tristate expolanets

Today was the (first) Tri-state Astronomy Conference, organized by Ari Maller (CUNY CityTech) and Marla Geha (Yale). There were good talks all day, with quite a few (though not all) New-York-area institutions represented. I learned the most from Ben Oppenheimer's (AMNH). He made a pitch for exoplanet research and showed me several things I had not thought about or seen before:

  • Although the properties of a star are set, pretty much, by mass and chemical composition (and age), this is not even close to true for planets. Look at the Solar System! This shows that once you get to low mass, formation history and environment matter, deeply.
  • There is no clear distinction between brown dwarfs and planets, observationally. The differences are entirely related to discovery technique! In mass and orbital radius distributions, planets and brown dwarfs overlap, and—in the absence of good theories—there is no reason to make hard distinctions (although we all do).
  • Polarimetry plus coronography combined do much better than either alone, and it is possible to see reflected light from planets and proto-planetary disks at incredibly small luminosity ratios with the combination. Coronography is limited, at the present day, by speckles (wavefront irregularities), which are introduced not just by the atmosphere but by every optical surface, of course.

I asked Oppenheimer about modeling the speckles to remove them, and he said that they are very complicated and change with time and wavelength. Of course that is true, but that also helps with modeling them. A better answer is that the modeling can only happen with the intensity data, whereas improving the optics makes use of the amplitudes and phases, a space in which you can cancel out (rather than just model) your instrument issues. So Oppenheimer is right to be putting time and money into great optics, and to work on software only after optimizing the hardware as much as possible.


merger origin of the halo, GALEX

Adi Zolotov—spending this year at Haverford with Willman—was back in the city today, and we spent some hours talking about projects. Her big project is about the signatures of hierarchical galaxy formation in the straightforward observables available to us from halo stars, such as spatial distributions, metallicities, and kinematics. She is developing a theory-motivated set of observational tests that will be sensitive to merger history.

Chris Martin (Caltech) came and gave the Physics Colloquium. He spoke about the GALEX satellite, with a focus on technical and hardware aspects. It was beautiful stuff.


quasar absorption lines, submitted

Nikhil Padmanabhan (Berkeley) showed up at NYU today, and we discussed various matters related to BOSS and the baryon acoustic feature. Nikhil argued that we do not yet have a fully worked-out plan for analyzing the quasar absorption-line spectra, and measuring the correlation function therefrom. We discussed this in detail and I got a bit interested in the data analysis problem, which, when written down correctly, is quite difficult: It involves marginalizing over all hypotheses about each spectrum's unabsorbed continuum.

In other news, Surhud More submitted the transparency paper to ApJ. Should be on arXiv on Monday.


from Gaia to gravity

In what research time was left after completing my NSF proposal (hooray!), I worked on the theoretical question of how one might infer the gravitational forces or gravitational potential of the Milky Way from the Gaia observations. The problem is extremely non-trivial, because Gaia only measures positions and velocities, but it is accelerations that constrain the gravitational potential or forces. As I have said before, all important questions in science are ill-posed; the challenge is to come up with well-posed approximations to the ill-posed questions. I think there might be some well-posed questions to ask with Gaia, but it is hard to write them down even if you are allowed to assume that the potential is time-independent and azimuthally symmetric (which you aren't).


predicting radial velocities

Most of the day was lost to an NSF proposal, but Bovy and I got in some quality time on his prediction of radial velocities in the Solar Neighborhood. He has a model of the velocity field from the transverse velocities; that model plus the measurement of each star's transverse velocity makes a prediction for each star's radial velocity, in the form of an error-convolved probability distribution function. Bovy can search these for the most discrepant values among those stars that do have radial velocities (these are stars from the halo, probably), find the stars for which the radial velocity prediction is most informative or constraining (these provide critical tests of the model), and find the stars for which the radial velocity prediction is the least informative (these provide the most valuable follow-up observations for improving the precision of the model).


transparency scoop, velocities, testing GR

More and Bovy found papers today that—to some extent—scoop our result on the transparency of the Universe with baryon acoustic feature and type Ia supernovae. We did some re-tooling to emphasize the new aspects of our work in this context.

Bovy and I discussed at length various issues related to the determination of the velocity field from Hipparcos. Bovy has implemented a beautiful system that determines the error-deconvolved distribution of velocities, even in the face of the issue that each data point has a different error. We discussed using his fit to the velocity field to predict the results of radial velocity surveys.

