We propose a deterministic algorithm based on Coppersmith's method that employs a rank-3 lattice to address factoring-related problems. An interesting aspect of our approach is that we utilize the second vector in the LLL-reduced basis to avoid trivial collisions in the Baby-step Giant-step method, rather than the shortest vector as is commonly used in the literature. Our results are as follows: 1. Compared to the result by Harvey and Hittmeir (Math. Comp. 91 (2022), 1367 - 1379), who achieved a complexity of O( N^(1/5) log^(16/5) N / (log log N)^(3/5)) for factoring a semiprime N = pq, we demonstrate that in the balanced p and q case, the complexity can be improved to O( N^(1/5) log^(13/5) N / (log log N)^(3/5) ). 2. For factoring sums and differences of powers, that is, numbers of the form N = a^n plus or minus b^n, we improve Hittmeir's result (Math. Comp. 86 (2017), 2947 - 2954) from O( N^(1/4) log^(3/2) N ) to O( N^(1/5) log^(13/5) N ). 3. For the problem of finding r-power divisors, that is, finding all integers p such that p^r divides N, Harvey and Hittmeir (Proceedings of ANTS XV, Research in Number Theory 8 (2022), no. 4, Paper No. 94) recently directly applied Coppersmith's method and achieved a complexity of O( N^(1/(4r)) log^(10+epsilon) N / r^3 ). By using faster LLL-type algorithms and sieving on small primes, we improve their result to O( N^(1/(4r)) log^(7+3 epsilon) N / ((log log N minus log(4r)) r^(2+epsilon)) ). The worst-case running time for their algorithm occurs when N = p^r q with q on the order of N^(1/2). By focusing on this case and employing our rank-3 lattice approach, we achieve a complexity of O( r^(1/4) N^(1/(4r)) log^(5/2) N ). In conclusion, we offer a new perspective on these problems, which we hope will provide further insights.
翻译:我们提出一种基于Coppersmith方法的确定性算法,该算法采用秩为3的格来处理与因式分解相关的问题。我们方法的一个有趣之处在于,我们利用LLL约简基中的第二向量来避免大步小步法中的平凡碰撞,而非如文献中常见的那样使用最短向量。我们的结果如下:1. 与Harvey和Hittmeir(Math. Comp. 91 (2022), 1367 - 1379)的结果相比,他们对半素数N = pq的分解实现了O( N^(1/5) log^(16/5) N / (log log N)^(3/5) )的复杂度,我们证明在p和q平衡的情况下,复杂度可以改进为O( N^(1/5) log^(13/5) N / (log log N)^(3/5) )。2. 对于幂和与幂差的因式分解,即形如N = a^n ± b^n的数,我们将Hittmeir的结果(Math. Comp. 86 (2017), 2947 - 2954)从O( N^(1/4) log^(3/2) N )改进为O( N^(1/5) log^(13/5) N )。3. 对于寻找r幂除数的问题,即寻找所有满足p^r整除N的整数p,Harvey和Hittmeir(Proceedings of ANTS XV, Research in Number Theory 8 (2022), no. 4, Paper No. 94)最近直接应用Coppersmith方法,实现了O( N^(1/(4r)) log^(10+epsilon) N / r^3 )的复杂度。通过使用更快的LLL类算法以及对小素数进行筛法,我们将他们的结果改进为O( N^(1/(4r)) log^(7+3 epsilon) N / ((log log N - log(4r)) r^(2+epsilon)) )。他们算法的最坏情况运行时间发生在N = p^r q且q的量级为N^(1/2)时。通过聚焦于这种情况并采用我们的秩为3的格方法,我们实现了O( r^(1/4) N^(1/(4r)) log^(5/2) N )的复杂度。总之,我们为这些问题提供了一个新的视角,希望这将带来进一步的见解。