Search results for merger

Spheroidal Post Merger Systems at the AAS

I think Chris said it best – any session which is ended by a guy in a bowtie went well. And for our AAS Galaxy Zoo session, that guy in a bowtie was Alfredo Carpineti from UCL, who talked about his work on the properties of spheroidal post-merger systems selected with the help of the Galaxy Zoo merger classifications, and using a control sample of non-merging spheroidals (or ellipticals) also selected from Galaxy Zoo.

Alfredo provided me with the below description, and his slides are available to download at Carpineti_AAS218talk.pdf.

In this talk we discuss the properties subset of galaxies from the GZ mergers catalogue that are spheroidal ‘post-mergers’, where a single remnant is in the final stages of relaxation after the collision and shows evidence for a dominant bulge, making them plausible progenitors of early-type galaxies.

Chandra X-ray Survey of Mergers Completed

Our Chandra programme to survey a sample of local merging galaxies found by you all to search for double black holes has just been completed. We’ve received the data for the final target. Now the data analysis can begin!

Mergers Author Poster

MergersPoster_900

The final in our series of Zooniverse project posters, created from the names of contributors, is Galaxy Zoo Mergers. The posters features an image of the Antennae Galaxies made up of the names of the 13,000 mergers participants who agreed to have their names published.

You can download the large, 5000-pixel version (15 MB) or the smaller 3,000-pixel version (6 MB).

Galaxy Zoo Multi Mergers

Our latest merger paper is called “Galaxy Zoo: Multi-Mergers and the Millennium Simulation.” We used the original catalogue of 3003 mergers from the previous mergers study to find the interesting subset of systems with three or more galaxies merging in a near-simultaneous manner. We found 39 such multi-mergers (which you can see in the image below) and from this we estimated the relative abundance of such multi-mergers as being ~2% the number of binary mergers (which were themselves ~3% the number of isolated ‘normal’ galaxies). We also examined the properties of these galaxies (colour, stellar mass and environment) and compared them to the properties of galaxies in isolated and binary-merger galaxies; we found that galaxies in multi-mergers tend to be more like elliptical galaxies on average: they’re large, red and in denser environments.

39 Multi-Mergers

Describing what we see in the world is all well and good, but the equally important thing in science is to compare what we see with what others have claimed to see or to have predicted through theory. Since ours is effectively the first such catalogue of multi mergers, there simply are no other observational sets to compare to. We therefore compared these merger fractions and galaxy properties to a large and well-known simulation called the Millennium Run. This is a cosmic scale simulation of Dark Matter that starts off smoothly distributed (similar to the CMB) within a 500 Mpc box and, over time, clumps together to form structures. Now, galaxies are of course made out of normal matter, so to model how galaxies form and evolve within the Dark Matter, one can take the resulting clumps of Dark Matter from the simulation and, using sensible sounding rules (e.g. bigger Dark Matter clumps get more normal matter because they’ll gravitationally attract more), come up with predictions for numbers of stars formed within the simulation (and where, when, etc.). This means that one can create (with enough fiddling) predictions of what galaxies will look like in such a Dark Matter dominated Universe. These are called ‘Semi-Analytic Models’ and are an important strategy for simulating the Universe since computers would struggle to compute the many many additional interactions between particles in a full N-Body simulation with both Dark Matter and normal matter (Dark Matter is relatively easy since it only feels the 1/r^2 force of gravity).

So what we did in the paper was to compare the results of our multi-merger galaxies to those of the Semi-Analytic Models in the Millennium Simulation (double ‘n’ because it’s a largely German initiative). This is a good test of the Semi Analytic Models because there is no way they could have been fiddled to get the right answer because ours is the first such observational constraint on what multi-mergers look like. And what we found is that the Simulation did rather well – it predicted the relative abundance of multi-mergers to within a few percent and it predicted that galaxies in these systems should have properties more like a typical elliptical rather than a typical spiral. This gives us independent confidence that these Simulations are on the right track and that the assumptions that went into them are sensible ways to get at how the Universe behaves.

In the future, the Galaxy Zoo interface might well allow users to indicate the presence of multi-mergers!

Many thanks to you all for your help in making this interesting study happen.

