The advent of quantum computers is surrounded by a lot of hype. New breakthroughs reported in the media often suggest the technology could soon be widely used to solve complex problems that are beyond the scope of classical computers. In July, for example, the start-up company Oxford Ionics based in Kidlington, U.K., announced it had created the highest performing quantum computer chip in the world that can be mass-produced in existing semiconductor plants, hinting that commercialization could be just around the corner.
Many start-ups are racing to create the first scalable quantum computer. During the recent Lindau Nobel Laureate Meeting, an annual international scientific forum that brings together about 30 Nobel Laureates and hundreds of young scientists to exchange ideas in Lindau, Germany, the topics of discussion included the current state of quantum computers and whether it may be over-hyped. Some of the aspects addressed were the breakthroughs still needed to advance the technology, and the most promising applications.
“I think the situation at the moment is very interesting, because we don’t know the end of the story,” said Alain Aspect, a professor at the Polytechnic Institute of Paris in France and joint recipient of the Nobel Prize in Physics in 2022 for his experiments with entangled photons. “It may be that quantum computers are as fantastic as we think they might be and allow us to solve problems we didn’t know how to solve,” he added, “but we are not sure. It may be that at some point we find an ultimate obstacle that we cannot overcome.”
Classical computers represent information using bits that can be in one of two states, either zero or one. In contrast, the basic unit of a quantum computer is a quantum bit or qubit, which harnesses bizarre quantum phenomena that occur at atomic and subatomic scales. A qubit can be in multiple states at the same time, for example, a situation called superposition. A pair or several qubits can also be entangled so they remain in the same quantum state even when separated by a large distance; if the state of one qubit is changed, the state of the others connected to it immediately changes as well.
“Without entanglement, there would be no research on quantum computers,” said Anton Zeilinger, a professor of physics emeritus at the University of Vienna in Austria, senior scientist at the Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences, and joint recipient (along with Aspect) of the 2022 Nobel Prize in Physics. “That way, a quantum computer can process things in a parallel way, so to speak, whereas a classical computer can only operate in a sequential way.”
In theory, quantum properties would allow quantum computers to work on many tasks at once and solve complex problems much faster than classical computers, in minutes compared to years. The technology is likely to have an impact in specific fields where complex calculations are involved. Quantum computers could help researchers develop new materials, and speed up drug discovery and decisions made about financial transactions, for example. The search for use cases is still on though: Google and Xprize announced a $5-million prize earlier this year for new quantum applications that could address global problems in areas such as climate, health, and sustainability.
There are still technical challenges to overcome, however, to building a scalable quantum computer. One of these is related to entanglement.
“You have to entangle thousands of individual quantum bits,” said Zeilinger, “and the problem is that quantum states are fragile.”
Last year, researchers at the University of Science and Technology of China broke records by successfully entangling a group of 51 qubits in a quantum computer. However, it was seen as a technical accomplishment, rather than advancing the abilities of quantum computers.
The ability to keep qubits in one state for a prolonged period of time so they can successfully perform a computation is another hurdle to overcome. Interacting with their environment can cause them to lose their quantum properties, changing their state and therefore losing stored information, called decoherence. The larger the group of qubits, the bigger the problem, which can cause errors in computations.
Different error correction solutions have been proposed to tackle this issue. Last year, researchers at the Google Quantum AI lab reached a milestone by showing for the first time in experiments that errors could be reduced by scaling up the number of qubits. However, an even-lower error rate is still needed to develop a widely-usable quantum computer. “At the moment, I don’t see any solution which has all the advantages,” said Aspect.
There is debate as to whether fundamental science is needed to advance problems such as quantum error correction, or if it purely relates to technology development and engineering, largely from the private sector. During a panel discussion on the potential and hype of quantum technologies at the Lindau meeting, Olivier Ezratty, an author and advisor on quantum technologies based in Paris, France, said that he thinks advancements in science will still be involved. However, he added, it would also be beneficial if the two fields collaborate and don’t remain in separate silos, since building a quantum computer requires many different skills and areas of expertise, from physics to mathematics to electronics.
Similarly, Ezratty thinks companies should collaborate as well. “There is probably going to be hybrid innovation in this space because to make a viable computer, you will need at least three technologies: you will need a technology for the qubits doing computing, you will need a technology for the memory or storage, and you will need a technology for communication,” Ezratty said. “I don’t think we will have a single company in the world that owns these scalable quantum computers, it will come from various companies.”
Most experts are reluctant to predict when a large-scale quantum computer will be commercialized. While we wait, other related technologies are already taking off.
For example, quantum simulators—devices designed to tackle specific physics problems in contrast to a wider range of problems, which is the goal with quantum computers—already are showing promise. In recent work, such a machine was used to visualize entanglement in a quantum material, which would not be possible with a classical computer due to the complexity of interactions between particles. A better understanding of entanglement could help physicists solve problems in condensed matter physics and material science, for example, and perhaps even provide new insight that could benefit quantum computing.
“In the domain of quantum simulation, we are at the stage where the quantum simulator can go beyond what a classical computer can do,” said Aspect.
There is also a lot of intermixing between quantum and classical technologies, particularly artificial intelligence (AI). Machine learning was used with experimental data generated by a quantum simulator to discover new quantum phases, and has been proposed to help address quantum error correction.
According to Ezratty, AI is helping quantum technologies more at the moment than the other way around. However, more generally, he predicts innovations from both classical and quantum computing will continue to complement each other for the foreseeable future. “It’s good news because it brings funding and new ideas,” he said.
Sandrine Ceurstemont is a freelance science writer based in London, U.K.
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