UCR-led Team Develops New Cosmological Tool for Weighing Galaxy Clusters

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Team led by UC Riverside graduate student Mohamed Elhashash designed a new cosmological tool for “weighing” galaxy clusters

A New Cosmological Tool for “Weighing” Galaxy Clusters

Most of the matter in the universe is made up of “dark matter”. Unlike ordinary baryonic matter, which includes atoms, stars, galaxies, and life, the nature of dark matter is not yet known, but may consist of some as-yet undiscovered subatomic particle. The astronomer Fritz Zwicky first came to suspect its existence in the 1930s when he noticed that the combined gravitational mass of the galaxies he observed in the nearby Coma galaxy cluster was insufficient to prevent those galaxies from flying away from the cluster. He realized that the galaxies must be held in place by gravity but in order to generate that gravity, most of the cluster had to be made up of a mysterious invisible matter which he dubbed “dark matter”.

We know much more about galaxy clusters now than Zwicky did then. Decades of study have revealed them to be the most massive gravitationally bound systems in the universe, consisting of hundreds of galaxies containing trillions of stars, as well as hot gas and dark matter. Nowadays, we know that only about 20% of the matter in the universe is made out of ordinary baryonic matter and 80% is made out of dark matter. However, even to this day, it remains a challenge to measure the total amount of matter in any given galaxy cluster.

A new technique, described in a paper led by UC Riverside graduate student Mohamed Elhashash, aims to do just that, by using an innovative method that has proven to be much more effective than others figuring out which galaxies found near to a cluster are actually gravitationally bound to it. Only those galaxies which are fiducial cluster members will provide an accurate estimate of the total mass of the cluster. Excluding fiducial members or including unbound galaxies, or interlopers, can lead to significantly incorrect estimates of the cluster mass. The team, which included Elhashash’s thesis advisor, Professor Gillian Wilson, and Professor Anatoly Klypin of the New Mexico State University tested a new technique called GalWeight. Comparing GalWeight against four well-known techniques, using thousands of artificially-generated clusters with a wide range of masses from numerical simulations, it proved to be more than 98% accurate in correctly assigning cluster membership, and compared very favorably to four well-known existing techniques. The team also applied their new technique to 12 clusters from the Sloan Digital Sky Survey, including the famous Coma cluster, which they estimate to have a mass just under a million billion times the mass of the Sun.

The team are now in the process of applying their GalWeight technique to thousands of galaxy clusters. They also plan to make their code publicly available. Their work was funded by the National Science Foundation and NASA, and the paper has been published in the Astrophysical Journal.


The paper was published in The Astrophysical Journal and can be found here.


Coma cluster of galaxies. Credit: Wikipedia.