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The Sagemanifolds Project
Tensor calculus with free softwares: the SageManifolds project Eric´ Gourgoulhon1, Micha l Bejger2 1Laboratoire Univers et Th´eories (LUTH) CNRS / Observatoire de Paris / Universit´eParis Diderot 92190 Meudon, France http://luth.obspm.fr/~luthier/gourgoulhon/ 2Centrum Astronomiczne im. M. Kopernika (CAMK) Warsaw, Poland http://users.camk.edu.pl/bejger/ Encuentros Relativistas Espa~noles2014 Valencia 1-5 September 2014 Eric´ Gourgoulhon, Micha l Bejger (LUTH, CAMK) SageManifolds ERE2014, Valencia, 2 Sept. 2014 1 / 44 Outline 1 Differential geometry and tensor calculus on a computer 2 Sage: a free mathematics software 3 The SageManifolds project 4 SageManifolds at work: the Mars-Simon tensor example 5 Conclusion and perspectives Eric´ Gourgoulhon, Micha l Bejger (LUTH, CAMK) SageManifolds ERE2014, Valencia, 2 Sept. 2014 2 / 44 Differential geometry and tensor calculus on a computer Outline 1 Differential geometry and tensor calculus on a computer 2 Sage: a free mathematics software 3 The SageManifolds project 4 SageManifolds at work: the Mars-Simon tensor example 5 Conclusion and perspectives Eric´ Gourgoulhon, Micha l Bejger (LUTH, CAMK) SageManifolds ERE2014, Valencia, 2 Sept. 2014 3 / 44 In 1969, during his PhD under Pirani supervision at King's College, Ray d'Inverno wrote ALAM (Atlas Lisp Algebraic Manipulator) and used it to compute the Riemann tensor of Bondi metric. The original calculations took Bondi and his collaborators 6 months to go. The computation with ALAM took 4 minutes and yield to the discovery of 6 errors in the original paper [J.E.F. Skea, Applications of SHEEP (1994)] In the early 1970's, ALAM was rewritten in the LISP programming language, thereby becoming machine independent and renamed LAM The descendant of LAM, called SHEEP (!), was initiated in 1977 by Inge Frick Since then, many softwares for tensor calculus have been developed.. -
Using Macaulay2 Effectively in Practice
Using Macaulay2 effectively in practice Mike Stillman ([email protected]) Department of Mathematics Cornell 22 July 2019 / IMA Sage/M2 Macaulay2: at a glance Project started in 1993, Dan Grayson and Mike Stillman. Open source. Key computations: Gr¨obnerbases, free resolutions, Hilbert functions and applications of these. Rings, Modules and Chain Complexes are first class objects. Language which is comfortable for mathematicians, yet powerful, expressive, and fun to program in. Now a community project Journal of Software for Algebra and Geometry (started in 2009. Now we handle: Macaulay2, Singular, Gap, Cocoa) (original editors: Greg Smith, Amelia Taylor). Strong community: including about 2 workshops per year. User contributed packages (about 200 so far). Each has doc and tests, is tested every night, and is distributed with M2. Lots of activity Over 2000 math papers refer to Macaulay2. History: 1976-1978 (My undergrad years at Urbana) E. Graham Evans: asked me to write a program to compute syzygies, from Hilbert's algorithm from 1890. Really didn't work on computers of the day (probably might still be an issue!). Instead: Did computation degree by degree, no finishing condition. Used Buchsbaum-Eisenbud \What makes a complex exact" (by hand!) to see if the resulting complex was exact. Winfried Bruns was there too. Very exciting time. History: 1978-1983 (My grad years, with Dave Bayer, at Harvard) History: 1978-1983 (My grad years, with Dave Bayer, at Harvard) I tried to do \real mathematics" but Dave Bayer (basically) rediscovered Groebner bases, and saw that they gave an algorithm for computing all syzygies. I got excited, dropped what I was doing, and we programmed (in Pascal), in less than one week, the first version of what would be Macaulay. -
Some Reflections About the Success and Impact of the Computer Algebra System DERIVE with a 10-Year Time Perspective