First X-ray Data of the Mergers with Chandra

I just got notice from the people at the Chandra Science Center that Chandra has executed the observation of the first Galaxy Zoo merger – part of our study to understand black holes in mergers. This is the first of twelve such observations that should take place over the next year or so. The main science question we have that this program will help us answer is: in how many mergers do both black holes feed?

All I have at the moment are the quick-look data that that they sent me. They are more or less raw images. Here is the full frame:

obs12812_0-984022

And here is a zoom-in:

obs12812_0_center-207369

This is raw data, rather than properly analyzed data, so we can’t really draw any firm conclusions based on it yet, but it seems like there is no significant source detected. What does that mean? Assuming that there really is no source after we properly analyze the data, then the black hole(s) in this particular merger are either not feeding very much, or they are hidden behind lots of gas and dust.

For now, we will wait for the actual data to fully analyze it, and for the remaining 11 targets to be observed.

Chandra Program to study Galaxy Zoo Mergers approved

Good news, everyone!

Earlier this year we submitted a proposal to use the Chandra X-ray Observatory to observe a set of merging galaxies in X-rays. The target list for Cycle 12 has just been released, and with a bit of scanning, you can find a set of targets with names like “GZ_Merger_AGN_1”. These targets are a set of beautiful merging galaxies discovered by YOU as part of Galaxy Zoo 1 and the Merger Hunt. The 12 approved targets are here:

GZ_merger_targets

These 12 mergers are all very pretty, but they have something else in common: they all host active galactic nuclei (AGN) – feeding supermassive black holes at their centers. X-rays are great for finding such hungry black holes, but we already know that all 12 of these mergers are AGN, so why observe them again? We’re looking for a mythical rare beast: the binary AGN!

Only a handful of these objects are known and they were discovered by chance. We believe that every massive galaxy has a supermassive black hole at its center and so when two galaxies merge, then there should be two black holes around for a while, that is, until they merge. The goal of our Chandra study of these 12 mergers is to systematically search for binary AGN in merging galaxies to work out what fraction of them feature two feeding black holes. Knowing whether such phases are common or not is important for understanding how black holes interact with galaxies in mergers and what exactly happens to them as they plunge towards the center of the new galaxies where they are doomed to merge and form a single supermassive black hole.

As usual, it may be quite a while before we get the data. The observing cycle won’t start for a while and takes about a year. Since our observations are short and we don’t have any time constraints (they’re galaxies, they don’t move!) the Chandra operators will most likely schedule our observations in between longer projects and time sensitive observations and so we won’t know when they will happen. Of course, once we do get the data, we’ll definitely update you.

Oh and you might notice some of the targets in the Merger Zoo in the near future. We’ll need your help to fully understand them….

Galaxy Zoo: Mergers – A personal perspective

Now that the launch of Galaxy Zoo: Understanding Cosmic Mergers has been completed, I wanted to give a personal perspective on this project.

For me, this project started twenty years ago  when I was in graduate school.    In my dissertation work, I  modeling the tidal features of interacting galaxies.  I wrote a Fortran code for doing some of this modeling work.   You would set up a run, and then wait hours to see the result.   If it didn’t match, you had to wait hours for the next attempt.

a82

The worst part about the modeling process was getting the “final” result.   Even if you got a close match, you never knew if you had actually found the best match.  It was always possible that a completely different set of parameters was the real solution, and you had just made a mistake.    Even with good fits, you couldn’t tell if you really had arrived at the ‘right’ solution.

Our understanding of galaxy collisions has been limited by the lack of dynamical models.  For example, we know that some galaxy collisions have very high star formation rates.   We also know that almost all extreme star burst galaxies (Ultra-luminous infrared galaxies) have undergone some type of collision.   Why isn’t this sort of reaction the inevitable result of a merger?   It seemed like the answer was always out of reach – unless we can understand the dynamics of lots of collisions.

The java applet developed for Mergers by Anthony Holincheck is the direct descendent of the old Fortran code.  Now you can run the same kind of simulations I ran for my dissertation in fractions of a second.    When Anthony and I first resurrected this code, we immediately tried using a Genetic Algorithm help us converge on the final solution.   It didn’t work.   We couldn’t reliably teach the computers how to recognize a good match.   We could run a few hundred thousand simulations per day, but we never knew if we got the right results.

The idea of using volunteers to help us happened a few years ago.   It was crazy and impractical to imagine volunteers helping out with a project like this.   Even so, a group of us proposed to do.  Of course, our proposal got shot down.  After all, there was no way that this type of thing would work.  How would you recruit such volunteers?

