There was a time, back in the early days of computing, when we had vacuum tubes, relays, mechanical gears plus several different types of analog computers. We’re kind of in that same era today with quantum computers. We have analog quantum computers that can be used to solve very specific problems, and several different approaches to general purpose quantum computers, including those with semiconducting qubits, trapped ions, spin qubits, quantum dots, topological qubits, photonic qubits, neutral atom qubits — and many more.
Each has its own strengths and weaknesses and use cases.
The type furthest along when it comes to actual real-world use cases are the analog quantum computers like those that use quantum annealing technology. This is useful for solving some quantum-related physics and optimization problems in a way similar to how a bathtub full of water can solve the problem of calculating the volume of an oddly-shaped physical object — such as, say, a crown. Eureka?
When it comes to the general-purpose quantum computers, the superconducting approach seems to be in the lead right now, according to Gartner analyst Chirag Dekate. “The physics is much better understood and it’s now an engineering problem, not a physics problem,” he says.
Despite the fact that we seem to be years away from having practical working quantum computers, or even a common set of standards for how to build these things, investors, governments, and large corporations are taking quantum computing seriously.
For example, this summer, the National Institute of Standards and Technology released a set of quantum-proof encryption algorithms, so that the world has time to get ready for when quantum computers do arrive.
NIST isn’t alone in seeing massive disruptive potential in quantum computing. So do investors.
As of mid-November, Crunchbase reports that quantum computing funding has hit a record high — $1.5 billion so far in 2024. That’s nearly twice the total of 2023 and significantly higher than the previous record, set in 2022, of $963 million.
And some large, cutting-edge enterprises are already beginning to spend money on quantum technology. Hyperion Research estimates that the global quantum computing market has reached the $1 billion mark this year and is expected to grow to $1.5 billion in 2026 — though the top use case for the next couple of years will remain research and development in quantum computing.
According to a September report from McKinsey, 55% percent of quantum industry leaders said they had a quantum use case in production this year, up from 33% last year. This means that they have developed an application that shows an advantage over a classical approach though not necessarily one that is fully rolled out and commercially viable at scale.
“We’re really at the level of real-world use cases,” says Holger Mueller, an analyst at Constellation Research. “We’ve jumped the qubit barrier.”
1. QuEra demonstrates new error correction method
This year started off with a series of announcements about breakthroughs in error correction. What’s the deal with error correction? Qubits are ridiculously sensitive and unreliable.
“Error correction is vital for enterprise users of quantum computing,” says Yoram Avidan, CTO of Citigroup’s Innovation Lab and global head of Citi Accelerator.
Error correction ensures the accuracy and reliability of quantum computations, he says, which is particularly important for financial monitoring. “Error correction capabilities are crucial for enabling stable, predictable, and accurate quantum-based solutions, especially in the context of financial applications we are running in the bank,” Avidan says. “Error correction will definitely accelerate the adoption of quantum-based solutions in the bank.”
But while Citigroup waits for that to happen, it’s already experimenting with the technology that’s available. Citi is using Amazon Braket, a cloud-based service, to see how well quantum computers could handle portfolio optimization tasks. Amazon Braket supports a number of physical quantum computers, including computers from IonQ, Rigetti, Oxford Quantum Circuits, and QuEra.
To solve the error problem, quantum computing companies use multiple physical qubits to create one error-corrected qubits. And by “multiple,” that can mean “thousands.”
Which brings us to the first major error correction news of the year: QuEra’s January announcement that it achieved a logical qubit using only eight physical qubits, demonstrating a new error correction method using transversal gates.
The company outlined a three-year roadmap that calls for a computer with 10 logical qubits in 2024, 30 in 2025 using “magic state distillation,” and 100 logical qubits by 2026. Their system is already available on Amazon Braket.
The trade-off is speed. QuEra’s system runs slower than alternatives but prioritizes error correction quality. On-premises systems can be ordered for 2025 delivery.
2. Alice & Bob devise cat qubits
Also in January, quantum computing startup Alice & Bob announced their new quantum error correction architecture.
