CosmoGAN: Training a neural network to study dark matter

As cosmologists and astrophysicists delve deeper into the darkest recesses of the universe, their need for increasingly powerful observational and computational tools has expanded exponentially. From facilities such as the ...

Mapping the global distribution of phytoplankton

Researchers at ETH have charted the distribution of phytoplankton in the world's oceans for the first time and investigated the environmental factors that explain this distribution. They concluded that plankton diversity ...

Forecasting the hunt for the first supermassive black holes

It is believed that the formation and growth of most galaxies across the history of the universe has been fueled by supermassive black holes growing together with their host galaxy as they collect matter to attain millions ...

Computing faster with quasi-particles

Majorana particles are very peculiar members of the family of elementary particles. First predicted in 1937 by the Italian physicist Ettore Majorana, these particles belong to the group of so-called fermions, a group that ...

New water cycle on Mars discovered

Approximately every two Earth years, when it is summer on the southern hemisphere of Mars, a window opens: Only in this season can water vapor efficiently rise from the lower into the upper Martian atmosphere. There, winds ...

An all-optical neural network on a single chip

A team of researchers from the University of Münster, the University of Oxford and the University of Exeter has built an all-optical neural network on a single chip. In their paper published in the journal Nature, the group ...

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