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2.2 Detecting large extended targets ¶

The outer wings of large and extended objects can sink into the noise very gradually and can have a large variety of shapes (for example, due to tidal interactions). Therefore separating the outer boundaries of the galaxies from the noise can be particularly tricky. Besides causing an under-estimation in the total estimated brightness of the target, failure to detect such faint wings will also cause a bias in the noise measurements, thereby hampering the accuracy of any measurement on the dataset. Therefore even if they do not constitute a significant fraction of the target’s light, or are not your primary target, these regions must not be ignored. In this tutorial, we will walk you through the strategy of detecting such targets using NoiseChisel.

Do not start with this tutorial: If you have not already completed General program usage tutorial, we strongly recommend going through that tutorial before starting this one. Basic features like access to this book on the command-line, the configuration files of Gnuastro’s programs, benefiting from the modular nature of the programs, viewing multi-extension FITS files, or using NoiseChisel’s outputs are discussed in more detail there.

We will try to detect the faint tidal wings of the beautiful M51 group⁴⁴ in this tutorial. We will use a dataset/image from the public Sloan Digital Sky Survey, or SDSS. Due to its more peculiar low surface brightness structure/features, we will focus on the dwarf companion galaxy of the group (or NGC 5195).

• Downloading and validating input data
• NoiseChisel optimization
• Skewness caused by signal and its measurement
• Image surface brightness limit
• Achieved surface brightness level
• Extract clumps and objects (Segmentation)