Momentum is building for quantum computing and some observers say that a usable, fault-tolerant quantum system could appear in the next few years. We have written about the significant steps that have been made by Google, Microsoft, and Amazon in error correction for their quantum chips, and there have been similar efforts by the likes of IBM and Rigetti. Cisco Systems, Nvidia, D-Wave, QuEra, and others continue to take steps forward.

Investment money is flowing in – according to one account, $1.25 billion in investments were made in quantum technologies in the first quarter – and the roster of quantum players continues to extend from hyperscalers and high-profile infrastructure companies down to a fast-growing number of pure-play startups.

Then there is the venerable Bell Labs – now part of Nokia after the major telecom equipment provider bought Alcatel-Lucent in 2016 for $16.6 billion – which this year is celebrating its first 100 years, a century of innovation that brought the transistor, lasers, photovoltaic cells, Unix, and the C programming language. Many of these firsts make up what Nokia Bell Labs refers to as Quantum 1.0 technologies, those that originated from the field of quantum mechanics.

We’re now in Quantum 2.0, defined by the ability to “manipulate individual particles of matter, making them do our bidding,” chief technology officer Michael Eggleston and Nishant Batra, Nokia’s chief strategy and technology officer, wrote earlier this year. “There is enormous potential in these quantum particles. A single electron, for example, can be used as a quantum bit, or qubit, which is the fundamental building block of quantum computing. Quantum 2.0 paves the way for unprecedented computational capabilities.”

A Ten Year Horizon

To Thierry Klein, president of Bell Labs solutions research at Nokia, ten years out is about the right timeframe for usable, fault-tolerant quantum computing. AI is at the heart of conversations now about computing, but it will take a significant leap forward when quantum makes the scene, he says.

“If we think about our main challenges of the current generation, we see this coming-together of our physical, digital, and human worlds, and all of that is driven by a lot of AI, and we’re obviously in the era of AI transformation and AI revolution,” Klein tells The Next Platform. “As much as we do research on AI, our research on networking is important because networking will really enable the AI revolution, whether it’s in the telecom sector or other sectors, and fundamentally we need to compute a lot of information to realize the potential of AI. As such, computing is equally important to really unlock the potential of AI and the massive knowledge and understanding that we can extract from the data that’s around us, that we’re collecting. While it will may be known as the AI era, we think that networking and computing and, by extension, quantum computing will be key to really enable the full potential of that AI.”

Bell Labs is embracing topological qubits, similar to Microsoft’s approach with its Majorana 1 quantum chip, according to Eggleston. As others, he sees the broad array of modalities being investigated as an indication of the relatively early stage of quantum computing, with the expectation that they’ll winnow down as the technology matures. Bell Lab scientists saw high error rates across all modalities as a key problem and looked to physics to understand why qubits are so fragile and faulty and what can be done to improve error rates to allow for better scaling.

The transistor allowed modern computers to perform and scale better than their earlier transistors, and they saw that the same promise with topological qubits, Eggleston tells The Next Platform.

“The fundamental problem we see is it’s really about how you store your quantum information,” he says. “If you look at all the modalities out there, whether it’s atoms or ions or superconductors or photons, the quantum information is stored in one discrete particle or state or location. You store it in an atom or an ion, and if anything happens to that – if a stray photon or phonon or energy or vibration, if anything comes in and touches it – it decoheres your system and you lose information.”

Distributed Storage For Quantum Info

With a topological approach, information is encoded into a non-local property. It’s distributed, so local disturbances here and there don’t affect it. The scientific challenges were determining what a non-local quantum state is and how something completely non-local is built. The scientists found a way to not only store information non-locally, but also to have long lifetime.

“We basically can measure quantum states, and they’re stable for hours, sometimes days,” Eggleston says.

It’s done using gallium arsenide, a compound material used in traditional semiconductors, so Bell Labs can make their devices via traditional semiconductor processing and wafers can be mass-produced, easy to scale and manufacture, he says.

