To help new users have a smooth and easy start with Gnuastro, in this chapter several thoroughly elaborated tutorials, or cookbooks, are provided. These tutorials demonstrate the capabilities of different Gnuastro programs and libraries, along with tips and guidelines for the best practices of using them in various realistic situations.
We strongly recommend going through these tutorials to get a good feeling of how the programs are related (built in a modular design to be used together in a pipeline), very similar to the core Unix-based programs that they were modeled on. Therefore these tutorials will greatly help in optimally using Gnuastro’s programs (and generally, the Unix-like command-line environment) effectively for your research.
In Sufi simulates a detection, we’ll start with a fictional20 tutorial explaining how Abd al-rahman Sufi (903 – 986 A.D., the first recorded description of “nebulous” objects in the heavens is attributed to him) could have used some of Gnuastro’s programs for a realistic simulation of his observations and see if his detection of nebulous objects was trust-able. Because all conditions are under control in a simulated/mock environment/dataset, mock datasets can be a valuable tool to inspect the limitations of your data analysis and processing. But they need to be as realistic as possible, so the first tutorial is dedicated to this important step of an analysis.
The next two tutorials (General program usage tutorial and Detecting large extended targets) use real input datasets from some of the deep Hubble Space Telescope (HST) images and the Sloan Digital Sky Survey (SDSS) respectively. Their aim is to demonstrate some real-world problems that many astronomers often face and how they can be solved with Gnuastro’s programs.
The ultimate aim of General program usage tutorial is to detect galaxies in a deep HST image, measure their positions and brightness and select those with the strongest colors. In the process, it takes many detours to introduce you to the useful capabilities of many of the programs. So please be patient in reading it. If you don’t have much time and can only try one of the tutorials, we recommend this one.
Detecting large extended targets deals with a major problem in astronomy: effectively detecting the faint outer wings of bright (and large) nearby galaxies to extremely low surface brightness levels (roughly one quarter of the local noise level in the example discussed). Besides the interesting scientific questions in these low-surface brightness features, failure to properly detect them will bias the measurements of the background objects and the survey’s noise estimates. This is an important issue, especially in wide surveys. Because bright/large galaxies and stars21, cover a significant fraction of the survey area.
Building the extended PSF tackles an important problem in astronomy: how the extract the PSF of an image, to the largest possible extent, without assuming any functional form. In Gnuastro we have multiple installed scripts for this job. Their usage and logic behind best tuning them for the particular step, is fully described in this tutorial, on a real dataset. The tutorial concludes with subtracting that extended PSF from the science image; thus giving you a cleaner image (with no scattered light of the brighter stars) for your higher-level analysis.
In these tutorials, we have intentionally avoided too many cross references to make it more easy to read. For more information about a particular program, you can visit the section with the same name as the program in this book. Each program section in the subsequent chapters starts by explaining the general concepts behind what it does, for example see Convolve. If you only want practical information on running a program, for example its options/configuration, input(s) and output(s), please consult the subsection titled “Invoking ProgramName”, for example see Invoking NoiseChisel. For an explanation of the conventions we use in the example codes through the book, please see Conventions.
The two historically motivated tutorials (Sufi simulates a detection is not intended to be a historical reference (the historical facts of this fictional tutorial used Wikipedia as a reference). This form of presenting a tutorial was influenced by the PGF/TikZ and Beamer manuals. They are both packages in in TeX and LaTeX, the first is a high-level vector graphic programming environment, while with the second you can make presentation slides. On a similar topic, there are also some nice words of wisdom for Unix-like systems called Rootless Root. These also have a similar style but they use a mythical figure named Master Foo. If you already have some experience in Unix-like systems, you will definitely find these Unix Koans entertaining/educative.
Stars also have similarly large and extended wings due to the point spread function, see Point spread function.