This computer works almost like a guitar. The ETH Zurich quantum physicist Yiwen Chu and her team use tiny mechanical vibrations to store and process information. These vibrations behave much like the vibrating strings of a guitar, which produce musical notes.
What sounds like music is, in fact, quantum physics. The vibrations that Chu and her team work with are far beyond the range of human hearing. They occur deep inside a quantum chip, where they are used to store quantum information.
These vibrations enable Chu's quantum computer to perform its calculations as efficiently as possible while making flexible use of a working memory. "The interaction between the quantum processor and the quantum memory provides a crucial foundation with a view to establishing quantum computers as a powerful and reliable way to perform computations that are not feasible with conventional computers," says Yiwen Chu.
The physics professor conducts research on quantum information and quantum computer architectures. Her team recently presented a new approach in the journal Science that separates computation from working memory much more clearly than many existing quantum computing models, which tightly integrate processing and storage.
To achieve this, Chu and her team developed a new quantum computer architecture that was intentionally modelled on classical digital computers. In these systems, a central processing unit (CPU) processes data that is stored separately in a working memory – known in classical computer science as random access memory (RAM). The computer architecture defines how a computer's individual components are organised to process data as efficiently as possible.
In Chu's approach, a so-called superconducting qubit takes on the role of the central processing and control unit performed by the central processing unit (CPU) in a digital computer. At the same time, the information to be processed is temporarily stored in a quantum memory, making it available throughout the computation.
“In our quantum working memory, however, information is not stored electromagnetically – as is usually the case today – but rather in the form of mechanical vibrations,” explains Chu.
This ability to place states in superposition or to entangle them opens up additional pathways for quantum computation. The major promise of quantum computers is therefore that, one day, they may solve certain highly complex problems more efficiently than classical computers – or even tackle tasks that conventional computers cannot solve at all.
In order that quantum computers can compute and store information reliably, researchers must be able to precisely control and manipulate these states. This is possible when the processing unit and the working memory are strongly coupled.
In Chu’s system, this works as follows: the resonators store the respective information in a specific vibrational state. When the qubit retrieves information from the quantum working memory, it processes and modifies this vibrational state and then stores it again.
Until now, many quantum computing models have combined electromagnetic memory with superconducting qubits, since both – individually and in combination – are well studied and proven. Electromagnetic memory technologies allow quantum states to be read out, modified and controlled with very high precision.
Their drawback: they are relatively large and require a great deal of space – which is likely to hinder the development of experimental laboratory devices into market-ready quantum computers for research and industry. This is where Chu comes in.
Mechanical resonators, by contrast, are significantly smaller and more compact. They also offer greater storage capacity, because they support many different vibrational modes and can therefore store more information simultaneously than electromagnetic memory. In addition, they keep quantum states stable for longer, without the vibrations fading and information being lost. This extends the storage time.
In Science, Chu has now experimentally demonstrated for the first time that mechanical resonators can be successfully coupled and combined with superconducting qubits to perform quantum computations. This provides proof of feasibility: vibrating memory systems can represent a promising alternative to electromagnetic approaches. Whether the method will prevail is now dependent on how well it can be scaled. In other words, Chu’s quantum chip must also function reliably in larger quantum computing systems with expanded computational capabilities.
Chu’s team is continuing this line of research. A proof of principle has already been published in Science: their approach of embedding qubits and resonators into a new computer architecture is capable not only of performing simple computational tasks, but also more demanding tasks.
The research group tested the computational capability of their approach using two key problems, which are among the most important computational methods in quantum computing: the quantum Fourier transform and period finding.
“The Quantum Fourier Transform is a fundamental computational procedure required for many quantum algorithms. The period-finding algorithm we implemented served as a demonstration of how this procedure can be used”, explains Igor Kladaric, doctoral student in Chu's team and co-author of the publication.
Both methods require a quantum computing system to precisely control, store and coherently link many quantum states simultaneously. If this is achieved, a quantum computer is considered fundamentally capable of computation – and this is exactly what Chu’s approach demonstrates.
In principle, Chu’s quantum computing system can perform all basic computational steps that are required to execute any arbitrary quantum computation. This shows that the approach is fundamentally suitable as a general-purpose and programmable quantum computer.
There is still a long way to go before a sufficiently powerful and reliable quantum computer can be used in research and industry. However, Chu’s approach represents a highly promising step forward.
Science
Mechanical resonator–based quantum computing
28-May-2026