Wish You Were All Here…
Today’s post is from Ivy Wong, Science Team member and PI of an upcoming new project. She also did an amazing job organizing our Galaxy Zoo conference in Australia. Read on for details!
It has been 2 weeks since the “Evolutionary Paths in Galaxy Morphology” meeting in Sydney and I am still recovering from the post-conference brain-melt, also described in Brooke’s blog post. Perhaps I am getting old.
The 4 days of cutting-edge science presentations and discussions went by all too quickly. And we are now left with new ideas for new projects and renewed motivation for finishing up current ones. It is also becoming clear that the term morphology is slowly evolving from a once vague division between early- and late-type galaxies (i.e. spheroids or spirals; as inferred from observations using optical telescopes) to include more specific descriptions of a galaxy’s form which includes the 3-dimensional dynamics and kinematics. Also, how a galaxy looks at a different wavelength will depend on factors such as how hot its interstellar medium is, how much gas it has, what state that gas is, how active is the galaxy’s central supermassive black hole and whether it is experiencing any harassment by its neighbours and local environment.
As our understanding of galaxy morphology evolves, so too will the Galaxy Zoo project. As you may have heard, the next generation Galaxy Zoo project will show us morphologies that will be completely alien to most of us, even those who enjoy a regular dose of science fiction. The new Radio Galaxy Zoo project will show us images observed in the radio wavelengths, typically coming from synchrotron radiation. Synchrotron emission results from accelerated charged particles moving at relativistic velocities and is usually seen as outflows/jets from a galaxy’s central supermassive black holes.
Though this already happened during the conference dinner, I’d like to take this opportunity to make a repeat of the toast (albeit virtually) to the >800,000 citizen scientists who has helped us thus far. It would have been lovely to have you all join us at the meeting, but we would have probably sunk our dinner boat. So if you’re interested in checking out some of the presentations from this meeting, please go to:
gzconf.galaxyzoo.org
The official conference program booklet will help put these presentations into context and can be found at:
atnf.csiro.au/research/conf…es/gzconf_booklet.pdf
Am definitely looking forward to the next big Galaxy Zoo conference. Perhaps somewhere up North next time?
A Galaxy Zoo conference is not complete without after hours drinks by the harbour. From left to right: Brooke, Karen, Jeyhan, Julie & Ivy in pic 1. Amit, Kyle, Bill, Chris L. & Chris S. in pic 2. (Photo credit: Amanda Bauer aka @astropixie)
Galaxy Zoo Continues to Evolve
Over the years the public has seen more than a million galaxies via Galaxy Zoo, and nearly all of them had something in common: we tried to get as close as possible to showing you what the galaxy would actually look like with the naked eye if you were able to see them with the resolving power of some of the world’s most advanced telescopes. Starting today, we’re branching out from that with the addition of over 70,000 new galaxy images (of some our old favorites) at wavelengths the human eye wouldn’t be able to see.
Just to be clear, we haven’t always shown images taken at optical wavelengths. Galaxies from the CANDELS survey, for example, are imaged at near-infrared* wavelengths. But they are also some of the most distant galaxies we’ve ever seen, and because of the expansion of the universe, most of the light that the Hubble Space Telescope (HST) captured for those galaxies had been “stretched” from its original optical wavelength (note: we call the originally emitted wavelength the rest-frame wavelength).
Optical light provides a huge amount of information about a galaxy (or a voorwerpje, etc.), and we are still a long way from having extracted every bit of information from optical images of galaxies. However, the optical is only a small part of the electromagnetic spectrum, and the other wavelengths give different and often complementary information about the physical processes taking place in galaxies. For example, more energetic light in the ultraviolet tells us about higher-energy phenomena, like emission directly from the accretion disk around a supermassive black hole, or light from very massive, very young stars. As a stellar population ages and the massive stars die, the older, redder stars left behind emit more light in the near-infrared – so by observing in the near-IR, we get to see where the old stars are.
The near-IR has another very useful property: the longer wavelengths can mostly pass right by interstellar dust without being absorbed or scattered. So images of galaxies in the rest-frame infrared can see through all but the thickest dust shrouds, and we can get a more complete picture about stars and dust in galaxies by looking at them in the near-IR.
Even though the optical SDSS image (left) is deeper than the near-IR UKIDSS image (right), you can still see that the UKIDSS image is less affected by the dust lanes seen at left.
