A comprehensive survey on quantum computer usage: How many qubits are employed for what purposes?

Quantum computers (QCs), which work based on the law of quantum mechanics, are expected to be faster than classical computers in several computational tasks such as prime factoring and simulation of quantum many-body systems. In the last decade, research and development of QCs have rapidly advanced. Now hundreds of physical qubits are at our disposal, and one can find several remarkable experiments actually outperforming the classical computer in a specific computational task. On the other hand, it is unclear what the typical usages of the QCs are. Here we conduct an extensive survey on the papers that are posted in the quant-ph section in arXiv and claim to have used QCs in their abstracts. To understand the current situation of the research and development of the QCs, we evaluated the descriptive statistics about the papers, including the number of qubits employed, QPU vendors, application domains and so on. Our survey shows that the annual number of publications is increasing, and the typical number of qubits employed is about six to ten, growing along with the increase in the quantum volume (QV). Most of the preprints are devoted to applications such as quantum machine learning, condensed matter physics, and quantum chemistry, while quantum error correction and quantum noise mitigation use more qubits than the other topics. These imply that the increase in QV is fundamentally relevant, and more experiments for quantum error correction, and noise mitigation using shallow circuits with more qubits will take place.Comment: 14 pages, 5 figures, figures regenerate

Reference values for the locomotive syndrome risk test quantifying mobility of 8681 adults aged 20–89 years: A cross-sectional nationwide study in Japan

Background The locomotive syndrome risk test was developed to quantify the decrease in mobility among adults, which could eventually lead to disability. The purpose of this study was to establish reference values for the locomotive syndrome risk test for adults and investigate the influence of age and sex. Methods We analyzed 8681 independent community dwellers (3607 men, 5074 women). Data pertaining to locomotive syndrome risk test (the two-step test, the stand-up test, and the 25-question geriatric locomotive function scale [GLFS-25]) scores were collected from seven administrative areas of Japan. Results The reference values of the three test scores were generated and all three test scores gradually decreased among young-to-middle-aged individuals and rapidly decreased in individuals aged over 60 years. The stand-up test score began decreasing significantly from the age of 30 years. The trajectories of decrease in the two-step test score with age was slightly different between men and women especially among the middle-aged individuals. The two physical test scores were more sensitive to aging than the self-reported test score. Conclusion The reference values generated in this study could be employed to determine whether an individual has mobility comparable to independent community dwellers of the same age and sex