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!
Next GZ Hangout: 3rd of September, 3 pm GMT
The hangouts have returned from a midsummer hiatus! Our next hangout will be Tuesday, September 3rd, at 3 pm GMT. That’s 8 am PDT, 11 am EDT, 4 pm BST, 5 pm CET, 6 pm CAT. Unfortunately I think that’s 11 pm in Japan and midnight in Sydney, but hopefully we’ll have a hangout at a different time very soon!
Just before the hangout we’ll update this post with the embedded video, so you can watch it live from here. If you’re watching live and want to jump in on Twitter, please do! we use a term you’ve never heard without explaining it, please feel free to use the Jargon Gong by tweeting us. For example: “@galaxyzoo GONG dark matter halo“.
In the meantime, please feel free to leave a question in the comments below. See you soon!
Update: read a summary of the Hangout here: What is a Galaxy?… the Return
Quench Boost: A How-To-Guide, Part 2
It was amazing how quickly the new Quench classifications were completed. We posted them on Friday and you were already done by Sunday morning. Wow, that’s awesome! This means we can turn our full attention to making sense of the data. And we need your help!
In Part 1 of this How-To-Guide to data analysis within Quench, you learned how to use Tools, our analysis platform, and were inspired (or so I hope) about ways to play with the data as you read the background literature about post-quenched galaxies and galaxy evolution.
In Part 2 of this How-To-Guide, we’re going to help you navigate using Tools to compare results from galaxies *you* classified with the rest of the post-quenched galaxy sample.
You’re 12 small steps away from your first comparison plot between your galaxies and the full sample… let’s get started!
Step 1: Enter Tools and log in using your Zooniverse login information.
Step 2: Choose ‘Quench’ in the pull-down menu in the upper-left, next to the words ‘zootools’. Now click ‘Create Dashboard*’ in the upper-right, and give it a name, like: ‘My Data in Context’.
Step 3: Click ‘Data’ in the upper-left and choose ‘Zooniverse’ in the pop-up options.
Step 4: In the window that pops up, choose ‘Recents’ or ‘Collections’. Your choice.
If you classified galaxies in quench.galaxyzoo.org, they’ll be accessible through ‘Recents’. Choose the max number possible. If you created a Collection of interesting galaxies in Quench Talk or want to look at someone else’s Collection, you can access them by clicking ‘Collections’.
I’ve created a Dashboard* in Tools called ‘Example: My Data in Context’. Take a look and, if you’d like, you can even make edits by copying it into your Tools environment.
In my Dashboard ‘Example: My Data in Context’, I chose ‘Collections’. I love #Quencher SUMO_2011’s Collection of ‘Blue’ galaxies from Quench. If you go to that URL, the Collection ID is listed after the final ‘/’ in the URL. In this case, the Collection ID is CGSS00000x. I inputted that ID into the pop-up window in Tools, in the box next to ‘Enter Collection Id:”. I then clicked on ‘Import Data’.
Step 5: Now that you have your galaxies’ information imported into the Dashboard, it’s time to play with them. Click on ‘Tools’ in the upper-left and choose ‘Table’ in the pop-up options.
Step 6: In your Table window, choose ‘Zooniverse-1’ in the pull-down menu under ‘Data Source’. Now the Table knows to work with that set of data.
Step 7: As in Part 1 of this How-To-Guide (https://blog.galaxyzoo.org/2013/08/23/quench-boost-a-how-to-guide-part-1/), you’ll make a new column that has color information about your galaxies. You do this by subtracting the brightness of your galaxy in one filter from the brightness of your galaxy in another filter.
In the open space under ‘Prompt’ in your Table, write: field ‘My Galaxies Color u-r’, .u-.r
If you scroll to the right in your table, you’ll see that you created a new column of information, called ‘My Galaxies Color u-r’.
Step 8: Click ‘Tools’ in the upper-left and choose ‘Scatterplot’ in the pop-up options.
Step 9: In your Scatterplot window, choose ‘Table-2’ in the pull-down menu under ‘Data Source’. Now the Scatterplot knows to work with the Table, which includes your new column with Color information.
Step 10: Choose ‘log_mass’ for the X-axis and ‘My Galaxies Color u-r’ for the Y-axis. Recent star formation is seen strongly in the u-band while older stars dominate the r-band. The color, u-r, tells you about the star formation history for each of your galaxies. Check out this post for more details.