Starting today, we are adding images of galaxies taken with the United Kingdom Infrared Telescope (UKIRT) for the recently-completed UKIDSS project. UKIDSS is the largest, deepest survey of the sky at near-infrared wavelengths, and the typical seeing is close to (often better than) the typical seeing of the SDSS. Every UKIDSS galaxy that we’re showing is also in SDSS, which means that volunteers at Galaxy Zoo will be providing classifications for the same galaxies in both optical and infrared wavelengths, in a uniform way. This is incredibly valuable: each of those wavelength ranges are separately rich with information, and by combining them we can learn even more about how the stars in each galaxy have evolved and are evolving, and how the material from which new stars might form (as traced by the dust) is distributed in the galaxy.
1 galaxy, 4 redshifts.
In addition to the more than 70,000 UKIDSS near-infrared images we have added to the active classification pool, we are also adding nearly 7,000 images that have a different purpose: to help us understand how a galaxy’s classification evolves as the galaxy gets farther and farther away from the telescope. To that end, team member Edmond Cheung has taken SDSS images of nearby galaxies that volunteers have already classified, “placed” them at much higher redshifts, then “observed” them as we would have seen them with HST in the rest-frame optical. By classifying these redshifted galaxies**, we hope to answer the question of how the classifications of distant galaxies might be subtly different due to image depth and distance effects. It’s a small number of galaxies compared to the full sample of those in either Galaxy Zoo: Hubble or CANDELS, but it’s an absolutely crucial part of making the most of all of your classifications.
As always, Galaxy Zoo continues to evolve as we use your classifications to answer fundamental questions of galaxy evolution and those answers lead to new and interesting questions. We really hope you enjoy these new images, and we expect that there will soon be some interesting new discussions on Talk (where there will, as usual, be more information available about each galaxy), and very possibly new discoveries to be made.
Thanks for classifying!
* “Infrared” is a really large wavelength range, much larger than optical, so scientists modify the term to describe what part of it they’re referring to. Near-infrared means the wavelengths are only a bit too long (red) to be seen by the human eye; there’s also mid-infrared and far-infrared, which are progressively longer-wavelength. For context, far-infrared wavelengths can be more than a hundred times longer than near-infrared wavelengths, and they’re closer in energy to microwaves and radio waves than optical light. Each of the different parts of the infrared gives us information on different types of physics.
** You might notice that these galaxies have a slightly different question tree than the rest of the galaxies: that’s because, where these galaxies have been redshifted into the range where they would have been observed in the Galaxy Zoo: Hubble sample, we’re asking the same questions we asked for that sample, so there are some slight differences.
Top Image Credits and more information: here.
Congratulations Edmond: another Galaxy Zoo paper accepted
A quick post to say congratulations to new Galaxy Zoo science team member Edmond Cheung, a PhD student from UC Santa Cruz, on the publication of his first Galaxy Zoo paper. Edmond approached us some time ago and was interested in doing further study on the barred galaxies in both Galaxy Zoo 2 and GZ: Hubble. This paper is the result of the excellent work he’s done looking at more detail on the properties of bars in the Galaxy Zoo 2 classifications.
The paper has recently been accepted to the Astrophysical Journal, and will appear on the arxiv very shortly.
The main result is a stronger proof than has ever before been seen that secular (that is, very slow) evolution affects the properties of barred galaxies, which grow larger bulges and slow down in their star formation the longer the bars grow (or the older the bars are).
Edit: This paper is now available on the arXiv at http://arxiv.org/abs/1310.2941
Astronomy & Geophysics Article on Arxiv
Just a quick note to say that the Astronomy & Geophysics article some of us wrote to review the Specialist Discussion we ran at the Royal Astronomical Society in May is now posted on the arxiv. A&G is the magazine of the RAS (so I get a copy, like all RAS members), but also makes some articles free to read for all (Free editors choice articles) – and in this case the entire magazine was made open access.
You might remember this article and the offer of a cover spot for a Galaxy Zoo related image sparked a vote for your favourite image, which was won by “The Penguin Galaxy”.
Here’s the lovely cover art to finish off the post.
Evolutionary Paths In Galaxy Morphology: A Galaxy Zoo Conference
This week much of the team has been in Sydney, Australia, for the Evolutionary Paths In Galaxy Morphology conference. It’s a meeting centered largely around Galaxy Zoo, but it’s more generally about galaxy evolution, and how Galaxy Zoo fits into our overall (ever unfolding) picture of galaxy evolution.
There’s a lot to that legacy already, and it’s still being written.
