1. Key Laboratory of Quantum Information, University of Science and Technology of China, Hefei 230026, China; 2. Synergetic Innovation Center of Quantum Information & Quantum Physics, University of Science and Technology of China, Hefei 230026, China; 3. Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
Abstract Parametric down-conversion (PDC) sources play an important role in quantum information processing, therefore characterizing their properties is necessary. Here we present a statistical model to assess the properties of the PDC source with certain distribution, such as the brightness and photon channel transmissions, we only need to measure the singles and coincidences counts in a few seconds. Furthermore, we validate the model by applying it to a PDC source generating highly non-degenerate photon pairs. The results of the experiment indicate that our method is more simple, efficient, and less time consuming.
Fund: Project supported by the Strategic Priority Research Program (B) of the Chinese Academy of Sciences (CAS) (Grant Nos. XDB01030100 and XDB01030300), the National Key Research and Development Program of China (Grant No. 2016YFA0302600), and the National Natural Science Foundation of China (Grant Nos. 61475148 and 61575183).
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.