Figure 8 - uploaded by Pierre Ocvirk
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Evolution of the volume filling factor of HII regions Q HII with cosmic times in both the original simulation (TEST-SIM) and the prediction of the neural network. Q HII is calculated from the whole 3D field of t reion in both cases by taking the cumulative sum of the histogram of the t reion values.
Source publication
We present a deep learning model trained to emulate the radiative transfer during the epoch of cosmological reionization. CRADLE (Cosmological Reionization And Deep LEarning) is an autoencoder convolutional neural network that uses two-dimensional maps of the star number density and the gas density field at z=6 as inputs and that predicts 3D maps o...
Contexts in source publication
Context 1
... a second test, we compute the evolution of the fraction of the volume that is ionized at a given cosmic time. In Fig .8, we present the evolution of the volume filling factor of HII regions QHII in both the TESTSIM simulation and the model prediction. ...
Context 2
... evolution of this quantity is calculated by binning the cosmic time period and by getting the cumulative sum of ionized cells at a given cosmic time from the treion field. We report an almost perfect match of the two curves in Fig .8 at all cosmic times. ...
Context 3
... a second test, we compute the evolution of the fraction of the volume that is ionized at a given cosmic time. In Fig .8, we present the evolution of the volume filling factor of HII regions QHII in both the TESTSIM simulation and the model prediction. ...
