Web: http://arxiv.org/abs/2205.01698

May 5, 2022, 1:11 a.m. | V. Akshay, H. Philathong, E. Campos, D. Rabinovich, I. Zacharov, Xiao-Ming Zhang, J. Biamonte

cs.LG updates on arXiv.org arxiv.org

Variational quantum algorithms are the centerpiece of modern quantum
programming. These algorithms involve training parameterized quantum circuits
using a classical co-processor, an approach adapted partly from classical
machine learning. An important subclass of these algorithms, designed for
combinatorial optimization on currrent quantum hardware, is the quantum
approximate optimization algorithm (QAOA). It is known that problem density - a
problem constraint to variable ratio - induces under-parametrization in fixed
depth QAOA. Density dependent performance has been reported in the literature,
yet …

arxiv on optimization quantum scaling

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