This research project was pursued during the IBM - Ascola Challenge, August-December 2020.
Although intermediate-scale quantum computers are available for use today, they suffer from quantum noise.
In order to combat this noise, our team aimed to predict the noise model applied to a quantum circuit using machine learning techniques.
We approached this problem as an open-ended question. Thus, a lot of time was devoted to
translating the problem into concrete terms.
Using Qiskit Simulators, we produced synthetic datasets which span the defined state-space uniformly.
The datasets can be found in the datasets folder. Due to size limitations, the largest dataset can be found here.
Finally, we explored the synthetic datasets produced using Jupyter Notebooks.
Noam Siegel - noamsi@post.bgu.ac.il
Raphaelbuzaglo - raphaelbuzaglo@gmail.com
Shelly Garion - shelly@il.ibm.com
Gadi Aleksandrowicz - gadial@gmail.com
Project Link: https://github.com/noamsgl/IBMAscolaChallenge
