Understanding quantum: A Computer Weekly Downtime Upload podcast

Last year Universal Quantum, the quantum computing firm spun out of Sussex University, announced it was collaborating with the Open Quantum Institute (OQI) on using quantum computing in drug discovery. The team has been investigating how quantum simulations might accelerate the discovery of novel, non-hormonal treatments for endometriosis, a disabling and progressive condition that affects around 10% of women globally.

Lucy Robson, a quantum algorithm scientist at Universal Quantum, is a member of this team. “My role is really about trying to understand what we can use large-scale quantum computers for taking problems which are too challenging to solve on classical computers, mapping them to quantum algorithms then implementing them in an experimental way.”

Robson’s background is as a computer scientist. She says: “Although it seems strange to talk about having a first career and then a second career, I actually began my journey in cybersecurity.” Robson studied computer science, gaining experience working in cybersecurity and network security. She says: “The way I originally got into computer science was actually as a self-taught programmer, going through the RFCs (Request for comments), understanding how internet protocols worked, you know, and getting into the Linux kernel.”

Although she had not trained as a physicist, Robson began taking an interest in quantum computing. When she began exploring it, she says: “There was this wealth of new material that was available, so I started trying to understand what on Earth is quantum and I discovered that actually there's an enormous crossover between quantum computing theoretical computer science. That's what really got me hooked.”

Robson says she then had the opportunity to work on a small scale project looking at applications of quantum computing for the defense sector. 

When asked about the challenges of understanding quantum computing, Robson  says: “It's certainly counterintuitive. Many of the concepts seem strange and alien. But I had the benefit of coming from a degree where we did a lot of linear algebra and so I would argue that one of the strongest prerequisites that you do need for quantum algorithms in particular, is to feel comfortable with linear algebra.” 

She recalls the advice Nobel laureate and physicist,  Roger Penrose, gave in the foreword of a book she was reading about learning difficult concepts. “I remember picking up one of his books when I was about 16 years old, just about to start A-level maths, so I was quite unfamiliar with a lot of the notation and the terminology that was being used. His advice for dealing with any sort of new or strange formula that you haven't seen before, is to try to get an intuitive understanding. That may not be about reading the equation or understanding the terminology, but reading a description, looking at a diagram and trying to get some concept in your mind of what this thing is actually trying to describe, and then go back and learn the notation and learn the formula.” 

This approach has always served her well. “It is a thing that I always do when I find something new and unfamiliar,” she says.