60 research outputs found
Algorithms for Highly Symmetric Linear and Integer Programs
This paper deals with exploiting symmetry for solving linear and integer
programming problems. Basic properties of linear representations of finite
groups can be used to reduce symmetric linear programming to solving linear
programs of lower dimension. Combining this approach with knowledge of the
geometry of feasible integer solutions yields an algorithm for solving highly
symmetric integer linear programs which only takes time which is linear in the
number of constraints and quadratic in the dimension.Comment: 21 pages, 1 figure; some references and further comments added, title
slightly change
The hydrodynamics of swimming microorganisms
Cell motility in viscous fluids is ubiquitous and affects many biological
processes, including reproduction, infection, and the marine life ecosystem.
Here we review the biophysical and mechanical principles of locomotion at the
small scales relevant to cell swimming (tens of microns and below). The focus
is on the fundamental flow physics phenomena occurring in this inertia-less
realm, and the emphasis is on the simple physical picture. We review the basic
properties of flows at low Reynolds number, paying special attention to aspects
most relevant for swimming, such as resistance matrices for solid bodies, flow
singularities, and kinematic requirements for net translation. Then we review
classical theoretical work on cell motility: early calculations of the speed of
a swimmer with prescribed stroke, and the application of resistive-force theory
and slender-body theory to flagellar locomotion. After reviewing the physical
means by which flagella are actuated, we outline areas of active research,
including hydrodynamic interactions, biological locomotion in complex fluids,
the design of small-scale artificial swimmers, and the optimization of
locomotion strategies.Comment: Review articl
On the String Consensus Problem and the Manhattan Sequence Consensus Problem
In the Manhattan Sequence Consensus problem (MSC problem) we are given
integer sequences, each of length , and we are to find an integer sequence
of length (called a consensus sequence), such that the maximum
Manhattan distance of from each of the input sequences is minimized. For
binary sequences Manhattan distance coincides with Hamming distance, hence in
this case the string consensus problem (also called string center problem or
closest string problem) is a special case of MSC. Our main result is a
practically efficient -time algorithm solving MSC for sequences.
Practicality of our algorithms has been verified experimentally. It improves
upon the quadratic algorithm by Amir et al.\ (SPIRE 2012) for string consensus
problem for binary strings. Similarly as in Amir's algorithm we use a
column-based framework. We replace the implied general integer linear
programming by its easy special cases, due to combinatorial properties of the
MSC for . We also show that for a general parameter any instance
can be reduced in linear time to a kernel of size , so the problem is
fixed-parameter tractable. Nevertheless, for this is still too large
for any naive solution to be feasible in practice.Comment: accepted to SPIRE 201
FPTAS for optimizing polynomials over the mixed-integer points of polytopes in fixed dimension
We show the existence of a fully polynomial-time approximation scheme (FPTAS)
for the problem of maximizing a non-negative polynomial over mixed-integer sets
in convex polytopes, when the number of variables is fixed. Moreover, using a
weaker notion of approximation, we show the existence of a fully
polynomial-time approximation scheme for the problem of maximizing or
minimizing an arbitrary polynomial over mixed-integer sets in convex polytopes,
when the number of variables is fixed.Comment: 16 pages, 4 figures; to appear in Mathematical Programmin
Square root algorithms for the number field sieve
The original publication is available at www.springerlink.comInternational audienceWe review several methods for the square root step of the Number Field Sieve, and present an original one, based on the Chinese Remainder Theorem
A parametric integer programming algorithm for bilevel mixed integer programs
We consider discrete bilevel optimization problems where the follower solves
an integer program with a fixed number of variables. Using recent results in
parametric integer programming, we present polynomial time algorithms for pure
and mixed integer bilevel problems. For the mixed integer case where the
leader's variables are continuous, our algorithm also detects whether the
infimum cost fails to be attained, a difficulty that has been identified but
not directly addressed in the literature. In this case it yields a ``better
than fully polynomial time'' approximation scheme with running time polynomial
in the logarithm of the relative precision. For the pure integer case where the
leader's variables are integer, and hence optimal solutions are guaranteed to
exist, we present two algorithms which run in polynomial time when the total
number of variables is fixed.Comment: 11 page
Implicit Factoring: On Polynomial Time Factoring Given Only an Implicit Hint
Abstract. We address the problem of polynomial time factoring RSA moduli N1 = p1q1 with the help of an oracle. As opposed to other ap-proaches that require an oracle that explicitly outputs bits of p1, we use an oracle that gives only implicit information about p1. Namely, our or-acle outputs a different N2 = p2q2 such that p1 and p2 share the t least significant bits. Surprisingly, this implicit information is already suffi-cient to efficiently factor N1, N2 provided that t is large enough. We then generalize this approach to more than one oracle query. Key words: Factoring with an oracle, lattices
Mersenne Factorization Factory
We present work in progress to completely factor seventeen Mersenne numbers using a variant of the special number field sieve where sieving on the algebraic side is shared among the numbers. It is expected that it reduces the overall factoring effort by more than 50%. As far as we know this is the first practical application of Coppersmith’s “factorization factory” idea. Most factorizations used a new double-product approach that led to additional savings in the matrix step
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