Cosmic Voids in GAN-Generated Maps of Large-Scale Structure

Understand

A Generative Adversarial Network (GAN) was used to investigate the statistics and properties of voids in a $\Lambda$CDMuniverse.

• The total number of voids and the distribution of void sizes is similar in both sets of images and, within the formal error bars, the mean void properties are consistent with each other.
• However, the generated images yield somewhat fewer small voids than do the simulated images.
• In addition, the generated images yield far fewer voids with central density contrast $\sim$ $-$1.