About a year later, I started talking with some of the team from Galaxy Zoo.    You – the volunteers of Galaxy Zoo-  have made the impossible possible.   With your help, we can create the models we need to understand the histories of hundreds of galaxy collisions.   These models will be more reliable than any a single scientist could create.    This result alone would incredibly important.   However, by carefully analyzing your inputs, we eventually hope to train the computers to do thousands of more models.   This kind of man/machine partnership is being planned for a number of future data projects, where computers need help learning how to be scientists.     We will never discover future Voorwerpen or new Peas without your help.   However, in return, we will also never make you do busy work that a machine can do.

Your efforts on the Zoo projects have created a new the way to do science.     This is nothing less than a transformation in how we look at data, analysis, and computing.

Of course, that’s just a personal perspective.

I just posted a new target for you to try.  We are going to be doing updates at 1600 GMT everyday. even Thanksgiving.  Of course, we will keep the old targets live for a week so you can go and revisit them.   This one is a repeat from some of the beta tests.   Getting a perfect model is hard, but getting close is easy.  We didn’t want to make things too difficult – at least for now.   Be assured, we will be kicking up a notch over the next days and weeks.

-John

Mergers Update

We have just changed the target on the Galaxy Zoo Mergers page (http://mergers.galaxyzoo.org).  The new system has a broken ring and a nearby companion.  It’s a very pretty system, and it seems to be a bit easier to model than the first one we posted.  For all the systems we are putting up as challenges, we do a quick run ourselves to see if we can find any solutions that might be on-track.   Although we found a few solutions right away, we don’t know if they are the best ones or if they are unique.  Of course, that’s why we need your help.

We are going to be updating the target daily.  Every day, we should will have a new cosmic collision for you to help us model.

If you can spend 10 minutes to quickly weed out the obvious bad ones on 20-30 screens, it would be a great help to us!   The more clicks we have, the better we constrain the collision.   Make sure you hit save when you are done looking at the images!  Although we automatically back up some clicks, we don’t want to lose any of your data.

Thanks for all you do.

– John Wallin, Computational Scientist/Astronomer

Galaxy Zoo: Understanding Cosmic Mergers

Starting at midnight 11/24, our new site ‘Galaxy Zoo: Understanding Cosmic Mergers’ went on-line as a new project in Galaxy Zoo. In Mergers, we are working to understand the cosmic collisions that lead to galaxy mergers. Every day we will have a new target galaxy that we need your help to model. Based on the basic input parameters that we provide, a Java applet running in your browser will simulate some possible collision scenarios. Computers don’t do a good job comparing simulations and real astronomical images, so we need your help to find out which simulations are the most similar to the real galaxy collision.

Working on Mergers will require some patience. Some of the collisions we are trying to model are rarer than others, so don’t get discouraged. In some cases, you will need to look at a few hundred images to get your first close match. Just remember, you aren’t looking for perfection. Just try to find a simulation that has some of the unusual and unique tidal features of the target galaxy. When you found something close, you might want to go further and “enhance” the image to make even a better match. The more data we have on these galactic collisions, the more we can narrow down the input parameters that caused these systems to form. You can be the most helpful by looking at a lot of images and then select the best of the best through the evaluate mode of the applet. This will happen automatically when you have selected eight possible merger images.

My graduate student Anthony Holincheck and I have been working on this project for a long time, and are very excited to see it see it launch today. We want to thank all the Zooites that participated in our beta test. Zooites rock! Of course, thanks also go out to Arfon, Chris, Lucy, Nancy, Geza, and Mark in their work in the development. Without all of your help, this project would not be possible. Our team will be adding more features in the coming weeks and months, so please stay tuned.

As I write this blog, we are T-5 hours before the full launch of our site. I cannot help but be humbled by the incredible dedication of the Zooites. With your help, we are going to model the dynamics of hundreds of galaxy collisions. This effort will help us connect the dynamics of galaxy collision to the star formation rates in galaxies. Thank you for your on-going support Galaxy Zoo!

– John Wallin – Computational Scientist/Astronomer

Merger Papers Accepted for Publication in MNRAS

Thanks for everyone’s work – both papers should soon be appearing in the Monthly Notices of the Royal Astronomical Society 🙂

merger_papers