| Speaker: | Hayato Shimabukuro (Observatoire de Paris) |
|---|---|
| Title: | Analysing the 21cm signal from epoch of reionization with artificial neural networks |
| Date (JST): | Fri, Mar 31, 2017, 13:30 - 14:30 |
| Place: | Seminar Room A |
| Abstract: | The 21 cm signal from the Epoch of Reionization should be observed within the next decade. To extract from the observed data constraints on the parameters describing the underlying astrophysical processes, inversion methods must be developed. Here we test possible inversion method for EoR parameter reconstruction: artificial neural networks (ANN). We find that the quality of the parameter reconstruction depends on the sensitivity of the power spectrum to the different parameters at a given redshift, that including thermal noise and sample variance decreases the quality of the reconstruction and that using the power spectrum at several redshifts as an input to the ANN improves the quality of the reconstruction. |
