scholarly journals Traps to the BGJT-algorithm for discrete logarithms

2014 ◽  
Vol 17 (A) ◽  
pp. 218-229 ◽  
Author(s):  
Qi Cheng ◽  
Daqing Wan ◽  
Jincheng Zhuang
Keyword(s):  
Finite Fields ◽  
Polynomial Time ◽  
Time Complexity ◽  
Complexity Analysis ◽  
Discrete Logarithm ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
New Approach ◽  
Discrete Logarithms ◽  
Polynomial Time Complexity

AbstractIn the recent breakthrough paper by Barbulescu, Gaudry, Joux and Thomé, a quasi-polynomial time algorithm is proposed for the discrete logarithm problem over finite fields of small characteristic. The time complexity analysis of the algorithm is based on several heuristics presented in their paper. We show that some of the heuristics are problematic in their original forms, in particular when the field is not a Kummer extension. We propose a fix to the algorithm in non-Kummer cases, without altering the heuristic quasi-polynomial time complexity. Further study is required in order to fully understand the effectiveness of the new approach.

scholarly journals POLYNOMIAL-TIME COMPLEXITY FOR INSTANCES OF THE ENDOMORPHISM PROBLEM IN FREE GROUPS

2007 ◽  
Vol 17 (02) ◽  
pp. 289-328 ◽  
Author(s):  
LAURA CIOBANU
Keyword(s):  
Free Group ◽  
Polynomial Time ◽  
Efficient Algorithm ◽  
Time Complexity ◽  
Free Groups ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
The Other ◽  
Polynomial Time Complexity

We say the endomorphism problem is solvable for an element W in a free group F if it can be decided effectively whether, given U in F, there is an endomorphism ϕ of F sending W to U. This work analyzes an approach due to Edmunds and improved by Sims. Here we prove that the approach provides an efficient algorithm for solving the endomorphism problem when W is a two-generator word. We show that when W is a two-generator word this algorithm solves the problem in time polynomial in the length of U. This result gives a polynomial-time algorithm for solving, in free groups, two-variable equations in which all the variables occur on one side of the equality and all the constants on the other side.

scholarly journals ON THE EDGE OF DECIDABILITY IN COMPLEXITY ANALYSIS OF LOOP PROGRAMS

2012 ◽  
Vol 23 (07) ◽  
pp. 1451-1464 ◽  
Author(s):  
AMIR M. BEN-AMRAM ◽  
LARS KRISTIANSEN
Keyword(s):  
Second Language ◽  
Programming Language ◽  
Polynomial Time ◽  
Time Complexity ◽  
Complexity Analysis ◽  
Feasibility Problem ◽  
Polynomial Time Complexity ◽  
Turing Complete ◽  
The Given

We investigate the decidability of the feasibility problem for imperative programs with bounded loops. A program is called feasible if all values it computes are polynomially bounded in terms of the input. The feasibility problem is representative of a group of related properties, like that of polynomial time complexity. It is well known that such properties are undecidable for a Turing-complete programming language. They may be decidable, however, for languages that are not Turing-complete. But if these languages are expressive enough, they do pose a challenge for analysis. We are interested in tracing the edge of decidability for the feasibility problem and similar problems. In previous work, we proved that such problems are decidable for a language where loops are bounded but indefinite (that is, the loops may exit before completing the given iteration count). In this paper, we consider definite loops. A second language feature that we vary, is the kind of assignment statements. With ordinary assignment, we prove undecidability of a very tiny language fragment. We also prove undecidability with lossy assignment (that is, assignments where the modified variable may receive any value bounded by the given expression, even zero). But we prove decidability with max assignments (that is, assignments where the modified variable never decreases its value).

FAST ISOMORPHISM TESTING IN ARITHMETICAL VARIETIES

2003 ◽  
Vol 13 (04) ◽  
pp. 499-506
Author(s):  
TOMASZ A. GORAZD
Keyword(s):  
Finite Fields ◽  
Polynomial Time ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Boolean Algebras ◽  
Heyting Algebras ◽  
Subdirectly Irreducible ◽  
Finite Algebras ◽  
Element Chain ◽  
Subdirectly Irreducible Algebras

Let [Formula: see text] be a finitely generated, arithmetical variety such that all subdirectly irreducible algebras from [Formula: see text] have linearly ordered congruences. We show that there is a polynomial time algorithm that tests the existing of an isomorphism between any two finite algebras from [Formula: see text]. This includes the following classical structures in algebra: • Boolean algebras. • Varieties of rings generated by finitely many finite fields. • Varieties of Heyting algebras generated by an n–element chain.

