量子機器學習，是將量子算法整合到機器學習程序中。[1][2][3][4][5][6][7]該術語最常見的用法是指用於分析量子計算機上執行的經典數據的機器學習算法，即量子增強機器學習。[8][9][10][11]常規機器學習算法被用來計算海量數據，而量子機器學習利用量子位和量子運算或專門的量子系統來提高算法在程序中完成的計算速度和數據存儲。[12]在實際操作中，量子機器學習會混合常規機器學習，先用常規計算機執行機器學習程序，然後將無法通過常規計算機完成的子程序交由量子計算機完成。[13][14][15]這些子程序可能比較複雜，在量子計算機上執行會有著更顯著的速度提升。[2]此外，量子算法可以用來分析量子態而不僅僅局限於常規數據。[16][17]
參考文獻[編輯]
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