Astronomers in Germany at the Leibniz
Institute for Astrophysics in Potsdam have developed an artificial intelligence
algorithm to help them chart and explain the structure and dynamics of the
universe around us with unprecedented accuracy. Scientists routinely use large telescopes to
scan the sky, mapping the coordinates and estimating the distances of hundreds
of thousands of galaxies and so enabling them to create a map of the
large-scale structure of the Universe. But the distribution that astronomers
see is intriguing and hard to explain, with galaxies forming a complex 'cosmic
web' showing clusters, filaments connecting them, and large empty regions in
between. The driving force for such a rich structure is gravitation. This force
originates from two components; firstly the 5% of the universe that appears to
be made of 'normal' matter that makes up the stars, planets, dust and gas we
can see and secondly the 23% made up of invisible 'dark' matter.
Alongside these some 72% of the
cosmos is made up of a mysterious 'dark energy' that rather than exerting a
gravitational pull is thought to be responsible for accelerating the expansion
of the universe. Together these three constituents are described in the Lambda
Cold Dark Matter (LCDM) model for the cosmos, the starting point for the work
of the Potsdam team. Measurements of the residual heat from the Big Bang – the
so-called Cosmic Microwave Background Radiation or CMBR emitted 13700 million
years ago – allow astronomers to determine the motion of the Local Group, the
cluster of galaxies that includes the Milky Way, the galaxy we live in.
Astronomers try to reconcile this motion with that predicted by the
distribution of matter around us and its associated gravitational force, but
this is compromised by the difficulty of mapping the dark matter in the same
region.
More information: