Hello! Our lab is a theory lab and my group and I are working on basic questions related to information theory, quantum theory, general relativity and cosmology. Here is the basic idea:

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 is a short video about what we do in cosmology. Here is a paper reviewing some of our progress. 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.

Here is some advice I wrote for new grad students: Handbook

## News

## We discovered two new acceleration-induced quantum effects

Here is an Article in Scientific American about our discovery of two new acceleration-induced quantum effects that generalize the Unruh effect. One is the new phenomenon of acceleration-induced transparency and the other discovery is that acceleration-induced light emission (the Unruh effect) can be stimulated, for example, by a laser.

## Three group members, and Google, develop Tensorflow Quantum

Congratulations to our three group members, Michael Broughton, Guillaume Verdon and Evan Peters for successfully developing and publishing Tensorflow Quantum in collaboration with Google. Have a look at their paper here.

## We are working with Google on Quantum Machine Learning

My group received a Google Faculty Research Award to work with Google on Quantum Machine Learning. My Ph.D. student Guillaume Verdon and my Master's student Evan Peters are at the forefront of this work.