Competition Shines Light on Dark Matter

The world's brightest physicists have been working for decades on solving one of the great unifying problems of our universe. It is a problem that explores our place in the cosmos and, as was the case with Newton's law of gravitation and Einstein's theory of relativity, would provide a generational leap in our understanding of the nature of the Universe if solved. Recently, top experts celebrated an exciting breakthrough from an unexpected place.

On May 23, a consortium of the very best from NASA, the European Space Agency, and the Royal Astronomical Society posted the problem on the data-mining website Kaggle and Challenge.gov for all the world to weigh in. In less than a week, Martin O'Leary, a PhD student in glaciology, had crafted an algorithm that outperformed the state-of-the-art algorithms most commonly used in astronomy for mapping dark matter.

[Gregory PS: as of June 29, there are 29 competitors which exceeded the state-of-the-art benchmark - see www.kaggle.com/c/mdm/Leaderboard ]

Chalk another one up for the power of crowdsoucing, and this Admnistration's commitment to using prizes and challenges to find solutions to some of our most pressing problems-here on Earth as well as in the furthest reaches of space!

The posted problem had to do with how scientists can go about mapping "dark matter." Our Universe, it turns out, behaves as if it contains far more matter than we can currently observe. That is, calculating the mass of the entire Universe returns a sum far greater than the sum of all the stars and reflective objects that scientists have been able to detect. We are missing something, it seems. And that's important because it means that either some basic principles about the Universe are wrong or, as most scientists believe, there are kinds of matter in the Universe that we have yet to discover. This hypothesized unobservable matter doesn't reflect or omit light, hence the name "dark matter." The challenge is to develop an algorithm that can mathematically, at least, "detect" this dark matter.

Read more.