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I am running some experiments on a real quantum backend of IBM with qmeans approach. My dataset has 2 features (2 dimensions).

I observe higher execution time on the Quantum Calculate Distance routine than on the classical euclidean distance. I cannot understand why, though. Any thoughts?

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I don't think you can currently compare a classical code and a quantum algorithm 1:1.

Firstly, running experiments on real quantum devices, especially today, can include quite some overhead (e.g. submission of jobs to the hardware, waveform generation, qubit resets, ...). Then, the clock speed of classical computers is of the order of GHz while qubit operations are typically much slower (and depend a lot on what types of qubits). Lastly, if a quantum algorithm has an advantage over classical ones, this speedup is mostly asymptotic and only shows for large problems -- definitely not for simple datasets with only 2 features :)

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