By Juljan Krause | iPhD Web Science Student
Earlier this year, I did a 10-week training course in quantum computing and communication with xPRO, the professional development unit at the Massachusetts Institute of Technology. I’m proud to say that I graduated with an overall mark of 97/100 and a Professional Certificate that carries a whopping 4.0 Continuing Education Units (CEUs).
The course was divided into two parts: ‘Introduction to Quantum Computing’ and ‘Quantum Computing Algorithms for Cybersecurity, Chemistry, and Optimization’. The course is not for the faint-hearted and requires a solid foundation in quantum mechanics, matrix algebra and logic. To brush up my skills I’d completed two maths and physics online courses on Udemy in preparation for the MIT programme.
And it was straight into Bloch spheres and quantum gates on day one! Each course was split into 4 separate modules. While learning was self-paced, the teaching staff encouraged us to complete each module in about a week’s time or else the workload would just get too heavy. The learning material was a blend of online lectures to watch, material to read and tons of graded activities along the way.
There were about 80 students altogether on this course, most of whom had an engineering or computer science background. MIT uses a one-stop online platform with an integrated discussion board to reach out to fellow learners and MIT teaching staff. Halfway through the course we had a chance to discuss our questions with Prof William D Oliver, the Director of the Programme, in an online webinar.
The first part of the course covered a comprehensive introduction into quantum computing and how it is different from classical computing. We covered engineering perspectives to building quantum quates, how quantum algorithms work and how quantum annealing is different from a universal quantum computer. Week 2 introduced the leading qubit modalities, i.e. the different approaches to picking the right kind of qubit for building a quantum machine. These are trapped ions and superconducting qubits (photons were covered later). Week 3 was about quantum algorithms and how they work in practice while week 4 covered quantum software. We then got to implement the Deutsch-Jozsa Algorithm ourselves on an IBM quantum cloud computer.
The second part of the course was a detailed introduction to applications. Needless to say, cryptography and Shor’s algorithm, which breaks RSA encryption thanks to efficiently finding the period of a large integer N in polynomial time, were the most prominent topic. If you’re keen to learn to implement Quantum Fourier Transformation protocols on quantum gates this module will be for you! We then ventured into the realm of quantum Hamiltonians and how quantum computing can be applied to optimisation problems, molecule design and cybersecurity.
I loved this course and was massively impressed with how much you can learn in just three months. As with any learning experience, the more time and effort you’re willing to invest the more you’ll get out. The material was difficult in places but not impossibly so and it was greatly rewarding to be doing so well in graded activities. Schrödinger equations, Hamiltonians, phase shifts and Hadamard gates are now my best friends! The most exciting part of the course was definitely the two “exams” at the end for which we got to implement quantum algorithms ourselves: the aforementioned Deutsch-Jozsa Algorithm and Grover’s Algorithm, for which we used QASM, the Quantum Assembly Language. I can recommend this course to anyone who’s keen to get a solid, technical foundation of quantum computing and communication. It was super exciting and a great, comprehensive introduction to the field and its applications in industry and research.