Comparison of detection performance between intensity detection and segmentation detection in Rydberg-atomic sensors.

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However, their unique physical characteristics make two basic signal reading programmes possible: intensity-based and decomposition-based testing. The former measured the electric field by laser strength, while the latter used the Autler-Townes extension. In doing so, we systematically classified and modeled existing signal reading methods and divided them into these two models. Then we came up with the maximum probability estimation procedures for each of the tests and the corresponding Cramér-Rao lower limit (CRLB). Through our analysis of CRLB, we proposed two strategies for reading programmes to increase sensitivity and minimize the difference in estimates: access to data in areas with the highest slopes. While this method has been implemented in intensity-based testing (e.g. hyperthermal energy detection programme), its application to decomposition-based testing has not been explored. The prioritization of samples in areas with maximum peak slopes, combined with the best possible separation estimation method that we have proposed, can significantly reduce the differences in estimates compared to traditional multi-body matching. Comparative analysis showed that the best test performance of the two testing programmes was found. This work has also helped to improve the accuracy of microwave calibration. The figures show that, based on the maximum probability estimation method that we have proposed, both basic signal reading methods have achieved lower estimated differences.