Juan Felipe Carrasquilla Alvarez

I am a physicist broadly interested in the ideas at the intersection between condensed matter theory, quantum computing, and machine learning. A significant fraction of my research is naturally devoted the development and use of large-scale numerical simulations, with an emphasis on Quantum Monte Carlo, Machine Learning, and (a little bit of) Tensor Networks, aimed at tackling challenging theoretical and technological problems in quantum many-body physics and quantum computing.

Some highlights of my research

• We revitalized the connection between the areas of computer vision and the theory of strongly correlated many-body systems. We showed that neural networks have the ability to learn representations of ordered and topologically ordered states of matter. Published in Nature Physics


• We used Restricted Boltzmann machines (RBMs) to perform quantum state tomography in systems of unprecedented size. Arxiv link


• We developed Monte Carlo simulations that led to a novel approach to search for potential topological quantum spin-liquids on a broad class of materials. Published in Nature communications .