Noname manuscript No. (will be inserted by the editor) Some reflections about the success and impact of the computer algebra system DERIVE with a 10-year time perspective Eugenio Roanes-Lozano · Jose Luis Gal´an-Garc´ıa · Carmen Solano-Mac´ıas Received: date / Accepted: date Abstract The computer algebra system DERIVE had a very important im- pact in teaching mathematics with technology, mainly in the 1990's. The au- thors analyze the possible reasons for its success and impact and give personal conclusions based on the facts collected. More than 10 years after it was discon- tinued it is still used for teaching and several scientific papers (most devoted to educational issues) still refer to it. A summary of the history, journals and conferences together with a brief bibliographic analysis are included. Keywords Computer algebra systems · DERIVE · educational software · symbolic computation · technology in mathematics education Eugenio Roanes-Lozano Instituto de Matem´aticaInterdisciplinar & Departamento de Did´actica de las Ciencias Experimentales, Sociales y Matem´aticas, Facultad de Educaci´on,Universidad Complutense de Madrid, c/ Rector Royo Villanova s/n, 28040-Madrid, Spain Tel.: +34-91-3946248 Fax: +34-91-3946133 E-mail: [email protected] Jose Luis Gal´an-Garc´ıa Departamento de Matem´atica Aplicada, Universidad de M´alaga, M´alaga, c/ Dr. Ortiz Ramos s/n. Campus de Teatinos, E{29071 M´alaga,Spain Tel.: +34-952-132873 Fax: +34-952-132766 E-mail: [email protected] Carmen Solano-Mac´ıas Departamento de Informaci´ony Comunicaci´on,Universidad de Extremadura, Plaza de Ibn Marwan s/n, 06001-Badajoz, Spain Tel.: +34-924-286400 Fax: +34-924-286401 E-mail: [email protected] 2 Eugenio Roanes-Lozano et al. -
Redberry: a Computer Algebra System Designed for Tensor Manipulation
Redberry: a computer algebra system designed for tensor manipulation Stanislav Poslavsky Institute for High Energy Physics, Protvino, Russia SRRC RF ITEP of NRC Kurchatov Institute, Moscow, Russia E-mail: [email protected] Dmitry Bolotin Institute of Bioorganic Chemistry of RAS, Moscow, Russia E-mail: [email protected] Abstract. In this paper we focus on the main aspects of computer-aided calculations with tensors and present a new computer algebra system Redberry which was specifically designed for algebraic tensor manipulation. We touch upon distinctive features of tensor software in comparison with pure scalar systems, discuss the main approaches used to handle tensorial expressions and present the comparison of Redberry performance with other relevant tools. 1. Introduction General-purpose computer algebra systems (CASs) have become an essential part of many scientific calculations. Focusing on the area of theoretical physics and particularly high energy physics, one can note that there is a wide area of problems that deal with tensors (or more generally | objects with indices). This work is devoted to the algebraic manipulations with abstract indexed expressions which forms a substantial part of computer aided calculations with tensors in this field of science. Today, there are many packages both on top of general-purpose systems (Maple Physics [1], xAct [2], Tensorial etc.) and standalone tools (Cadabra [3,4], SymPy [5], Reduce [6] etc.) that cover different topics in symbolic tensor calculus. However, it cannot be said that current demand on such a software is fully satisfied [7]. The main difference of tensorial expressions (in comparison with ordinary indexless) lies in the presence of contractions between indices. -
CAS (Computer Algebra System) Mathematica
CAS (Computer Algebra System) Mathematica- UML students can download a copy for free as part of the UML site license; see the course website for details From: Wikipedia 2/9/2014 A computer algebra system (CAS) is a software program that allows [one] to compute with mathematical expressions in a way which is similar to the traditional handwritten computations of the mathematicians and other scientists. The main ones are Axiom, Magma, Maple, Mathematica and Sage (the latter includes several computer algebras systems, such as Macsyma and SymPy). Computer algebra systems began to appear in the 1960s, and evolved out of two quite different sources—the requirements of theoretical physicists and research into artificial intelligence. A prime example for the first development was the pioneering work conducted by the later Nobel Prize laureate in physics Martin Veltman, who designed a program for symbolic mathematics, especially High Energy Physics, called Schoonschip (Dutch for "clean ship") in 1963. Using LISP as the programming basis, Carl Engelman created MATHLAB in 1964 at MITRE within an artificial intelligence research environment. Later MATHLAB was made available to users on PDP-6 and PDP-10 Systems running TOPS-10 or TENEX in universities. Today it can still be used on SIMH-Emulations of the PDP-10. MATHLAB ("mathematical laboratory") should not be confused with MATLAB ("matrix laboratory") which is a system for numerical computation built 15 years later at the University of New Mexico, accidentally named rather similarly. The first popular computer algebra systems were muMATH, Reduce, Derive (based on muMATH), and Macsyma; a popular copyleft version of Macsyma called Maxima is actively being maintained. -
