Åaround a feature detected at $\lambda_0$ Å, truncated only [*once*]{} for repetition if two features are too close. We call this identification list model [trunk-1]{}.

Similar studies have been carried out in the past where measured absorption features are compared with a theoretical features in a given identification list (e.g., [@krongold2003a; @netzer2003a]). However, these studies present two important limitations: the identification list employed typically contain a relatively small number of theoretical features (e.g., $\sim 50$), and their identification is based on comparing the wavelength position of the observed feature with those calculated theoretically using undefined identification window (how much is allowed for an observed feature to be compared with theory, e.g., 0.1 Å, is too large). The latter restriction is particularly important because the larger the identification window becomes, the more are the chances of an incorrect identification.

To demonstrate the efficacy of our methodology, we have applied the [trunk-1]{} algorithm to the synthetic spectra produced with Model A, i.e., the model consisting of two warm absorbers (Table 1).

Because we know exactly which lines are contained in the synthetic spectra, we can then assess how well [trunk-1]{} identify the observed lines. Figure \[matching\_lista1\] shows the level of matching in 