It is definitely the golden age in cosmology because of this unique confluence of ideas and instruments. We live in a very peculiar universe—one that is dominated by dark matter and dark energy—the true nature of both of these remains elusive. Dark matter does not emit radiation in any wavelength and its presence is inferred by its gravitational influence on the motions of stars and gas in its vicinity. Dark Energy, discovered in 1998, meanwhile is believed to be powering the accelerated expansion of the universe. Despite not knowing what the dark matter particle is or what dark energy really is, we still have a very successful theory of how galaxies form and evolve in a universe with these mysterious and invisible dominant components. Technology has made possible the testing of our cosmological theories at a level that was unprecedented before. All of these experiments have delivered very exciting results, even if they're null results. For example, the LHC, with the discovery of the Higgs, has given us a lot more comfort in the standard model. The Planck and WMAP satellites probing the leftover hiss from the Big Bang—the cosmic microwave background radiation—have shown us that our theoretical understanding of how the early fluctuations in the universe grew and formed the late universe that we see is pretty secure. Our current theory despite the embarrassing gap of not knowing the true nature of dark matter or dark energy, has been tested to a pretty high degree of precision.
It's also consequential that the dark matter direct detection experiments have not found anything. That's interesting too, because that's telling us that all these experiments are reaching the limits of their sensitivity, what they were planned for, and they're still not finding anything. This suggests paradoxically that while the overall theory might be consistent with observational data, something is still fundamentally off and possibly awry in our understanding. The challenge in the next decade is to figure out which old pieces don't fit. Is there a pattern that emerges that would tell us, is it a fundamentally new theory of gravity that's needed, or is it a complete rethink of some aspects of particle physics that are needed? Those are the big open questions.
PRIYAMVADA NATARAJAN is a professor in the Departments of Astronomy and Physics at Yale University, whose research is focused on exotica in the universe—dark matter, dark energy, and black holes. Priyamvada Natarajan's Edge Bio Page.
We know there's a law of nature, the second law of thermodynamics, that says that disorderliness grows with time. Is there another law of nature that governs the complexity of what happens? That talks about multiple layers of the structures and how they interact with each other? Embarrassingly enough, we don't even know how to define this problem yet. We don't know the right quantitative description for complexity. This is very early days. This is Copernicus, not even Kepler, much less Galileo or Newton. This is guessing at the ways to think about these problems.
SEAN CARROLL is a research professor at Caltech and the author of The Particle at the End of the Universe, which won the 2013 Royal Society Winton Prize, and From Eternity to Here: The Quest for the Ultimate Theory of Time. He has recently been awarded a Guggenheim Fellowship, the Gemant Award from the American Institute of Physics, and the Emperor Has No Clothes Award from the Freedom From Religion Foundation. Sean Carroll's Edge Bio Page
In modern science, and I include the humanities here, science in a German sense of science—rigorous scholarship across all domains—in modern science we've gotten used to the idea that science doesn't offer meaning in the way that institutional religions did in the past. I'm increasingly thinking that this idea that modernity puts us in a world without meaning—philosophers have banged on about this for a century-and-a-half—may be completely wrong. We may be living in an intellectual building site, where a new story is being constructed. It's vastly more powerful than the previous stories because it's the first one that is global. It's not anchored in a particular culture or a particular society. This is an origin story that works for humans in Beijing as well as in Buenos Aires.
It's a global origin story, and it sums over vastly more information than any early origin story. This is very, very powerful stuff. It's full of meaning. We're now at the point where, across so many domains, the amount of information, of good, rigorous ideas, is so rich that we can tease out that story.
DAVID CHRISTIAN is Professor of History, Macquarie University, Sydney; Author, Maps of Time: An Introduction to Big History. David Christian's Edge Bio Page
People have to go around measuring things. There's no escape from that for most of that type of work. There's a deep relationship between the two. No one's going to come up with a model that works without going and comparing with experiment. But it is the intelligent use of experimental measurements that we're after there because that goes to this concept of Bayesian methods. I will perform the right number of experiments to make measurements of, say, the time series evolution of a given set of proteins. From those data, when things are varying in time, I can map that on to my deterministic Popperian model and infer what's the most likely value of all the parameters that would be Popperian ones that would fit into the model. It's an intelligent interaction between them that's necessary in many complicated situations.
