Events by date

Title: Quantum information science for combinatorial optimization

Speaker: Stephen Jordan Affiliation: Microsoft Quantum & University of Maryland Zoom: Please email Emma Watson

Abstract:

Due to input-output bottlenecks, quantum computers are expected to be most applicable to problems for which the quantity of data specifying the instance is small but the computational cost of finding a solution is large. Aside from cryptanalysis and quantum simulation, combinatorial optimization provides some of the best candidates for problems of real-world impact fitting these criteria. Many of these problems are NP-hard and thus unlikely to be solvable on quantum computers with polynomial worst-case time complexity.