A stacked LSTM-GRU-CNN emulator reportedly reconstructs the global 21-cm brightness temperature with 99.93% accuracy, but a residual feature derived from the target values makes the reported accuracy invalid.
A New Constraint on the Simulation of the Intergalactic Medium through the Evolution of the Neutral Hydrogen Fraction in the Epoch of Reionization
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abstract
The thermal history of the intergalactic medium is full of extremely useful data in the field of astrophysics and cosmology. In other words, by examining this environment in different redshifts, the effects of cosmology and astrophysics can be observed side by side. Therefore, simulation is our very powerful tool to reach a suitable model for the intergalactic medium, both in terms of cosmology and astrophysics. In this work, we have simulated the intergalactic medium with the help of the 21cmFAST code and compared the evolution of the neutral hydrogen fraction in different initial conditions. Considerable works arbitrarily determine many important effective parameters in the thermal history of the intergalactic medium without any constraints, and usually, there is a lot of flexibility for modeling. Nonetheless, in this work, by focusing on the evolution of the neutral hydrogen fraction in different models and comparing it with observational data, we have eliminated many models and introduced only limited simulation models that could confirm the observations with sufficient accuracy. This issue becomes thoroughly vital from the point that, in addition to restricting the models through the neutral hydrogen fraction, it can also impose restrictions on the parameters affecting its changes. However, we hope that in future works, by enhancing the observational data and increasing their accuracy, more compatible models with the history of the intergalactic medium can be achieved.
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Stacked Hybrid RNN-CNN Reconstruction of X-ray Influence on 21-cm Brightness Temperature
A stacked LSTM-GRU-CNN emulator reportedly reconstructs the global 21-cm brightness temperature with 99.93% accuracy, but a residual feature derived from the target values makes the reported accuracy invalid.