Quantum computer systems, computer systems based on the key principles of quantum theory, can significantly outperform conventional computer systems in both speed and performance. Over the past decade, many physicists around the world have therefore sought to develop these systems and assess their potential.

Instead of encoding information into bits, units of information with binary values (ie 1 or 0), quantum computers use quantum bits or qubits. Qubits are quantum mechanical analogs of bits that can exist in more than one state (ie 1 and 0 at the same time).

Most quantum computer systems developed to date consist of a series of qubits placed on a 2D chip that directly compute information. Classic computers, on the other hand, consist of a processor, which processes information, and a memory, which stores information.

Researchers from the Université Paris-Saclay, CNRS, CEA, recently conducted a study evaluating the performance of a quantum computer with a structure similar to that of conventional computers. Their results, published in *Physical Assessment Letters*, suggest that incorporating quantum information storage units into quantum computing systems could make it possible to create devices that contain significantly fewer qubits in their processors.

“The architecture usually considered for quantum computers is to put all the qubits on a 2D chip and do the calculation directly on those qubits,” Élie Gouzien, one of the researchers who conducted the study, told Phys.org. . “In our work, we wanted to challenge this idea of having all the qubits on one processor and explore a different architecture, closer to that of a classic computer, where a small processor is coupled to a memory.”

To effectively compare their architecture to existing quantum computing systems, Gouzien and his colleagues decided to evaluate their ability to execute a particular algorithm. More specifically, they evaluated the resources their architecture needed to run this algorithm, including the error correction overhead.

“We detailed the decomposition of the algorithm into elementary gates and adapted it to the architecture studied,” Gouzien said. “We also considered the overhead of the error correction. We then merged those two parts together to evaluate the physical resources needed to run the factorization algorithm.”

The researchers showed that using a processor made of 13,436 physical qubits combined with a memory that can store 28 million spatial modes and 45 temporal modes, a 2048-bit RSA integer can be calculated over 177 days using 3D meter color codes. . They also suggest inserting additional error correction steps of the stored qubits every second, which would only increase the run time by about 23%. The team found that they could also achieve shorter run times and storage times by simply increasing the number of qubits in the processing unit.

Overall, Gouzien and his colleagues found that the addition of a memory component could drastically reduce the number of qubits in the processor of a quantum computer system. In their paper, the team suggests that their architecture can be realized by placing a microwave interface between a processor made of superconducting qubits and multiplexed memory.

“Of course, designing efficient quantum memory is not an easy task, but it is already a field of research and it is more challenging than fitting millions of qubits into a cryostat,” Gouzien said. “We hope that our paper will stimulate research on quantum memories and also orient it towards their use for computation.”

An entangled state of three qubits has been realized in a fully controllable array of spin qubits in silicon

**More information:**

Elie Gouzien et al, Factoring 2048-bit RSA integers in 177 days with 13 436 Qubits and a multimode memory,

*Physical Assessment Letters*(2021). DOI: 10.1103/PhysRevLett.127.140503

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**Quote**: Study demonstrates the potential of a quantum computer composed of a small processor and a storage unit (2021, Oct. 13) retrieved Oct. 13, 2021 from https://phys.org/news/2021-10-potential-quantum-comprised-small -processor.html

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