Faculty Advisor: PhD Researcher, University of Cambridge

Program Start Time: TBD (meetings will take place for around one hour per week)

Research Practicum Introduction

From the foundations to the applications: how can the quirky yet fundamental physics of quantum mechanics be turned into disruptive technologies? Quantum computing and related technologies promise to revolutionize fields such as pharmacology, cryptography and machine learning. Therefore, a worldwide research effort is focused on this technology as the scientific and commercial recompense would be enormous.

This program introduces students to the mathematical principles of quantum mechanics and its implementation in physics. With these primitives in place, we will move to a discussion of the application of quantum mechanics in state-of-the-art technologies. Quantum technologies are currently used for artificial intelligence, revolutionary drug discovery, financial portfolio optimisation and even the creation of art! We will explore these applications and everything in between.

Weekly meetings will consist of discussion around the students’ mathematical exercises and their programming exercises. Later in the program, these exercises would have prepared the students to develop a programming project and technical report – the content of which will be closely linked to modern research in quantum technologies.

Final Deliverables

Students will complete a final programming project with an accompanying technical report. Depending on the nature of the project, the program should be in a high-level language such as  python or MatLab or in a high-performance language such as C++. The technical report should cover the theory behind the project, details on its efficient implementation, and results from their simulations and/or experiments. It will also discuss how these results fit into the wider field of quantum technologies.

Possible Topics For Final Project

• Simulating a quantum computer running Shor’s algorithm from scratch in Python, C or C++.

• Executing Grover’s algorithm on a real/simulated quantum computer to identify objects in a small database.

• Simulate the violation of CHSH equalities in python.

• Simulating photon wavefunction interference to demonstrate the Hong-Ou-Mandel effect.

• Simulate a quantum teleportation protocol.

• Implement supervised quantum machine learning for simple classification with a small dataset from Kaggle on a real/simulated quantum computer.

• Simulate the BB84 quantum key distribution protocol in python.

• Or other topics in this subject area that you are interested in, and that your professor approves after discussing it with you.

Program Detail

• Cohort Size: 3-5 students

• Duration: 12 weeks

• Workload: Around 4-5 hours per week (including class time and homework time)

• Target Students: 9-12th grade students interested in quantum mechanics, mathematics, theoretical physics and/or computer science.

• Prerequisites: Quantum mechanics is intimately tied to linear algebra. Students should have a good understanding of mathematics, particularly in vectors and matrices. Students should also learn the basics of python.