#galaxy classification

Based on how well my last post on galaxy classification was received, I would say that you all enjoy seeing what I have to say about the multitude of celestial bodies in our universe. So I’m here again with more information on galaxies and how they’re classified, including information on the system designed by Edwin Hubble in 1926.

So to begin. What system is used to classify galaxies?

That would be the Hubble Sequence, or the Hubble Tuning Fork, called so for the shape it takes.

As was discussed in the last post, the sequence begins with the elliptical galaxies on the left, smooth and featureless galaxies that are far less efficient at producing stars than their spiral cousins. It breaks off into two junctions once you reach a certain point, and you get your typical spiral galaxies on one prong and barred spirals on the other. Edwin then arranged the spirals sub-categories (SBa, SBb, SBc etc) based on how open the arms of the spirals are.

You may notice that there are no irregular galaxies in the sequence. As discussed previously, the reason they’re called irregular in the first place is that they can’t fit into the sequence cleanly due to their chaotic appearances and behavior that don’t fully encompass neither spiral nor elliptical galaxies, so they’re left out of the sequence entirely.

“What about lenticular galaxies, where do they fit?” you may ask. Right in the middle, just before the fork splits. S0 (and some would lump in certain E7 galaxies) is where lenticular galaxies lie in the sequence.

Lenticular galaxies are disk like with a central bulge but no spiral arms, and don’t produce very many new stars, if any at all. From a certain angle, they look like a lens, hence their name. This disk like shape is also what discerns them from elliptical galaxies, which have no disk structure at all.

Example:

This is NGC 5866, a lenticular galaxy in the constellation Draco. Note the clear flat disk of dust in the center, and the structure of the disk. Remember, an elliptical galaxy would have no such structure, and appear more vaguely oval shaped with not as much dust.

Example:

This is NGC 1132, an elliptical galaxy in the constellation Eridanus. Note the ellipsoidal shape, the lack of disk-like structure, and how it appears to have almost no dust at all, which means this galaxy most likely doesn’t produce stars at all anymore. A lenticular galaxy, while nowhere near as proficient at star production as a sprial galaxy, has at least some potential to produce stars, while ellipticals have significantly less.

There is one other type of galaxy that I haven’t talked about yet. Seyferts.

A Seyfert galaxy, named for American astronomer Carl K. Seyfert, is one of the two most active ‘galaxies’ in the universe, the other being quasars (which I will have to make a separate post about, as they’re not really galaxies, they’re sort of their own thing called an Active Galactic Nucleus ((AGN, which Seyferts have too)) but don’t fit into the Hubble sequence at all). They’re separated into two main types, Type I and Type II, with much smaller groups consisting of Type 1.2, 1.5, 1.8, and 1.9, but I’ll only be going into the two main types.

Nearly all Seyfert galaxies are spiral or barred spiral galaxies with extremely bright sources of ultraviolet light and x-rays, in addition to the light coming from their tiny cores. This light can and does frequently fluctuate in brightness. Most are powerful sources of infrared radiation. In addition, some emit intensely in the radio, X ray, and gamma ray regimes. The radiation excites gas around the central regions, giving rise to the observed emission lines (which are specific patterns of wavelengths that are generated when atoms of hydrogen, oxygen, or nitrogen are bombarded by high-energy radiation). They’re classified according to the relative widths of the emission lines in their spectra. 

Type I Seyferts have broad emission lines of hydrogen, but narrow forbidden lines of heavier elements.

Example:

This is NGC 5548, a Seyfert spiral in the Boötes constellation.You can see the arms that have more hydrogen in them have much thicker widths, and the ones that contain less hydrogen are much thinner and dimmer. Also note the extremely bright core. Its light is the result of matter falling into the accretion disk of a supermassive black hole over 65 million solar masses in size.

Conversely, in type II Seyferts, the hydrogen lines and forbidden lines are, relatively, the same width, typically broader than the forbidden lines in type I, but not as broad as the hydrogen lines.

Example:

This is NGC 1068, a Seyfert spiral in the constellation Cetus. Note how more or less uniform the emission lines’ widths are. This galaxy’s core is also extremely bright, but less so than the type I example due to having a much smaller supermassive black hole at its center, perhaps only 15 million solar masses in size.

And, once again, I’m (unfortunately) not an astrophysicist, I’m simply a person who really, really loves space and wants to share my knowledge of the universe with everyone else. There’s plenty of actual scholarly papers you can find that explain galaxy types much more in depth and intelligently than I did, but I still hope that this little science lesson was interesting to some of you.

