Practical Quantum Computing

Adrien Suau, G. Staffelbach, H. Calandra
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引用次数: 20

Abstract

In the last few years, several quantum algorithms that try to address the problem of partial differential equation solving have been devised: on the one hand, “direct” quantum algorithms that aim at encoding the solution of the PDE by executing one large quantum circuit; on the other hand, variational algorithms that approximate the solution of the PDE by executing several small quantum circuits and making profit of classical optimisers. In this work, we propose an experimental study of the costs (in terms of gate number and execution time on a idealised hardware created from realistic gate data) associated with one of the “direct” quantum algorithm: the wave equation solver devised in [32]. We show that our implementation of the quantum wave equation solver agrees with the theoretical big-O complexity of the algorithm. We also explain in great detail the implementation steps and discuss some possibilities of improvements. Finally, our implementation proves experimentally that some PDE can be solved on a quantum computer, even if the direct quantum algorithm chosen will require error-corrected quantum chips, which are not believed to be available in the short-term.
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实用量子计算
在过去的几年中,已经设计了几种试图解决偏微分方程求解问题的量子算法:一方面,“直接”量子算法旨在通过执行一个大量子电路来编码PDE的解;另一方面,变分算法通过执行几个小量子电路并利用经典优化器来近似解PDE。在这项工作中,我们提出了一项与一种“直接”量子算法相关的成本(从实际门数据创建的理想硬件上的门数和执行时间)的实验研究:[32]中设计的波动方程求解器。我们证明了我们的量子波动方程求解器的实现符合算法的理论大0复杂度。我们还非常详细地解释了实现步骤,并讨论了一些改进的可能性。最后,我们的实现在实验上证明了一些PDE可以在量子计算机上解决,即使选择的直接量子算法需要纠错量子芯片,这在短期内是不可用的。
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