Cosmos may not have a dense forest or wildlife animals wandering around, but they definitely do have other some objects like the black holes, moving meteoroids, and so on. The dark matter is found to have many non-stellar black holes and they are believed to have formed in the primordial Universe. According to Riccardo Murgia and his colleagues from CERN, International School for Advanced Studies, and Istituto Nazionale di Fisica Nucleare, the primordial black holes are objects that came into being seconds after the Big Bang. The gravitational waves by the VIRGO and LIGO detectors used in 2016 had helped explain the nature of dark matter. The primordial black holes are believed to be a hypothetical component even though they are presented in some models of the primordial Universe.
In 1971, Stephen Hawking had proposed the concept of primordial black holes and it is now that it is being used to explain dark matter. It is believed to cover 80% of the matter in the Universe. The earlier black holes have been found to be 50 times bigger than the solar mass. The interaction of light released from far-off quasars with the cosmic web, which is a network of filaments formed of gas and dark matter. Lyman-alpha forest is generally referred to the interactions of the photons with cosmic filaments composed of hydrogen and it is the usual nature of dark matter. The Ulysses supercomputer of SISSA and ICTP has been used to simulate the interactions between photons and hydrogen plus to compare it with the real interactions captured by the Keck telescope. The simulations helped understand the mass and abundance of primordial black holes.
The new way can help alternate the standard cosmological model that helps understand that dark matter is composed of particles called Weakly Interacting Massive Particles (WIMPs). The development of new theoretical models is necessary for making new hypotheses about the nature of dark matter and acquiring a better understanding of the mysterious cosmos. Likewise, at ETH Zurich, the Department of Physics and the Department of Computer Science researchers believe that artificial intelligence can help improve the standard methods for estimating the dark matter content of the Universe. The deep artificial neural networks can extract the largest possible amount of information from the dark matter maps and the technologies like the facial recognition-based artificial intelligence used on Facebook can help capture a clear picture and also trace the exact location of dark matter.