Bhuvnesh Jain (Penn) gave a great astro seminar on testing gravity using the comparison of lensing and kinematic / dynamical measures of the potential. He featured Adam Bolton's strong lenses as among the best tests of this, although Bolton's test is at smaller length scales (kpc) than the scales of interest to most cosmologists (Mpc to Gpc). Jain made a very good argument that if you want to test GR, you have to work at all scales and with all techniques; the different cosmological tests can only be combined or ranked if you believe GR.


white dwarfs

In between grant-proposal writing I discussed with NYU undergraduate Antony Kaplan that he might run Lang and my faint motion software on the white dwarfs in the SDSS Southern Stripe to determine all the proper motions and parallaxes, even below the individual-epoch detection limits.


rule of thumb

Phil Marshall emailed me, asking about the original citation / derivation of the rule of thumb that a source detected in an image at some signal-to-noise ratio [s/n] can be centroided to an accuracy of about the FWHM divided by [s/n]. It was funny he asked, because we had discussed the very same issue only days earlier in responding to the referee for the faint-motion paper. Rix found King (1983), which probably is the first paper to discuss this (interested if anyone out there knows a more recent reference). Nowadays, the standard answer is the Cramer-Rao bound (Robert Lupton said this in response to a query from me), but that isn't quite the answer most people are looking for.


USNO-B and GALEX, supervised

I got stranded in Nantucket by high winds (cancelled ferries). This cost me Monday, and I spent parts of today making up for it. My research time was spent with Schiminovich, talking about what we should do with the SDSS and GALEX, and what we will do in the very short term. The very short term project is to use SDSS and GALEX to learn what quasars look like and then find them all-sky with USNO-B1.0 and GALEX. Same with white dwarfs. This is a nice project in supervised methods for automated classification, something I was railing against in Ringberg.



Spent the afternoon at the AAVSO annual meeting in Nantucket (yes, my travel schedule is not sane). My word are the AAVSO observers impressive! Every talk showed ridiculous light curves with incredible sampling and huge signal-to-noise, and many of the photometry sources are people working visually (with their eyes, no detectors). The data are consistent from observer to observer and highly scientifically productive. Of course, many of the AAVSO members use CCDs too, and these tend to be among the best calibrated and understood among hobbyist setups. Naturally, that is why I am here.


minimum message length

On the plane home from Germany, I worked on various writing projects, including the transparency paper and my Class2008 proceedings. I tried to write down what minimum message length could say about the Milky-Way-reconstruction problem from astrometric measurements of stellar motions and parallaxes. I have a strong intuition that there is a correct—or at least very useful—approach that could be inspired by or directly derived in the context of the idea that the most probable (posterior-probable) model is the one that provides the best (lossless) compression of the data given the coding scheme suggested by your priors. If I could write it down, it might help with the upcoming GAIA data.


class2008, day three

On the third day of Classification and Discovery, I chaired a session on the time domain; I was blown away by the data from the CoRoT experiment. But I was even more fired up by Anthony Brown's description of the problem of inferring Galactic structure from GAIA data. This problem has so many awesome aspects, including a good argument for generating the data with the model (think Lutz-Kelker problems with parallaxes), to a huge issue with priors (because the mission measures positions and velocities but not accelerations, and accelerations are what the Galaxy produces). I will say more about the latter when I get it sorted out in my head. GAIA really will provide the best inference problem ever encountered in astrophysics.


class2008, day two

This morning concentrated on understanding galaxies in large surveys. Among a set of interesting talks about galaxy classification, Boris Haeussler gave a nice talk in which he put the standard 2-d galaxy fitting codes through their paces, and found some very interesting things, including underestimated errors—even when he puts in fake data for which the fitting codes are not making approximations! Vivienne Wild spoke about a robust PCA and its use in understanding rare populations such as post-starbursts and their role in galaxy continuity. Two of my favorite topics in one talk! The PCA adjustment is very smart although somewhat ad-hoc (not described in terms of probabilistic inference). The post-starburst work is even better; it confirms our results that suggest that post-starbursts are key in the evolution of stellar mass from the blue to red sequences. Many other good contributions too numerous to mention, with a lot of people working on optimal extraction of information from spectra; very encouraging for the future of spectroscopy.


class2008, day one

The afternoon of the first day of Classification and Discovery concentrated on classification methods, almost all supervised (learn with training set, run on larger data). I am largely against these methods, in part because very few of them make good use of the individual noise estimates, and in part because your training data are never the same—in important respects—as your real data. However, a nice discussion ensued, led in large part by Alexander Gray (Georgia Tech); in this I argued for generative models for classification, but of course these are only possible when you have a good model of both the Universe and your hardware!


more writing

Spent my research time today cleaning up my class2008 proceedings, which is now a full-on polemic about massive data analysis. In the process, I learned something about minimum message length in Bayesian model selection; we have been using this but I didn't know how rich the subject is (though I don't like the persistent comment that it encodes Occam's razor—another good subject for a polemic). On the airplane to Germany I will have to convert all this into a talk.


wrote like the wind

In a miraculous couple of hours, I cranked out the remainder of our class2008 proceedings—the necessity of automating calibration, and methodologies for automated discovery in the context of a comprehensive generative model—to make a zeroth draft. In writing this, I realized that we have actually demonstrated most of the key concepts in this automated discovery area in our faint-source proper-motion paper.

