Our detectors today are almost perfect, so it's hard to gain anything by building better detectors. The only way we can get more information about planets around other stars, or distant galaxies, is to make larger telescopes. That's why we have to build these big observatories in Hawaii, and it's why we have to build the James Webb Space Telescope. It isn't because we want to spend billions of dollars, it's because we've been doing space science for four hundred years, and the low-hanging fruits have been picked.
To answer some of the more profound questions -- Is there life around another star? How did the first galaxies form? -- requires us to look at some very faint things, and we need large, complex facilities to do that.
That unfortunately moves you away from a traditional academic model of the solitary scientist writing a solitary paper to one where you need a complex machine and a complex organization like this one. And so the other thing you're seeing is a move towards teams; increasingly, it's large teams that are doing the really high impact research and that's because you need a multidisciplinary skill-set to do this stuff. This institution is an expression of that, and in some ways was slightly ahead of its time. We have scientists here, yes, but we also have engineers and software people---we've created a layer of interdisciplinary skills, and that layer allows astronomers to interface with very complicated machines like the Hubble Space Telescope in a very straightforward way. We've hidden the complexity.
It's a totally different paradigm, and it can be tough for some astronomers to wrap their heads around it, because they're wedded to the ideal of the lone astronomer going up to the mountaintop with his lab book and his worshipful post docs following behind. That's a model that has huge romance and pull, but it's actually not very effective anymore.
What are some of the most notable successes of the team model?
Mountain: Well take Adam Reiss and his team, who, together with two other teams, won the Nobel Prize last year for discovering dark energy. An individual couldn't have made this discovery. To do what they did, you needed people who understood the theory of supernova explosions, you needed people to figure out how to run these complicated telescopes, both on the ground and in space, and you needed people worrying about data and sophisticated statistics. And this is all very complicated stuff; the person who's an expert in Bayesian statistics and sampling methodologies isn't quite the same person who's an expert in getting the maximum signal from a really faint supernova. But in the end, there's a pay off: Reiss and his team spent most of their Nobel money getting the whole crew to the Nobel ceremony.
Now let's think about where the team model might take us next. Think about the big question right now: Are we alone? What would it take to answer that question? We've got the Kepler Space Telescope telling us that there are probably planets around every star, so we know that. But now we have another problem: these planets are really, really faint. So faint, in fact, that you need a big telescope to see them, and it has to be quite sophisticated because the planets are next to a very bright star. This is right at the limits of optical technology, which means you need experts in optics and telescopes. So let's say you get a spectrum of the planet's atmosphere, which will allow you to see its chemical makeup. Even then you're still not in the clear, because you've got to understand atmospheric circulation and ecosystems, not to mention how planets form.