THE Meeting, day 2

Today at the Terra Hunting Experiment meeting, we got deeply into software and calibration issues. The HARPS family of instruments are designed to be extremely stable in all respects, but also monitored by a Fabry–Perot signal imprinted on the detector during the science exposures. The calibration data are taken such that the data obtain absolute calibration information (accuracy) from arc exposures and relative calibration (precision) from F—P data. There was discussion of various replacements for the arcs, including Uranium–Neon lamps, for which the atlas of lines is not yet good enough, and laser-frequency combs, which are not yet reliable.

Another big point of discussion today was the target selection. We (the Experiment) plan to observe a small number (40-ish) stars for a long time (1000-ish individual exposures for each star). The question of how to choose these targets was interesting and contentious. We want the targets to be good for finding planets! But this connects to brightness, right ascension, stellar activity, asteroseismic mode amplitudes, and many other things, none of which we know in advance. How much work do we need to do in early observing to cut down a parent sample to a solid, small sample? And how much can we figure out from public data already available? By the end of the day there was some consensus that we would probably spend the first month or so of the project doing sample-selection observations.

At the end of the day we discussed data-analysis techniques and tellurics and stellar activity. There are a lot of scientific projects we could be doing that would help with extreme-precision radial-velocity measurements. For instance, Suzanne Aigrain (Oxford) showed a toy model of stellar activity which, if correct at zeroth order, would leave an imprint on a regression of stellar spectrum against measured radial velocity. That's worth looking for. The signal will be very weak, but in a typical spectrum we have tens of thousands of pixels, each of which has signal-to-noise of more than 100. And if a linear regression works, it will deliver a linear subspace-projector that just straight-up improves radial-velocity measurements!