The first talk of the conference was a public talk by Chris, fitting for a project that would not have been possible without public participation. Chris also gave a science talk later in the conference, summarizing many of the different results from Galaxy Zoo (and with a focus on presenting the results of team members who couldn’t be at the meeting). For me, Karen’s talk describing secular galaxy evolution and detailing the various recent results that have led us to believe “slow” evolution is very important was a highlight of Tuesday, and the audience questions seemed to express a wish that she could have gone on for longer to tie even more of it together. When the scientists at a conference want you to keep going after your 30 minutes are up, you know you’ve given a good talk.
In fact, all of the talks from team members were very well received, and over the course of the week so far we’ve seen how our results compare to and complement those of others, some using Galaxy Zoo data, some not. We’ve had a number of interesting talks describing the sometimes surprising ways the motions of stars and gas in galaxies compare with the visual morphologies. Where (and how bright) the stars and dust are in a galaxy doesn’t always give clues to the shape of the stars’ orbits, nor the extent and configuration of the gas that often makes up a large fraction of a galaxy’s mass.
Karen explains her simple and clear diagram showing different galaxy evolutionary processes.
This goes the other way, too: knowing the velocities of stars and gas in a galaxy doesn’t necessarily tell you what kinds of stars they are, how they got there, or what they’re doing right now. I suspect a combination of this kinematic information with the image information (at visual and other wavelengths) will in the future be a more often used and more powerful diagnostic tool for galaxies than either alone.
Overall, the meeting was definitely a success, and throughout the meeting we tried to keep a record of things so that others could keep up with the conference even if they weren’t able to attend. There was a lot of active tweeting about the conference, for example, and Karen and I took turns recording the tweets so that we’d have a record of each day of the Twitter discussion. Here those are, courtesy of Storify:
Also, remember at our last hangout when we said we’d have a hangout from Sydney? That proved a bit difficult, not just because of the packed meeting schedule but also because of bandwidth issues: overburdened conference and hotel wifi connections just aren’t really up to the task of streaming a hangout. We eventually found a place, but then it turned out there was construction going on next door, so instead of the sunny patio we had intended to run the hangout from we ended up in an upstairs bedroom to get as far away from the noise as possible. Ah, well. You can see our detailed discussion of how the meeting went below, including random contributions from the jackhammer next door (but only for the first few minutes):
(click here for the podcast version)
And now we’ll all return (eventually) to our respective institutions to reflect on the meeting, start work on whatever new ideas the conference discussions, talks and posters started brewing, and continue the work we had set aside for the past week. None of this is really as easy as it sounds; the best meetings are often the most exhausting, so it takes some time to recover. I asked our fearless leader Chris if he had a pithy statement to sum up his feeling of exhilarated post-meeting fatigue, and he took my keyboard and offered the following:
gt ;////cry;gvlbhul,kubmc ;dptfvglyknjuy,pt vgybhjnomk
I’m sure that, if any tears were shed, they were tears of joy. This is a great project and it’s only getting better.
Left to Right: Tom, Kevin, Bob, Amit, Ed, Chris S, Bill, Kyle, Chris L, Ivy, Brooke, Karen, Julie
We got (some) observing time!
Great news everybody!
We applied for radio observations with the e-MERLIN network of radio telescopes in the UK. The e-MERLIN network can link up radio dishes across the UK to form a really, really large radio telescope using the interferometry technique. Linking all these radio dishes means you get the resolution equivalent to a country-sized telescope. You don’t alas get the sensitivity, as the collecting area is still just that of the sum of the dishes you are using.
The e-MERLIN network (from http://www.e-merlin.ac.uk) of radio telescopes.
Our proposal was to observe the Voorwerpjes. We wanted to take a really high resolution look at what the black holes are doing right now by looking for nuclear radio jets. The Voorwerpjes, like their larger cousin, Hanny’s Voorwerp, tell us that black holes can go from a feeding frenzy to a starvation diet in a short time scale (for a galaxy, that is). We really want to see what happens to the central engine of the black hole as that happens. There’s a suspicion that as the black hole stops gobbling matter as fast as it can, it starts “switching state” and launches a radio jet that starts putting a lot of kinetic energy (think hitting the galaxy with a hammer).
So, we want to look for such radio jets in the Voorwerpjes. We asked for a LOT of time, and the e-MERLIN time allocation committee approved our request…
… partially. Rather than giving us the entire time, they gave us time for just one source to prove that we can do the observations, and that they are as interesting as we claimed. So, we’re trying to decide which target to pick (argh! so hard).
