Three galaxies observed by the SDSS MaNGA survey
The top row shows the galaxies’ images, while the bottom row shows the velocity of the stars within the galaxies; red means the stars are moving away from us and blue means towards us.
The panel on the left shows an isolated spiral galaxy, not undergoing a merger. The middle panels show a spectacular pair of merging galaxies, obvious in both the image and the velocity map. The right panels show what appears in the image to be a single galaxy – but the velocity map reveals that it is actually a galaxy that has just merged. This is evident in the disturbed (counter-rotating) features in the velocity map. This example demonstrates the power of the team’s new method, which will identify merging galaxies using both imaging and kinematics.
Image credit: Rebecca Nevin (University of Colorado Boulder) and the SDSS collaboration. Hi-res image
Don’t judge a book by its cover, and don’t judge a galaxy by its image alone.
Today, at the 233rd AAS meeting in Seattle, astronomers from the Sloan Digital Sky Survey (SDSS) announce that they have developed a new tool to find otherwise-hidden galaxy mergers in data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey of SDSS. These results show that by going beyond simple searches for merging galaxies based just on how they look, astronomers will now be able find more galaxy mergers than ever before.
“Merging galaxies are key to understanding galaxy evolution, but finding them can be tricky,” says Rebecca Nevin of the University of Colorado, the lead author of the study. Nevin is presenting this work this week as a Dissertation talk, as it formed the basis of her PhD thesis at Colorado with Professor Julie Comerford.
A pair of merging galaxies is one of the most beautiful sights in
astronomy, with giant tidal streams of stars and unusual shapes
sometimes resembling animals (e.g. the Antennae, Mice, Tadpole, or
Penguin galaxies). However, these beautiful visible features are visible
are only found in a small fraction of merging galaxies – and even then
only for a small part of the billions of years it takes for two galaxies
to fully merge into one. Some galaxies that otherwise look “normal” may
still be in the process of merging.
Astronomers have developed a way to find these hidden mergers. They
created a method that uses simulations of merging galaxies to predict
both how the mergers would look and how the stars in the galaxies would
move. By comparing their results with observations of galaxies from the
SDSS’s Mapping Nearby Galaxies at Apache Point Observatory (MaNGA)
survey, astronomers will be able to do much better at identifying
merging galaxies in the wild.
“These simulations allow us to predict the more subtle signs of
merging galaxies, so we can find mergers in SDSS data that were
previously hidden,” explains Laura Blecha (University of Florida),
another key member of the team.
What the team is presenting today is the part of their method that analyzes galaxy images. They have essentially made a galactic photo album, including pictures of galaxies in all stages of merging. In the past, astronomers’ “photo albums” of galaxy mergers were sparse, including only galaxies in the stage of merging where they looked like spectacular mergers.
“Nowadays, it would be totally unthinkable to take only one or two
selfies every year,” said Nevin. “We have modernized the galaxy merger
photo album – now it’s like taking one galaxy merger selfie a day for
years.”
The astronomers plan to make these extensive photo albums publicly
available to everyone. Astronomers will use them to study how galaxies
change as they undergo mergers.
The team’s work so far is already a giant step forward in merger
identification, but they are already taking the next step. They have
already begun to incorporate data on how the stars move in the galaxies
from the SDSS MaNGA survey. This will allow the team to identify even
more mergers – those where the galaxy looks completely “normal.”
The key to this new analysis is to incorporate data from MaNGA on how
stars within galaxies are moving. “By going beyond images alone and
incorporating stellar kinematics, we will find many more merging
galaxies,” says Karen Masters of Haverford College, the Spokesperson for
SDSS. “We’ll be able to learn how the merger process impacts how
galaxies in our Universe evolve.”
These stellar kinematics are revealed in the maps created by the
SDSS’s MaNGA survey. Because the spectra that MaNGA observes come from
the light of all the stars in a particular part of a galaxy, stars, the
spectra are slightly shifted by the Doppler Effect – blueshifted for the
parts of a galaxy that are moving toward Earth and redshifted for the
parts moving away from Earth. These subtle shifts reveal how the stars
are moving around the galaxy.
When galaxies merge, the stars in them almost never collide, but they
are thrown all around, creating dramatic distortions in the pattern of
how stars move around the galaxy – patterns that astronomers refer to as
“stellar kinematics.” In a typical, non-merging spiral galaxy, the
stars rotate in a simple, predictable pattern. But if such a galaxy is
undergoing a merger, that simple pattern becomes chaotic, creating wild
(but predictable) arrangements of stellar motion. When a galaxy’s
patterns of stellar motion have become distorted by a merger, the
stellar kinematics data from MaNGA provides direct evidence of the
merger. Nevin’s team, which includes astronomers from the University of
Colorado Boulder, the University of Florida, and Princeton University,
is beginning to add stellar kinematics data into their work.
This animation shows one of the galaxy merger simulations the team
created. The first 38 seconds shows the simulation running, covering 2.5
billion years of history. From each step of the simulation, the team
figures out what the galaxy would look like when viewed from Earth by
the Sloan Digital Sky Survey (shown from 0:39 to 1:06). The last part of
the video (1:06-1:30) shows a collection of simulated images and how
they are used to create a classification method that can then be applied
to real SDSS images. Image credit: Rebecca Nevin (University of Colorado), Laura Blecha (University of Florida), and the SDSS collaboration.
“As we improve our machine learning algorithms to incorporate the
stellar kinematics of merging galaxies, we are able to identify
different stages of the merger. The disturbances in the stars can last
longer than imaging signatures of a merger like faint tidal tails, which
fade much quicker. This means we can identify later stages in the
merger, when in the imaging the galaxies look just like normal galaxies.
This is a powerful new technique in the study of merging galaxies.”
Understanding mergers is not only important to astronomers like
Nevin’s team; this understanding can help us predict the future of our
own Galaxy. The Milky Way will merge with the Large and Small Magellanic
Clouds in about 2.5 billion years – and is then predicted to merge with
the much more massive Andromeda galaxy in five billion years, combining
to form a single super-galaxy, which some dub “Milkdromeda.” This event
might throw the Sun out of the galaxy, but it won’t matter to future
inhabitants of Earth, which will have been swallowed by the Sun as it
turns into a red giant star at around the same time. But maybe our
descendants will see this for themselves as they travel among the stars.