Alice & Bob’s biggest breakthrough in error correction comes from cat qubits — named after Schroedinger’s Cat — which reduce the number of dimensions that noise comes from. And, on top of that, the company also gets some error correction by bounding photos around an electronic circuit, says CEO Théau Peronnin
3. Nord Quantique claims industry-first quantum error correction at qubit level
In February, Nord Quantique announced a 14% improvement in qubit reliability using a similar error correction technique, one that bounces photons in an aluminum container the size of a walnut. And this approach doesn’t suffer from QuEra’s speed problem.
Nord Quantique links the photons to physical qubits, providing redundancy without the massive overhead of traditional error correction. The company plans to deliver a 100-logical-qubit system by 2028.
Their approach works particularly well with superconducting circuits and operates at megahertz frequency, 100 to 1,000 times faster than competing systems, the company says.
4. IBM launches Qiskit functions catalog
After a bit of slowdown in the summer, quantum computing news announcements picked up again in the fall. First came a breakthrough on the ecosystem side.
IBM launched its Qiskit Functions catalog, offering six quantum services designed to make it easier for enterprise developers to work with quantum algorithms. The catalog includes functions from IBM and partners like Algorithmiq and Q-CTRL that improve error correction and simplify quantum circuit development. Two functions remove the need to understand quantum circuits, focusing on optimization and chemistry applications.
The system is part of IBM’s vision for quantum-centric supercomputing, combining quantum and classical resources. Early users include Cleveland Clinic for molecular simulations and RIKEN for materials research.
5. Microsoft and Quantinuum announce 12 logical qubits
Also in September, Microsoft announced that it partnered with Quantinuum to create 12 logical qubits, which, according to Krysta Svore, Microsoft’s vice president of advanced quantum development, was, at the time, the most logical qubits on record. Quantinuum provided the quantum hardware and Microsoft handled the error correction.
These quantum computers are still too small to do anything that classical computers can’t do, but they can already allow companies to experiment with use cases and test algorithms. “We have entered the era of reliable quantum computation,” Svore says.
6. Microsoft and Atom Computing’s announce 24 working logical qubits
Then, since 12 logical qubits weren’t enough, in November Microsoft followed up with a joint announcement with a different quantum hardware company, Atom Computing. This time, the two companies hit a massive milestone by creating 24 working logical qubits, the most ever demonstrated, on a base of 112 physical qubits.
Atom Computing uses the “neutral atoms” approach to quantum computing, and in this approach, the neutral atom qubits, in addition to developing errors, can also become completely lost. This announcement is the first demonstration on record of loss correction in a commercial neutral-atom system.
The team used a clever combination of hardware and software, trapping the atoms in a grid using lasers, then applied Microsoft’s error-correction software. As a result, they cut error rates by more than four times compared to regular physical qubits.
“Microsoft, with Atom, has a scalable way of achieving logical qubits,” says Gartner’s Dekate. “There is real progress happening. The quantum industry is building better, larger, more scalable computers. The pace of innovation continues to accelerate.”
Enterprise customers can order the system now through Microsoft Azure, with delivery in 2025. It works with regular cloud computing and AI tools, so businesses can start integrating quantum capabilities into their existing operations.
According to Microsoft’s Svore, the total number of usable, logical qubits will go up to 50, and the bigger number of qubits allow customers to start integrating reliable logical quantum computing into their workflows for applications such as chemistry and materials science.
“First deployments are expected to be a hybrid solution of an on-premises machine and cloud, to enable easy access to cloud offerings like Azure HPC and Azure Elements,” she says. “Full cloud deployment is also possible per customer request.”
7. IBM doubles capability, increases speed 50-fold
Not to be outdone, IBM announced in November that it, too, has doubled its quantum computing capacity — its new 156-qubit Heron quantum processor can run circuits with up to 5,000 two-qubit gate operations. Plus, there was a dramatic speedup in performance — the system completed a task in 2.2 hours that previously took 112 hours.
Using Qiskit software, IBM’s system enables researchers to explore quantum applications in chemistry, materials science, and other fields, the company said. The Cleveland Clinic is already using it to simulate molecular bonds for drug discovery.
The improvements come from both hardware and software advances. IBM’s platform now integrates quantum and classical computing resources, allowing customers to choose the best tools for each part of their calculations.
