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.

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.

To detect the presence of dark matter, the consortium asked competition entrants to use a phenomenon called gravitational lensing. The process stems from Einstein’s theory of gravity, which predicts that as light emanates from a galaxy and passes through dark matter, the path the light takes is distorted. The amount of distortion depends on the amount of dark matter present along the line of sight between Earth and the galaxy. Therefore, by identifying the distortions of light coming from an array of luminous galaxies, one can generate a three dimensional dark matter-map of the Universe.

Since the competition began, entrants from all over the world have used different techniques to try to measure these distortions. O'Leary applied techniques used in his field – glaciology - such as detecting edges in glacier fronts from satellite images. This might seem like an unlikely source of progress, but it is exactly why competitions like this one are so often successful: they encourage people who usually focus on problems unrelated to the question at hand to apply their problem-solving skills to analogous problems in other fields. So it is that the study of glaciers on Earth has now deepened our understanding of the cosmos.

There are countless approaches that can be applied to any scientific problem, but it is impossible to know at the outset which technique will achieve the most accurate result. Opening up a problem to analysts, data-miners, and researchers based all over the world in a vast spectrum of scientific fields, as Kaggle and Challenge.gov do, increases the likelihood of finding more suited methodologies and more accurate results.

The Mapping Dark Matter competition still has almost two months to run, so even more innovation is likely. The winner will receive an invitation to work with a team of NASA experts to turn the winning idea into a working tool—and, just perhaps, to bring dark matter to light.

Jason Rhodes is an astrophysicist at the Jet Propulsion Laboratory

