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Monte Carlo Markov chain based quantum program optimization

机译:基于蒙特卡洛马尔可夫链的量子程序优化

摘要

From a quantum program a first mutant is generated using a processor and a memory, where the first mutant is a randomly-generated transformation of the quantum program. A quality score, a correctness distance, and a probability of acceptance corresponding to the first mutant are computed. An acceptance corresponding to the first mutant is determined according to the probability of acceptance. Upon determining that an acceptance of the first mutant corresponding to the probability of acceptance exceeds an acceptance threshold, the quantum program is replaced with the first mutant. Upon determining that the quality score exceeds a storage threshold and that the correctness distance is zero, the first mutant is stored. These actions are iterated until reaching an iteration limit.
机译:从量子程序中,使用处理器和内存生成第一个突变体,其中第一个突变体是量子程序的随机生成转换。计算与第一个突变体相对应的质量分数、正确距离和接受概率。根据接受的概率确定对应于第一个突变体的接受。在确定对应于接受概率的第一个突变体的接受超过接受阈值时,量子程序将替换为第一个突变体。在确定质量分数超过存储阈值且正确距离为零后,将存储第一个突变体。这些操作将迭代,直到达到迭代限制。

著录项

  • 公开/公告号US11651232B2;US2023011651232B2;US11651232B2;US11651232

    专利类型

  • 公开/公告日2023-05-16

    原文格式PDF

  • 申请/专利权人 INTERNATIONAL BUSINESS MACHINES CORPORATION;

    申请/专利号US16052348;US201800016052348;US201816052348A;US201816052348

  • 发明设计人

    申请日2018-08-01

  • 分类号G06N3/126;G06F8/41;G06F17/18;G06N10;

  • 国家

  • 入库时间 2024-06-14 23:57:18

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