论文标题

使用量子算法在豪华实验中跟踪重建

Track reconstruction at the LUXE experiment using quantum algorithms

论文作者

Crippa, Arianna, Funcke, Lena, Hartung, Tobias, Heinemann, Beate, Jansen, Karl, Kropf, Annabel, Kühn, Stefan, Meloni, Federico, Spataro, David, Tüysüz, Cenk, Yap, Yee Chinn

论文摘要

Luxe(激光XFEL实验)是DESY提出的一个实验,该实验将在强场状态中研究量子电动力学(QED),在该状态下,QED变为非扰动。使用硅像素跟踪探测器测量创建的电子峰值对的速率是研究该制度的重要组成部分。横穿跟踪检测器四层的正上音的精确跟踪在高激光强度下变得非常具有挑战性,这对于古典计算机而言可能在计算上昂贵。在这项工作中,我们更新了先前关于使用量子计算重建正电子轨迹的潜力的研究。重建任务被公式为二次不受约束的二进制优化,并使用模拟量子计算机和混合量子量子算法(即变异量子eigensolver)求解。研究了不同的ANSATZ电路和优化器。讨论了结果并将使用图神经网络和组合Kalman滤波器与经典轨道重建算法进行比较。

LUXE (Laser Und XFEL Experiment) is a proposed experiment at DESY which will study Quantum Electrodynamics (QED) in the strong-field regime, where QED becomes non-perturbative. Measuring the rate of created electron-positron pairs using a silicon pixel tracking detector is an essential ingredient to study this regime. Precision tracking of positrons traversing the four layers of the tracking detector becomes very challenging at high laser intensities due to the high rates, which can be computationally expensive for classical computers. In this work, we update our previous study of the potential of using quantum computing to reconstruct positron tracks. The reconstruction task is formulated as a quadratic unconstrained binary optimisation and is solved using simulated quantum computers and a hybrid quantum-classical algorithm, namely the variational quantum eigensolver. Different ansatz circuits and optimisers are studied. The results are discussed and compared with classical track reconstruction algorithms using a graph neural network and a combinatorial Kalman filter.

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