Galaxy classification says trans rights

Starlit “Fossils” And The Mysteries Of Massive Galactic Evolution

Starlit “Fossils” And The Mysteries Of Massive Galactic Evolution

  Starlit “Fossils” And The Mysteries Of Massive Galactic Evolution By Judith E Braffman-Miller

Massive, starlit galaxies are thought to have attained their majestic sizes as the result of collisions and mergers between small, amorphous protogalaxiesinhabiting the ancient Universe. The earliest galaxies created a multitude of…

Using Neural Networks to Classify Galaxies 

Title: Rotation-invariant convolutional neural networks for galaxy morphology prediction

Author: Sander Dieleman, Kyle W. Willett, Joni Dambre

No two galaxies are exactly the same. They come in many different shapes, sizes, and colors. Studying these structural properties of galaxies provides a way to group similar looking galaxies together. Their morphology, the properties that describe what a galaxy looks like, is used to study their formation and evolution.

Traditionally, the classification of galaxies has been performed by someone visually inspecting each image. Now, with new large sky surveys producing extremely large amounts of images in one night, using the traditional galaxy classification inspection techniques will be time consuming and not very efficient.

To address this growing problem, the need for an automated classification approach that can handle large amounts of data is increasing. One solution lies in the field of machine learning. Training computers to see and analyze images would allow for more images to be classified in a timely manner. To do this, the Galaxy Zoo crowdsourcing project teamed up with Kaggle, an online predictive modeling platform, to create The Galaxy Challenge, a competition to build the best galaxy classification model.

Sander Dieleman, a PhD student at Ghent University in Belgium and first author of the paper, finished in first place with his model. He presents a convolutional neural network that classifies images of galaxies based on their morphology. A convolutional neural network (CNN) is a machine learning algorithm based on biological neural networks, such as the central nervous system. It uses artificial neurons to create connections to other artificial neurons based on the information it learns from the data.

The images provided by the competition hosts were separated into two groups: a training set and an evaluation set. The training set consisted of over 61,000 color images of galaxies that were annotated with morphological data. The evaluation set consisted of almost 80,000 images, but unlike the training set, had no morphological data associated with it. As their names suggest, the training set is used to train the model and the evaluation set is used to evaluate the model’s learning capabilities.

The goal of the model was to determine the probability that a galaxy belongs to a particular class. There were 37 possible classes, each one representing a possible answer that corresponds to the questions asked of Galaxy Zoo participants. The list of questions presented to Galaxy Zoo participants creates a decision tree, a tree-like graph that shows all possible decisions and outcomes, and is supposed to represent all classes described in the Hubble tuning fork classification scheme.

To increase the performance of the model, Dieleman used rotational symmetry, allowing the rules of the model to be applied multiple times to various versions of the images.

At the end of the competition, Dieleman’s model placed first out of 326 participants with near-perfect accuracy. Analyzing the results showed that there was agreement between the Galaxy Zoo participants’ answers and the model’s output. Due to the training, the model had difficulty identifying images with morphology features that appeared infrequently. An interesting outcome pertains to images that feature black lines running across them. The black lines are caused by dead pixels in the camera, which the model doesn’t know. As a result, it tries to classify those images as disturbed galaxies. The galaxies that were easiest to classify were elliptical galaxies.

(The Atlas3D team suggests this "comb" diagram as an alternative to Hubble's tuning fork diagram to classify galaxies. Early-type galaxies arranged on the handle, are classified according to their net rotation. The spirals are placed along three teeth. The fast-rotators at the junction of the teeth and comb likely evolved from that family of spirals.  Credit: Atlas3D / Michele Cappellari)

"In 1926, astronomer Edwin Hubble gave us our first basic galaxy classification scenario – the Hubble Sequence. Using photographic plates, Hubble derived a simplistic system based on three visually known structures: elipitical, spiral and lenticular. This sequence, when plotted out, gave the appearance of a common object and eventually became known as the “Hubble Tuning Fork” (as seen above). For many decades, this served as a standard. Now the ATLAS3D Project is calling a different tune…"

A major revision to the standard Hubble Sequence of galaxies has been proposed based on "kinematic" evidence, or the result of the internal motions of stars within galaxies rather than "morphological" evidence like that used by Hubble in constructing his original sequence, often called the "Tunking Fork Diagram":

(Credit: NASA)