Ripples in the Fabric of the Universe May Peer Back to the Beginning of Everything We Know

Neutron Stars Merging To Form a Black Hole

Numerical simulation of the neutron stars merging to form a black hole, with their accretion disks interacting to produce electromagnetic waves. Credit: L. Rezolla (AEI) & M. Koppitz (AEI & Zuse-Institut Berlin)

Scientists have advanced in discovering how to use ripples in space-time known as gravitational waves to peer back to the beginning of everything we know. The researchers say they can better understand the state of the cosmos shortly after the Big Bang by learning how these ripples in the fabric of the universe flow through planets and the gas between the galaxies.

“We can’t see the early universe directly, but maybe we can see it indirectly if we look at how[{” attribute=””>gravitational waves from that time have affected matter and radiation that we can observe today,” said Deepen Garg, lead author of a paper reporting the results in the Journal of Cosmology and Astroparticle Physics. Garg is a graduate student in the Princeton Program in Plasma Physics, which is based at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (

Garg and his advisor Ilya Dodin, who is affiliated with both

Garg and Dodin created formulas that could theoretically lead gravitational waves to reveal hidden properties about celestial bodies, like stars that are many light years away. As the waves flow through matter, they create light whose characteristics depend on the matter’s density.

A physicist could analyze that light and discover properties of a star millions of light years away. This technique could also lead to discoveries about the smashing together of neutron stars and black holes, ultra-dense remnants of star deaths. They could even potentially reveal information about what was happening during the

Reference: “Gravitational wave modes in matter” by Deepen Garg and I.Y. Dodin, 10 August 2022, Journal of Cosmology and Astroparticle Physics.
DOI: 10.1088/1475-7516/2022/08/017

This research was supported by the U.S. National Science Foundation through Princeton University.