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GuillermoNavasICMS.pdf
README.md
mezzarobba-icms-20160711.pdf

README.md

ICMS 2016 Session: High-precision arithmetic, effective analysis and special functions

ICMS 2016: Home, Sessions

Organizers

Aim and Scope

High-precision methods have become an important tool to get reliable results when solving numerical problems of increased size and complexity. The goal of this session is to present advances in software for high-precision or certified numerical methods, particularly in the context of effective complex analysis and computation of transcendental functions. Possible subjects include but are not limited to:

  • Arbitrary-precision and mixed-precision arithmetic
  • Interval arithmetic and Taylor methods
  • High-precision or rigorous computation of D-finite functions, L-functions and modular forms
  • Certified numerical integration and solution of ODEs
  • Applications, for instance in number theory, combinatorics, and mathematical physics

Work in these areas combining numerical methods with computer algebra is particularly welcome.

Publications

A short abstract will appear on the permanent conference web page (see below) as soon as accepted.

An extended abstract will appear on the permanent conference web page (see below) as soon as accepted. It will also appear on the proceedings that will be distributed during the meeting.

Submission Guidelines

If you would like to give a talk at ICMS, you need to submit first a short abstract and then later an extended abstract. See the guideline (http://icms2016.zib.de/call-for-submission.html) for the details.

This session is now closed for new submissions.

Talks/Abstracts

Special functions and interval arithmetic

Speaker: Fredrik Johansson

This short introductory talk will discuss recent work and open problems related to supporting special functions in interval arithmetic.

On the computation of confluent hypergeometric functions for large imaginary part of b and z

Slides: https://github.com/fredrik-johansson/ICMS2016/blob/master/GuillermoNavasICMS.pdf

Authors:

  • Guillermo Navas-Palencia (Dept. Computer Science, Universitat Politècnica de Catalunya and Numerical Algorithms Group, Oxford)
  • Argimiro Arratia (Dept. Computer Science/BGSMath, Universitat Politècnica de Catalunya)

We present an efficient algorithm for the confluent hypergeometric functions when the imaginary part of b and z is large. The algorithm is based on the steepest descent method, applied to a suitable representation of the confluent hypergeometric function as a highly oscillatory integral, which is then integrated by using various quadrature methods.

The performance of the algorithm is compared with open-source and commercial software solutions with arbitrary precision, and for many cases the algorithm achieves high accuracy in both the real and imaginary part. Our motivation comes from the need for accurate computation of the characteristic function of the Arcsine distribution and the Beta distribution; the latter being required in several financial applications, for example, modeling the loss given default in the context of portfolio credit risk.

Rigorous Multiple-Precision Evaluation of D-Finite Functions in Sage

Slides: https://github.com/fredrik-johansson/ICMS2016/blob/master/mezzarobba-icms-20160711.pdf

Author: Marc Mezzarobba (LIP6, Université Pierre et Marie Curie)

We present an implementation, on top of the SageMath computer algebra system, of various algorithms for the numerical evaluation of so-called D-finite functions. A complex analytic function is D-finite when it satisfies an ordinary differential equation whose coefficients are polynomial in the independent variable. D-finite functions can be viewed as a class of special functions analogous to those of algebraic or hypergeometric functions (but more general). They come up in areas such as analytic combinatorics and mathematical physics, and lend themselves well to symbolic manipulation by computer algebra systems.

The main task our package performs is the “numerical analytic continuation” of D-finite functions. This process results in a numerical approximation of the transition matrix that maps “initial values” of an ODE somewhere on the complex plane to “initial values” elsewhere that define the same solution. Numerical analytic continuation then serves to compute things like values or polynomial approximations of D-finite functions anywhere on their Riemann surfaces, and monodromy matrices of differential operators. The code supports the important limit case where the (generalized) initial values are provided at regular singular points of the ODE, making it possible in particular to compute connection constants between regular singularities. It is rigorous in the sense that it returns interval results that are guaranteed to enclose the exact mathematical result.

The new package can be considered a successor of NumGfun, a Maple package by the same author with similar features.

