A Survey of User Interfaces for Computer Algebra Systems
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The Mathdeck Formula Editor
The MathDeck Formula Editor: Interactive Formula Entry Combining LATEX, Structure Editing, and Search Yancarlos Diaz Gavin Nishizawa Behrooz Mansouri [email protected] [email protected] [email protected] Rochester Institute of Technology Rochester Institute of Technology Rochester Institute of Technology Rochester, NY, USA Rochester, NY, USA Rochester, NY, USA Kenny Davila Richard Zanibbi [email protected] [email protected] University at Buffalo Rochester Institute of Technology Buffalo, NY, USA Rochester, NY, USA Figure 1: MathDeck Search Interface. Formulas are created using the rendered formula, the LATEX string at right, formulas in tabs, and ‘chips’ on the canvas and in the ‘deck’ at bottom. Cards in the deck update for the current formula, and may be expanded to reveal descriptions. Formulas and keywords may be added to the query bar, and sent to a search engine. ABSTRACT CCS CONCEPTS Writing formulas in LATEX can be difficult, especially for complex • Information systems ! Search interfaces; • Mathematics formulas. MathDeck simplifiesA LTEX formula entry by: 1) allowing of computing ! Mathematical software. rendered formulas to be edited directly alongside their associated LATEX strings, 2) helping build formulas from smaller ones, and KEYWORDS 3) providing searchable formula cards with associated names and equation editor, structure editor, LaTeX, Mathematical Information descriptions. Cards are searchable by formula and title. Retrieval (MIR) Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed ACM Reference Format: for profit or commercial advantage and that copies bear this notice and the full citation Yancarlos Diaz, Gavin Nishizawa, Behrooz Mansouri, Kenny Davila, and Richard on the first page. -
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. -
Rapid Research with Computer Algebra Systems
doi: 10.21495/71-0-109 25th International Conference ENGINEERING MECHANICS 2019 Svratka, Czech Republic, 13 – 16 May 2019 RAPID RESEARCH WITH COMPUTER ALGEBRA SYSTEMS C. Fischer* Abstract: Computer algebra systems (CAS) are gaining popularity not only among young students and schol- ars but also as a tool for serious work. These highly complicated software systems, which used to just be regarded as toys for computer enthusiasts, have reached maturity. Nowadays such systems are available on a variety of computer platforms, starting from freely-available on-line services up to complex and expensive software packages. The aim of this review paper is to show some selected capabilities of CAS and point out some problems with their usage from the point of view of 25 years of experience. Keywords: Computer algebra system, Methodology, Wolfram Mathematica 1. Introduction The Wikipedia page (Wikipedia contributors, 2019a) defines CAS as a package comprising a set of algo- rithms for performing symbolic manipulations on algebraic objects, a language to implement them, and an environment in which to use the language. There are 35 different systems listed on the page, four of them discontinued. The oldest one, Reduce, was publicly released in 1968 (Hearn, 2005) and is still available as an open-source project. Maple (2019a) is among the most popular CAS. It was first publicly released in 1984 (Maple, 2019b) and is still popular, also among users in the Czech Republic. PTC Mathcad (2019) was published in 1986 in DOS as an engineering calculation solution, and gained popularity for its ability to work with typeset mathematical notation in combination with automatic computations. -
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. -
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). -
About the Polynomial System Solve Facility of Axiom, Macsyma, Maple
Ab out the Polynomial System Solve Facility of Axiom, Macsyma, Maple, Mathematica, MuPAD, and Reduce Hans-Gert Grab e Institut fur Informatik, Universitat Leipzig, Germany February 23, 1998 In memoriam to Renate. Abstract We rep ort on some exp eriences with the general purp ose Computer Algebra Systems (CAS) Axiom, Macsyma, Maple, Mathematica, MuPAD, and Reduce solving systems of p olynomial equations and the way they present their solutions. This snapshot (taken in the spring 1996) of the current power of the di erent systems in a sp ecial area concentrates b oth on CPU-times and the quality of the output. 1 Intro duction Let S := k [x ;::: ;x ] be the p olynomial ring in the variables x ;::: ;x over the eld 1 n 1 n k and B := ff ;::: ;f g S be a nite system of p olynomials. Denote by I (B ) the 1 m ideal generated by these p olynomials. One of the ma jor tasks of constructive commutative n algebra is the derivation of information ab out the structure of Z (B ) := fa 2 k : 8 f 2 B such that f (a)=0g, the set of common zero es of the system B over the algebraic closure k of k . Splitting the system into smaller ones, solving them separately, and patching all solu- tions together is often a go o d guess for a quick solution of even highly nontrivial problems. This can b e done by several techniques, e.g. characteristic sets, resultants, the Grobner fac- torizer or some ad ho c metho ds. -
Undergraduate Catalog 14-16