Quench Boost: A How-To-Guide, Part 4
Now that we’ve been initiated into the cool waters of Tools (Part 1), we’ve compared our *own* galaxies to the rest of the post-quenched sample (Part 2), and we’ve put your classifications to use, looking for what makes post-quench galaxies special compared to the rest of the riff-raff (Part 3), we’re ready for Part 4 of the Quench ‘How-To-Guide’.
This segment is inspired by a post on Quench Talk in response to Part 3 of this guide. One of our esteemed zoo-ite mods noted:
There are more Quench Sample mergers (505) than Control mergers (245)… It seems to suggest mergers have a role to play in quenching star formation as well.
Whoa! That’s a statistically significant difference and will be a really cool result if it holds up under further investigation!
I’ve been thinking about this potential result in the context of the Kaviraj article, summarized by Michael Zevin at http://postquench.blogspot.com/. The articles finds evidence that massive post-quenched galaxies appear to require different quenching mechanisms than lower-mass post-quenched galaxies. I wondered — can our data speak to their result?
Let’s find out!
Step 1: Copy this Dashboard to your Quench Tools environment, as you did in Part 3 of this guide.
- This starter Dashboard provides a series of tables that have filtered the Control sample data into sources showing merger signatures and those that do not, as well as sources in low, mid, and high mass bins.
- Mass, in this case, refers to the total stellar mass of each galaxy. You can see what limits I set for each mass bin by looking at the filter statements under the ‘Prompt’ in each Table.
Step 2: Compare the mass histogram for the Control galaxies with merger signatures with the mass histogram for the total sample of Control galaxies.
- Click ‘Tools’ and choose ‘Histogram’ in the pop-up options.
- Choose ‘Control’ as the ‘Data Source’.
- Choose ‘log_mass’ as the x-axis, and limit the range from 6 to 12.
- Repeat the above, but choose ‘Control – Merging’ as the ‘Data Source’.
The result will look similar to the figure below. Can you tell by eye if there’s a trend with mass in terms of the fraction of Control galaxies with merger signatures?
It’s subtle to see it in this visualization. Instead, let’s look at the fractions themselves.
Step 3: Letting the numbers guide us… Is there a higher fraction of Control galaxies with merger signatures at the low-mass end? At the high-mass end? Neither?
To answer this question, we need to know, for each mass bin, the fraction of Control galaxies that show merger signatures. I.e.,
Luckily, Tools can give us this information.
- Click on the ‘Control – Low Mass’ Table and scroll to its lower right.
- You’ll see the words ‘1527 Total Items’.
- There are 1527 Control galaxies in the low mass bin.
- Similarly, if you look in the lower right of the ‘Control – Merging – Low Mass’ Table, you’ll see that there are 131 galaxies in this category.
- This means that the merger fraction for the low mass bin is 131/1527 or 8.6%.
- Find the fraction for the middle and high mass bins.
Does the fraction increase or decrease with mass?
Step 4: Repeat the above steps but for the post-quenched galaxy sample.
You may want to open a new Dashboard to keep your window from getting too cluttered.
Step 5: How do the results compare for our post-quenched galaxies versus our Control galaxies? How can we best visualize these results?
- In thinking about the answer to this question, you might want to make a plot of mass (on the x-axis) versus merger fraction (on the y-axis) for the Control galaxies.
- On that same graph, you’d also show the results for the post-quenched galaxies.
- To determine what mass value to use, consider taking the median mass value for each mass bin.
- Determine this by clicking on ‘Tools’, choosing ‘Statistics’ in the pop-up options, selecting ‘Control – Low Mass’ as your ‘Data Source’, and selecting ‘Log Mass’ as the ‘Field’.
- This ‘Statistics’ Tool gives you the mean, median, mode, and other values.
- You could plot the results with pen on paper, use Google spreadsheets, or whatever plotting software you prefer. Unfortunately Tools, at this point, doesn’t provide this functionality.
It’d be awesome if you posted an image of your results here or at Quench Talk. We can then compare results, identify the best way to visualize this for the article, and build on what we’ve found.
You might also consider repeating the above but testing for the effect of choosing different, wider, or narrower mass bins. Does that change the results? It’d be really useful to know if it does.
Quench Boost: A How-To-Guide, Part 3
I’m very happy to be posting again to the How-To-Guide. We’ve made a number of updates to Quench data and Quench Tools. Before I launch into Part 3 of the Guide, here are the recent updates:
- The classification results for the 57 control galaxies that needed replacements have been uploaded into Quench Tools.
