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The passage around this formula

in time that scales as $\text{poly}(\log N, \kappa)$ , an exponential improvement in the matrix dimension N over the best classical algorithms available at the time, which scale roughly as N$\sqrt{\kappa}$ for a matrix with condition number $\kappa$ [ 6 ] . What became known as the HHL algorithm is now routinely cited as the theoretical seed that later, explicitly labeled “quantum machine learning” proposals built their linear-algebra subroutines on top of.

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