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COSMOLOGY

Learning from the machine

Nature Astronomy volume 3, pages 18–19 (2019)Cite this article

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Large cosmological datasets have been probing the properties of our Universe and constraining the parameters of dark matter and dark energy with increasing precision. Deep learning techniques have shown potential to be smarter than — and greatly outperform — human-designed statistics.

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Fig. 1: Comparison between a mock lensing map and a random Gaussian field.

Jose Manuel Zorrilla Matilla / columbialensing.org

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  1. Department of Astronomy, Columbia University, New York, NY, USA

    Zoltán Haiman

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  1. Zoltán Haiman
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Correspondence to Zoltán Haiman.

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Haiman, Z. Learning from the machine. Nat Astron 3, 18–19 (2019). https://doi.org/10.1038/s41550-018-0623-9

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