Step 11: How do your galaxies compare with the full sample of post-quenched galaxies? To answer this, we redo the steps 3-10 above, but for the post-quenched galaxy sample.
- Click on ‘Data’ in the upper-left and choose ‘Quench’ in the pop-up options.
- Click on ‘Quench Sample’ in the pop-up window.
- Click on ‘Tools’ in the upper-left and choose ‘Table’ in the pop-up options.
- In the new Table window, choose ‘Quench-4’ in the pull-down menu under ‘Data Source’. This loads the Quench Sample into that Table.
- In the open space under ‘Prompt’ in your Table, write: field ‘Quench Galaxies Color u-r’, .u-.r
- Click on ‘Tools’ in the upper-left and choose ‘Scatterplot’ in the pop-up options.
- In the new Scatterplot window, choose ‘Table-5’ in the pull-down menu under ‘Data Source’.
- Choose ‘log_mass’ for the X-axis and ‘Quench Galaxies Color u-r’ for the Y-axis.
- Zoom in on the data, for example, choosing Xmin: 7, Xmax: 12, Ymin: 1, and Ymax: 4.
Step 12: Place your two scatterplots side by side. For a fair comparison, make sure the x- and y-axis range is the same for both plots, otherwise the stretch might skew your analysis. I tend to make the axes ranges in the plot showing My Galaxies match the plot showing the Quench Sample.
What do you notice about your subsample of post-quenched galaxies compared to the full sample? Do they occupy a particle sub-space within the plot? Or are they randomly distributed throughout the quench space?
The figure below shows what you’ll see if, like me, you uploaded SUMO_2011’s Collection of blue galaxies. You’ll notice that all of the blue-collection galaxies are way bluer (closer to the bottom of the plot, near values u-r = 1.5) than the full post-quenched galaxy sample (which spread from u-r values of 1 to u-r values of 3.5 and higher). This is a reassuring reality check given what you see visually when you look at the color of the galaxies. The plot also tells us that since these blue galaxies have such low values of ‘u-r’, they’ve had more recent star formation than most of the post-quenched galaxies.
In looking at these two plots side-by-side, I wondered: Why are there so few massive post-quenched galaxies (log_mass > 11) with bluer colors (u-r < 2.0)? If we compare our post-quenched galaxies with our control galaxies, do I see any difference? Specifically, are there massive (log_mass > 11) control galaxies with bluer colors (u-r < 2.0)? If there are, what might that be telling me about our post-quenched galaxy sample?
Stay tuned for Part 3 of our How-To-Guide for taking part in the analysis phase of the research process. If you have suggestions for what you’d like to learn more about, please post here. Thank you all, and keep on Quenching!
*Dashboard is the place within Tools (tools.zooniverse.org) for volunteers to observe, collect, and analyze data from Zooniverse citizen science projects.
Quench Boost: A How-To Guide, Part 1
The reaction to GZ Quench has been amazing. It has been great to see the interest and enthusiasm for supporting citizen scientists in experiencing the full scientific process.
This morning’s post was about how we have a small sample of additional galaxies to classify. I’ve really enjoyed watching how fast those are being done… gotta love the counter at http://quench.galaxyzoo.org/. Thank you all!
This post is Part 1 of our How-To-Guide for analyzing our classification results. It’s clear that you’re interested in getting your analysis on, but it may be that you’re not sure where to start. That’s 100% understandable and we’re here to help. We’ve broken down the steps into bite-size chunks. Let’s get started.
The first thing to do is to meet Quench Tools. This is the web platform to help you play with the data. To enter Quench Tools, click here. An in-line Tutorial will automatically pop-up, and guide you through entering the Quench area, loading the data, and creating your first figure. For additional information about Tools, check out our GZ Hangout about Tools, our text-based Tools Tutorial, and this Quench Talk discussion forum post.
In parallel with getting to know Tools, you may be interested in understanding the science context for why post-quenched galaxies (the GZ Quench sample) are so interesting for galaxy evolution studies. A great starting place for getting a sense of the science context and motivation is to read the summaries (written for the general public) of science articles at http://postquench.blogspot.com/. It’s modeled after the astrobites blog, a great resource for any astronomy enthusiast!
As you read those posts, you might want to join the conversation within the Quench Talk discussion forum. There are also a slew of links to popular science articles and websites for additional information about post-quenched galaxies and galaxy evolution.
And if you feel it would help to take a step back and see the big picture, definitely check out our initial GZ Quench blog post and this Quench Talk post.
