TL;DR
This paper introduces an unbiased Bayesian method for accurately measuring the ratio of two data sets in astronomical analysis, minimizing errors and applicable to multiple ratios without relying on specific models.
Contribution
It derives an analytical expression for the posterior distribution of the ratio, enabling fast, unbiased, and minimally error-prone measurements based solely on proportionality assumptions.
Findings
Method produces nearly Gaussian posterior distributions.
Achieves high signal-to-noise ratios (4.9 to 8.4).
Demonstrated with lensing ratio using DESI, DECaLS, and Planck data.
Abstract
In certain cases of astronomical data analysis, the meaningful physical quantity to extract is the ratio between two data sets. Examples include the lensing ratio, the interloper rate in spectroscopic redshift samples, the decay rate of gravitational potential and to test gravity. However, simply taking the ratio of the two data sets is biased, since it renders (even statistical) errors in the denominator into systematic errors in . Furthermore, it is not optimal in minimizing statistical errors of . Based on Bayesian analysis and the usual assumption of Gaussian error in the data, we derive an analytical expression of the posterior PDF . This result enables fast and unbiased measurement, with minimal statistical errors. Furthermore, it relies on no underlying model other than the proportionality relation between the two data sets. Even more generally, it…
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