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Mechanisms and machine science

Hadron Collider and Quantum Computer

Aleksandr B. Vavrenyuk, Victor V. Makarov, Victor A. Shurygin

Published Jan 1, 2020• 1 citation
Publisher
DOI
10.1007/978-3-030-33491-8_22

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Particle collider experiments aim to understand Nature at small scales. Particle accelerators, such as the Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN), collide particles at high rates (MHz) and high energies (TeV) in order to probe such small scales. High collision rates may bring many computational challenges. One of these challenges is particle track reconstruction, which is the task of distinguishing the trajectories of charged particles passing through the detector. The upcoming High Luminosity upgrade of the LHC is going to increase the collision rates and require more computational resources. Particle track reconstruction algorithms will also be under much more stress, as the current algorithms are scaling worse than quadratically. This work presents a hybrid Quantum-Classical model to solve the particle track reconstruction problem by combining novel Graph Neural Networks with Quantum Neural Networks that are compatible with Noisy Intermediate Scale Quantum (NISQ) computers. Results indicate that the hybrid model can match the performance of the classical model within the limits of 16 qubits and 16 hidden dimensions.

•Aug 20, 2021•0 citations
Chinese scientists won a major victory, by proving that the Majorana fermion-a particle we've found tantaliying hints for years-genuinely exists.This discovery has huge implications for quantum computing, and it might change the world.Don Lincoln, a senior physicist at Fermilab, does research using the Large Hadron Collider.He is the author of "The Large Hadron Collider: The Extraordinary Story of the Higgs Boson and Other Stuff That Will Blow Your Mind" and produces a series of science education videos.To the question: Why is there (in our Universe) something including cancer, rather than nothing?He is giving the simplest scientific answer: We shouldn't exist at all.
Chinese scientists won a major victory, by proving that the Majorana fermions – a particle we’ve found tantalizing hints for years – genuinely exists. This discovery has huge implications for quantum computing, and it might change the world. Don Lincoln, a senior physicist at Fermi lab, does research using the Large Hadrons Collider. He is the author of “The Large Hadrons Collider: The Extraordinary Story of the Higgs Boson and Other Stuff That Will Blow Your Mind”, and produces a series of science education videos. To the question: Why is there (in our Universe) something including cancer, rather than nothing? He is giving the simplest scientific answer: We shouldn’t exist at all.
Particle collider experiments aim to understand Nature at small scales. Particle accelerators, such as the Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN), collide particles at high rates (MHz) and high energies (TeV) in order to probe such small scales. High collision rates may bring many computational challenges. One of these challenges is particle track reconstruction, which is the task of distinguishing the trajectories of charged particles passing through the detector. The upcoming High Luminosity upgrade of the LHC is going to increase the collision rates and require more computational resources. Particle track reconstruction algorithms will also be under much more stress, as the current algorithms are scaling worse than quadratically. This work presents a hybrid Quantum-Classical model to solve the particle track reconstruction problem by combining novel Graph Neural Networks with Quantum Neural Networks that are compatible with Noisy Intermediate Scale Quantum (NISQ) computers. Results indicate that the hybrid model can match the performance of the classical model within the limits of 16 qubits and 16 hidden dimensions.