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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. -
Plotting Direction Fields in Matlab and Maxima – a Short Tutorial
Plotting direction fields in Matlab and Maxima – a short tutorial Luis Carvalho Introduction A first order differential equation can be expressed as dx x0(t) = = f(t; x) (1) dt where t is the independent variable and x is the dependent variable (on t). Note that the equation above is in normal form. The difficulty in solving equation (1) depends clearly on f(t; x). One way to gain geometric insight on how the solution might look like is to observe that any solution to (1) should be such that the slope at any point P (t0; x0) is f(t0; x0), since this is the value of the derivative at P . With this motivation in mind, if you select enough points and plot the slopes in each of these points, you will obtain a direction field for ODE (1). However, it is not easy to plot such a direction field for any function f(t; x), and so we must resort to some computational help. There are many computational packages to help us in this task. This is a short tutorial on how to plot direction fields for first order ODE’s in Matlab and Maxima. Matlab Matlab is a powerful “computing environment that combines numeric computation, advanced graphics and visualization” 1. A nice package for plotting direction field in Matlab (although resourceful, Matlab does not provide such facility natively) can be found at http://math.rice.edu/»dfield, contributed by John C. Polking from the Dept. of Mathematics at Rice University. To install this add-on, simply browse to the files for your version of Matlab and download them. -
A Note on Integral Points on Elliptic Curves 3
Journal de Th´eorie des Nombres de Bordeaux 00 (XXXX), 000–000 A note on integral points on elliptic curves par Mark WATKINS Abstract. We investigate a problem considered by Zagier and Elkies, of finding large integral points on elliptic curves. By writ- ing down a generic polynomial solution and equating coefficients, we are led to suspect four extremal cases that still might have non- degenerate solutions. Each of these cases gives rise to a polynomial system of equations, the first being solved by Elkies in 1988 using the resultant methods of Macsyma, with there being a unique rational nondegenerate solution. For the second case we found that resultants and/or Gr¨obner bases were not very efficacious. Instead, at the suggestion of Elkies, we used multidimensional p-adic Newton iteration, and were able to find a nondegenerate solution, albeit over a quartic number field. Due to our methodol- ogy, we do not have much hope of proving that there are no other solutions. For the third case we found a solution in a nonic number field, but we were unable to make much progress with the fourth case. We make a few concluding comments and include an ap- pendix from Elkies regarding his calculations and correspondence with Zagier. Resum´ e.´ A` la suite de Zagier et Elkies, nous recherchons de grands points entiers sur des courbes elliptiques. En ´ecrivant une solution polynomiale g´en´erique et en ´egalisant des coefficients, nous obtenons quatre cas extr´emaux susceptibles d’avoir des so- lutions non d´eg´en´er´ees. Chacun de ces cas conduit `aun syst`eme d’´equations polynomiales, le premier ´etant r´esolu par Elkies en 1988 en utilisant les r´esultants de Macsyma; il admet une unique solution rationnelle non d´eg´en´er´ee. -
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. -
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. -
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. -
Arxiv:Cs/0608005V2 [Cs.SC] 12 Jun 2007
AEI-2006-037 cs.SC/0608005 A field-theory motivated approach to symbolic computer algebra Kasper Peeters Max-Planck-Institut f¨ur Gravitationsphysik, Albert-Einstein-Institut Am M¨uhlenberg 1, 14476 Golm, GERMANY Abstract Field theory is an area in physics with a deceptively compact notation. Although general pur- pose computer algebra systems, built around generic list-based data structures, can be used to represent and manipulate field-theory expressions, this often leads to cumbersome input formats, unexpected side-effects, or the need for a lot of special-purpose code. This makes a direct trans- lation of problems from paper to computer and back needlessly time-consuming and error-prone. A prototype computer algebra system is presented which features TEX-like input, graph data structures, lists with Young-tableaux symmetries and a multiple-inheritance property system. The usefulness of this approach is illustrated with a number of explicit field-theory problems. 1. Field theory versus general-purpose computer algebra For good reasons, the area of general-purpose computer algebra programs has histor- ically been dominated by what one could call “list-based” systems. These are systems which are centred on the idea that, at the lowest level, mathematical expressions are nothing else but nested lists (or equivalently: nested functions, trees, directed acyclic graphs, . ). There is no doubt that a lot of mathematics indeed maps elegantly to problems concerning the manipulation of nested lists, as the success of a large class of LISP-based computer algebra systems illustrates (either implemented in LISP itself or arXiv:cs/0608005v2 [cs.SC] 12 Jun 2007 in another language with appropriate list data structures). -
