Figure showing the proposed quantum computer architecture by the researchers. Credit: Gouzien & Sangouard.
Quantum computing systems are computer systems that are based upon the key principles of quantum theory. They could be significantly faster and more efficient than conventional computing systems in terms of speed as well as performance. Many physicists around the world have been working on these systems over the past decade.
Quantum computers instead of encode information in bits with binary values (i.e. either 1 or 0,) use quantum bits, or qubits. Qubits, which are quantum mechanical analogs to bits, can exist in multiple states (i.e. 1 and 0 simultaneously).
Quantum computing systems consist of a number of qubits that are placed on a 2D chips. These qubits directly compute information. Classical computers are composed of a processor that processes information and a memory which stores it.
Recent research by researchers at Universit ParisSaclay and CNRS, CEA has evaluated the performance of a quantum computing device with a structure similar to that of conventional computers. The results were published in Physical Review Letters. They suggest that quantum computing systems with quantum information storage units could be made to have significantly fewer qubits.
One of the researchers involved in the study, lie Gouzien, said to Phys.org that the architecture most commonly used for quantum computers consists of laying all the qubits onto a 2D chip and then running the computation directly on these qubits. "In our work we wanted to challenge the idea of having all of the qubits on one processor and explored another architecture closer to that of a classic computer where a small processor can be coupled with a storage."
Gouzien and his team decided to assess their ability to run an algorithm in order to effectively compare their architecture to existing quantum computing systems. They evaluated the resources their architecture required to run the algorithm, as well as the overhead for error correction.
Gouzien stated that the algorithm was broken down into elementary gates and then adapted to the architecture being investigated. We also considered the overhead associated with error correction. These two components were then combined to determine the physical resources needed to run the factorization algorithm.
Researchers found that a processor with 13,436 physical qubits and a memory capable of storing 28 million spatial modes as well as 45 temporal modes could factor a 2048-bit RSA number in 177 days using 3D gauge color codes. The researchers also suggested that additional error-correction steps be added to the qubits stored every second. This would increase the runtime by around 23%. They found that increasing the number qubits within the processing unit could result in shorter storage times and run times.
Gouzien and his coworkers found that adding a memory component to a quantum computing system's processing unit could significantly reduce the number qubits. The team proposes that the microwave interface could be used to connect a superconducting processor and multiplexed memories.
Gouzien stated that while designing an efficient quantum memory can be difficult, it is still a research area and a greater challenge than fitting millions upon millions of qubits in a cryostat. We hope our article will encourage research on quantum memories and orient it towards their use in computation.
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More information: lie Gouzien et., Factoring 2048 RSA Integers within 177 Days with 13436 Qubits, and a Multimode memory, Physical Review Letters (2021). Information from the Journal: Physical Review Letters lie Gouzien et al., Factoring 2048 bit RSA Integers within 177 Days with 13436 Qubits, and a Multimode Memory. (2021). DOI: 10.1103/PhysRevLett.127.140503
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