Two neural-network emulators, 21cmLSTM and 21cmKAN, are reported to accurately mimic simulated global 21 cm signals and enable fast Bayesian parameter constraints for lunar far-side cosmology experiments.
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Emulating Global 21 cm Cosmology Observations from the Lunar Far Side to Achieve Quick and Reliable Physical Constraints
Two neural-network emulators, 21cmLSTM and 21cmKAN, are reported to accurately mimic simulated global 21 cm signals and enable fast Bayesian parameter constraints for lunar far-side cosmology experiments.