PETER COVENEY holds a chair in Physical Chemistry, and is director of the Centre for Computational Science at University College London and co-author, with Roger Highfield, of The Arrow of Time and Frontiers of Complexity. Peter Coveney's Edge Bio Page.
My vision of life is that everything extends from replicators, which are in practice DNA molecules on this planet. The replicators reach out into the world to influence their own probability of being passed on. Mostly they don't reach further than the individual body in which they sit, but that's a matter of practice, not a matter of principle. The individual organism can be defined as that set of phenotypic products which have a single route of exit of the genes into the future. That's not true of the cuckoo/reed warbler case, but it is true of ordinary animal bodies. So the organism, the individual organism, is a deeply salient unit. It's a unit of selection in the sense that I call "a vehicle".
There are two kinds of unit of selection. The difference is a semantic one. They're both units of selection, but one is the replicator, and what it does is get itself copied. So more and more copies of itself go into the world. The other kind of unit is the vehicle. It doesn't get itself copied. What it does is work to copy the replicators which have come down to it through the generations, and which it's going to pass on to future generations. So we have this individual replicator dichotomy. They're both units of selection, but in different senses. It's important to understand that they are different senses.
RICHARD DAWKINS is an evolutionary biologist; Emeritus Charles Simonyi Professor of the Public Understanding of Science, Oxford; Author, The Selfish Gene; The Extended Phenotype; Climbing Mount Improbable; The God Delusion; An Appetite For Wonder; and (forthcoming) A Brief Candle In The Dark. Richard Dawkins's Edge Bio Page
The reasons why I'm engaged in trying to lower the existential risks has to do with the fact that I'm a convinced consequentialist. We have to take responsibility for modeling the consequences of our actions, and then pick the actions that yield the best outcomes. Moreover, when you start thinking about—in the pallet of actions that you have—what are the things that you should pay special attention to, one argument that can be made is that you should pay attention to areas where you expect your marginal impact to be the highest. There are clearly very important issues about inequality in the world, or global warming, but I couldn't make a significant difference in these areas.
JAAN TALLINN is a co-founder of the Centre for the Study of Existential Risk in Cambridge, UK as well as the Future of Life Institute in Cambridge, MA. He is also a founding engineer of Kazaa and Skype. Jaan Tallinn's Edge Bio Page
...Today, you can send a design to a fab lab and you need ten different machines to turn the data into something. Twenty years from now, all of that will be in one machine that fits in your pocket. This is the sense in which it doesn't matter. You can do it today. How it works today isn't how it's going to work in the future but you don't need to wait twenty years for it. Anybody can make almost anything almost anywhere.
...Finally, when I could own all these machines I got that the Renaissance was when the liberal arts emerged—liberal for liberation, humanism, the trivium and the quadrivium—and those were a path to liberation, they were the means of expression. That's the moment when art diverged from artisans. And there were the illiberal arts that were for commercial gain. ... We've been living with this notion that making stuff is an illiberal art for commercial gain and it's not part of means of expression. But, in fact, today, 3D printing, micromachining, and microcontroller programming are as expressive as painting paintings or writing sonnets but they're not means of expression from the Renaissance. We can finally fix that boundary between art and artisans.
...I'm happy to take claim for saying computer science is one of the worst things to happen to computers or to science because, unlike physics, it has arbitrarily segregated the notion that computing happens in an alien world.
NEIL GERSHENFELD is a Physicist and the Director of MIT's Center for Bits and Atoms. He is the author of FAB. Neil Gershenfeld's Edge Bio Page
What interests me is how bits and atoms relate—the boundary between digital and physical. Scientifically, it's the most exciting thing I know. It has all sorts of implications that are widely covered almost exactly backwards. Playing it out, what I thought was hard technically is proving to be pretty easy. What I didn't think was hard was the implications for the world, so a bigger piece of what I do now is that. Let's start with digital.
Digital is everywhere; digital is everything. There's a lot of hubbub about what's the next MIT, what's the next Silicon Valley, and those were all the last war. Technology is leading to very different answers. To explain that, let's go back to the science underneath it and then look at what it leads to.