Parameter | Value | Interval Size |
( ergs)&dotfill#dotfill; | - | |
( K)&dotfill#dotfill; | - | |
(cm)&dotfill#dotfill; | ||
(cm)&dotfill#dotfill; | ||
(ergcms)&dotfill#dotfill; | ||
(kms)&dotfill#dotfill; | ||
&dotfill#dotfill; | - | |
&dotfill#dotfill; | - |
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We used the ionizing SED made in §5.1 to generate grids of XSTAR models. We utilized MPI_XSTAR 4 (Danehkar et al., 2018) that allows parallel execution of multiple XSTAR runs on a computer cluster (in this case, the ODYSSEY cluster at Harvard University). It employs the xstar2table script (v.1.0) to produce multiplicative tabulated model files: an absorption spectrum imprinted onto a continuum (xout_mtable.fits), a reflected emission spectrum in all directions (xout_ain.fits), and an emission spectrum in the transmitted direction of the absorption (xout_aout.fits). The first and second tabulated model files are used as absorption and emission components of the ionized outflows (or infalls) in spectroscopic analysis tools. Table 4 lists the parameters used for producing XSTAR model grids. To cover the possible range of physical conditions, we initially considered a large range of gas densities from to cm, column densities from to cm, ionization parameters from to ergcms, and turbulent velocities of 100-500 kms, for use in spectral fitting.
We computed a grid of XSTAR models on the two-dimensional - plane, sampling the fundamental parameter space with 15 logarithmic intervals in the column density (from to cm with the interval size of ) and 29 logarithmic intervals in the ionization parameter (from to ergcms with the interval size of ), assuming a gas density of cm. For diagnostic purposes, we have initially constructed some grids with the same - parameter space for -cm (interval size of ), and -kms (interval size of ). However, we found that results were indistinguishable for this wide range of the gas density in highly-ionized absorbers. Hereafter, all XSTAR models correspond to a gas density of cm.
The turbulent velocity is another important parameter in photoionization modeling. An increase in the turbulent velocity increases the equivalent width of an absorption line for a given column density of each ion. To estimate equivalent widths correctly, the velocity width, which is associated with line broadening, must be measured precisely. The high spectral resolution of MEG and HEG data allows for the possibility of determining the velocity width. However, due to insufficient counts, our HETGS observations pointed to a wide range of velocity widths with high uncertainties, so we could not measure the exact value of for each ion. From the line width measurements (see Table 3), we adopted a velocity turbulence of kms for the warm absorber, which approximately corresponds to the HETGS optimal spectral resolution.
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We proceeded to fit the combined MEG and HEG data shown in Figure 5, multiplying our continuum model by the XSTAR tabulated grids produced from the ionizing SEDs in §5.1. There are a total of two free parameters in the tabulated grid fitting, namely, the ionization parameter and column density of the ionized absorber. Using the base continuum model described in §4.1, the model for the spectra containing 1 ionized absorber and 4 Fe emission lines are implemented as follows: . These models successfully described the data with an ionization parameter of and a column density of (90% confidence levels), with an observed redshift of . The model with these parameters has a goodness-of-fit of . These results allowed us to refine our parameter estimations in performing the warmabs model fitting described in the subsequent section.
Ashkbiz Danehkar