虚拟并行计算与矩阵乘积状态搜索算法
Virtual Parallel Computing and a Search Algorithm using Matrix Product States
摘要：
我们提出了一种形式的并行计算的经典计算机是基于矩阵产品的状态。虚拟并行化是通过用矩阵表示比特并通过从编码多个输入的初始产品状态演化这些矩阵来实现的。矩阵演化是由门的顺序应用引起的，就像在逻辑电路中一样。经典的概率性一位和确定性两位门（如NAND）的动作是根据矩阵运算来实现的，与量子计算相反，它可以复制位。我们提出了一种方法来探索这种计算方法来解决搜索问题，并计算解决方案的数量。我们认为，如果经典的计算成本的测试解决方案（证人）需要小于$O(n^2)$本地2位门作用于$n$位，搜索问题可以完全解决在次指数时间。因此，对于这种受限类型的搜索问题，虚拟并行化方案比Grover的量子算法更快
英文摘要：
We propose a form of parallel computing on classical computers that is based on matrix product states. The virtual parallelization is accomplished by representing bits with matrices and by evolving these matrices from an initial product state that encodes multiple inputs. Matrix evolution follows from the sequential application of gates, as in a logical circuit. The action by classical probabilistic one-bit and deterministic two-bit gates such as NAND are implemented in terms of matrix operations and, as opposed to quantum computing, it is possible to copy bits. We present a way to explore this method of computation to solve search problems and count the number of solutions. We argue that if the classical computational cost of testing solutions (witnesses) requires less than $O(n^2)$ local two-bit gates acting on $n$ bits, the search problem can be fully solved in subexponential time. Therefore, for this restricted type of search problem, the virtual parallelization scheme is faster than Grover's quantum algorithm
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