Nav: Home

Machine learning improves accuracy of particle identification at LHC

October 31, 2018

Scientists from the Higher School of Economics have developed a method that allows physicists at the Large Hadron Collider (LHC) to separate between various types of elementary particles with a high degree of accuracy. The results were published in the Journal of Physics.

http://iopscience.iop.org/article/10.1088/1742-6596/1085/4/042036/meta

One of major unsolved problems of modern physics is the predominance of matter over antimatter in the Universe. They both formed within a second after the Big Bang, in presumably equal fractions, and physicists are trying to understand where antimatter has disappeared to. Back in 1966, Russian scientist Andrei Sakharov suggested, that imbalance between matter and antimatter appeared as a result of CP violation, i.e., an asymmetry between particles and antiparticles. Thus only particles remained after their annihilation (mutual destruction) of resulting unbalanced contributions.

The Large Hadron Collider beauty experiment (LHCb) studies unstable particles called B-mesons. Their decays demonstrate the clearest asymmetry between matter and antimatter. The LHCb consists of several specialised detectors, particularly calorimeters to measure the energy of neutral particles. Calorimeters also identify different types of particles. These are done by search and analysing of corresponding clusters of energy deposition. It is, however, not easy to separate signals from two types of photons - primary photons and photons from energetic π0 meson decay. HSE scientists developed a method that will allow physicists to classify these two with a high accuracy.

The authors of the study applied artificial neural networks and gradient boosting (a machine-learning algorithm) to classify energies collected in the individual cells of the energy cluster.

'We took a 5X5 matrix with a centre at the calorimeter cell with the largest energy,' comments Fedor Ratnikov, one of the study's authors and a leading researcher in the HSE Laboratory of Methods for Big Data Analysis. 'Instead of analysing the special characteristics constructed from raw energies in cluster cells, we pass these raw energies directly to the algorithm for analysis. The machine was able to make sense of the data better than a person.'

Compared with the previous method of data pre-processing, the new machine-learning-based method has quadrupled quality metrics for the identification of particles on the calorimeter. The algorithm improved the classification quality from 0.89 to 0.97; the higher this figure is, the better the classifier works. With a 98% effectiveness rate of initial photon identification, the new approach has lowered the false photon identification rate from 60% to 30%.

The proposed method is unique in that it allows for elementary particles to be identified without initial studying the characteristics of the cluster being analysed. 'We can afford to avoid limiting data processing by our particular knowledge about data, but rather pass data to machine learning in the hope that the algorithm finds correlations we might not considered. Such approach obviously worked out in this case,' Fedor Ratnikov concludes.
-end-


National Research University Higher School of Economics

Related Antimatter Articles:

First trace of differences between matter and 'ordinary' antimatter
The world around us is mainly constructed of baryons, particles composed of three quarks.
Research grant for development of positron pulses of unprecedented intensity
The German research foundation DFG (Deutsche Forschungsgemeinschaft) has granted 750,000 euros for the research project 'Creation of intense positron pulses on NEPOMUC' -- a collaboration between the University of Greifswald, the Max Planck Institute for Plasma Physics, and the Technical University of Munich.
Improved measurements of antiproton's magnetic moment deepen mystery of baryonic asymmetry
In work published in Nature Communications, scientists have found, using a sophisticated technique that involves trapping individual particles in a magnetic device, that the magnetic moment of the antiproton is extremely close to that of the proton, with six-fold higher accuracy than before.
New antimatter breakthrough to help illuminate mysteries of the Big Bang
Swansea University physicists working with an international collaborative team at CERN, conduct the first precision study of antihydrogen, the antimatter equivalent of hydrogen.
Antimatter helps to unveil the secrets of liquid crystals
The chaos typical of liquid molecules, and the ordering characteristics of crystals.
Iowa State physicist analyzes first electron neutrino data from NOvA Experiment
Iowa State physicists are part of the huge NOvA Neutrino Experiment that just published two papers about the first experimental observations of muon neutrinos changing to electron neutrinos.
Calcium isotope holds the secret to the mass of neutrinos
Scientists around the world are being kept in suspense by the negligible mass of neutrinos, subatomic particles that could be matter and antimatter at the same time.
Neutral result charges up antimatter research
Scientists of the international ALPHA Collaboration are once again pushing the boundaries of antimatter research with their latest breakthrough studying the properties of antihydrogen.
After repeated pounding, antihydrogen reveals its charge: Zero
Per the Standard Model of Particle Physics, the electrical charge of matter and antimatter should be opposite and equal.
Minutest absolute magnetic field measurement
Every measurement is potentially prone to systematic error. The more sensitive the measurement method, the more important it is to make sure it is also accurate.

Related Antimatter Reading:

Best Science Podcasts 2019

We have hand picked the best science podcasts for 2019. Sit back and enjoy new science podcasts updated daily from your favorite science news services and scientists.
Now Playing: TED Radio Hour

Anthropomorphic
Do animals grieve? Do they have language or consciousness? For a long time, scientists resisted the urge to look for human qualities in animals. This hour, TED speakers explore how that is changing. Guests include biological anthropologist Barbara King, dolphin researcher Denise Herzing, primatologist Frans de Waal, and ecologist Carl Safina.
Now Playing: Science for the People

#SB2 2019 Science Birthday Minisode: Mary Golda Ross
Our second annual Science Birthday is here, and this year we celebrate the wonderful Mary Golda Ross, born 9 August 1908. She died in 2008 at age 99, but left a lasting mark on the science of rocketry and space exploration as an early woman in engineering, and one of the first Native Americans in engineering. Join Rachelle and Bethany for this very special birthday minisode celebrating Mary and her achievements. Thanks to our Patreons who make this show possible! Read more about Mary G. Ross: Interview with Mary Ross on Lash Publications International, by Laurel Sheppard Meet Mary Golda...