# The future of quantum computing

With big investments from national governments, academic institutions, and titans of the tech industry like Google, IBM, Microsoft, and Amazon, quantum computing is a hot topic across the globe. Research firm Contrive Datum Insights recently projected a compound annual growth rate of nearly 37% from 2023 to 2030 and anticipated that the market will reach $125 billion annually. But what is quantum computing, and what will these investments fund?

Quantum computing exists at the intersection of computer science, mathematics, and physics. It works on the principles of quantum mechanics to solve problems that are intractable on the conventional, classical computers we use today. Classical computers process information using bits, or binary digits that are 0 or 1. Quantum computers use quantum bits, or qubits for short. Unlike a classical bit, a qubit does not have to be entirely 0 or 1; the state of a qubit is the combination of its 0 and 1 components. Think of a qubit as having two properties: “zero-ness” and “one-ness,” where the amount of each determines the probability of measuring that value.

**The growing field of quantum computing**

The biggest misconception about quantum computing, says Tufts alum Richard Preston, E18 and EG19, is that it’s just another evolution in computing technology, notable for being faster than a classical computer. Instead, quantum computing is a different type of computation altogether – one that offers an entire world of new possibilities thanks to the ability to solve problems that are intractable on classical computers.

Take the example of prime factorization – finding out which prime numbers can be multiplied together to reach the original number. “There’s really no way to do that on a classical computer that doesn’t scale terribly with the size of the number,” says Preston. However an algorithm developed by Peter Shor in 1994 shows that factoring would be far more digestible for a quantum computer. The implications are crucial in fields like cybersecurity, where cryptographic algorithms rely on the difficulty of prime factorization. The prospect of a cryptographically relevant quantum computer raises big questions for national security.

Researchers are still early in the process of developing practical quantum computers. Some exist now – IBM, for instance, offers free public use of its five-qubit machines. But there are drawbacks to our current early-stage quantum computers. The scale, or number of qubits, is still relatively low. Even more crucially, qubits must be isolated from the outside environment and from environmental noise that could cause the quantum state to decohere. In practice, it is extremely difficult to keep a quantum state in place long enough to perform useful computation. The resources required to maintain a modern quantum computer are substantial – to return to the IBM example, the company super-cools its quantum computers close to absolute zero. These limitations to early-stage quantum computers are currently being studied by researchers across the globe.

**A personal path**

Richard Preston first became interested in quantum computing as a network security engineer at the MITRE Corporation, where he has worked since 2017. In the spring of his junior year at Tufts as a computer engineering major, Preston had a meeting with his academic advisor Karen Panetta, who is both the Dean of Graduate Education for Tufts School of Engineering and a professor in the Department of Electrical and Computer Engineering. Panetta asked Preston what his plans were for the summer and when he answered that he was interested in MITRE, she connected him to a summer internship at the company which ultimately led to the position he holds today.

MITRE is home to the MITRE Institute, an internal professional development program where technical staff at the company teach classes to their peers. Preston, who had always been interested in physics and computation, took a MITRE Institute class on quantum computing offered by colleague Joe Clapis and was fascinated. “When I was learning about quantum computing, it felt like when I first learned how to program classical computers; when I was learning HTML or even playing around with [in-game technological resource] redstone in [the computer game] *Minecraft*, learning how these things work,” he says. “It brought me back to that because it was so new to me, and that was really cool.”

Preston dove into quantum computing headfirst. MITRE offered the opportunity for staff to develop research proposals in a program dedicated to the professional development of early-career staff, and in 2019, Preston submitted a successful proposal that led to him working part-time for a year on how to apply Grover’s algorithm to accelerating password-cracking for certain cryptographic hash functions. He ultimately wrote a software implementation of the quantum algorithm and used that to do resource estimation. His internal research at MITRE on quantum computing has continued since then, and he now teaches others too – including students at Tufts School of Engineering, as a part-time lecturer.

**Tufts past and present**

During his own time as a Tufts student, Preston earned both a BS in Computer Engineering and an MS in Electrical Engineering through the School of Engineering’s fifth-year master’s degree program. “It really worked out well because I got to stay a fifth year [after completing his BS]. I got to continue to see a lot of my friends and professors and TA for some of the courses I actually took, and then I was done and had a graduate degree,” says Preston.

He stayed in touch with many of his former professors, including Professor of the Practice Ron Lasser, who leads junior and senior design courses in the Department of Electrical and Computer Engineering. “[Junior and senior design] was really where I learned how to actually do engineering,” says Preston. “We got a chance to build something and learn how difficult that was. I experienced what it was like to fail and then learn from that failure when my assumptions were wrong. That was a really great learning experience.” Bringing everything full circle, Preston now works with Lasser from the perspective of a professional and educator, serving as an expert reviewer for students’ senior design projects.

Preston is doing his part to grow a quantum-capable workforce. At MITRE, he now co-teaches the internal course where he first learned about quantum computing. He and colleague Clapis re-tooled the course to offer it to high school students at MIT’s Beaver Works Summer Institute, and Preston leads introductory workshops for college students and for fellow professionals through IEEE Boston.

At Tufts, Preston is now wrapping up his first semester teaching a new graduate-level course called Quantum Software Development, which helps students develop practicable quantum software engineering skills and learn to implement and analyze quantum algorithms. The course is part of a growing slate of quantum computing classes available to Tufts students, with other recent offerings including Introduction to Quantum Information and Quantum Computation from the Department of Physics, and Quantum Computer Science taught by Assistant Professor Saeed Mehraban of the Department of Computer Science.

For his part, Preston is passionate about the need to ensure that the current and next generations of engineers are ready to work with quantum computers and to understand the different way of thinking that they require. “Assuming we’ll have capable quantum computers – that we are able to do error correction and we are able to scale these devices up for use on practical problems – we’ll need people who are able to program them, just like we need software engineers,” Preston says. “You don’t need to be a physicist with a PhD in order to write a Qiskit script or Q# script. The idea with growing a quantum-capable workforce is priming students and professionals to be able to use these devices and apply them to our problems, and also to multiply the potential opportunities that we could reap from this technology.”

### Department:

Electrical and Computer Engineering