Stay tuned for Part 2 of our How-To-Guide. In it, I’ll guide you through the next bite-size piece of this adventure – playing with your own classification results!
Quench: New Classifications Needed
We have a few dozen new galaxies in GZ Quench that need your classification savvy. As with all research projects, there are sure to be some glitches. Luckily we have a great group of Quenchers on the job. And as a few pointed out (including the force of nature that is Jean Tate!), 57 of our 3002 control sample galaxies were duplicates. We’ve identified suitable replacements and, to make sure no bias is introduced, we’ve added some of the original post-quenched galaxies to the mix as well. So let’s get classifying!
For a reminder about what GZ Quench is all about, check out the first Quench blog post. Yes, in this project, we’re not only classifying galaxies, but we’re going all the way to support our citizen scientists in experiencing the full process of science.
We’re now into Phase 2 of GZ Quench, analyzing the results of the classifications and making sense of our data. Our amazing group of Quenchers have provided incredibly useful feedback on the analysis tools we’ve made available and the analysis process. And there are already a number of intriguing results (for example, here and here)!
We’re now ready to give Quench a boost. Later today I’ll post Part 1 of our How-To-Guide, breaking the analysis phase into bite-size pieces and providing a smoother on-ramp for all of you out there who want to join in the GZ Quench experience, but aren’t sure where to begin.
Stay tuned…
GZ: Quench data update
Since finishing the classifications for the GZ: Quench project, many of our volunteers have been analyzing that consensus data using the tools at tools.galaxyzoo.org. We made a few changes to the site earlier this week, and I’d like to describe them and talk about how it might affect your work on the project.
First, a quick reminder of how the data is presented. As most of you probably remember, the classification process on GZ: Quench (and all GZ projects since GZ2) is what we call a “decision tree”. We begin with a broad question on morphology (ie, “Is this galaxy smooth, or does it have features or a disk?”) for the volunteer to answer. We then ask more specific follow-up questions that depend on the previous answers. For example – if you said the galaxy doesn’t have any spiral arms, it doesn’t make sense for us to then ask you how many arms there are – it doesn’t apply to this galaxy! So, out of 11 potential questions covering galaxy morphology, a single classifier will only answer a subset (between 4 and 9) of them. Here’s a flowchart of the decision tree for GZ: Quench — it’s an interesting exercise to look at it and work out how many unique morphologies you could sort galaxies into by going through the tree.
Flowchart of the morphology decision tree for GZ: Quench
So, why this discussion? When we added the data to the Tools website, we added a label in each category that gave the most common response to that question. For example, under “Arm tightness”, you could see that all galaxies were either “Tight”, “Medium”, or “Loose”. However, this is problematic when you’re trying to analyze data and compare different sets of galaxies. For smooth (or elliptical) galaxies, though, this arm classification is the result of very few votes (or even none) — they don’t represent the majority of classifications, and thus we really shouldn’t be including them when trying to compare what makes a medium-wound vs. a loosely-wound spiral.
The solution we’ve adopted has been to edit the data on Tools — questions whose answers don’t apply to the consensus morphology (eg, spiral arms in a smooth galaxy, or the roundness of a spiral) are now blank. This means that if you look at the average color or size of any of these morphology properties, you’re now truly comparing similar groups of objects (apples to apples). Including other galaxies in earlier samples likely introduced a significant amount of bias – the science team thinks that this will largely help to address that.
Example of the new GZ: Quench classification set in Tools
What does this mean for your analysis? Most of your old Dashboards and results should still work and remain valid results. For any work where you were analyzing morphological details (especially for spiral structure), though, we encourage you to revisit these and run them again on the new, filtered dataset. Please keep posting any questions you have on Talk, and we’ll answer them as soon as we can. Good luck!
And the winner is….. Arp 142 (The Penguin Galaxy)
Well it was a very close fought battle, but the winner of our fun vote to pick the cover image for the October A&G was:
Apr 142 (aka The Penguin Galaxy):
I include below a screen shot of the poll from today, which confirms that choice. We have now sent this choice to the cover editor, so we won’t count any more votes.
(Most) Galaxy Zoo Papers now Open Access
As announced on the Zooniverse blog, Oxford University Press have agreed that to make the Zooniverse papers published in Monthly Notices of the Royal Astronomical Society open access. While they’ve always been freely available on astro-ph, it’s nice that everyone who contributed can now get access – for free – via the main journal site.
Galaxy Zoo 