"How much matter exists in the universe?" is one of the most intriguing and
significant topics in cosmology. Now, for the second time, the whole amount
of matter has been successfully measured by an international team that
includes experts from Chiba University. According to their findings, which
were published in The Astrophysical Journal, matter makes up 31% of all
matter and energy in the universe, with dark energy making up the remaining
percentage.
Approximately 20% of matter is thought to be made up of regular or
"baryonic" matter, which includes atoms, galaxies, stars, and life,
according to cosmologists. Dr. Mohamed Abdullah, the first author, is a
researcher at Chiba University's National Research Institute of Astronomy
and Geophysics-Egypt in Egypt. Approximately 80% of it is composed of dark
matter, which may include some as-yet-undiscovered subatomic particles
despite its enigmatic nature being unknown.
Says co-author Gillian Wilson, a professor of physics and vice chancellor
for research, innovation, and economic development at UC Merced, "the team
used a well-proven technique to determine the total amount of matter in the
universe, which is to compare the observed number and mass of galaxy
clusters per unit volume with predictions from numerical simulations."
Wilson was Abdullah's former graduate advisor.
"Cluster abundance," or the number of clusters currently observable, is
very sensitive to cosmological circumstances, particularly the total mass of
matter in the universe."
According to University of Virginia researcher Anatoly Klypin, "more
clusters would be formed if a larger percentage of the total matter in the
universe was present." "However, since the majority of the matter in a
galaxy cluster is dark and invisible to telescopes, it is challenging to
determine its mass with accuracy."
The group was compelled to employ an indirect tracer of cluster mass in
order to get around this obstacle. Their reliance was based on the mass
richness relation (MRR), which states that galaxies are more abundant in
more massive clusters than in less massive clusters. Since galaxies are made
up of bright stars, one may infer the entire mass of a cluster by counting
the number of galaxies inside it.
The scientists estimated the overall mass of each cluster by counting the
number of galaxies in each sample taken from the Sloan Digital Sky Survey.
The measured number and mass of galaxy clusters per unit volume were then
compared to estimates from computer models.
The cosmos that accounted for 31% of all matter was the best fit between
simulations and observations; this estimate was in great agreement with that
derived from cosmic microwave background (CMB) studies made by the Planck
spacecraft. Interestingly, CMB is a whole another method.
According to Chiba University's Tomoaki Ishiyama, "We have succeeded in
making the first measurement of matter density using the MRR, which is in
excellent agreement with that obtained by the Planck team using the CMB
method," "This study indicates that cluster abundance is a viable method for
limiting cosmological parameters, and it can be used in conjunction with
non-cluster approaches like gravitational lensing, Type Ia supernovae,
baryon acoustic oscillations, and CMB anisotropies."
The group prides itself on being the first to accurately measure the
distance to each cluster and the true member galaxies that are
gravitationally bound to the cluster rather than background or foreground
interlopers along the line of sight using spectroscopy, a technique that
divides radiation into a spectrum of individual bands or colors.
In earlier attempts to use the MRR approach, the distances to each cluster
and the neighboring galaxies that were genuine members were calculated using
far less sophisticated and accurate imaging techniques, such as utilizing
images of the sky taken at certain wavelengths.
In addition to showing that the MRR technique is an effective means of
establishing cosmological parameters, the paper, which was published in The
Astrophysical Journal, also describes how it can be used with new datasets
that come from spectroscopic galaxy surveys, such as those carried out with
the Subaru Telescope, eROSITA Telescope, James Webb Space Telescope, Dark
Energy Survey, and large, wide, and deep-field imaging.
