A new email newsletter for SETI research

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A few months ago I became frustrated with the difficulty in conducting academic research on SETI (that is the Search for Extra Terrestrial Intelligence). Specifically it can be challenging to read the academic literature on SETI because articles are few, and are published in a variety of outlets.

SETI is a controversial topic, both for funding and for "legitimate" research, because it is often associated with conspiracy theories and blatant speculation. There's a lot of this kind of junk on the internet, so I'll let you find it if you're interested... but this material poses an extra layer of obfuscation towards scientists trying to read through the literature. When you search Google for SETI research you have to wade through a lot of junk.

Furthermore, professional astronomers have largely avoided publishing about SETI due to a lack of data. When new technology or new cutting edge datasets become available there's usually a handful of papers written about new imaginative ways we might detect alien life, or conversely that Earth might be detectable using similar techniques on other worlds. These papers get put in to any of a large number of academic journals that, despite heroic efforts by NASA and Harvard/SAO, still take a good deal of effort to read through.

Finally, given the low rate of academic papers on SETI research, it is easy for the occasional bit of brilliant work to slip by unnoticed by scientists. Like many astronomers, I read through the latest daily batches of papers on the "astro-ph" preprint server on arXiv.org every day. This can be dozens of new research articles to scan over each day. Typically I only read the titles for every paper, and the abstracts for only those that stand out. Sometimes I don't even see papers that I'm a co-author on appearing due to the volume of papers to look over!

For all these reasons, SETI is a difficult topic to learn about and stay abreast of!

After chatting with some folks who shared this concern, I decided one way to help was to start an email newsletter each month that highlights new research articles about SETI (and related topics). It's called SETI.news, it's free, and if you're interested in keep up to date on SETI research you should subscribe!

Each month, SETI.news simply sends a brief email listing articles I find on the arXiv that mention SETI. If there are other sources of research results (say, a GitHub project, a Zenodo group, or just a paper not on the arXiv) then I would also list those if people send them to me! SETI.news is not an academic journal or publisher, though I think an open journal of SETI research (run by academics, with editors, referees, etc) would be a great idea for collecting this material.

Check out the March edition of SETI.news here, and be sure to subscribe!

NFL Coaches Salary

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Recently in the local news I saw that our beloved Seattle Seahawks coach, Pete Carroll (or "Uncle Pete" as he's known at our house) is up for a contract negotiation soon. He's been the heart and soul behind turning the Seahawks from a national "meh" to one of the top teams in the NFL, including back to back Super Bowl appearances, and one of the best records in the league. Naturally, he'll be asking for more money.

So I was wondering: Does the Win/Loss record indicate Pete Carroll deserves more money?

For reference, I toyed with this idea a few years ago for NCAA coaches

I searched Google and quickly gathered some data on NFL Coaches Salaries, as well as their age. I then grabbed a few years of Win/Loss standings from ESPN (again, top hit on Google). Averaging together the results from the past 3 years of NFL play, let's see how they look! Of course I've highlighted the Seahawks with a bright green star.

The line of best fit was simply calculated using a least squares regression in Python. There's a lot of scatter (much more than in my NCAA analysis previously), but I'm only averaging 3 years of play instead of 10 this time. Here's how to read this graph: points above the line are winning more than average given their level of pay, and points below are winning less.

Right away you can see two interesting (or just obvious) things:

  1. Uncle Pete is already one of the top paid NFL coaches
  2. The Seahawks are one of the best performing teams in the NFL over this time period

So he might have a good case for being paid more! Let's see just how undervalued he might be. By subtracting the model from the data, we can compute the coaches "value":

This is a pretty noisy distribution, and not a great discriminant of "value", but thats ok... this is definitely not my most absurd football related article to date...

So, teams with the best value coaches by this metric are:
1 - Denver Broncos
2 - Carolina Panthers
3 - Cincinnati Bengals

and Seattle's Pete Carroll is a respectable 8th. Given that he's one of the oldest coaches in the NFL, I don't know how much room he'll have to negotiate. However, if the salary data I've grabbed is accurate, this year's NFL champions, the Denver Broncos, are getting a hell of a deal with Gary Kubiak.

Of course we have to talk about the other end of the distribution. The team with the "worst valued" coach in the NFL currently is:
32 - Tampa Bay Buccaneers

Look, don't put too much stock in what I'm saying based on random numbers from the internet. As I understand it the coach's salary doesn't count towards the team's salary cap, but still, it doesn't look great Tampa....

The data and Python code to make these figures is of course available for use on GitHub!

Spots and Flares animation

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Here's a fun astronomy data visualization I've been working on to put in talks, which I thought was worth sharing!

What you're seeing is a model of a spinning star that is covered in starspots (grey circles), and transient flares (red dots). The starspot sizes and impact on the resulting light curve (bottom panel) are generated using a real and super neat starspot modeling code one of my collaborators has built. The flares occur at random (based on some "rate" parameter I've set), but their sizes and shapes are based on results from a pair of papers my PhD thesis advisor and I wrote in 2014.

Remember, when studying stars with Kepler all we get is the light curve (bottom panel), and it is very difficult (sometimes impossible) to infer the true spatial distribution of spots and flares on the surface.   A model like this can help us visualize what really may be happening on the star, and how our intuition can betray us.

I've tried to make everything going in to the light curve as physically realistic as possible, making this a "phenomenological model" of sorts. As a result, we get a model that looks very similar to real data. For example, when I run the model forward 10 more rotations and stack all the data, you see there is no strong correlation between # of flares and rotation phase. This despite the presence of a large active polar starspot that dominates the spot light curve.

This looks very similar to a result from Hawley & Davenport et al. (2014). A modified version of the published figure is below that also shows no correlation with flare energy (labeled Ekp) and rotation, indicating big flares and small flares come from all over the star.

I originally made this toy model and animation to help explain results from Kepler in a talk. The cool thing is that we might actually be able to do some real science using this model, both in generating mock data to use for training, and in estimating flare rates and flare properties for real stars!

Of course, the code to make this is available on GitHub as well.

Gender in Astro Conferences: AAS 227

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If you will be at the upcoming AAS 227 meeting next week (#aas227), I could sure use your help!

We will be continuing the ongoing study of gender in conference talks vs questions, and We Need YOU to help collect data. This project gathers data using anonymous volunteer submissions, and casting a wide net is critical. The basic goals are to understand:

  1. Do Women/Men get asked the same number of questions during talks?
  2. Do Women/Men ask the same numbers of questions?
  3. If no to 1 or 2, are there other correlating factors that may suggest how to construct a more perfect conference environment?

For more details on this project, check out our report from AAS 223!

Web Form HERE!

Even if you won't be at AAS, I appreciate any retweets or Facebook posts you can contribute before or during the meeting! It's important to remind people every day to contribute, so I tend to pester them repeatedly (sorry!)

Bonus: If you'll be at the AAS hack day (#hackaas) we will once again be studying the results from this and previous years. I got sidetracked last year after AAS (sorry, had to finish getting PhD), so there's much to do!
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