arXiv:1707.02800v2 Announce Type: cross
Abstract: In this paper we propose that artificial neural network, the basis of machine learning, is useful to generate the inflationary landscape from a cosmological point of view. Traditional numerical simulations of a global cosmic landscape typically need an exponential complexity when the number of fields is large. However, a basic application of artificial neural network could solve the problem based on the universal approximation theorem of the multilayer perceptron. A toy model in inflation with multiple light fields is investigated numerically as an example of such an application.
Infectious disease burden and surveillance challenges in Jordan and Palestine: a systematic review and meta-analysis
BackgroundJordan and Palestine face public health challenges due to infectious diseases, with the added detrimental factors of long-term conflict, forced relocation, and lack of resources.




