The Quantum Revolution
A leading national expert comes to Colby to discuss the next technological wave
The quantum computing revolution is here, and Colby is bringing a leading expert to campus on Thursday, April 2, who will explain how it will impact us and why 2026 is a milestone year in the so-called quantum advantage over classical computers.
Quantum computers have the potential to solve complex statistical problems that are beyond the limits of today’s computers, across a range of industries and fields, and “are poised to take computing to a whole new level,” according to a report from McKinsey.
Right now, our society is in the early stages of the second quantum revolution. The first quantum revolution of the 20th century was about the development of lasers, transistors, magnetic resonance imaging, and semiconductors. This second quantum revolution is enabling technologies like quantum computers, ultraprecise sensors, and secure communication.
At Colby, leaders have been discussing the quantum revolution and the dramatic shifts it will bring to the world of work, intellectual life, and research, and how to strategically position the College to help shape the revolution, rather than being a bystander. As with artificial intelligence, Colby believes its liberal arts foundation is key to training leaders who possess a deep technical understanding and a broad education that allows them to think in a holistic way, ensuring they implement the necessary guardrails.
“We have barely begun to scratch the surface of what might be possible with quantum computing,” said David Watts, director of the Davis Institute for Artificial Intelligence. “An interdisciplinary approach to quantum computing will drive creative thinking for solutions to problems that we haven’t even yet conceived.”
Quantum computing acts as a booster or accelerator.
People often use a coin flip to describe quantum computing. When you flip a coin, it lands heads or tails, or either 1 or 0. In quantum computing, while the coin is spinning, a quantum computer calculates all possible outcomes at once before it settles into a single result. So, binary heads or tails for classical computing, versus a “superposition” of heads and tails for quantum.
“The important point is that it opens up many more possibilities than the two, which is the key to how quantum computing gets at complex problems that would take classical computing too long to be practical,” Watts said.
‘We have barely begun to scratch the surface of what might be possible with quantum computing. An interdisciplinary approach to quantum computing will drive creative thinking for solutions to problems that we haven’t even yet conceived.’
David Watts, director of the Davis Institute for Artificial Intelligence
On Thursday, April 2, the Davis Institute and the Departments of Physics and Computer Science will host Borja Peropadre, head of quantum algorithms engineering for IBM Quantum, for a discussion about the Dawn of Quantum Advantage. Part of the Distinguished AI Speaker Series, the talk starts at 7 p.m. in the Olin Science Center.
A physicist, Peropadre has extensive experience in the field of quantum information science, including leading quantum computing industry initiatives. Following a postdoc at Harvard University focused on quantum applications for chemistry, he has published more than 30 scientific papers, and his current research at IBM spans superconducting circuits, circuit QED, and quantum simulations.
Peropadre’s talk will trace the recent years of the quantum journey, leading to this current moment in time when quantum computers allow users to tackle problems at a scale once thought impossible. He believes our society is just beginning to understand the power and potential of quantum computing, and students who are involved in the technology today will be in a position of influence and advantage going forward.
He spoke about the quantum revolution before his arrival on Mayflower Hill.
Let’s start with the basics. What is quantum computing and why does it represent the next technological wave?
Quantum Computing is a fundamentally different computer paradigm, based on the laws of quantum mechanics, that we use to solve problems that are exponentially hard to solve with classical computers. Quantum computing can get past some of the limitations we are currently dealing with, and it will allow us to explore things we have not yet discovered. It is a tool for discovery. It is more than giving us solutions to problems we didn’t deem possible. It will solve problems we haven’t even thought of yet.
You’ve noted that 2026 marks the verge of verifiable quantum advantage. What does that mean?
The quantum advantage is the moment that we can demonstrate a quantum computer does something that is either faster, more accurate, or more efficient than a classical computer alone, and verifiable means we can establish trust on that computer. The thing is, the problems a quantum computer tries to solve many times are not verifiable. They are so difficult, we don’t have a mechanism to verify. So how can you trust the result of a quantum computer is true if you cannot verify the result? At IBM we started building some tools that allow for this verifiability. Even if we cannot reverse the problem and check that it is correct, we have found and developed certain algorithms that allow for the verifiability of the result. And that is the magic of one of the things we do well at IBM. We are expecting this will happen in 2026, that kind of crossover.
In what ways will quantum-centric supercomputing specifically accelerate or transform the development of large language models and generative AI?
We don’t really have an answer to that yet. There are many people doing research, actively researching how quantum computers can accelerate AI. And there are people looking at how AI can accelerate quantum. We are trying to explore both, and right now, we really need to find the synergies.
For Colby students interested in this frontier, what foundational skills should they be building now? Is it more important to master classical computer science, or should they be diving deep into linear algebra and quantum mechanics?
Quantum computing, for a long time, was a field for physicists because of quantum mechanics. But we are transitioning to a point where you can abstract away some of the details of physics. So physics is not necessarily something they need to know anymore, like the quantum nature of particles. On the other hand, linear algebra is something they need to know. It is at the core of everything in quantum computing. But the more you know about the basics of quantum mechanics, the better you can understand how these systems work and what might be possible.
