the capability to detect the additional line. Another source of residuals can be fluctuations in the average response (see bottom panels Fig. \[fig:fakelinemerge\] for combined ARF and RMF). These minor fluctuations did not affect our detection efficiency since they averaged out over the width of a spectral line. We extensively tested the detection efficiency using different stacking methods. Additional smoothing of the response files resulted in lower sensitivity for detecting the simulated line (e.g. using mean, median, and Gaussian filters) because it introduced residuals around spectral features due to broadening of the response. Using linear interpolation to remap the response resulted in smoother response but the simulated line was not recovered. The method we used for the final analysis was the most efficient at recovering the simulated line.

Multi-temperature residuals in ACIS-S {#sec:residuals}
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When we fit the merged spectrum of the cluster sample for the ACIS-S detectors (Fig. \[fig:linemerge\]) there were two significant residuals ($\rm{>1\sigma}$). In the simulated merged spectra such strong residuals are not found (Fig. \[fig:fakelinemerge\]). We simulated each cluster with a two-temperature plasma X-ray emission model (`XSPEC` `apec`) and then modelled the merged spectrum with two temperatures (actually the average of $\rm{2\times33}$ temperatures). The reasons for 