only be derived as an upper limit by comparing the observed data with the two lines, estimating for the FS splitting itself (or by a least-squares optimization outlined below). In making these comparisons, we adopted the optically thin ratio of 2.09 for the two lines from CHIANTI (Young et al. 2016 ). Some typical profiles are illustrated in Figure 3 . Figure 3. Observed profiles and fits are shown for a specified line width of 0.23 Å, of the 1603.2 Å region of the S082B data obtained above the solar limb. The solid line shows the S082B data, the dotted lines show the two components of the Fe x transitions in their optically thin ratio, and the dotted–dashed lines show the total modeled emission for the given FS splitting. The panel labeled “4 cm −1 ” shows an acceptable by-eye fit, yielding an FS splitting close to 4 cm −1 . The other panels show the fits, with residuals at least 10 times higher, for splitting values of 1, 7, and 10 cm −1 . For values of FS splitting near and below the line width ( cm −1 ) there is some redundancy between FS splitting and line width. The figure shows observed profiles over-plotted with models with a given (1/ e ) width of 0.23 Å (taken from the optimization calculation below) for four values of the FS splitting. The figure suggests an FS splitting value of , certainly cm −1 . The variances, sum of model minus data squared evaluated over the fit to a 1 Å wide band centered at the line, are 2.5, 3, and 9 times the optimal value for 1, 7, and 10 cm −1 respectively. A trade-off exists between line width and FS splitting: the larger the width, the lower the splitting needed to fit the same data. Therefore, we can place only an upper limit on the FS splitting from this analysis of cm −1 . However, we can go a step further. While the data are photographic and subject to nonlinearities in photographic density versus intensity, we nevertheless performed a formal analysis of variances by fitting the two lines and varying the strong line's wavelength, line widths and the FS splitting. Both lines were given the same width and the ratio of the intensities was fixed at 2.09. The pikaia genetic algorithm was used (Charbonneau 1995 ). Figure 4 shows the surface as a function of width and FS splitting. We adopted a constant value for the observational error across the line profiles for the calculation, because the photographic densities lie on top of a large pedestal (equivalent to a dark current). We multiplied the errors by Gaussian functions centered near
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