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25th International Conference on Computing in High Energy & Nuclear Physics

17–21 May 2021
Europe/Paris timezone

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Session

Quantum Computing

20 May 2021, 10:50

Conveners

Quantum Computing: Thu AM

  • Sofia Vallecorsa (CERN)
  • Andrea Sartirana (Centre National de la Recherche Scientifique (FR))

Presentation materials

Mattermost
Video recording Thursday morning
Zoom
  1. 98. Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications
    Koji Terashi (University of Tokyo (JP))
    20/05/2021, 10:50
    Offline Computing
    Short Talk

    There is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivities, and coherence times, circuit optimization is essential to make the best use of near-term quantum devices. We introduce two separate ideas for circuit optimization and combine them in a multi-tiered quantum circuit optimization protocol called AQCEL. The first ingredient is a...

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  2. 157. Dual-Parameterized Quantum Circuit GAN Model in High Energy Physics
    Su Yeon Chang (EPFL - Ecole Polytechnique Federale Lausanne (CH))
    20/05/2021, 11:03
    Offline Computing
    Short Talk

    Generative Models, and Generative Adversarial Networks (GAN) in particular, are being studied as possible alternatives to Monte Carlo. Meanwhile, it has also been proposed that, in certain circumstances, simulation using GANs can itself be sped-up by using quantum GANs (qGANs).

    Our work presents an advanced prototype of qGAN, that we call the dual-Parameterized Quantum Circuit (PQC) GAN,...

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  3. 201. Embedding of particle tracking data using hybrid quantum classical neural networks
    Carla Sophie Rieger
    20/05/2021, 11:16
    Offline Computing
    Short Talk

    The High Luminosity Large Hadron Collider (HL-LHC) at CERN will involve a significant increase in complexity and sheer size of data with respect to the current LHC experimental complex. Hence, the task of reconstructing the particle trajectories will become more complex due to the number of simultaneous collisions and the resulting increased detector occupancy. Aiming to identify the particle...

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  4. 210. Higgs analysis with quantum classifiers
    Vasileios Belis (ETH Zurich (CH))
    20/05/2021, 11:29
    Offline Computing
    Short Talk

    We have developed two quantum classifier models for the $t\bar{t}H$ classification problem, both of which fall into the category of hybrid quantum-classical algorithms for Noisy Intermediate Scale Quantum devices (NISQ). Our results, along with other studies, serve as a proof of concept that Quantum Machine Learning (QML) methods can have similar or better performance, in specific cases of low...

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