Predicting 21cm-line map from Lyman $α$ emitter distribution with Generative Adversarial Networks

no code implementations • 20 Apr 2020 • Shintaro Yoshiura, Hayato Shimabukuro, Kenji Hasegawa, Keitaro Takahashi

We show that the signal is detectable at $k < 0. 1~{\rm Mpc}^{-1}$ with 1000 hours of MWA observation even if the foreground residuals are 5 times larger than the 21\, cm-line power spectrum.

Cosmology and Nongalactic Astrophysics

Estimation of HII Bubble Size Distribution from 21cm Power Spectrum with Artificial Neural Networks

no code implementations • 19 Feb 2020 • Hayato Shimabukuro, Yi Mao, Jianrong Tan

The bubble size distribution of ionized hydrogen regions probes the information about the morphology of \HII\ bubbles during the reionization.

Cosmology and Nongalactic Astrophysics

Analysing the 21cm signal from the Epoch of Reionization with artificial neural networks

no code implementations • 24 Jan 2017 • Hayato Shimabukuro, Benoit Semelin

Then we test the trained network on the new set of 54 test samples with different values of the parameters.

Cosmology and Nongalactic Astrophysics