Search

What are you looking for?

  1. The CAMELS project: Cosmology and Astrophysics with MachinE Learning Simulations

    Publication
    We present the Cosmology and Astrophysics with MachinE Learning Simulations --CAMELS-- project. CAMELS is a suite of 4,233 cosmological simulations of …

  2. The Quijote Simulations

    Publication
    The Quijote simulations are a set of 44,100 full N-body simulations spanning more than 7000 cosmological models in the …

  3. Astrometry with the Wide-Field InfraRed Space Telescope

    Publication
    The Wide-Field Infrared Space Telescope (WFIRST) will be capable of delivering precise astrometry for faint sources over the enormous field of view of its main camera, the …

  4. The Simons Observatory: Astro2020 Decadal Project Whitepaper

    Publication
    The Simons Observatory (SO) is a ground-based cosmic microwave background (CMB) experiment sited on Cerro Toco in the Atacama Desert in Chile that promises to provide breakthrough …

  5. Alignment between filaments and galaxy spins from the MaNGA integral-field survey

    Publication
    Halos and galaxies acquire their angular momentum during the collapse of surrounding large-scale structure. This process imprints alignments between galaxy spins and nearby filaments and sheets. Low …

  6. Astro2020 Science White Paper: Science at the edges: internal kinematics of globular clusters' external fields

    Publication
    The outer regions of globular clusters can enable us to answer many fundamental questions concerning issues ranging from the formation and evolution of clusters and their multiple stellar …

  7. From Dark Matter to Galaxies with Convolutional Networks

    Publication
    Cosmological surveys aim at answering fundamental questions about our Universe, including the nature of dark matter or the reason of unexpected accelerated expansion of the Universe. In order …

  8. Learning to Predict the Cosmological Structure Formation

    Publication
    Matter evolved under influence of gravity from minuscule density fluctuations. Non-perturbative structure formed hierarchically over all scales, and developed non-Gaussian features in the Universe, known as …

  9. CosmoFlow: Using Deep Learning to Learn the Universe at Scale

    Publication
    Deep learning is a promising tool to determine the physical model that describes our universe. To handle the considerable computational cost of this problem, we present CosmoFlow: a …

  10. Likelihood Non-Gaussianity in Large-Scale Structure Analyses

    Publication
    Standard present day large-scale structure (LSS) analyses make a major assumption in their Bayesian parameter inference --- that the likelihood has a Gaussian form. For summary statistics currently …