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'New methods to boost data analysis for Large Hadron Collider'

Press Trust of India  |  New York 

Scientists say they have created new techniques that deploy to significantly improve data analysis for the (LHC), the world's most powerful particle accelerator.

"The methods we developed greatly enhance our discovery potential for new at the LHC," said Kyle Cranmer, a at the (NYU) in the US.

Located at the laboratory near Geneva, Switzerland, the LHC is probing a new frontier in high-energy

The facility may reveal the origin of mass of fundamental particles, the source of the illusive dark matter that fills the universe, and even extra dimensions of space, researchers said.

In 2012, data collected by the LHC backed the existence of the Higgs boson, a sub-atomic particle that plays a key role in our understanding of the universe.

The following year, and received the Nobel Prize in in recognition of their work in developing the theory of what is now known as the Higgs field, which gives elementary particles mass.

The study, published in the journal Physical Review Letters, offers the possibility for additional, pioneering discoveries.

"In many areas of science, simulations provide the best descriptions of a complicated phenomenon, but they are difficult to use in the context of data analysis," said Cranmer.

"The techniques we have developed build a bridge allowing us to exploit these very accurate simulations in the context of data analysis," Cranmer said.

excels at gleaning patterns in data, and this capability can be used to summarise simulated data providing the modern-day equivalent to a black board full of equations, Cranmer said.

(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)

First Published: Thu, September 13 2018. 12:40 IST