Research article

Probabilistic bounds on the number of elements to generate finite nilpotent groups and their applications to quantum algorithms

  • Published: 07 April 2026
  • MSC : 20P05, 68Q12

  • This work establishes a new probabilistic bound on the number of elements needed to generate finite nilpotent groups. Let $ \varphi_k(G) $ denote the probability that $ k $ random elements generate a finite nilpotent group $ G $. For any $ 0 < \epsilon < 1 $, we prove that $ \varphi_k(G) \ge 1 - \epsilon $ if $ k \ge \operatorname{rank}(G) + \lceil \log_2(2/\epsilon) \rceil $ (a bound based on the group rank) or if $ k \ge \operatorname{len}(G) + \lceil \log_2(1/\epsilon) \rceil $ (a bound based on the composition length). Moreover, these bounds are shown to be nearly tight. Both bounds sharpen the previously known requirement of $ k \ge \lceil \log_2 |G| + \log_2(1/\epsilon) \rceil + 2 $. Our results provide a foundational tool to analyze probabilistic algorithms, thereby enabling a better estimation of the iteration count for the finite abelian hidden subgroup problem (AHSP) standard quantum algorithm and a reduction in the circuit repetitions required by Regev's factoring algorithm.

    Citation: Ziyuan Dong, Xiang Fan, Tengxun Zhong, Daowen Qiu. Probabilistic bounds on the number of elements to generate finite nilpotent groups and their applications to quantum algorithms[J]. AIMS Mathematics, 2026, 11(4): 9380-9397. doi: 10.3934/math.2026389

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  • This work establishes a new probabilistic bound on the number of elements needed to generate finite nilpotent groups. Let $ \varphi_k(G) $ denote the probability that $ k $ random elements generate a finite nilpotent group $ G $. For any $ 0 < \epsilon < 1 $, we prove that $ \varphi_k(G) \ge 1 - \epsilon $ if $ k \ge \operatorname{rank}(G) + \lceil \log_2(2/\epsilon) \rceil $ (a bound based on the group rank) or if $ k \ge \operatorname{len}(G) + \lceil \log_2(1/\epsilon) \rceil $ (a bound based on the composition length). Moreover, these bounds are shown to be nearly tight. Both bounds sharpen the previously known requirement of $ k \ge \lceil \log_2 |G| + \log_2(1/\epsilon) \rceil + 2 $. Our results provide a foundational tool to analyze probabilistic algorithms, thereby enabling a better estimation of the iteration count for the finite abelian hidden subgroup problem (AHSP) standard quantum algorithm and a reduction in the circuit repetitions required by Regev's factoring algorithm.



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  • © 2026 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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