Computer Algebra Tems
short and expensive. Consequently, computer centre managers were not easily persuaded to install such sys Computer Algebra tems. This is another reason why many specialized CAS have been developed in many different institutions. From the Jacques Calmet, Grenoble * very beginning it was felt that the (UFIA / INPG) breakthrough of Computer Algebra is linked to the availability of adequate computers: several megabytes of main As soon as computers became avai handling of very large pieces of algebra memory and very large capacity disks. lable the wish to manipulate symbols which would be hopeless without com Since the advent of the VAX's and the rather than numbers was considered. puter aid, the possibility to get insight personal workstations, this era is open This resulted in what is called symbolic into a calculation, to experiment ideas ed and indeed the use of CAS is computing. The sub-field of symbolic interactively and to save time for less spreading very quickly. computing which deals with the sym technical problems. When compared to What are the main CAS of possible bolic solution of mathematical problems numerical computing, it is also much interest to physicists? A fairly balanced is known today as Computer Algebra. closer to human reasoning. answer is to quote MACSYMA, RE The discipline was rapidly organized, in DUCE, SMP, MAPLE among the general 1962, by a special interest group on Computer Algebra Systems purpose ones and SCHOONSHIP, symbolic and algebraic manipulation, Computer Algebra systems may be SHEEP and CAYLEY among the specia SIGSAM, of the Association for Com classified into two different categories: lized ones. -
Singular Value Decomposition and Its Numerical Computations
Singular Value Decomposition and its numerical computations Wen Zhang, Anastasios Arvanitis and Asif Al-Rasheed ABSTRACT The Singular Value Decomposition (SVD) is widely used in many engineering fields. Due to the important role that the SVD plays in real-time computations, we try to study its numerical characteristics and implement the numerical methods for calculating it. Generally speaking, there are two approaches to get the SVD of a matrix, i.e., direct method and indirect method. The first one is to transform the original matrix to a bidiagonal matrix and then compute the SVD of this resulting matrix. The second method is to obtain the SVD through the eigen pairs of another square matrix. In this project, we implement these two kinds of methods and develop the combined methods for computing the SVD. Finally we compare these methods with the built-in function in Matlab (svd) regarding timings and accuracy. 1. INTRODUCTION The singular value decomposition is a factorization of a real or complex matrix and it is used in many applications. Let A be a real or a complex matrix with m by n dimension. Then the SVD of A is: where is an m by m orthogonal matrix, Σ is an m by n rectangular diagonal matrix and is the transpose of n ä n matrix. The diagonal entries of Σ are known as the singular values of A. The m columns of U and the n columns of V are called the left singular vectors and right singular vectors of A, respectively. Both U and V are orthogonal matrices. -
Mathematical Modeling with Technology PURNIMA RAI