An O(m^2)-depth quantum algorithm for the elliptic curve discrete logarithm problem over GF(2^m)

2009 ◽  
Vol 9 (7&8) ◽  
pp. 610-621
Author(s):  
D. Maslov ◽  
J. Mathew ◽  
D. Cheung ◽  
D.K. Pradhan
Keyword(s):  
Elliptic Curve ◽  
Elliptic Curves ◽  
Finite Fields ◽  
Nearest Neighbor ◽  
Discrete Logarithm ◽  
Quantum Algorithm ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Discrete Logarithm Problem ◽  
Quantum Polynomial

We consider a quantum polynomial-time algorithm which solves the discrete logarithm problem for points on elliptic curves over $GF(2^m)$. We improve over earlier algorithms by constructing an efficient circuit for multiplying elements of binary finite fields and by representing elliptic curve points using a technique based on projective coordinates. The depth of our proposed implementation, executable in the Linear Nearest Neighbor (LNN) architecture, is $O(m^2)$, which is an improvement over the previous bound of $O(m^3)$ derived assuming no architectural restrictions.

Computing the residual Galois representations

2011 ◽  
Author(s):  
Bas Edixhoven
Keyword(s):  
Finite Fields ◽  
Polynomial Time ◽  
Galois Representations ◽  
Las Vegas ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Complex Numbers ◽  
Rigorous Proof ◽  
Main Result Theorem ◽  
Result Theorem

This chapter proves the main result on the computation of Galois representations. It provides a detailed description of the algorithm and a rigorous proof of the complexity. It first combines the results of chapters 11 and 12 in order to work out the strategy of Chapter 3. This gives the main result, Theorem 14.1.1: a deterministic polynomial time algorithm, based on computations with complex numbers. The crucial transition from approximations to exact values is done, and the proof of Theorem 14.1.1 is finished later in the chapter. The chapter then replaces the complex computations with the computations over finite fields from Chapter 13, and gives a probabilistic (Las Vegas type) polynomial time variant of the algorithm in Theorem 14.1.1.

scholarly journals On Counting the Number of Consistent Genotype Assignments for Pedigrees

2005 ◽  
Vol 12 (28) ◽  
Author(s):  
Jirí Srba
Keyword(s):  
Polynomial Time ◽  
Complexity Analysis ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Consistency Checking ◽  
Counting Problem ◽  
Number Of Children ◽  
Genotype Information ◽  
Two Generations ◽  
Hard Problems

Consistency checking of genotype information in pedigrees plays an important role in genetic analysis and for complex pedigrees the computational complexity is critical. We present here a detailed complexity analysis for the problem of counting the number of complete consistent genotype assignments. Our main result is a polynomial time algorithm for counting the number of complete consistent assignments for non-looping pedigrees. We further classify pedigrees according to a number of natural parameters like the number of generations, the number of children per individual and the cardinality of the set of alleles. We show that even if we assume all these parameters as bounded by reasonably small constants, the counting problem becomes computationally hard (#P-complete) for looping pedigrees. The border line for counting problems computable in polynomial time (i.e. belonging to the class FP) and #P-hard problems is completed by showing that even for general pedigrees with unlimited number of generations and alleles but with at most one child per individual and for pedigrees with at most two generations and two children per individual the counting problem is in FP.

Learning Importance of Preferences

10.29007/v68w ◽  
2018 ◽  
Author(s):  
Ying Zhu ◽  
Mirek Truszczynski
Keyword(s):  
Polynomial Time ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Scoring Rules ◽  
Np Hard ◽  
Individual Preferences

We study the problem of learning the importance of preferences in preference profiles in two important cases: when individual preferences are aggregated by the ranked Pareto rule, and when they are aggregated by positional scoring rules. For the ranked Pareto rule, we provide a polynomial-time algorithm that finds a ranking of preferences such that the ranked profile correctly decides all the examples, whenever such a ranking exists. We also show that the problem to learn a ranking maximizing the number of correctly decided examples (also under the ranked Pareto rule) is NP-hard. We obtain similar results for the case of weighted profiles when positional scoring rules are used for aggregation.

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