26,391 research outputs found

    Note on Integer Factoring Methods IV

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    This note continues the theoretical development of deterministic integer factorization algorithms based on systems of polynomials equations. The main result establishes a new deterministic time complexity bench mark in integer factorization.Comment: 20 Pages, New Versio

    Approximately counting semismooth integers

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    An integer nn is (y,z)(y,z)-semismooth if n=pmn=pm where mm is an integer with all prime divisors y\le y and pp is 1 or a prime z\le z. arge quantities of semismooth integers are utilized in modern integer factoring algorithms, such as the number field sieve, that incorporate the so-called large prime variant. Thus, it is useful for factoring practitioners to be able to estimate the value of Ψ(x,y,z)\Psi(x,y,z), the number of (y,z)(y,z)-semismooth integers up to xx, so that they can better set algorithm parameters and minimize running times, which could be weeks or months on a cluster supercomputer. In this paper, we explore several algorithms to approximate Ψ(x,y,z)\Psi(x,y,z) using a generalization of Buchstab's identity with numeric integration.Comment: To appear in ISSAC 2013, Boston M

    Bounding Rationality by Discounting Time

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    Consider a game where Alice generates an integer and Bob wins if he can factor that integer. Traditional game theory tells us that Bob will always win this game even though in practice Alice will win given our usual assumptions about the hardness of factoring. We define a new notion of bounded rationality, where the payoffs of players are discounted by the computation time they take to produce their actions. We use this notion to give a direct correspondence between the existence of equilibria where Alice has a winning strategy and the hardness of factoring. Namely, under a natural assumption on the discount rates, there is an equilibriumwhere Alice has a winning strategy iff there is a linear-time samplable distribution with respect to which Factoring is hard on average. We also give general results for discounted games over countable action spaces, including showing that any game with bounded and computable payoffs has an equilibrium in our model, even if each player is allowed a countable number of actions. It follows, for example, that the Largest Integer game has an equilibrium in our model though it has no Nash equilibria or epsilon-Nash equilibria.Comment: To appear in Proceedings of The First Symposium on Innovations in Computer Scienc

    Bounding Rationality by Discounting Time

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    Consider a game where Alice generates an integer and Bob wins if he can factor that integer. Traditional game theory tells us that Bob will always win this game even though in practice Alice will win given our usual assumptions about the hardness of factoring. We define a new notion of bounded rationality, where the payoffs of players are discounted by the computation time they take to produce their actions. We use this notion to give a direct correspondence between the existence of equilibria where Alice has a winning strategy and the hardness of factoring. Namely, under a natural assumption on the discount rates, there is an equilibriumwhere Alice has a winning strategy iff there is a linear-time samplable distribution with respect to which Factoring is hard on average. We also give general results for discounted games over countable action spaces, including showing that any game with bounded and computable payoffs has an equilibrium in our model, even if each player is allowed a countable number of actions. It follows, for example, that the Largest Integer game has an equilibrium in our model though it has no Nash equilibria or E-Nash equilibria.Bounded rationality; Discounting; Uniform equilibria; Factoring game

    A deterministic version of Pollard's p-1 algorithm

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    In this article we present applications of smooth numbers to the unconditional derandomization of some well-known integer factoring algorithms. We begin with Pollard's p1p-1 algorithm, which finds in random polynomial time the prime divisors pp of an integer nn such that p1p-1 is smooth. We show that these prime factors can be recovered in deterministic polynomial time. We further generalize this result to give a partial derandomization of the kk-th cyclotomic method of factoring (k2k\ge 2) devised by Bach and Shallit. We also investigate reductions of factoring to computing Euler's totient function ϕ\phi. We point out some explicit sets of integers nn that are completely factorable in deterministic polynomial time given ϕ(n)\phi(n). These sets consist, roughly speaking, of products of primes pp satisfying, with the exception of at most two, certain conditions somewhat weaker than the smoothness of p1p-1. Finally, we prove that O(lnn)O(\ln n) oracle queries for values of ϕ\phi are sufficient to completely factor any integer nn in less than exp((1+o(1))(lnn)1/3(lnlnn)2/3)\exp\Bigl((1+o(1))(\ln n)^{{1/3}} (\ln\ln n)^{{2/3}}\Bigr) deterministic time.Comment: Expanded and heavily revised version, to appear in Mathematics of Computation, 21 page

    A Note on Integer Factorization Using Lattices

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    We revisit Schnorr's lattice-based integer factorization algorithm, now with an effective point of view. We present effective versions of Theorem 2 of Schnorr's "Factoring integers and computing discrete logarithms via diophantine approximation" paper, as well as new elementary properties of the Prime Number Lattice bases of Schnorr and Adleman

    Distributed quantum computing: A distributed Shor algorithm

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    We present a distributed implementation of Shor's quantum factoring algorithm on a distributed quantum network model. This model provides a means for small capacity quantum computers to work together in such a way as to simulate a large capacity quantum computer. In this paper, entanglement is used as a resource for implementing non-local operations between two or more quantum computers. These non-local operations are used to implement a distributed factoring circuit with polynomially many gates. This distributed version of Shor's algorithm requires an additional overhead of O((log N)^2) communication complexity, where N denotes the integer to be factored.Comment: 13 pages, 12 figures, extra figures are remove
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