International Journal of Innovative Research in Computer Science & Technology (IJIRCST) ISSN: 2347-5552, Volume-3, Issue-2, March 2015 Mathematical Modeling with Technology PURNIMA RAI Abstract— Mathematics is very important for an Computer Algebraic System (CAS) increasing number of technical jobs in a quantitative A Computer Algebra system is a type of software package world. Over recent years technology has progressed to that is used in manipulation of mathematical formulae. The the point where many computer algebraic systems primary goal of a Computer Algebra system is to automate (CAS) are widely available. These technologies can tedious and sometimes difficult algebraic manipulation perform a wide variety of algebraic tasks. Computer Algebra systems often include facilities for manipulations.Computer algebra systems (CAS) have graphing equations and provide a programming language become powerful and flexible tools to support a variety for the user to define their own procedures. Computer of mathematical activities. This includes learning and Algebra systems have not only changed how mathematics is teaching, research and assessment. MATLAB, an taught at many universities, but have provided a flexible acronym for “Matrix Laboratory”, is the most tool for mathematicians worldwide. Examples of popular extensively used mathematical software in the general systems include Maple, Mathematica, and MathCAD. sciences. MATLAB is an interactive system for Computer Algebra systems can be used to simplify rational numerical computation and a programmable system. functions, factor polynomials, find the solutions to a system This paper attempts to investigate the impact of of equation, and various other manipulations. In Calculus, integrating mathematical modeling and applications on they can be used to find the limit of, symbolically integrate, higher level mathematics in India. -
An Alternative Algorithm for Computing the Betti Table of a Monomial Ideal 3
AN ALTERNATIVE ALGORITHM FOR COMPUTING THE BETTI TABLE OF A MONOMIAL IDEAL MARIA-LAURA TORRENTE AND MATTEO VARBARO Abstract. In this paper we develop a new technique to compute the Betti table of a monomial ideal. We present a prototype implementation of the resulting algorithm and we perform numerical experiments suggesting a very promising efficiency. On the way of describing the method, we also prove new constraints on the shape of the possible Betti tables of a monomial ideal. 1. Introduction Since many years syzygies, and more generally free resolutions, are central in purely theo- retical aspects of algebraic geometry; more recently, after the connection between algebra and statistics have been initiated by Diaconis and Sturmfels in [DS98], free resolutions have also become an important tool in statistics (for instance, see [D11, SW09]). As a consequence, it is fundamental to have efficient algorithms to compute them. The usual approach uses Gr¨obner bases and exploits a result of Schreyer (for more details see [Sc80, Sc91] or [Ei95, Chapter 15, Section 5]). The packages for free resolutions of the most used computer algebra systems, like [Macaulay2, Singular, CoCoA], are based on these techniques. In this paper, we introduce a new algorithmic method to compute the minimal graded free resolution of any finitely generated graded module over a polynomial ring such that some (possibly non- minimal) graded free resolution is known a priori. We describe this method and we present the resulting algorithm in the case of monomial ideals in a polynomial ring, in which situ- ation we always have a starting nonminimal graded free resolution. -
Computations in Algebraic Geometry with Macaulay 2
Computations in algebraic geometry with Macaulay 2 Editors: D. Eisenbud, D. Grayson, M. Stillman, and B. Sturmfels Preface Systems of polynomial equations arise throughout mathematics, science, and engineering. Algebraic geometry provides powerful theoretical techniques for studying the qualitative and quantitative features of their solution sets. Re- cently developed algorithms have made theoretical aspects of the subject accessible to a broad range of mathematicians and scientists. The algorith- mic approach to the subject has two principal aims: developing new tools for research within mathematics, and providing new tools for modeling and solv- ing problems that arise in the sciences and engineering. A healthy synergy emerges, as new theorems yield new algorithms and emerging applications lead to new theoretical questions. This book presents algorithmic tools for algebraic geometry and experi- mental applications of them. It also introduces a software system in which the tools have been implemented and with which the experiments can be carried out. Macaulay 2 is a computer algebra system devoted to supporting research in algebraic geometry, commutative algebra, and their applications. The reader of this book will encounter Macaulay 2 in the context of concrete applications and practical computations in algebraic geometry. The expositions of the algorithmic tools presented here are designed to serve as a useful guide for those wishing to bring such tools to bear on their own problems. A wide range of mathematical scientists should find these expositions valuable. This includes both the users of other programs similar to Macaulay 2 (for example, Singular and CoCoA) and those who are not interested in explicit machine computations at all. -
