23,115 research outputs found
On the complexity of real root isolation using Continued Fractions
We present algorithmic, complexity and implementation results concerning real root isolation of integer univariate polynomials using the continued fraction expansion of real algebraic numbers. One motivation is to explain the method's good performance in practice. We improve the previously known bound by a factor of , where is the polynomial degree and bounds the coefficient bit size, thus matching the current record complexity for real root isolation by exact methods (Sturm, Descartes and Bernstein subdivision). Namely our complexity bound is \sOB(d^4 \tau^2) using a standard bound on the expected bit size of the integers in the continued fraction expansion. Moreover, using a homothetic transformation we improve the expected complexity bound to \sOB( d^3 \tau) under the assumption that d = \OO( \tau). We compute the multiplicities within the same complexity and extend the algorithm to non square-free polynomials. Finally, we present an efficient open-source \texttt{C++} implementation and illustrate its completeness and efficiency as compared to other available software. For this we use polynomials with coefficient bit size up to 8000 bits and degree up to 1000
SqFreeEVAL: An (almost) optimal real-root isolation algorithm
Let f be a univariate polynomial with real coefficients, f in R[X].
Subdivision algorithms based on algebraic techniques (e.g., Sturm or Descartes
methods) are widely used for isolating the real roots of f in a given interval.
In this paper, we consider a simple subdivision algorithm whose primitives are
purely numerical (e.g., function evaluation). The complexity of this algorithm
is adaptive because the algorithm makes decisions based on local data. The
complexity analysis of adaptive algorithms (and this algorithm in particular)
is a new challenge for computer science. In this paper, we compute the size of
the subdivision tree for the SqFreeEVAL algorithm.
The SqFreeEVAL algorithm is an evaluation-based numerical algorithm which is
well-known in several communities. The algorithm itself is simple, but prior
attempts to compute its complexity have proven to be quite technical and have
yielded sub-optimal results. Our main result is a simple O(d(L+ln d)) bound on
the size of the subdivision tree for the SqFreeEVAL algorithm on the benchmark
problem of isolating all real roots of an integer polynomial f of degree d and
whose coefficients can be written with at most L bits.
Our proof uses two amortization-based techniques: First, we use the algebraic
amortization technique of the standard Mahler-Davenport root bounds to
interpret the integral in terms of d and L. Second, we use a continuous
amortization technique based on an integral to bound the size of the
subdivision tree. This paper is the first to use the novel analysis technique
of continuous amortization to derive state of the art complexity bounds
On the Complexity of Real Root Isolation
We introduce a new approach to isolate the real roots of a square-free
polynomial with real coefficients. It is assumed that
each coefficient of can be approximated to any specified error bound. The
presented method is exact, complete and deterministic. Due to its similarities
to the Descartes method, we also consider it practical and easy to implement.
Compared to previous approaches, our new method achieves a significantly better
bit complexity. It is further shown that the hardness of isolating the real
roots of is exclusively determined by the geometry of the roots and not by
the complexity or the size of the coefficients. For the special case where
has integer coefficients of maximal bitsize , our bound on the bit
complexity writes as which improves the best bounds
known for existing practical algorithms by a factor of . The crucial
idea underlying the new approach is to run an approximate version of the
Descartes method, where, in each subdivision step, we only consider
approximations of the intermediate results to a certain precision. We give an
upper bound on the maximal precision that is needed for isolating the roots of
. For integer polynomials, this bound is by a factor lower than that of
the precision needed when using exact arithmetic explaining the improved bound
on the bit complexity
Computing Real Roots of Real Polynomials
Computing the roots of a univariate polynomial is a fundamental and
long-studied problem of computational algebra with applications in mathematics,
engineering, computer science, and the natural sciences. For isolating as well
as for approximating all complex roots, the best algorithm known is based on an
almost optimal method for approximate polynomial factorization, introduced by
Pan in 2002. Pan's factorization algorithm goes back to the splitting circle
method from Schoenhage in 1982. The main drawbacks of Pan's method are that it
is quite involved and that all roots have to be computed at the same time. For
the important special case, where only the real roots have to be computed, much
simpler methods are used in practice; however, they considerably lag behind
Pan's method with respect to complexity.
In this paper, we resolve this discrepancy by introducing a hybrid of the
Descartes method and Newton iteration, denoted ANEWDSC, which is simpler than
Pan's method, but achieves a run-time comparable to it. Our algorithm computes
isolating intervals for the real roots of any real square-free polynomial,
given by an oracle that provides arbitrary good approximations of the
polynomial's coefficients. ANEWDSC can also be used to only isolate the roots
in a given interval and to refine the isolating intervals to an arbitrary small
size; it achieves near optimal complexity for the latter task.Comment: to appear in the Journal of Symbolic Computatio
On the Various Bisection Methods Derived from Vincentâs Theorem
In 2000 A. Alesina and M. Galuzzi presented Vincentâs theorem âfrom a modern point of viewâ along with two new bisection methods derived from it, B and C. Their profound understanding of Vincentâs theorem is
responsible for simplicity â the characteristic property of these two methods. In this paper we compare the performance of these two new bisection
methods â i.e. the time they take, as well as the number of intervals they examine in order to isolate the real roots of polynomials â against that of
the well-known Vincent-Collins-Akritas method, which is the first bisection
method derived from Vincentâs theorem back in 1976. Experimental results
indicate that REL, the fastest implementation of the Vincent-Collins-Akritas
method, is still the fastest of the three bisection methods, but the number
of intervals it examines is almost the same as that of B. Therefore, further
research on speeding up B while preserving its simplicity looks promising
- âŠ