\n

\nTh ere are many practical and theoretical challenges in the emerging area of quantum information processing\, which seeks to optimally use the information embedded in the state of a quantum system to solve previou sly intractable computational problems and revolutionize simulation. T he engineering goal is to develop scalable quantum hardware that circu mvents the physical limits on the computational power of existing tech nologies\, which are ultimately constrained by energy dissipation as t he physical size of the components is reduced to the nanometer scale. In parallel with such “practical” difficulties\, new theory is req uired to understand the limitations of quantum media and capitalize on the advantages of quantum superposition and entanglement. This includ es the creation of new quantum algorithms that are targeted toward rea l-world problems\, e.g.\, in finance\, chemistry\, and medicine\; a st udy of the required resources to achieve a particular outcome\, as wel l as methods to efficiently characterize such resources\; and the deve lopment of novel protocols for secure quantum-enhanced communication\, as well as classical ‘post-quantum encryption’ methods that are i mmune to quantum hacking. For all of these\, quantum information theor y relies on and draws inspiration from many different aspects of mathe matics and theoretical computer science\, including geometry\, group t heory\, functional analysis\, number theory\, operator theory\, probab ility theory\, topology\, complexity theory\, and learning theory. Fur thermore\, the recent resolution of Connes’ embedding conjecture usi ng quantum information-theoretic methods shows that ideas and results from quantum information theory can also influence research in pure ma thematics. URL:https://www.physics.wisc.edu/events/?id=6454 END:VEVENT END:VCALENDAR