Abstract:Abstract. We present new algorithms for computing orders of elements, discrete logarithms, and structures of finite abelian groups. We estimate the computational complexity and storage requirements, and we explicitly determine the O-constants and Ω-constants. We implemented the algorithms for class groups of imaginary quadratic orders and present a selection of our experimental results.Our algorithms are based on a modification of Shanks' baby-step giantstep strategy, and have the advantage that their computat… Show more
“…The numbers in brackets indicate which of the five giant-step sizes used was optimal for the given ideal class and algorithm. Note that in the case of ∆ = −4(10 10 + 1), and v = 2, |∆| 1 4 /2, and |∆| 1 4 (middle four rows of Tables 1, 4, and 5) my results for the BJT algorithm agree with those in [1].…”
Section: Theorem 22 For the Above Algorithm We Havesupporting
confidence: 59%
“…every positive integer n can be expressed as the difference t j − i, where t j is the least number in the sequence (t j ) not exceeding n and 0 ≤ i < j + v. The algorithm proceeds as follows. (My notation is the same as in [1].) (17) Proof.…”
Section: The Order Algorithmmentioning
confidence: 99%
“…Shanks' baby-step giant-step algorithm [1,2] is a well-known procedure for finding the order n of an element g of a finite group G. Running it involves 2 √ K + O(1) group multiplications (GM), and √ K + O(1) table lookups (TL), where K is an upper bound on n (for instance, one often uses K = |G|). Often, however, K is unknown or much larger than n. In this case, a faster algorithm is desired.…”
Abstract. I describe a modification to Shanks' baby-step giant-step algorithm for computing the order n of an element g of a group G, assuming n is finite. My method has the advantage of being able to compute n quickly, which Shanks' method fails to do when the order of G is infinite, unknown, or much larger than n. I describe the algorithm in detail. I also present the results of implementations of my algorithm, as well as those of a similar algorithm developed by Buchmann, Jacobson, and Teske, for calculating the order of various ideal classes of imaginary quadratic orders.
“…The numbers in brackets indicate which of the five giant-step sizes used was optimal for the given ideal class and algorithm. Note that in the case of ∆ = −4(10 10 + 1), and v = 2, |∆| 1 4 /2, and |∆| 1 4 (middle four rows of Tables 1, 4, and 5) my results for the BJT algorithm agree with those in [1].…”
Section: Theorem 22 For the Above Algorithm We Havesupporting
confidence: 59%
“…every positive integer n can be expressed as the difference t j − i, where t j is the least number in the sequence (t j ) not exceeding n and 0 ≤ i < j + v. The algorithm proceeds as follows. (My notation is the same as in [1].) (17) Proof.…”
Section: The Order Algorithmmentioning
confidence: 99%
“…Shanks' baby-step giant-step algorithm [1,2] is a well-known procedure for finding the order n of an element g of a finite group G. Running it involves 2 √ K + O(1) group multiplications (GM), and √ K + O(1) table lookups (TL), where K is an upper bound on n (for instance, one often uses K = |G|). Often, however, K is unknown or much larger than n. In this case, a faster algorithm is desired.…”
Abstract. I describe a modification to Shanks' baby-step giant-step algorithm for computing the order n of an element g of a group G, assuming n is finite. My method has the advantage of being able to compute n quickly, which Shanks' method fails to do when the order of G is infinite, unknown, or much larger than n. I describe the algorithm in detail. I also present the results of implementations of my algorithm, as well as those of a similar algorithm developed by Buchmann, Jacobson, and Teske, for calculating the order of various ideal classes of imaginary quadratic orders.
“…There is another generic algorithm for group structure computation [BJT97], which is based on Shanks' Baby-Step Giant-Step method [Sha71]. It has runtime complexity O( |G|), but it has the disadvantage that it has high storage requirements.…”
Abstract. We present a new algorithm for computing the structure of a finite abelian group, which has to store only a fixed, small number of group elements, independent of the group order. We estimate the computational complexity by counting the group operations such as multiplications and equality checks. Under some plausible assumptions, we prove that the expected run time is O( √ n) (with n denoting the group order), and we explicitly determine the Oconstants. We implemented our algorithm for ideal class groups of imaginary quadratic orders and present experimental results.
“…Now, as ord p (µ i ) = 0 for all i, we can consider the group M/p n . Using an algorithm like the ones in [1] or [6], one can determine the group structure of the M/p n as a product of cyclic groups C 1 ×. .…”
Abstract. In this paper we generalize the method of Wildanger for finding small solutions to unit equations to the case of S-unit equations. The method uses a minor generalization of the LLL based techniques used to reduce the bounds derived from transcendence theory, followed by an enumeration strategy based on the Fincke-Pohst algorithm. The method used reduces the computing time needed from MIPS years down to minutes.
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