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Quantum computing has the potential to contribute to fields such as pharmaceuticals, data security, materials development, and more. This computational model takes advantage of the behavior of quantum particles. Quantum computers harness phenomena like superposition, entanglement, and quantum interference, and use them in computing.
Amazon Web Services (AWS) is pursuing the development of quantum computers, and enabling researcher, educators, and enterprises to use quantum computers through its Amazon Braket service. Its AWS Center for Quantum Computing recently released an architecture paper, "Building a fault-tolerant quantum computer using concatenated cat codes", which described a new model for correcting errors in quantum computers.
James Whitfield, an assistant professor of physics at Dartmouth College, recently joined the AWS quantum computing efforts as an Amazon Visiting Academic (AVA). The AVA program is aimed at pre-tenure to newly tenured academics who seek to apply research methods to tackle complex technical challenges while continuing their university work.
Whitfield earned his bachelor of science degree in chemistry and mathematics from Morehouse College, graduating magna cum laude, and has a PhD in chemical physics from Harvard. Currently he is working in the AWS quantum computing effort focusing on academic and educational programs.
Amazon Science recently spoke with Whitfield about his interest in quantum computing and his work with Amazon.
Q. When and how did you develop an interest in quantum computing, and what is the concept behind the Whitfield Group at Dartmouth?
Before I began grad school, my PhD supervisor said, “Hey, read Quantum Computation and Quantum Information over the summer.” That book, by Michael Nielsen and Isaac Chuang, was one of the first on quantum computing. Back then, there were not many industry internships. There was no quantum industry, basically. It’s not at all like now, where there are many internships and non-academic quantum jobs.
Before that, my interest in mathematics began with the objectiveness of grading and the peaceful solitude when problem solving. When I was in college, my mother gave me her “Standard Mathematical Tables”. When I’d get really stressed, I would open the book, turn to a random integral, and solve it to confirm the solution given. There was something deeply personal and quieting about each of those experiences.
At the Whitfield Group, we’re working to understand the abilities and limitations of new and existing computers to perform physical simulations. In particular, we are interested in the role that quantum mechanics plays in computation, both in terms of quantum computers and classical models of quantum information.
We're thinking about how to simulate fermions (specific kinds of subatomic particles) with quantum computers; about how electrons form, make bonds, and work in both classical and quantum algorithms; and about how we can push classical algorithms to the point where we might not need quantum computers.
Q. How has quantum computing evolved in your 15 years of focus within the field, and what are some of the challenges in teaching the concepts of quantum computing to your students at Dartmouth?
It could not be more different. The very idea of a fault-tolerant quantum computer just sounded so far off. Now there are concrete proposals such as that developed by Oskar Painter (director of the Quantum Photonics Group at Caltech and head of quantum hardware at the AWS Center for Quantum Computing ). But it took a lot of work by the scientific community to get us here.
As to teaching, a lot of people come in as a blank slate, and they don't really know what they're looking for. I think one of the most exciting parts of teaching quantum computing — and doing research in quantum computing — is that there are so many facets to it.
Ran into my Physics colleague @JDWhitfield11 preparing a fun class demonstration in mechanics for PHYS13 @dartmouth using a motorcycle! #ScienceTwitter #STEMeducation pic.twitter.com/PE7rEpldhO
— Katherine Mirica (@KMirica) January 9, 2020
It reminds me of the parable about the blind men and the elephant. An elephant came to town and the men went to inspect it by touch. The first touched its trunk and said it felt like a thick snake. The next touched its ear and said it seemed like a fan. Another touched its leg and said it felt like a tree trunk.
Quantum computing is like that. You can have a microwave engineer thinking about how microwave pulses are designed. A computer scientist will think about algorithms, a chemist will look at applications for chemistry, a physicist will think about novel materials and high-energy particles. So perhaps the biggest challenge of teaching quantum computing is understanding the perspectives and passion that each student brings, and then tapping into that passion.
It’s also important for people to understand the limits of quantum computers. Chemistry is one area where people say quantum computers can have an impact — one common area of discussion is using quantum computers to help synthesize fertilizers cheaply and easily. But there are so many people working in classical computing in chemistry that the minute you say, “This is a problem suitable for a quantum computer,” 50 developers will set out to show that’s not true, that classical computers can solve it. We’ve already improved a lot of classical algorithms by applying quantum principles to them.
Q. What do you hope to accomplish in your role as a visiting academic at Amazon?
As a visiting academic, the work I’m doing takes ownership of the broader educational efforts around quantum computing. The goal is to coordinate and execute AWS’s educational plans in quantum computing.
There’s a lot of interest from AWS customers, so I’m thinking about how to approach the educational needs of different customer groups, from students and teachers, to enterprise teams curious about quantum.
AWS has a variety of initiatives underway around quantum computing. My job is to help the team connect to key internal and external resources, so we can get leverage and accelerate learning in quantum computing for our customers. Another key aspect of the role is to help customers, such as cloud engineers and machine learning practitioners who already know about AWS, to better understand how they could apply quantum technologies to address some of their business needs in the future.
