A frequentist reanalysis of Planck and KiDS-1000 data shows that a two-body decaying dark matter model can produce S8 values consistent with weak lensing surveys, and that prior choices dominated earlier Bayesian exclusions.
Stochastic optimization methods for extracting cosmological parameters from CMBR power spectra
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abstract
The reconstruction of the CMBR power spectrum from a map represents a major computational challenge to which much effort has been applied. However, once the power spectrum has been recovered there still remains the problem of extracting cosmological parameters from it. Doing this involves optimizing a complicated function in a many dimensional parameter space. Therefore efficient algorithms are necessary in order to make this feasible. We have tested several different types of algorithms and found that the technique known as simulated annealing is very effective for this purpose. It is shown that simulated annealing is able to extract the correct cosmological parameters from a set of simulated power spectra, but even with such fast optimization algorithms, a substantial computational effort is needed.
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A frequentist view on the two-body decaying dark matter model
A frequentist reanalysis of Planck and KiDS-1000 data shows that a two-body decaying dark matter model can produce S8 values consistent with weak lensing surveys, and that prior choices dominated earlier Bayesian exclusions.