From the invisible world of elementary particles to the mysteries of the cosmos, recipients of this prestigious award for early career scientists explore nature...
Edward Hohenstein, Emma McBride and Caterina Vernieri study what happens to molecules hit by light, recreate extreme states of matter like those inside stars...
For the first time, DES scientists can combine measurements of the distribution of matter, galaxies, and galaxy clusters to advance our understanding of dark...
SLAC cosmologists are using multiple images of the same quasars, produced by massive galaxies’ gravitational pull, to calibrate cosmic distances. Their work may help...
Daniel Ratner, head of SLAC’s machine learning initiative, explains the lab’s unique opportunities to advance scientific discovery through machine learning.
Q-NEXT will tackle next-generation quantum science challenges through a public-private partnership, ensuring U.S. leadership in an economically crucial arena.
From the invisible world of elementary particles to the mysteries of the cosmos, recipients of this prestigious award for early career scientists explore nature at every level.
Edward Hohenstein, Emma McBride and Caterina Vernieri study what happens to molecules hit by light, recreate extreme states of matter like those inside stars and planets, and search for new physics phenomena at the most fundamental level.
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...
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.
Daniel Ratner, head of SLAC’s machine learning initiative, explains the lab’s unique opportunities to advance scientific discovery through machine learning.
Q-NEXT will tackle next-generation quantum science challenges through a public-private partnership, ensuring U.S. leadership in an economically crucial arena.