stellar ages and fish-eye cameras

Ness and I are getting red-giant ages from APOGEE spectroscopy using The Cannon and a training set from Kepler. We worked on making plots that would help us understand where this age information is coming from. Options include: Chromospheric activity (which decreases with time in stars as the magnetic field decays), dredge-up of C, N, O from the nucleosynthetic core (which pollutes the surface abundances over time), trace element abundances (which might indicate birth place and time beyond the information in gross indicators like metallicity and alpha-enhancement), and non-LTE effects (which might be different in different stars since convection patterns and scale are a function of mass).

Tom Herbst (MPIA) showed me his fish-eye all-sky camera and data acquisition system, and we discussed science projects for it with Markus Pössel (MPIA). The whole system is on the roof, so its computer and controller and everything are isolated from all the building systems to protect the building and its IT infrastructure from lightning strikes!

Rix and I asked Yuan-Sen Ting (Harvard) to compute derivatives with respect to elements for the stellar models being used to analyze the APOGEE data. The idea is that we want to ask how well we can linearize the models around fiducial points and then model (and therefore make measurements from) the spectra.

Dr. Berry Holl

I was the opponent today in the PhD defense of Berry Holl (Lund). As opponent, my role was to draw out the content of the thesis with questions and also subject the candidate to (extremely public) scientific scrutiny. It was great fun, in part because the thesis was so good, and in part because Holl handled the questions so well and so completely. His thesis has a lot of challenging linear algebra in its core (and I love linear algebra) but in the end I found myself spending most of my time on the 2/7 of his thesis that dealt with radiation damage to the Gaia CCDs. The question Holl answered is what that damage is likely to do to the data and to the precise measurement (and more importantly modeling) of the transit times of the stars. The conclusion we came to during the event is that the Gaia science data will actually contain more information about charge-transfer inefficiency and radiation damage than any other source of data before or during the mission. And that includes all the data that have been taken expressly for the purpose of learning about radiation damage!

Many Gaia projects have this character: The nasty systematic effect (general relativity in the Solar System, substellar companions, surface convection on giants) that matter at Gaia precision turn Gaia into the world's most sensitive measuring device for those effects. So in particular, at the end of the Gaia mission, we will have a great deal of precise quantitative knowledge about the behavior of CCDs that have been damaged; a great deal of precise knowledge about CCDs in general, really.

Holl passed his defense unanimously, of course, and it is with this post that I congratulate him and welcome him to the community of scholars!

electromagnetism

In a strange coincidence (though perhaps not totally unexpected), I am teaching advanced electromagnetism to a few of our seniors (fourth-year undergraduates) and at the same time, after a long session staring at images from the Project 1640 coronograph, Fergus and I decided that we need to at least discuss and explore the possibility that we might model the electromagnetic fields inside the instrument. That is, we need to figure out if it is possible to model not just the intensity field but the electric and magnetic fields (or, in the steady state, you can think of it as an amplitude and a phase at the detector surface). To my knowledge, except in radio astronomy, this has not been done: Optical (and near-optical) astronomers think of the "thing" in the telescope as being the intensity field (or worse, photons), not the electric and magnetic fields. The challenge is: Superposition really applies only to the electric and magnetic fields, not the intensity field; but at the same time, CCD-like detectors only measure (a noisy sampling of) the intensity field. Saturday night found me starting to write and test some very simple code, with delta-function sources and delta-function pixels.

segmenting images and inferring motion

Over in Fergus's computer science group, Deqing Sun (Brown) gave a very nice talk about measuring motion in image sequences (think movies) by building a generative model of moving layers with sharp boundaries. He constructs a prior over image segmentations by segmenting the image using threshold-crossing of a (very local) smooth Gaussian process; this permits an analytic prior. The results are beautiful and effective and conform to common sense and also come close to world-record performance against quantitative benchmark tests (with known ground truth). His system performs well in part because it is a (approximate, simplified, sensible) full generative model for the data: It has a large number of parameters, a proper prior over those parameters, and a sensible likelihood function, and he can optimize it. He didn't try to sample from the posterior PDF, but he has only worked (so far) at very high signal-to-noise.