- We’ve applied two sets of corrections to the galaxies magnitudes: the magnitudes are now corrected for both the effect of extinction by dust and the redshifting of light (specifically, the k-correction).
- We’ve uploaded the emission line characteristics for all the control galaxies.
- We’ve uploaded a few additional properties for all the galaxies (e.g., luminosity distances and star formation rates).
- We corrected a bug in the code that mistakenly skipped galaxies identified as ‘smooth with off-center bright clumps’.
In Part 1 of this How-To-Guide to data analysis within Quench, you learned how to use Tools and were introduced to the background literature about post-quenched galaxies and galaxy evolution.
In Part 2 you used Tools to compare results from galaxies *you* classified with the rest of the post-quenched galaxy sample.
In Part 3 we’re going to use the results from the classifications that you all provided to see if there’s anything different about the post-quenched galaxies that have merged or are in the process of merging with a neighbor, and those that show no merger signatures.
The figure below is of one of my favorite post-quenched galaxies with merger signatures. Gotta love those swooping tidal tails!
Let’s get started!
Step 1: Because of the updates to Tools, first clear your Internet browser’s cache, so it uploads the latest Quench Tools data.
Step 2: Copy my starter dashboard with emission line ratios ready for play.
- Open my Dashboard and click ‘Copy Dashboard’ in the upper right. This way you can make changes to it.
- In this Dashboard, I’ve uploaded the post-quenched galaxy data.
- I also opened a Table, just as you did in Part 2 of this How-To-Guide. I called the Table ‘All Quench Table’.
- In the Table, notice how I’ve applied a few filters, by using the syntax:
filter .’Halpha Flux’ > 0
- This reduces the table to only include sources that fulfill those criteria.
- Also notice that I’ve created a few new columns of data, just as you did in Part 2, by using the syntax:
field ‘o3hb’, .’Oiii Flux’/.’Hbeta Flux’
- That particular syntax means that I took the flux for the doubly ionized oxygen emission line ([0III]) and divided it by the flux in one of the Hydrogen emission lines (Hbeta).
- This ratio and the ratio of [NII]/Halpha are quite useful for identifying Active Galactic Nuclei (AGN).
- It’d be really interesting if we find that AGN play a role in shutting off the star formation in our post-quenched galaxies. A major question in galaxy evolution is whether there’s any clear interplay between merging, AGN activity, and shutting off star formation.
Step 3: Create the BPT diagram using the ratios of [OIII]/Hb and [NII]/Ha.
- BPT stands for Baldwin, Phillips, and Terlevich (1981), among the first articles to use these emission line ratios to identify AGN. Check out the GZ Green Peas project’s use of the BPT diagram.
- Click on ‘Tools’. Choose ‘Scatter plot’ in the pop-up options.
- In the new Scatterplot window, choose ‘All Quench Table’ as your ‘Data Source’.
- For the x-axis, choose ‘logn2ha’. For the y-axis, choose ‘logo3hb’.
- Adjust the min/max values so the data fits nicely within the window, as shown in the figure below.
- Remember that you can click on the comb icon in the upper-left of the plot to make the menu overlay disappear.
- Do you notice the two wings of the seagull in your plot? The left-hand wing is where star forming galaxies reside (potentially star-bursting galaxies) while the right-hand wing is where AGN reside. Our post-quenched sample of galaxies covers both wings.
Step 4: Compare the BPT diagram for post-quenched galaxies with and without signatures of having experienced a merger.
- To do this, you’ll need to first create two new tables, one that filters out merging galaxies and the other that filters out non-merging galaxies.
- Click on ‘Tools’. Choose ‘Table’ in the pop-up options.
- In the new Table window, choose ‘All Quench Table’ as the ‘Data Source’. Notice how this new table already has all the new columns that were created in the ‘All Quench Table’. That makes our life easier!
- Look through the column names and find the one that says ‘Merging’. Possible responses are ‘Neither’, ‘Merging’, ‘Tidal Debris’, or ‘Both’.
- Let’s pick out just the galaxies with no merger signatures.
- Under ‘Prompt’ type:
filter .Merging = ‘Neither’
- If you scroll to the bottom of the Table, you’ll notice that you now have only 2191 rows, rather than the original 3002.
- Call this Table ‘Non-Mergers Table’ by double clicking on the ‘Table-4’ in the upper-left of the Table and typing in the new name.
