Astronomical Catalogues: From Well Known To Lesser Know

Bogdan Teodorescu

Author at ‘The Secrets Of The Universe’, I am a science student from Romania. I am also the founder of Astronomy Hub, an organization for popularizing astronomy and astrophysics. I love reading philosophy and literature, enjoy classical rock, blues, and watch movies.

This has been an article I’ve been looking forward to for a long time. Hopefully, a lot of you will find it interesting, although it will be more useful to amateur astronomers and more advanced passionates. 

In brief, astronomical catalogues are used basically everywhere. I will discuss here the well-known Messier catalogue, but also some lesser-known ones, of which there are extremely entertaining ones, and also very used ones in different areas of research. 

What do I mean by ‘used’ ones? Well, I started working out of need with Python, which is, as it is widely said over the internet by everyone, ‘the most important, useful, popular’ and so on, programming language. So how exactly is Python used in scientific research, and particularly in astronomical research? It’s all data science, really. And that is what you can do, very efficiently, with Python. It is working with large databases, large quantities of different information regarding all you can possibly know about an astronomical object. And that is where astronomical catalogues come in the game because they are really the databases we are trying to work out. 

Let’s say you have a big catalogue of stars. You have their names (or identification numbers, whatever the type is), and all sorts of other information, like their mass, chemical composition, radial velocity, and so on. You need to sort all of that, and you want to find some patterns, or maybe make some classification.

Even more, scientists need to make use of all the new​​ data they get. They need to interpret it, maybe make visual representations of what they see in numbers. They want to get what they need from the enormous quantities of ‘brute’ information they receive. And that is what we call data science. It is important to mention that I learned basic data science and basic Python by myself, and it is something you can teach yourself just for the fun of it. We’ll get to that later.

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Besides that, we can make use of astronomical catalogues just as a hobby. We can use them just like we use the Messier catalogue when we get outside for some skywatching. 

The Messier Catalogue

Most of you probably heard about the Messier objects. And definitely, all of you heard about some​ Messier object, but you didn’t know that it was a Messier object. For example, the galaxy Andromeda is M31, meaning it is the object with the number 31 in the Messier catalogue. 

What is its story? Firstly, it is named Messier after Charles Messier, a French astronomer, who was interested in comets, and so he started making a list with all the objects (galaxies, nebulae, or clusters of stars) that were making problems for his search. Worth mentioning is that the objects can be observed from the Northern Hemisphere. So basically, every amateur astronomer has watched some Messier object, because it’s so fun to go out and look for them.

Some are common targets, such as M42, the Orion Nebula, and pretty easy to spot, and some are more uncommon, and harder to spot. Some can be seen with the naked eye (of course, you need some really good eyes and sky conditions), and some can be seen only with really good telescopes. There are even marathons, where people embark on the quest of finding all the Messier objects in one night. You definitely need to try and do it on the right days of the year, but you can easily find them on the internet.

Of course, you need a good telescope for that. Other nice objects other than the ones I mentioned would be M101, M1, M57, M45, M20, or M78. The Messier objects are cool. I actually have a ‘periodic table’ of all the Messier objects above my desk.

The CN And The NGC Catalogue

The first one mentioned is a catalogue of nebulae, published in 1786 by William Herschel. In 1789, he added 1000 more entries, and finally, 500 more in 1802. The total came to 2500 entries. 

In 1864, the CN was expanded into the General Catalogue of Nebulae and Clusters of Stars​ (GC) by William Herschel’s son, John Herschel. In 1878, John Louis Emil Dreyer wanted to make a supplement to the General Catalogue, but he was asked by the Royal Society to make a new one instead. And so came out the New General Catalogue​​, which is basically the best version of the CN published by William Herschel. 

Why is this important? If you are an amateur astronomer, or willing to get into skywatching and amateur astronomy (not to mention, if you are preparing for a career in astronomy), you will see a lot of NGC objects around. Mostly, the Messier objects are also in the NGC, so that is why you might see them under different designations. 

There is a very important update to the NGC, namely the Index Catalogues​ published by Dreyer in two parts in 1895, adding a total of 5836 new objects, which you will see with the IC​   abbreviation. For example, IC 2497 is a spiral galaxy, former quasar, which is close to the well-known Hanny’s Voorwerp.

Some interesting NGC objects could be NGC 6543 (The Cat’s Eye Nebula) or NGC 3311, to give some examples.

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The Henry Draper Catalogue

There are not many things to say about the Henry Draper catalogue, except the fact that it has great historical importance. Of course, as you might guess, it was compiled by Henry Draper between 1918 and 1936. It basically gives an identification number and some spectral information about almost every star in the sky down to the magnitude of 9. It is important to know about this catalogue because you will find most stars (which don’t have given names) written down with the prefix HD. There are 225,300 stars in the original Henry Draper catalogue.

The Atlas of Peculiar Galaxies

Now this one I found extremely entertaining to look through, and it may be one of my personal favorites too. Not many people know about it, but believe me, it’s a catalogue worth knowing about. If you have an intrinsic romantic passion for everything Universe-related, such as I do, you won’t find a funnier thing to look through than a whole atlas full of interesting galaxies. The catalogue was made by Halton Arp and published in 1966 at the California Institute of Technology. It contains a total of 338 galaxies. 

Of course, most of the phenomena that made those galaxies ‘peculiar’ are now well-known. But at the time, Arp’s effort was useful in translating and putting together some of the experimental data and giving it to the scientific community. It is important for putting together a lot of examples of different phenomena observed with galaxies. 

Some notable ‘peculiar’ objects would be Arp 107, Arp 148, Arp 152, or Arp 193 (also known as IC 883)

Also read: Studying the nature of galaxies in the Arp catalogue (Project report)

Some other ‘modern’ ones you can really learn data science on

Getting back to what I said at the beginning of the article, regarding data science, there are some catalogues we constantly use, and which you can learn to use too. Of course, that is not really needed if all you want to do is skywatching, but if you want to go further, you will need some real data and some real ways to interpret it. 

Just mentioning them in brief, there is SDSS (Sloan Sky Digital Survey), ​​the FK (Fundamental​ Catalogues)​, of which the last one is FK6, ​​or the 2​ MASS (Two Micron All-Star Survey)​. The last one is mainly used for infrared astronomy, and it recorded 470 million point sources (most of them being stars), and 1,7 million other sources (mostly galaxies and nebulae), so it’s a lot of data for you to work with. 

How do you work with it? Get to Python. It will do all the job if you know how to make it do it. You can get some good IDE to work in, but I will leave that to you, because as you will start learning Python and data science from somewhere, the people there or the tutorial you use will tell you what to start with, and guide you through it. I personally use Jupyter Notebook now, along with PyCharm, and I can tell you that they are the work environments most preferred by scientists. 

Read all the articles of Basics of Astrophysics here

What’s great is that you have all these catalogues and databases available on the internet, so all you need to do is try to learn how to use them. And who knows, you may even develop some new algorithm of your own. That is basically what data scientists do. 

There are others, of course

There are a lot of important catalogues worth talking about, of course, such as the Abell catalogue, or Vorontsov-Vel’yaminov Interacting Galaxies atlas, but I tried to choose the most important and entertaining ones, at least for me. Also, I tried to explain how they are used, and how you can use each of them too. 

Of course, if you have any questions, or article suggestions, you can contact me on Facebook. I will be more than happy to answer you.

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