On the highest level of abstraction, the laws of nature are about how the information content in natural processes evolves. On this level, it matters that the flow and processing of all information in the universe is subject to quantum theory and general relativity.
On one hand, this means that deep insights about the laws of nature are to be gained by developing and applying information-theoretic methods. These are insights, for example, into the origin of structure in the universe and into the fate of what falls into a black hole. (Here's an interview that I gave to the YouTube channel Scholarly about some of our research. Here's the video of a talk I gave at Perimeter Institute.) On the other hand, there are concrete applications in science and technology, such as in quantum communication and quantum computing.
We are also working on information-theoretic aspects of engineering and biology, and we have started to study deep learning. Oh, and yes, we showed that one can integrate by differentiating - see for example the two equations on the top right of this page. No kidding: Journal, Arxiv, Journal, Arxiv, Video. The new methods are now implemented in Maple and are making Maple (from version Maple2019 onwards) faster and more powerful than the competition in integration and integral transforms.
- June 18, 2018
We published a paper in PRL and another paper in Foundations of Physics with a fully covariant prediction for the signature of Planck scale physics in the Cosmic Microwave Background. Here's one of the popular news items about these results.
- May 10, 2016
Here is a popular science news item about David Layden's Master's research. Congratulation, David!
- Feb. 28, 2016
I am co-organizing the RQI-N 2016 conference. We'll have it here at the Institute for Quantum Computing, 21-24 June 2016.