TAU leads discovery of star detection technique

International team of astronomers discover new model for detecting the universe's first stars.

By JUDY SIEGEL-ITZKOVICH
Earth from orbit 370 (photo credit: Thinkstock/Imagebank)
Earth from orbit 370
(photo credit: Thinkstock/Imagebank)
An international team of astronomers led by scientists at Tel Aviv University have discovered a new model for detecting the first stars formed when the universe was in its infancy.
Using powerful 3-D computer models, they have shown that due to a difference in the speed of gas and dark matter in the early stages of the universe, the first stars clumped together into a “cosmic web” formation. Their discovery of these web-like structures now makes it feasible for radio astronomers to detect the light wavelength from hydrogen that was heated by the first stars when the universe was only 200 million years old, said the astronomers, who recently published their findings in the journal Nature.
Star formation is a part of our cosmic history, said team leader Prof. Rennan Barkana, a researcher at TAU’s School of Physics and Astronomy. Astronomers know that long before there were stars, the early universe was filled with a hot, uniform gas. But today, there is a complex universe of stars and galaxies. A great unknown frontier is the era of the formation of the first stars, which marked the transformation of the universe into its current state.
The most distant galaxy that can be reliably detected is from a cosmic age of around 800 million years ago, but it is difficult to go much further back and detect individual galaxies. Since the universe was filled with hydrogen atoms in those early times, the most promising method for observing the epoch of the first stars is using the prominent emission of hydrogen at a wavelength of 21 cm. (corresponding to radio waves). Measuring the cosmic 21- cm. emission is difficult, though, due to the foreground emission from our own Milky Way and other nearby galaxies. However, if the cosmic signal fluctuates, it is much easier to distinguish it from the bright local emission, Barkana explained.
The first stars and galaxies are expected to show large fluctuations, so that some regions will be shown to contain many stars (collected into mini-galaxies, each much smaller than current galaxies such as the Milky Way), and other regions to be nearly empty.
This, he continued, is more understandable if one imagines searching on Earth for mountain peaks above 5,000 meters. The 200 such peaks are not distributed uniformly, but are found in a few distinct clusters on top of large mountain ranges. Given a mountain range, every small hill on top of it becomes a high mountain peak, while in a valley it would be just a small hill. Similarly, said the TAU astronomer, to find the early galaxies, one must first locate a region with a large-scale density enhancement; a large number of galaxies would be found there, since the higher overall density enhances gravity throughout the region and makes it easier to form high concentrations of dark matter, into which gas falls and forms stars.
Scientists discovered recently that dark matter and ordinary matter (gas) moved at different velocities in the early universe. Over the last two years, researchers have studied the effect of this velocity difference with analytical models and numerical simulations. The TAU-led research team produced the first-ever simulated 3-D maps of the distribution of the first stars, and these show that the relative velocity effect significantly enhances large-scale fluctuations.
The spatial structure makes it much more feasible for radio astronomers to detect early stars from a cosmic age of around 180 million years (1.3% of the current age of the universe), Barkana said.
The expected signal comes with a characteristic signature that would mark the existence of small mini-galaxies at that time and the presence of the velocity effect.
“This exciting possibility should stimulate observational efforts focused on this early epoch,” said the TAU researcher.
Other members of the team were Eli Visbal of Harvard University, Anastasia Fialkov of TAU, and Dmitriy Tseliakhovich and Chris Hirata of the California Institute of Technology.