Description

The purpose of this project is to learn about, get practical experience with, and develop practical applications for, Quantum Annealers.

Quantum Annealing is a form of quantum computing based on quantum tunnelling. It is different from the kind of quantum computing you will encounter in the Quantum Computing III course if you are taking that (which is not mandatory). Unlike more standard (gate-model) quantum computing it is more akin to simulated annealing, and works by a dissipative evolution of an Ising spin Hamiltonian (i.e. a system of coupled qubits) in order to find the ground state. It is effective at solving discrete problems when the search spaces have many local minima. Therefore the crux of solving any problem lies in formulating its solution as the minimum of an Ising model. Once in this form many practical problems can be tackled: for example travelling salesman problems, route finding, bus-scheduling, traffic-flow, protein-folding, financial portfolio management, and so forth. Due to the already large size of available machines (7000 qubits) there have already been many successful real-world applications of this technique.

What will I do in this project?

You will learn about, remotely access and code Quantum Annealers using the D-wave software environment (linked below). Using python you will develop code for solving one or several problems of your choosing. These could be more physical, or discrete optimisation problems, or even number theoretic ones (for example it is possible to solve Diophantine problems such as finding Hardy-Ramanujan "taxicab" numbers using this method). Note that the Epiphany term will be taught remotely.

Prerequisites

Mathematical Physics II (or equivalent Physics module covering Quantum Mechanics) is required. Ability to programme in python to the level covered in first year Programming (other programming experience is fine if you didn't take the Programming I module in Maths).

Corequisites

Quantum Computing III or Quantum Mechanics III (or equivalent Physics modules).

Resources

A good place to start to get a few details and pictures is Wikipedia-Quantum Annealing. There is an excellent introduction and practical starting point in the D-wave documentation D-Wave: what is quantum annealing? . For one of several recent applications in finance see Phillipson and Bhatia .