- Now follow the instructions from Step 3 to create a BPT scatter plot for your post-quenched galaxies with no merger signatures. Be sure to choose ‘Non-Mergers Table’ as the ‘Data Source’.
- You might notice that this plot looks pretty similar to the plot for the full post-quenched galaxy sample, just with fewer galaxies.
What about post-quenched galaxies that show signatures of merger activity? Do they also show a similar mix of star forming galaxies and AGN?
- To find out, create a new Table, but this time under ‘Prompt’ type:
filter .Merging != ‘Neither’
- The ‘!=’ syntax stands for ‘Not’, which means this filter picks out galaxies that had any other response under the ‘Merging’ column (i.e, tidal tails, merger, both). Notice how there are 505 sources in this Table.
- Now create a BPT scatter plot for your ‘Mergers Table’.
- Make sure this plot has a similar xmin,xmax,ymin,ymax as your other plots to ensure a fair comparison.
- You might also compare histograms of log(NII/Ha) for the different subsamples.
What do you find? Do you notice the difference? What could this be telling us about our post-quenched galaxies?!
Before you get too carried away in the excitement, it’s a good idea to compare the post-quenched galaxy sample BPT results against the control galaxy sample.
This comparison with the control sample will tell you whether this truly is an interesting and unique result for post-quenched galaxies, or something typical for galaxies in general. You might consider doing this in a new Dashboard, as I have, to keep things from getting too cluttered. In that new Dashboard, click ‘Data’, choose ‘Quench’ in the pop-up options, and choose ‘Quench Control’ as your data to upload. Now repeat Steps 1-4.
Do you notice any differences between your control galaxy and post-quenched galaxy sample results? What do you think this tells us about our post-quenched galaxies?
Stay tuned for Part 4 of this How-To-Guide. I’d love to build from your results from this stage, so definitely post the URLs for your Dashboards here or within Quench Talk and your questions and comments.
More Galaxies, More Clicks, More Science!
Just a quick update: recently we brought some of our high-redshift (i.e., very distant) galaxies out of retirement. There’s enough going on in these galaxies that having more clicks from you will really help tease out the nuances of the various features and make the classifications even better.
How would you classify these?
So, for those of you who noticed you hadn’t seen many CANDELS galaxies recently, well, you’re about to see a few more. I can’t promise they’ll always be easy to classify, but I hope they’ll at least be an interesting puzzle. As ever, thank you for your classifications!
What is a Galaxy? …the return
The first time I gave a public talk, I spent an hour describing why galaxy classification is fundamentally important to the study of the Universe, the origins of Galaxy Zoo, the amazing response of the volunteers and the diverse results from their collective classifications of a million galaxies near and far. I showed many gorgeous galaxy images, a few dark matter simulations and even a preview of the Hubble image of Hanny’s Voorwerp.
As I finished my talk and the Q&A began, I braced myself for the inevitably interesting and challenging questions (I seem to get a lot of questions about black holes and spacetime).
A brief pause, and then the first question echoed from somewhere in the darkened auditorium: …”What’s a galaxy?”
Oops. Apparently I’d forgotten that little detail at the start of the talk. So I described a typical galaxy (if there is such a thing): a collection of stars, gas, dust, dark matter, all gravitationally bound together. Then I made a joke about scientists forgetting to define their terms, and we moved on to the next raised hand.
Turns out, though, it’s not such an easy question. Even though my casual definition works fine for most galaxies, it’s not at all an agreed-upon standard. We’ve discussed this on the blog before, and even in the short time (astronomically speaking) since Karen wrote that very nice post, more work has been done to find galaxies that push the boundaries and force us to re-think what it really means to be a galaxy.
The circled stars (plus a lot of dark matter you can’t see) are Segue 1, one of the smallest galaxies we know about. To read more on this, click the image.
So, spurred by a very broad interpretation of a question left for us in the comments on the post announcing this hangout, we decided to re-visit the discussion, covering the various properties a galaxy must have, should have, could have, and can’t have. We discussed the smallest galaxies, found by counting and measuring each of their individual stars. We discussed the biggest, brightest galaxies in the universe, living in rich environments and grown fat by eating other galaxies. And everything in between.
Note: when we talk about Segue 1 and 2, I say that these galaxies are unique because they have low mass-to-light ratios. Despite the pause that indicated I was trying to keep from inverting numerator and denominator… that’s exactly what I did. The galaxies have very few stars compared to the amount of dark matter in them, so their mass is high and their light is low, so their mass-to-light ratios are high. Oops (again)!
Galaxy Zoo 