CMYK

I finally coded up and got running a RGB-to-CMYK conversion that is based on the physical properties of the printing device. The (perhaps insane) idea I have in mind is the following: Our RGB images of SDSS galaxies, if you view them on a normal RGB monitor, have a definite, quantitative relationship between the light hitting your eyes and the intensity hitting the telescope. It is non-trivial and non-linear, but it is quantitatively traceable and (lossy) invertible. When we print these out on a CMYK printer, this is not true, in part because the RGB-to-CMYK conversion is heuristic and doesn't in any way model the physical process of light hitting the page, being attenuated by the ink, and then reflecting. This process, for example, is multiplicative (not subtractive as is usually said). It is multiplicative with multipliers less than one, and (strongly) wavelength-dependent. The model I have built of this process can (in principle) make it once again true that the reflected light from the page (when viewed with a standard room illumination, say) has properties that are quantitatively and (lossy) invertible back to the intensity falling on the telescope. Why do I do these thing?

Intelligent Systems, day 3

In the morning we continued our discussions of multi-exposure imaging. I love the style of this computational imaging group: Work hard all day, but work equals sitting in the garden arguing! We particularly discussed what you could believe about a model made by forward-modeling through the PSF (that is, a deconvolution). My position is that because there are near-degeneracies in such modeling, you have to return a posterior probability distribution over deconvolved images (or probably a sampling of that); Fergus thought it might be possible to make an adaptive model complexity designed to maintain unimodality in the posterior PDF. Either way, representing the posterior PDF is not going to be trivial! We postponed all such issues to subsequent projects; we have a scope for a first paper that skirts such issues.

In the afternoon, Christopher Burger, Stefan Harmeling, and I discussed making probabilistic models of CCD bias, dark-current, flat, and read-noise frames, from a combination of zero, dark, flat, and science data. We decided to make some experiments with a laboratory CCD camera and, if they work, repeat them with archival HST data.

computational photography, gravitomagnetism

Adrian Price-Whelan and I met with some prospective undergraduate researchers, Abi Polin and Layla Quinones, to look at computational photography things; they are both amateur photographers. We discussed the baby steps towards doing some calibration of commercial digital cameras.

In the afternoon, Scott Hughes (MIT) brought us up to date on the two-body problem in general relativity, where there has been enormous progress in the six years or so since his last visit. He showed that the leading-order Newtonian approximation of GR contains a gravitometric term, which (in my opinion) should have been discovered way before GR: It permits the speed of gravity to be finite but objects to continue in Keplerian orbits! Hughes's talk was not particularly about this, but I have been thinking about it ever since I read Sciama's excellent (out of print) book.

dark current

Price-Whelan made a remarkable discovery today—which may be false or an error of some kind, so don't quote me—that commercial digital cameras do not always subtract the dark frame, and the dark currents of the pixels are significant and vary from pixel to pixel. If this is right, we are going to be able to vastly improve the sensitivity of the cameras we have. Time to start writing the paper!

back to work

Whew! I didn't want to go three days without something. I helped Hou find the SDSS-III MARVELS data; and later in the day Bovy pointed out to me that we could do a fast project with them based on our predictions of Hipparcos star radial velocities (from our moving groups work). I had lunch with Jagannath, where we talked about the origins of tidal streams (and the collapse of the wave function, which I am suspicious never happens). This afternoon, Price-Whelan and I got robust median-absolute-difference estimates for image noise implemented because we want to be very robust and very precise in our analysis of the noise in commercial digital camera images.

digital SLRs

Adrian Price-Whelan and I figured out today the dependence of the RAW-file median levels and noise on exposure time and ISO for the Canon Digital Rebel XSi cameras we have been testing. We are trying to build a noise models for the pixels—on average and individually—as a function of illumination and camera settings. I have always wondered if changing the ISO setting on a digital camera changes the bias or anything else about the readout electronics, or whether it just changes the way the camera converts the RAW file into a human-viewable JPEG. We started to get some evidence today that it actually changes the bias on the CCD, but we haven't built a noise model yet. That's the project for the coming week.