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\begin{document}

\title{Experimental pairwise entanglement estimation for an N-qubit system}



\author[1]{Elizabeth Behrman }%
\author[2]{Nathan Thompson }%
\author[2]{Nam Nguyen }%
\author[2]{James Steck }%
\affil[1]{Wichita State University}%
\affil[2]{Affiliation not available}%


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  \date{May 16, 2024}


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\begin{abstract}
Designing and implementing algorithms for medium and large scale quantum
computers is not easy. In previous work we have suggested, and
developed, the idea of using machine learning techniques to train a
quantum system such that the desired process is ``learned,'' thus
obviating the algorithm design difficulty. This works quite well for
small systems. But the goal is macroscopic physical computation. Here,
we implement our learned pairwise entanglement witness on Microsoft's
Q\textbackslash{}\#, one of the commercially available gate model
quantum computer simulators; we perform statistical analysis to
determine reliability and reproducibility; and we show that after
training the system in stages for an incrementing number of qubits (2,
3, 4, \textbackslash{}ldots) we can infer the pattern for mesoscopic
\$N\$ from simulation results for three-, four-, five-, six-, and
seven-qubit systems. Our results suggest a fruitful pathway for general
quantum computer algorithm design and for practical computation on noisy
intermediate scale quantum devices.%
\end{abstract}%



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