Lang has promised me not just criticism, but a direct re-write of parts, within 24 hours.



In the small amount of research time I got today, I wrote my Class2008 proceedings as rapidly as possible.


catalogs as image models

I worked more on my position on catalogs, with some help from Lang. Here are some key ideas:

  • Catalogs originated as a way for astronomers to communicate information about images. For example, Abell spent thousands of hours poring over images of the sky; his catalog communicated information he found in those images, so that other workers would not have to repeat the effort. This was at a time that you couldn't just send them the data and the code.
  • Why did the SDSS produce a catalog and didn't just release the images? Because people want to search for sources and measure the fluxes of those sources, and people do this in standard ways; the SDSS made it easier for them by pre-computing all these fluxes and making them searchable. But the SDSS could have produced a piece of fast code and made it easy to run that code on the data instead; that would have been no worse (though harder to implement at the present day).
  • One of the reasons people use the SDSS catalogs is not just that they are easy to use, but that they contain all of the Collaboration's knowledge about the data, encoded as proper data analysis procedures. But here it would have been more useful to produce code that knows about these things than a dataset that knows about these things, because the code would be readable (self-documenting), re-usable, and modifiable. Code passes on knowledge, whereas a catalog freezes it.
  • The catalogs are ultimately frequentist, in that hard decisions (about, say, deblending) are made based on arithmetic operations on the data, and then the down-stream data analysis goes according to those decisions, even when the real situation is that there is uncertainty. If, instead of a fixed catalog there was a piece of code that takes any catalog and returns the likelihood of that catalog given the imaging, we could analyze those decisions probabilistically and do real inference.

And other Important Things like that.


catalogs polemic

I started writing my contribution to Classification and Discovery in Large Astronomical Surveys; I am writing about a generative model of every astronomical image ever taken. But right now the part I am most interested in is the part about catalogs being—explicitly—bayesian models of the imaging on which they are based. If the community adopted this point of view, it would have a number of advantages, in the documentation, usability, communication, interoperability, construction, and analysis of astronomical catalogs. I am trying to make this argument very clear for the proceedings.


lucky supernova, classification of algorithms

Alicia Soderberg (CfA) gave the astro seminar today, on a supernova she discovered by a soft x-ray flash apparently immediately at shock break-out, in other words at the beginning of the explosion, long before the optical came to maximum light. This permitted the study of the supernova from beginning to end. Unfortunately, her discovery involved an incredible amount of luck and we will have to wait for the next generation of x-ray experiments to discover these routinely. In answer to an off-topic question from me, she said that to her knowledge, there is no pre-cursor activity that precedes break-out. I asked because this would be an interesting effect to look for in historical data sets.

In the evening I finished writing up my short document that describes my classification of standard data-analysis algorithms.


insane theories, super-k-means

I can't say I did much research today, but while I failed to do research, Bovy (who is also attending a scientific meeting) looked at contemporary models that violate transparency to fix the supernovae Ia results in an Einstein—de Sitter Universe. These models are somewhat crazy, because they end up building epicycles to fix a problem that isn't really a problem, but in principle we will rule them all out with BOSS.

In my sliver of research time (and with Roweis's help), I figured out that PCA, k-means, mixture-of-gaussians EM, the analysis we did in our insane local standard of rest paper, and taking a weighted mean are all different limits of one uber-problem that consists of fitting a distribution function to data with (possibly) finite individual-data-point error distributions. I am trying to write something up about this.


Tolman and Etherington

In working on the More paper, I found myself looking through cosmography literature from 1929 through 1933. There is a series of papers by Tolman, in which he works out the Tolman test for the expansion of the Universe, which I think of as being a test of transparency and Lorentz invariance. Tolman worked out the test in the context of one world model (de Sitter's); his interest was in understanding the possible physics underlying the steady-state model; Etherington generalized it to a wider range of world models in 1933. After Etherington's generalization, the community should have realized that the test doesn't really test expansion per se, but it does test relativity and electromagnetism in that context.