“The way to conceptualize it is, we’re able to actually create what’s effectively a quantum liquid,” Eggleston says. “We have these electrons and they all basically condense into a liquid and they form this state – you can kind of think of it like a pond – where they’re all coupled together and this allows us to basically store information over this kind of global area. You could basically manipulate it by just making small movements of these individual electrons throughout the entire liquid.”

Most modalities store quantum information in a single electron or atom. With topological qubits, the information is distributed over millions of electrons, he says.

Smaller Qubits For Larger Scale

Also important in scaling is size, from the size of the qubit to the systems they’re housed in. In quantum computing, that also includes how the qubits are cooled.

“Really, all quantum computing technologies require very low temperatures,” he says. “Some of them do it through these dilution refrigerators or cryostats. Ions and neutral atoms, they can do laser cooling. They still have to cool it to very low temperatures, but they can use lasers to do it. But there’s a lot of infrastructure on that, so when it comes to scaling, some of the things that are important are how many qubits you can actually fit into a small area. What’s the size of your actual qubit?”

The topological qubits Bell Labs scientist create are about 15-by-15 microns, which means they’re small enough o allow a million or more to fit in the size of a traditional processing unit, Eggleston says. It something that could easily fit in a single dilution refrigerator, so a very large number of qubits are kept in a very cold environment but, from a scaling perspective, can fit in a relatively small space.

In Bell Labs’ work, there are a couple of key milestones. The first is setting a quantum state, which needs to be done before a qubit can be made, something that can be set as a 0 or 1. It can be trivial; if you’re using a photon, it can be polarization, he says. However, for topological quantum computing, it’s a challenge, though the organization showed in 2023 it can be done.

“We can initialize these states, we can measure them, we can actually monitor them over long periods of time, and we can observe, basically, state flipping over periods of tens of hours to days,” Eggleston says. “We have these really nice robust quantum states.”

Controlling The Qubit

What’s needed now is the ability to control the qubit, to be able to change it on command, flipping it between 0 and 1, something that in classical computing is called a NOT gate, or inverter. In quantum, it’s called a Pauli-X gate, or X gate or quantum NOT gate. That’s Bell Labs’ next big milestone with hopes of announcing results by the end of the year, Eggleston says.

Once the quantum state is in place and the qubit can be swapped between 0 and 1, the next step is creating a superposition, which also is on the scientists’ roadmap.

“Once you can create a superposition, then you have a qubit,” he says. “You need to be able to create a zero and one at the same time. That’s on our roadmap for next year. By the end of 2026, it’s our goal to actually have demonstrated a topological qubit that’s in a superposition.”

Having a stable quantum state from the start helps Bell Labs differentiate itself from others in the quantum field.

“A lot of other players kind of started with maybe a more faulty qubit and a focus more on error correcting,” Eggleston says. “We definitely believe error correcting will have a huge role in it, just like it does in traditional communication networks, but you want to start with the most robust quantum state that you can, and we think that that’s really the key to scalable quantum computing.”

One More Computing Tool

When considering what quantum computing will look like, Eggleston falls in line with what others are saying. It will be another tool available to organizations, primarily cloud-based and similar to how CPUs and GPUs are used today for particular jobs. Quantum systems already are being integrated into cloud networks to allow people to understand how to use them and to build the tools needed to interface with them.

At a higher level, Bell Labs scientists are taking a full view of the quantum environment beyond the qubit. That includes quantum security, sensing, and – unsurprisingly, given the parent company – networking also is a key part.

“We’re really excited about the potential of quantum networking,” he says. “There’s a lot of really exciting applications, from physical-layer security and networks to distributed quantum computing, but there’s also new areas in expanding capacity and improving energy efficiency when you actually start looking at quantum networks.”

Bell Labs has people working from the low hardware-device layer up to the network architecture, addressing such issues as how to coordinate multiple quantum systems.

“Communication is so vital to computation, and as we incorporate more and more quantum 2.0 technology into our networks, we need ways of communicating that quantum information, and that’s a capability that we’ll be bringing to kind of enable the quantum computing of the future,” he says.

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