Using Xcas in Calculus Curricula: a Plan of Lectures and Laboratory Projects
Computational and Applied Mathematics Journal 2015; 1(3): 131-138 Published online April 30, 2015 (http://www.aascit.org/journal/camj) Using Xcas in Calculus Curricula: a Plan of Lectures and Laboratory Projects George E. Halkos, Kyriaki D. Tsilika Laboratory of Operations Research, Department of Economics, University of Thessaly, Volos, Greece Email address [email protected] (K. D. Tsilika) Citation George E. Halkos, Kyriaki D. Tsilika. Using Xcas in Calculus Curricula: a Plan of Lectures and Keywords Laboratory Projects. Computational and Applied Mathematics Journal. Symbolic Computations, Vol. 1, No. 3, 2015, pp. 131-138. Computer-Based Education, Abstract Xcas Computer Software We introduce a topic in the intersection of symbolic mathematics and computation, concerning topics in multivariable Optimization and Dynamic Analysis. Our computational approach gives emphasis to mathematical methodology and aims at both symbolic and numerical results as implemented by a powerful digital mathematical tool, CAS software Received: March 31, 2015 Xcas. This work could be used as guidance to develop course contents in advanced Revised: April 20, 2015 calculus curricula, to conduct individual or collaborative projects for programming related Accepted: April 21, 2015 objectives, as Xcas is freely available to users and institutions. Furthermore, it could assist educators to reproduce calculus methodologies by generating automatically, in one entry, abstract calculus formulations. 1. Introduction Educational institutions are equipped with computer labs while modern teaching methods give emphasis in computer based learning, with curricula that include courses supported by the appropriate computer software. It has also been established that, software tools integrate successfully into Mathematics education and are considered essential in teaching Geometry, Statistics or Calculus (see indicatively [1], [2]). -
Singular in Sage L-38 22November2019 1/40 Computing with Polynomials in Singular
Computing with Polynomials in Singular 1 Polynomials, Resultants, and Factorization computer algebra for polynomial computations resultants to eliminate variables 2 Gröbner Bases and Multiplication Matrices ideals of polynomials and Gröbner bases normal forms and multiplication matrices multiplicity as the dimension of the local quotient ring 3 Formulas for the 4-bar Coupler Point formulation of the problem processing a Gröbner basis MCS 507 Lecture 38 Mathematical, Statistical and Scientific Software Jan Verschelde, 22 November 2019 Scientific Software (MCS 507) Singular in Sage L-38 22November2019 1/40 Computing with Polynomials in Singular 1 Polynomials, Resultants, and Factorization computer algebra for polynomial computations resultants to eliminate variables 2 Gröbner Bases and Multiplication Matrices ideals of polynomials and Gröbner bases normal forms and multiplication matrices multiplicity as the dimension of the local quotient ring 3 Formulas for the 4-bar Coupler Point formulation of the problem processing a Gröbner basis Scientific Software (MCS 507) Singular in Sage L-38 22November2019 2/40 Singular Singular is a computer algebra system for polynomial computations, with special emphasis on commutative and non-commutative algebra, algebraic geometry, and singularity theory, under the GNU General Public License. Singular’s core algorithms handle polynomial factorization and resultants characteristic sets and numerical root finding Gröbner, standard bases, and free resolutions. Its development is directed by Wolfram Decker, Gert-Martin Greuel, Gerhard Pfister, and Hans Schönemann, within the Dept. of Mathematics at the University of Kaiserslautern. Scientific Software (MCS 507) Singular in Sage L-38 22November2019 3/40 Singular in Sage Advanced algorithms are contained in more than 90 libraries, written in a C-like programming language.