Revisiting the emission line source detection problem in integral field spectroscopic data

We present a 3-dimensional matched filtering approach for the blind search of faint emission-line sources in integral-field spectroscopic datasets. The filter is designed to account spectrally rapidly varying background noise due telluric air glow spectrum. A software implementation this implemented an updated version Line Source Detection Cataloguing tool (LSDCat2.0). Using public data from MUSE-Wide survey we show how new design provides higher detection significances emission line buried between atmospheric [OH]-bands at $\lambda \gtrsim 7000$\,\AA{}. also how, given source parameterisation, selection function improved algorithm can be derived analytically variances data. verify analytic solution against insertion and recovery experiments recently released dataset MUSE eXtreme Deep Field (MXDF). then illustrate has re-scaled 3D profiles that are not fully congruent with template. This procedure alleviates construction realistic functions by removing need computationally cumbersome experiments.