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I am attempting to use a quantum algorithm, like a QAOA, to solve an optimization problem. I saw that qPCA can be used to simplify datasets and make them easier to analyze. Can quantum optimization be used on a dataset that is reduced by qPCA? If the qPCA is extracting only the largest eigenvalues, which I believe are points with the highest energy, to be looked at by the optimization algorithm, which is trying to find the energy minimums, would using a qPCA before an optimization algorithm actually be a detriment to the results? In other words, is it okay to only look at the highest energy values when trying to find the minimum? Otherwise, can qPCA perhaps be used in the opposite way, to extract only minimums for the optimization algorithm to look at?

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