For the team at Nokia Bell Labs, the solution lies in better
qubits rather than bigger machines.
Specifically, rather than information encoded in individual
elementary particles, the team is focused on qubits that hold this
same information in the way matter is spatially oriented—what is
known as a topological qubit.
This alternative approach uses electromagnetic fields to manipulate
charges around a supercooled electron liquid, triggering the qubits
to switch between topological states and locking them in place for
far longer periods of time.
It is inherently more stable as a result, explains Eggleston. “We
have these electrons, and they’re sitting in a plane, in one state.
If I move them around each other, they’re now in a different state.
But that’s really hard to accidentally do, it doesn’t happen
randomly. And so that allows you to build a stable system that you
can control.”
In fact, while existing qubits have a lifespan of milliseconds, for
topological qubits this could be several days, he adds. “It’s
incredibly stable. Many, many orders of magnitude more stable.”
Some of the science that underpins the topological qubit dates back
decades. In 1998 Bell Labs scientists Daniel Tsui and Horst Störmer
were awarded
the Nobel Prize in Physics
for their discovery six years earlier of a counterintuitive physical
phenomenon, later dubbed the fractional quantum Hall (FQH) effect.
FQH refers to how electrons manipulated under strong magnetic fields
and at very low temperatures can create new states of matter. These
states are being leveraged nearly 40 years later to form the basis
of topological qubits.
But in so many other ways, the push toward a topological qubit has
placed scientists firmly in unknown territory. “The development of
the technology can be frustrating because nobody’s done this
before,” admits Eggleston. “It’s completely open sky. We’re often
ahead of the theorists.”
“Nobody’s ever actually shown you can control the topological
state and switch it on and off. And that’s what we’re wanting to
demonstrate this year. That’s what the scientists in our lab are
working on as we speak.”
Michael Eggleston, Research Group Leader, Nokia Bell Labs
That’s why the Nokia Bell Labs team has often worked collaboratively
with the competition to advance the field. Much of the early
research saw them work closely with Microsoft, for example. But
they’re also hoping that 2025 will mark the year that sets their
research apart.
In the coming months, the team at Nokia Bell Labs hopes to
demonstrate their ability to control the qubit for the first time,
intentionally moving it between states to offer enhanced stability
and resilience against errors.
“That will be a first,” says Eggleston. “Nobody’s ever actually
shown you can control the topological state and switch it on and
off. And that’s what we’re wanting to demonstrate this year. That’s
what the scientists in our lab are working on as we speak.”
“Then next year, we’ll build on that to show the quantum gating
operations that you’d need to build a quantum computer,” Eggleston
adds.
If the Bell Labs team can reach these milestone moments, they will
move closer toward a fully workable topological qubit that could
prove transformative for the future of quantum computing.
Although the breakthrough may not shorten the timeline to a
full-scale, fault-tolerant quantum computer, it will demonstrably
alter the scale and scope of what quantum computers can achieve.
Topological qubits could unlock the future potential that has made
quantum computing a topic of scientific fascination for years.
Rather than multi-billion-dollar machines that occupy entire
buildings to deliver a mere fraction of the potential functionality,
topological qubits could pave the way for far more efficient
machines capable of tackling extremely complex optimization tasks
and simulation problems with billions of variables at both
microscopic and global levels.
In short, they could unlock the future potential that has made
quantum computing a topic of scientific fascination for years.
Think about their application in chemistry, points out Eggleston, an
area in which trial and error materially slows progress. “You have
chemicals where it’s impossible to understand how they bind and
interface with each other, and so teams synthesize, run tests, and
see what works and what doesn’t,” he explains.
“But when someone designs a bridge, they don’t just build a bunch
and see which one doesn’t fall down. Instead we have tools that
allow you to simulate the mechanics of these giant structures, test
them, and optimize them before you build anything. That’s what I see
quantum computing being able to offer for the chemistry field,”
Eggleston adds.
Such a breakthrough could also transform the design and development
of lifesaving drugs, with quantum computers able to carry out
molecular modelling for new therapeutic compounds at far greater
speeds and levels of complexity than current computational methods
allow.
And quantum systems could enable the simulation of exponentially
more complex supply chains, crafting intricate digital twins that
allow organizations to optimize operations. They could allow
scientists to better predict the course of climate change, or
develop advanced materials for use in aerospace. The use cases go
on.
But before all that possibility can be materialized, a qubit that’s
up to the task must come to fruition.
This content was produced by Insights, the custom content arm of
MIT Technology Review. It was not written by MIT Technology
Review’s editorial staff.
This content was researched, designed, and written entirely by
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the writing of surveys and collection of data for surveys. AI
tools that may have been used were limited to secondary production
processes that passed thorough human review.
by MIT Technology Review Insights
