We heuristically show that Shor's algorithm for computing general discrete logarithms achieves an expected success probability of approximately 60% to 82% in a single run when modified to enable efficient implementation with the semi-classical Fourier transform. By slightly increasing the number of group operations that are evaluated quantumly and performing a single limited search in the classical post-processing, or by performing two limited searches in the post-processing, we show how the algorithm can be further modified to achieve a success probability that heuristically exceeds 99% in a single run. We provide concrete heuristic estimates of the success probability of the modified algorithm, as a function of the group order $r$, the size of the search space in the classical post-processing, and the additional number of group operations evaluated quantumly. In the limit as $r \rightarrow \infty$, we heuristically show that the success probability tends to one. In analogy with our earlier works, we show how the modified quantum algorithm may be heuristically simulated classically when the logarithm $d$ and $r$ are both known. Furthermore, we heuristically show how slightly better tradeoffs may be achieved, compared to our earlier works, if $r$ is known when computing $d$. We generalize our heuristic to cover some of our earlier works, and compare it to the non-heuristic analyses in those works.
翻译:我们从表面可以看出,Shor用于计算普通离散对数的算法,在经过修改后,如果能够以半古典的Fourier变换使半古典的Fourier变形能够高效实施,预期一次成功概率约为60%至82%。通过略微增加在古典后处理中进行量性评估并进行一次有限搜索的组操作数量,或者在后处理中进行两次有限的搜索,我们展示了如何进一步修改算法,以便实现在一次运行中超常超过99 %的成功概率。我们提供了对修改算法成功概率的具体超常估计,作为集团订单的函数,即$美元、古典后处理中搜索空间的大小以及额外组操作量性评估。在以$为单位的限度内,我们粗略地表明成功概率是1。与我们早先的作品相比,修改的量值算算算算法如何以典型的方式模拟修改后算法的概率,因为对美元和美元作对美元的对价的对价的对价,如果我们之前的对价分析可以稍为了解,那么,那么,那么,我们的贸易成本对价的计算就会显示我们之前的作品的对价成本对美元的比就会比。</s>