**Summary**

To address questions in modern physics such as “what is the structure of matter inside neutron stars?” we need better computational methods to evaluate the interplay of fundamental forces between elementary particles. To-date the response to such questions rests on numerical computer simulations that are inherently limited. In this project, we develop new theoretical tools for quantum simulations of non-Abelian problems in high energy physics (HEP), and HEP problems beyond one dimension. Our work is conducted in close collaboration with experimental groups to design robust and feasible simulation schemes that are custom-designed to particular quantum platforms. We will integrate methods from machine learning and artificial intelligence to create a conceptually new framework for hybrid quantum-classical simulations. These novel tools are expected to find useful applications beyond HEP in material science and chemistry. Through collaborations with Creative Destruction Lab and the Vector Institute we plan to accelerate the path to industry deployment.

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