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. -
Sage Tutorial (Pdf)
Sage Tutorial Release 9.4 The Sage Development Team Aug 24, 2021 CONTENTS 1 Introduction 3 1.1 Installation................................................4 1.2 Ways to Use Sage.............................................4 1.3 Longterm Goals for Sage.........................................5 2 A Guided Tour 7 2.1 Assignment, Equality, and Arithmetic..................................7 2.2 Getting Help...............................................9 2.3 Functions, Indentation, and Counting.................................. 10 2.4 Basic Algebra and Calculus....................................... 14 2.5 Plotting.................................................. 20 2.6 Some Common Issues with Functions.................................. 23 2.7 Basic Rings................................................ 26 2.8 Linear Algebra.............................................. 28 2.9 Polynomials............................................... 32 2.10 Parents, Conversion and Coercion.................................... 36 2.11 Finite Groups, Abelian Groups...................................... 42 2.12 Number Theory............................................. 43 2.13 Some More Advanced Mathematics................................... 46 3 The Interactive Shell 55 3.1 Your Sage Session............................................ 55 3.2 Logging Input and Output........................................ 57 3.3 Paste Ignores Prompts.......................................... 58 3.4 Timing Commands............................................ 58 3.5 Other IPython -
A Framework for Representing Knowledge Marvin Minsky MIT-AI Laboratory Memo 306, June, 1974. Reprinted in the Psychology of Comp
A Framework for Representing Knowledge Marvin Minsky MIT-AI Laboratory Memo 306, June, 1974. Reprinted in The Psychology of Computer Vision, P. Winston (Ed.), McGraw-Hill, 1975. Shorter versions in J. Haugeland, Ed., Mind Design, MIT Press, 1981, and in Cognitive Science, Collins, Allan and Edward E. Smith (eds.) Morgan-Kaufmann, 1992 ISBN 55860-013-2] FRAMES It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account–either practically or phenomenologically–for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities. Similar feelings seem to be emerging in several centers working on theories of intelligence. They take one form in the proposal of Papert and myself (1972) to sub-structure knowledge into "micro-worlds"; another form in the "Problem-spaces" of Newell and Simon (1972); and yet another in new, large structures that theorists like Schank (1974), Abelson (1974), and Norman (1972) assign to linguistic objects. I see all these as moving away from the traditional attempts both by behavioristic psychologists and by logic-oriented students of Artificial Intelligence in trying to represent knowledge as collections of separate, simple fragments. I try here to bring together several of these issues by pretending to have a unified, coherent theory. The paper raises more questions than it answers, and I have tried to note the theory's deficiencies. -
An Overview of the Evolution of the Devices Running Computer Algebra Systems and Their Educational Implications
Electrical & Electronic Technology Open Access Journal Short Communication Open Access An overview of the evolution of the devices running computer algebra systems and their educational implications Abstract Volume 1 Issue 1 - 2017 Only back in late 60’s and early 70’s powerful computers were required to run the Eugenio Roanes-Lozano then just released computer algebra systems (brand new software mainly designed as Instituto de Matemática Interdisciplinar & Depto de Álgebra, a specialized aid for astronomy and high energy physics). In the late 80’s they could Universidad Complutense de Madrid, Spain be run in standard computers. And in 1995 the first calculator including a computer algebra system was released. Now some of these pieces of software are freely available Correspondence: Eugenio Roanes-Lozano, Instituto de for Smartphones. That this software has been ported to these electronic devices is a Matemática Interdisciplinar & Depto de Álgebra, Universidad challenge to different aspects of mathematical and physics education, like: problem Complutense de Madrid, c/ Rector Royo Villanova s/n, solving, assessment and standardized assessment. 28040-Madrid, Spain, Tel 913-946-248, Fax 913-944-662, Email [email protected] Keywords: computer algebra systems, computers, calculators, smartphones, mathematical education Received: May 05, 2017 | Published: June 20, 2017 Introduction symbolic manipulations such as symbolic differentiation and integra- tion can be implemented. The incredible increase of microprocessors 1 Computer algebra systems have two main differences w.r.t. clas- power makes it possible to have CAS available for Smartphones. This sic computer languages: induces serious challenges in teaching mathematics as well and in the a) They perform numerical computations in exact arithmetic (by assessment of this subject.