L functions in Pari/GP

Author: Pascal Molin (Institut de mathématiques de Jussieu, Université Paris 7)

I will present a package to compute with general L functions now available in the Pari/GP computer algebra system. L functions of all classical objects already in Pari/GP are available (Dirichlet and Hecke characters, elliptic curves, some modular forms), but this package is meant to handle L functions of any kind. I will explain the methods used and their limits. (This is joint work with B. Allombert, K. Belabas, and H. Cohen).

Real root isolation in FLINT

Author: Elias Tsigaridas (PolSys, Inria Paris-Rocquencourt)

We present an implementation in FLINT of an exact algorithm based on Descartes's rule of signs for isolating the real roots of a univariate polynomial with integer coefficients. We describe the technicalities behind our approach and we study the efficiency of the solver by an experimental analysis on various datasets.

Recursive double-size fixed precision arithmetic

Authors:

  • Alexis Breust
  • Christophe Chabot
  • Jean-Guillaume Dumas
  • Laurent Fousse
  • Pascal Giorgi

We propose a new fixed precision arithmetic package called RecInt. It uses a recursive double-size data-structure. Contrary to arbitrary precision packages like GMP, that create vectors of words on the heap, RecInt large integers are created on the stack. The space allocated for these integers is a power of two and arithmetic is performed modulo that power. Arithmetic operations are thus easily implemented recursively by a divide and conquer strategy. Among those, we show that this packages is particularly well adapted to Newton-Raphson like iterations or Montgomery reduction. Recursivity is implemented via doubling algorithms on templated data-types. The idea is to extend machine word functionality to any power of two and to use template partial specialization to adapt the implemented routines to some specific sizes and thresholds. The main target precision is for cryptographic sizes, that is up to several tens of machine words. Preliminary experiments show that good performance can be attained when comparing to the state of art GMP library: it can be several order of magnitude faster when used with very few machine words. This package is now integrated within the Givaro C++ library and has been used for efficient exact linear algebra computations.

CAMPARY: Cuda Multiple Precision Arithmetic Library and Applications

Authors:

  • Mioara Joldes (LAAS-CNRS)
  • Jean-Michel Muller (LIP Laboratory, ENS Lyon)
  • Valentina Popescu (LIP Laboratory, ENS Lyon)
  • Warwick Tucker (Department of Mathematics, Uppsala University)

Many scientific computing applications demand massive numerical computations on parallel architectures such as Graphics Processing Units (GPUs). Usually, either floating-point single or double precision arithmetic is used. Higher precision is generally not available in hardware and software extended precision libraries are much slower and rarely supported on GPUs. We develop CAMPARY: a multiple-precision floating-point arithmetic library using the CUDA programming language for the NVidia GPU platform. In our approach, the precision is extended by representing real numbers as the unevaluated sum of several standard machine precision floating-point numbers. We make use of error-free transforms addition and multiplication algorithms, which are based only on native precision operations, but keep track of all rounding errors. This offers the simplicity of using hardware highly optimized floating-point operations, while also allowing for rigorously proven rounding error bounds. This allows as well for an interval arithmetic. Currently, all basic multiple-precision arithmetic operations are supported. Our target applications are in chaotic dynamical systems or automatic control.

Automatic implementation of the numerical Taylor series method

Authors:

  • M. Rodriguez (Centro Universitario de la Defensa de Zaragoza)
  • A. Abad (University of Zaragoza)
  • R. Barrio (University of Zaragoza)
  • M. Marco-Buzunariz (University of Zaragoza)

In the last few years, the requirements in the numerical solution of ordinary differential equations in physics and in dynamical systems have pointed to new kind of methods capable to maintain geometric properties of the equations or looking for arbitrary high-precision. One method that can solve most of these problems is the Taylor series method. TIDES is a free software based on the Taylor series method that uses an optimized variable-stepsize variable-order formulation. The kernel of this software consists of a C library that permits to compute up to any precision level (by using multiple precision libraries for high precision when needed) the solution of an ordinary differential system from a C driver program containing the equations of the ODE. In this talk we present the symbolic methods, implemented in a computer algebra system (Sagemath and Mathematica), used to automatically write the code based on the automatic differentiation processes that integrates a particular differential system by means of the Taylor method. The precompiler has been written in Mathematica and Sage (which includes tides since version 6.4). Finally, we show several examples computing in a direct way solutions with 1000 precision digits of chaotic problems like the Lorenz model.