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We present studies of quantum algorithms exploiting machine learning to classify events of interest from background events, one of the most representative machine learning applications in high-energy physics.
Journal of Physics: Conference Series 219
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Phys. Rev. D 101
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URL https://quantum-computing.ibm.com/docs/cloud/backends/systems/
ibmq_boeblingen, IBM Quantum team. Retrieved from https://quantum-computing.ibm.com (2020) · 2020
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Bauer, C.W., De Jong, W.A., Nachman, B., Provasoli, D.: A quantum algorithm for high energy physics simulations (2019)
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Nature 567
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DOI 10.5281/zenodo.2562110
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Quantum Science and Technology 5
Provasoli, D., Nachman, B., Bauer, C., de Jong, W.A.: A quantum algorithm to efficiently sample from interfering binary trees · 2058
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