With progress in both error correction and on the software side, IBM is the company to watch, says Constellation Research’s Mueller. “It puts the whole market into overdrive,” he says.
8. RIKEN and NTT launch world first general-purpose optical quantum computer
RIKEN and NTT launched the world’s first general-purpose optical quantum computer in November. The system operates at nearly room temperature and processes at speeds up to several hundred terahertz.
The computer uses continuous-variable analog design with time-division multiplexing, where computations occur through quantum teleportation. It can handle approximately 100 continuous quantity inputs. The system is accessible through a cloud service and is designed for materials science, chemistry, and AI applications.
One major benefit of this approach to quantum computing is that it operates at room temperature. By comparison, superconducting qubits and trapped ion cubits operate at temperatures close to absolute zero. According to Riken, the optical quantum computer is also faster than other quantum computing platforms.
9. D-Wave speeds up processing 25,000 times
And in yet another kind of quantum computing — the analog kind — D-Wave released the benchmark results for its latest 4,400-plus qubit Advantage2 processor in November, with big performance gains. The system solves materials science problems 25,000 times faster than its previous version, the company claims.
The new processor doubles qubit coherence time and has improved qubit connectivity, enabling solutions to larger problems.
The system delivered five times better solutions for high-precision applications and outperformed the previous version in 99% of satisfiability problem tests, the company said. It’s available now through D-Wave’s quantum cloud service.
D-Wave’s qubits can’t be directly compared to those of other companies, however, because it’s not a general-purpose computer but a narrow-purpose analog one.
10. Google uses AI to improve error correction
We can expect to see even more progress on error correction next year. One reason? Artificial intelligence.
In late November, Google announced an AI system that spots errors in quantum computers. This uses the same transformer technology that’s behind large language models and other types of generative AI, but trained specifically on quantum processes.
The system is too slow to be actually used in real-time to spot errors, Google says, but, as AI technology improves, it could point to an additional way to reduce error rates.
The road ahead
So, when will we have working quantum computers?
Analysts at the Boston Consulting Group say they’ve been disappointed in the lack of recent progress of actual enterprise use cases.
“Quantum computing today provides no tangible advantage over classical computing in either commercial or scientific applications,” Boston Consulting Group researchers wrote in a July report. “Though experts agree that there are clear scientific and commercial problems for which quantum solutions will one day far surpass the classical alternative, the newer technology has yet to demonstrate this advantage at scale.”
According to the firm, our current era, that of “noisy intermediate-scale quantum” will last until 2030.
At this stage, quantum computers have too few qubits and too many errors to be practically useful, but they can be used to test algorithms and do other preliminary research.
Broad quantum advantage — where quantum computers can be used to solve problems that traditional computers can’t handle — will last from approximately 2030 to 2040, according to the Boston Computing Group. At that time, the research firm predicts that end users will see between $80 and $170 billion in total annual value creations.
In 2040, according to the research firm, we’ll enter the era of full-scale fault tolerance, and end users will see between $450 and $850 billion of value creation per year. This is when errors are reduced to the point that quantum computers can be scaled up to handle pretty much anything thrown at them.
Some quantum computing companies expect to get there even faster. For example, IBM’s quantum roadmap has the company delivering a fully error-corrected system in 2029. It expects to have a quantum computer with over 2,000 error-corrected qubits — or logical qubits — after 2033.
It takes many physical qubits to create one error-corrected logical qubit, so IBM expects to have a 100,000-qubit computer by then, capable of running 1 billion gates.
IBM is the company to watch, says Gartner’s Dekate. “It’s very clear that IBM is leading,” he says. “They’re innovating at every layer of the stack. But it is early days.” Achieving workable quantum computers is a marathon, he says. “And we’re in the first five minutes.”
Whoever is ahead today might not necessarily win the race, he says. “Enterprises should not fall into the trap of trying to figure out who’s ahead and who’s behind — that will lead enterprises to make bad decisions, because the leaderboard will change quite dramatically.”
He suggests that companies looking to take the lead in finding ways to take advantage of quantum computing should partner with multiple vendors and explore different pathways. And, instead of focusing on finding short-term investment returns, they should instead think about skills development, building capabilities, investigating use cases, and preparing for disruptions.
Source:: Network World