Quantum state preparation is an important ingredient for other higher-level quantum algorithms, such as Hamiltonian simulation, or for loading distributions into a quantum device to be used e.g. in the context of optimization tasks such as machine learning. Starting with a generic "black box" method devised by Grover in 2000, which employs amplitude amplification to load coefficients calculated by an oracle, there has been a long series of results and improvements with various additional conditions on the amplitudes to be loaded, culminating in Sanders et al.'s work which avoids almost all arithmetic during the preparation stage. In this work, we construct an optimized black box state loading scheme with which various important sets of coefficients can be loaded significantly faster than in $O(\sqrt N)$ rounds of amplitude amplification, up to only $O(1)$ many. We achieve this with two variants of our algorithm. The first employs a modification of the oracle from Sanders et al., which requires fewer ancillas ($\log_2 g$ vs $g+2$ in the bit precision $g$), and fewer non-Clifford operations per amplitude amplification round within the context of our algorithm. The second utilizes the same oracle, but at slightly increased cost in terms of ancillas ($g+\log_2g$) and non-Clifford operations per amplification round. As the number of amplitude amplification rounds enters as multiplicative factor, our black box state loading scheme yields an up to exponential speedup as compared to prior methods. This speedup translates beyond the black box case.
翻译:量子状态制备是其它更高水平量算算法(如汉密尔顿模拟等)的重要成分,或者将分布器装入量子装置的重要成分,例如用于机器学习等优化任务。从2000年格罗弗设计的通用“黑箱”方法开始,该方法使用振幅振幅放大法来加载一个神器计算的系数,我们用两个变方算法实现了这一点。第一个变法是桑德斯等人(Sanders et al.),这在准备阶段避免了几乎所有算术。在这项工作中,我们建造了一个优化黑箱状态装载方案,其中各种重要系数的装载速度可以大大超过美元(sqrt N)的增量数,最多只能达到美元(1美元)。我们用两种变法实现了这一点。第一个变法是桑德斯等人(Sanderphery et al.) 的变法,这需要更少的acilla(log_ 2 g) 和 $2美元(g+2美元) 在比亚精度精确 美元(sqral) 的计算中, 各种增量法方法在前的递增一个不比Cral-crialcrialalI化方法。