21cmlstm: A Fast Memory-based Emulator of the Global 21 cm Signal with Unprecedented Accuracy
J. Dorigo Jones,
S. M. Bahauddin,
D. Rapetti
et al.
Abstract:Neural network (NN) emulators of the global 21 cm signal need an emulation error much less than the observational noise in order to be used to perform unbiased Bayesian parameter inference. To this end, we introduce 21cmLSTM—a long short-term memory (LSTM) NN emulator of the global 21 cm signal that leverages the intrinsic correlation between frequency channels to achieve exceptional accuracy compared to previous emulators, which are all feedforward, fully connected NNs. LSTM NNs are a type of recurrent NN des… Show more
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