An analysis of the first three years of Dark Energy Survey data is consistent with predictions from the current best model of the universe. Nevertheless, hints remain from DES and other experiments that matter in the current universe is a...

An international collaboration aims to create a 3D map of the universe, unraveling the mysterious nature of dark energy.

Rebecca Leane and colleagues showed dark matter could heat planets in our galaxy to incredible temperatures. Here, she explains how that works and how it could pave the way for sensitive new searches for the mysterious substance.

For the first time, DES scientists can combine measurements of the distribution of matter, galaxies, and galaxy clusters to advance our understanding of dark energy.

SLAC cosmologists are using multiple images of the same quasars, produced by massive galaxies’ gravitational pull, to calibrate cosmic distances. Their work may help resolve long-standing debates about how quickly the universe is expanding.

Rubin Observatory will bring new capabilities to the studies of dark matter and dark energy.

Daniel Ratner, head of SLAC’s machine learning initiative, explains the lab’s unique opportunities to advance scientific discovery through machine learning.

The camera will explore cosmic mysteries as part of the Rubin Observatory’s Legacy Survey of Space and Time.

Their work uses machine learning to transform the way scientists tune particle accelerators for experiments and solve longstanding mysteries in astrophysics and cosmology.

Researchers developed a way to measure the basic properties of matter at the highest pressures thus far achieved in a controlled laboratory experiment.

Observations of dwarf galaxies around the Milky Way have yielded simultaneous constraints on three popular theories of dark matter.

New research could offer insights into the formation of planets like Earth and inform the design of more resilient materials.