24.09.2012 - (idw) Leibniz-Institut fr Astrophysik Potsdam <\/p>\n
Astronomers in Germany have developed an artificial intelligence algorithm to help them chart and explain the structure and dynamics of the universe around us. The team, led by Francisco Kitaura of the Leibniz Institute for Astrophysics in Potsdam, report their results in the journal Monthly Notices of the Royal Astronomical Society. 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 scientists to map the large-scale structure of the Universe. But the distribution they 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. <\/p>\n
The driving force for such a rich structure is gravitation. Around 5 percent of the cosmos appears to be made of normal matter that makes up the stars, planets, dust and gas we can see and around 23 percent is made up of invisible dark matter. The largest component, some 72 percent of the cosmos, is made up of a mysterious dark energy thought to be responsible for accelerating the expansion of the Universe. This Lambda Cold Dark Matter (LCDM) model for the universe was the starting point for the work of the Potsdam team. <\/p>\n
Measurements of the residual heat from the Big Bang the so-called Cosmic Microwave Background Radiation or CMBR 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, but this is compromised by the difficulty of mapping the dark matter in the same region. <\/p>\n
Finding the dark matter distribution corresponding to a galaxy catalogue is like trying to make a geographical map of Europe from a satellite image during the night which only shows the light coming from dense populated areas, says Dr Kitaura. <\/p>\n
His new algorithm is based on artificial intelligence (AI). It starts with the fluctuations in the density of the universe seen in the CMBR, then models the way that matter collapses into todays galaxies over the subsequent 13700 million years. The results of the AI algorithm are a close fit to the observed distribution and motion of galaxies. <\/p>\n
Dr Kitaura comments, Our precise calculations show that the direction of motion and 80 percent of the speed of the galaxies that make up the Local Group can be explained by the gravitational forces that arise from matter up to 370 million light years away. In comparison the Andromeda Galaxy, the largest member of the Local Group, is a mere 2.5 million light years distant so we are seeing how the distribution of matter at great distances affects galaxies much closer to home. <\/p>\n
Despite this caveat, our model is a big step forward. With the help of AI, we can now model the universe around us with unprecedented accuracy and study how the largest structures in the cosmos came into being. <\/p>\n
Since 2011 Francisco Kitaura has been working at the AIP. His publication is available online on http:\/\/arxiv.org\/abs\/1205.5560<\/a> and will soon be published in Monthly Notices of the Royal Astronomical Society (MNRAS). <\/p>\n Science contact: Dr. Francisco-Shu Kitaura, +49 331-7499 447, fkitaura@aip.de<\/a> Research, Images, Movies: http:\/\/www.aip.de\/Members\/fkitaura<\/a> <\/p>\n<\/p>\n Continue reading here: <\/p>\n Using artificial intelligence to chart the Universe<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" 24.09.2012 - (idw) Leibniz-Institut fr Astrophysik Potsdam Astronomers in Germany have developed an artificial intelligence algorithm to help them chart and explain the structure and dynamics of the universe around us. The team, led by Francisco Kitaura of the Leibniz Institute for Astrophysics in Potsdam, report their results in the journal Monthly Notices of the Royal Astronomical Society. 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 scientists to map the large-scale structure of the Universe. Continue reading