Morphological metrics in galaxy images suffer systematic biases from resolution, depth, and noise that can be quantified and corrected empirically, with new metrics proposed to reduce those effects.
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Morphological merger fractions exceed close-pair fractions across 0.2<z<0.9 in DEVILS, with minimal sample overlap, attributed to different merger stages and timescales.
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statmorph-lsst: Quantifying and correcting morphological biases in galaxy surveys
Morphological metrics in galaxy images suffer systematic biases from resolution, depth, and noise that can be quantified and corrected empirically, with new metrics proposed to reduce those effects.
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Deep Extragalactic VIsible Legacy Survey (DEVILS): Morphologically-selected galaxy merger fractions and their direct comparison to close-pair samples
Morphological merger fractions exceed close-pair fractions across 0.2<z<0.9 in DEVILS, with minimal sample overlap, attributed to different merger stages and timescales.