Published June 1, 2023 | Version v1
Dataset Open

Data and code example for the article: "Massively parallel hybrid quantum-classical machine learning for kernelized time-series classification"

  • 1. Agnostiq
  • 2. Brookhaven National Laboratory

Description

Data needed to reproduce the figures of https://arxiv.org/abs/2305.05881 and a simple code example of a quantum-convex-classical neural network used to train a sine versus cosine classification problem.

Notes

This research used quantum computing resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. This research used resources of the National Energy Research Scientific 13 Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC award DDR-ERCAP0024165. We acknowledge the use of IBM Quantum services for this work. The views expressed are those of the authors and do not reflect the official policy or position of IBM or the IBM Quantum team.

Files

time_series_hamiltonain_kernel.zip

Files (12.8 MB)

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Additional details

Related works

Is cited by
Preprint: arXiv:2305.05881 (arXiv)