Yandex in new CERN experiment: how to find dark matter in just 13 years

Despite the fact that physicists sometimes try to present conservative, in fact, they are just waiting to find something that goes beyond the current understanding of nature. But they have such a long time did not work.

Once again, hope to update Standard Model collapsed after CERN found the Higgs boson. And despite the fact that, по According to Stephen Hawking , this discovery made physics boring problems that the Standard Model can not explain, still remain. One of them - what a particle may be a candidate for dark matter ? As you know, it is contained in the universe, but to see it we can not.

And now scientists at CERN are starting a new experiment - SHiP (Search for Hidden Particles). If these particles are discovered, then the Standard Model can be extended. This will mean that our understanding of the structure and evolution of the universe may change. And scientists may well qualify for a Nobel Prize. Conduct astrophysical research for space telescope will SHiP Astro-H . Yandex for this experiment not only provide its technology CERN machine learning: students and researchers of the School of data analysis Yandex will work together with its scientists.

Cooperation Yandex and CERN began in 2011, when we gave him his server. In 2012, we developed the to organize a search service, which was used in one of the four major experiments at CERN's Large Hadron LHC - Large Hadron Collider beauty experiment ( LHCb ). In 2013, physicists were able to use our own technology for machine learning - MatrixNet. Then Yandex became an associate member of the European Center for Nuclear Research in project CERN openlab .

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Two years ago, Yandex has performed Andrew Golutvin , scientific consultant director of CERN. It was exactly one day before it was officially announced the discovery of the Higgs boson. And last week at a special seminar Andrew spoke about the new experiment SHiP, which is already in the planning phase is supposed to use technology and knowledge Yandex. The lecture consists of five parts: