of wavelength shifts due to velocity components in the absorbing material. Thus, starting with the best-fit for the line centroid $\lambda_0$ of a given observed line, we search for theoretical lines within a $\pm\Delta\lambda_0$ identification window (IW) around $\lambda_0$. This allows for the identification of blue or redshifted lines. If more than one theoretical line is present in the identification window, we choose the line with the largest optical depth at the core ($\tau_0$).

A second observed feature can be found close enough such that its identification window cover a similar range, including the same strong lines. If the next observed feature is identified by the same theoretical line as in the feature just before, we do not allow for repetition but rather choose the second strongest line in the identification window. This allows for the detection of duplets. Nevertheless, this constrain is only applied to two consecutive lines. Thus, if a third consecutive observed line (i.e. two features next) is identify with the same strongest theoretical lines as the first, this one is assigned again. This allows the detection of more than one velocity component. The result is an identification list based on the strongest predicted absorption line, $\pm\Delta\lambda_0$ 