From theory to reality: IBM’s quantum journey

“It’s close to the coldest place in the universe,” says IBM Fellow Jerry Chow. “Not exactly. But a couple of orders of magnitude colder than it is in outer space.”

He’s talking about the refrigerators inside IBM’s Thomas J. Watson Research Center, where quantum processors are cooled to just 15 millikelvin — cold enough for superconducting qubits to behave according to the strange rules of quantum mechanics. The engineering is extraordinary. The experience of using it, increasingly, is not.

“What’s phenomenal about this refrigeration technology is that it’s basically turnkey,” Chow says. “You just plug it into the wall . . . they can stay reliably cold for certainly months, if not even years.”

More than 50 years ago, inside that same research center, physicist Charlie Bennett scribbled three words on a notecard: quantum information theory. He couldn’t have known it at the time, but he was naming an entirely new field, one that’s now producing computers capable of tackling problems classical machines were never designed to solve.

Chow explains the leap the same way he explains it to his own friends: as a new mode of transportation capable of exploring places previously out of reach.

“The comparison I often like to make between quantum computers and classical computers is how we as humans went from transportation on land with cars and trains to transportation with airplanes and flights. Cars and trains get us to different places. We get to go to different cities, we get to see different things, but when we can fly, we go to new continents, we cross oceans, we enter this new dimension.”

The metaphor reflects a more fundamental shift in how information is represented. “If we talk about classical computers, we’re really talking about today’s transistor-based computers where, fundamentally, the unit of information is a bit,” Chow says. “The fundamental unit of information for a quantum computer is the quantum bit, or qubit.” Unlike classical bits, he explains, qubits “can be zeros, they can be ones, they can be superpositions of zeros and ones,” while multiple qubits “can be in entangled states where they’re effectively correlated to one another.”

For Chow, the distinction isn’t simply speed. “At the very core fundamental [of] computation, it comes down to the math,” he says. “We know there’s a set of math that governs how we compute with classical computers. Then we know from using quantum mechanics that’s a different set of math that lets us compute a very different set of problems more efficiently.”

That different mathematical framework is particularly powerful for modeling nature itself. Researchers writing in Nature Physics describe simulations of quantum chemistry and quantum materials as “among the most important applications of quantum information processors,” highlighting why molecular simulation has become one of quantum computing’s most promising early applications.

That promise is already beginning to translate into tangible results. IBM, the Cleveland Clinic, and the RIKEN Institute recently used a quantum-centric workflow to simulate a 12,635-atom protein, the largest biologically meaningful molecule ever modeled.

For Chow, the significance extends beyond setting a record. “We’re looking at understanding proteins and, in fact, proteins in terms of how [they] react with water,” he says. “That’s something that is fundamental to study in the longer term different molecules and different drugs and how they react with other molecules that might be in the body.”

Understanding those interactions is foundational to drug discovery and molecular biology — not simply finding a new medicine, but better understanding the chemistry that governs living systems.

Rather than demonstrating that quantum computers are simply faster than classical machines, results like these point toward something more important: the ability to solve scientific problems that have remained out of reach using conventional approaches. And for Chow, they show that technology once considered impossibly fragile is becoming practical engineering.

“Quantum is here,” he says. “Quantum is now. It’s not too late to get started.”

Learn more at https://www.ibm.com/quantum.