Quantum algorithms for big data

This work package will develop quantum algorithms for tasks which occur in “big data” applications: those where the quantities of data produced are so large that traditional data processing methods are inadequate. We have identified several specific directions where there is good preliminary evidence that quantum algorithms could substantially outperform classical computing. Each models a practically relevant task in sufficient generality to enable quantum speedups that are applicable across many different problems. These are sketching, property testing, and systems of partial differential equations.

Workpackage leader: Ashley Montanaro (University of Bristol)