论文标题

通过叠加掩模来卸载量子计算

Offloading Quantum Computation by Superposition Masking

论文作者

Jaques, Samuel, Gidney, Craig

论文摘要

误差校正将为大型量子计算增加太多的开销,我们怀疑最有效的算法将使用经典的协调员来做尽可能多的工作。我们提出了一种通过产生隐藏量子输入的面具的叠加来将量子计算的部分卸载到经典计算机的方法。使用掩码,我们可以在不更改原始输入的情况下测量结果,然后对测量的输出执行经典计算。如果任务具有足够的结构,则经典计算将等同于叠加中执行的量子计算。我们将此技术应用于模块化,根发现的,剩余的,稀疏的基质反转和反相通用组同构的分裂,至少可以改善每个量子操作的恒定因素。不幸的是,由于测量值,很难取消计算或倒转这项技术,因此我们不知道有用的算法可以从叠加掩盖中受益。

Error correction will add so much overhead to large quantum computations that we suspect the most efficient algorithms will use a classical co-processor to do as much work as possible. We present a method to offload portions of a quantum computation to a classical computer by producing a superposition of masks which hide a quantum input. With the masks, we can measure the result without altering the original input and then perform classical computations on the measured output. If the task has enough structure, the classical computations will be equivalent to a quantum computation performed in superposition. We apply this technique to modular inversion, root-finding, division with remainder, sparse matrix inversion, and inverting generic group homomorphisms, achieving at least a constant-factor improvement in quantum operations for each. Unfortunately, it is difficult to uncompute or invert this technique because of the measurement, and thus we know of no useful algorithm which benefits from superposition masking.

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