The complexity class $PSPACE$ includes all computational problems that can be solved by a classical computer with polynomial memory. All $PSPACE$ problems are known to be solvable by a quantum computer too with polynomial memory and are, therefore, known to be in $BQPSPACE$. Here, we present a polynomial time quantum algorithm for a $PSPACE$-complete problem, implying that $PSPACE$ is a subset of the class $BQP$ of all problems solvable by a quantum computer in polynomial time. In particular, we outline a $BQP$ algorithm for the $PSPACE$-complete problem of evaluating a full binary $NAND$ tree. An existing best of quadratic speedup is achieved using quantum walks for this problem, which is still exponential in the problem size. By contrast, we achieve an exponential speedup for the problem, allowing for solving it in polynomial time. There are many real-world applications of our result, such as strategy games like chess or Go. As an example, in quantum sensing, the problem of quantum illumination, that is treated as that of channel discrimination, is $PSPACE$-complete. Our work implies that quantum channel discrimination, and therefore, quantum illumination, can be performed by a quantum computer in polynomial time.
翻译:复杂等级 $PSPACE$ 包含所有可以通过具有多元记忆的古典计算机解决的计算问题。 所有的 $PSPACE$ 问题都被一个具有多元记忆的量子计算机所知道, 并且因此以$BQPACE$为名。 在这里, 我们为一个 $PSPACE$- 完整的问题提出了一个多元时间量算算法, 意味着 $PSPACE$是所有在多元记忆中可以通过量子计算机解决的所有问题中的一部分。 特别是, 我们为一个完全的量子计算机计算机计算机计算机计算机计算机计算机计算机计算机计算机化系统, 以数量化为例, 我们的量子化系统, 我们的量子化系统, 我们的量子化系统, 我们的量子化系统, 我们的量子化系统, 的量子化系统, 我们的量子化系统, 的量子化系统, 以量子化的量子化系统, 我们的量子化系统, 的量子化系统, 的量化的量子化系统, 的量子化, 的量化的量化的量化系统, 我们的量化系统, 的量化的量化的量化的量化的量化, 的量化的量化的量化, 可以被处理。