English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We present the Cosmology and Astrophysics with MachinE Learning Simulations(CAMELS) Multifield Dataset, CMD, a collection of hundreds of thousands of 2Dmaps and 3D grids containing many different properties of cosmic gas, darkmatter, and stars from 2,000 distinct simulated universes at several cosmictimes. The 2D maps and 3D grids represent cosmic regions that span $\sim$100million light years and have been generated from thousands of state-of-the-arthydrodynamic and gravity-only N-body simulations from the CAMELS project.Designed to train machine learning models, CMD is the largest dataset of itskind containing more than 70 Terabytes of data. In this paper we describe CMDin detail and outline a few of its applications. We focus our attention on onesuch task, parameter inference, formulating the problems we face as a challengeto the community. We release all data and provide further technical details athttps://camels-multifield-dataset.readthedocs.io.

The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence