Astronomical crowdsourcing

I just read a short piece in this month's issue of Nature Physics about a number of astronomical discoveries made this past month. One exciting discovery was of a Neptune-sized exoplanet found in a complicated orbit around four stars about 5000 light years away. I find this absolutely amazing, and even more so considering that it was found by a crowdsourcing website called PlanetHunters.org that recruits public users in identifying transits from a large database of astronomical data.

This is one example of data-centric science, but it is slightly different from the way I've presented it in past posts. In particular, this is an observation that was not driven by some unanswered question. Rather, people were simply looking at data to find planets.

I think that this is really cool, but I do wonder why somebody hasn't written some code to do the data analysis.

An optical method for finding exoplanets

This morning I read an Optics Letter from 2005 entitled "Optical Vortex Coronograph" that described an optical system for detecting exoplanets orbiting a star that could be up to 1e8 times brighter than the planet's reflected light.

The system is detailed below. In a traditional coronograph (i.e. one not employing a vortex phase mask), the mask in focal plane FP1 is a zero light-transmitting block of very small angular extent. Because the image of a star that the system is pointed at is formed in plane FP1, its light is filtered out of the final image by this mask. The Lyot stop in plane PP2 then blocks the light from the star that is diffracted by the mask. The resulting intensity collected in plane FP3 is largely contributed to by any point source near the star, e.g. an exoplanet.

 

What is not clear to me is why replacing the block in FP1 by a vortex phase mask improves the performance of the coronograph. Mathematical arguments are presented, but I find an intuitive explanation lacking.