CERN's Large Hadron Collider: Quantum Computing for Particle Physics Data Analysis

The Large Hadron Collider (LHC), the world's largest and most powerful particle accelerator, is located at CERN on the border of Switzerland and France. Since Estonia became a full member of CERN this year, our opportunities to develop science, technology, and entrepreneurship have expanded. CERN is a leading center for particle physics research. It is one of the few innovation centers and directions where Europe is competitive in the world.

Protons are collided in the LHC millions of times per second. Each collision produces hundreds of thousands of particles that carry information about the laws of nature at very high energies or in the very early stages of the universe's evolution. In 2012, a completely new type of particle was discovered at CERN - the spinless Higgs boson, which gives mass to other particles. These discoveries do not happen on their own: every breakthrough requires the processing of a huge amount of data. LHC detectors record millions of collisions per second, so petabytes of data are generated every day, which must be thoroughly analyzed. Such data analysis is becoming increasingly complex for two reasons. First, the LHC's ongoing upgrades are constantly increasing data streams. In addition, searching for new particles and phenomena requires more precise analysis to distinguish rare events from ordinary ones. Current computing systems are reaching their limits as the complexity of this task grows.

Here, quantum computers could come to the rescue in the future, which can solve certain tasks exponentially better and faster than a conventional computer. For example, when analyzing particle physics data, it is difficult to reconstruct particles, separate weak signals from background noise, and make data-based predictions based on current laws of nature, or simulate artificial data. Quantum computers can often solve classical algorithms used today, which are based on combinatorics, optimization, or machine learning, faster.

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