UNDERGRADUATE CATALOG: 2014-2016 Connecticut State Colleges and Universities ACADEMIC DEPARTMENTS, PROGRAMS, AND Accreditation and Policy COURSES Message from the President Ancell School of Business Academic Calendar School of Arts & Sciences Introduction to Western School of Professional Studies The Campus School of Visual and Performing Arts Admission to Western Division of Graduate Studies Student Expenses Office of Student Aid & Student Employment Directory Student Affairs Administration Academic Services and Procedures Faculty/Staff Academic Programs and Degrees Faculty Emeriti Graduation Academic Program Descriptions WCSU Undergraduate Catalog: 2014-2016 1 CONNECTICUT STATE COLLEGES & UNIVERSITIES The 17 Connecticut State Colleges & Universities (ConnSCU) provide affordable, innovative and rigorous programs that permit students to achieve their personal and career goals, as well as contribute to the economic growth of Connecticut. The ConnSCU System encompasses four state universities – Western Connecticut State University in Danbury, Central Connecticut State University in New Britain, Eastern Connecticut State University in Willimantic and Southern Connecticut State University in New Haven – as well as 12 community colleges and the online institution Charter Oak State College. Until the state’s higher education reorganization of 2011, Western was a member of the former Connecticut State Unviersity System that also encompassed Central, Eastern and Southern Connecticut state universities. With origins in normal schools for teacher education founded in the 19th and early 20th centuries, these institutions evolved into diversified state universities whose graduates have pursued careers in the professions, business, education, public service, the arts and other fields. Graduates of Western and other state universities contribute to all aspects of Connecticut economic, social and cultural life. -
Lisp: Program Is Data
LISP: PROGRAM IS DATA A HISTORICAL PERSPECTIVE ON MACLISP Jon L White Laboratory for Computer Science, M.I.T.* ABSTRACT For over 10 years, MACLISP has supported a variety of projects at M.I.T.'s Artificial Intelligence Laboratory, and the Laboratory for Computer Science (formerly Project MAC). During this time, there has been a continuing development of the MACLISP system, spurred in great measure by the needs of MACSYMAdevelopment. Herein are reported, in amosiac, historical style, the major features of the system. For each feature discussed, an attempt will be made to mention the year of initial development, andthe names of persons or projectsprimarily responsible for requiring, needing, or suggestingsuch features. INTRODUCTION In 1964,Greenblatt and others participated in thecheck-out phase of DigitalEquipment Corporation's new computer, the PDP-6. This machine had a number of innovative features that were thought to be ideal for the development of a list processing system, and thus it was very appropriate that thefirst working program actually run on thePDP-6 was anancestor of thecurrent MACLISP. This earlyLISP was patterned after the existing PDP-1 LISP (see reference l), and was produced by using the text editor and a mini-assembler on the PDP-1. That first PDP-6 finally found its way into M.I.T.'s ProjectMAC for use by theArtificial lntelligence group (the A.1. grouplater became the M.I.T. Artificial Intelligence Laboratory, and Project MAC became the Laboratory for Computer Science). By 1968, the PDP-6 wasrunning the Incompatible Time-sharing system, and was soon supplanted by the PDP-IO.Today, the KL-I 0, anadvanced version of thePDP-10, supports a variety of time sharing systems, most of which are capable of running a MACLISP. -
SMT Solving in a Nutshell
SAT and SMT Solving in a Nutshell Erika Abrah´ am´ RWTH Aachen University, Germany LuFG Theory of Hybrid Systems February 27, 2020 Erika Abrah´ am´ - SAT and SMT solving 1 / 16 What is this talk about? Satisfiability problem The satisfiability problem is the problem of deciding whether a logical formula is satisfiable. We focus on the automated solution of the satisfiability problem for first-order logic over arithmetic theories, especially using SAT and SMT solving. Erika Abrah´ am´ - SAT and SMT solving 2 / 16 CAS SAT SMT (propositional logic) (SAT modulo theories) Enumeration Computer algebra DP (resolution) systems [Davis, Putnam’60] DPLL (propagation) [Davis,Putnam,Logemann,Loveland’62] Decision procedures NP-completeness [Cook’71] for combined theories CAD Conflict-directed [Shostak’79] [Nelson, Oppen’79] backjumping Partial CAD Virtual CDCL [GRASP’97] [zChaff’04] DPLL(T) substitution Watched literals Equalities and uninterpreted Clause learning/forgetting functions Variable ordering heuristics Bit-vectors Restarts Array theory Arithmetic Decision procedures for first-order logic over arithmetic theories in mathematical logic 1940 Computer architecture development 1960 1970 1980 2000 2010 Erika Abrah´ am´ - SAT and SMT solving 3 / 16 SAT SMT (propositional logic) (SAT modulo theories) Enumeration DP (resolution) [Davis, Putnam’60] DPLL (propagation) [Davis,Putnam,Logemann,Loveland’62] Decision procedures NP-completeness [Cook’71] for combined theories Conflict-directed [Shostak’79] [Nelson, Oppen’79] backjumping CDCL [GRASP’97] [zChaff’04] -
General Relativity Computations with Sagemanifolds
General relativity computations with SageManifolds Eric´ Gourgoulhon Laboratoire Univers et Th´eories (LUTH) CNRS / Observatoire de Paris / Universit´eParis Diderot 92190 Meudon, France http://luth.obspm.fr/~luthier/gourgoulhon/ NewCompStar School 2016 Neutron stars: gravitational physics theory and observations Coimbra (Portugal) 5-9 September 2016 Eric´ Gourgoulhon (LUTH) GR computations with SageManifolds NewCompStar, Coimbra, 6 Sept. 2016 1 / 29 Outline 1 Computer differential geometry and tensor calculus 2 The SageManifolds project 3 Let us practice! 4 Other examples 5 Conclusion and perspectives Eric´ Gourgoulhon (LUTH) GR computations with SageManifolds NewCompStar, Coimbra, 6 Sept. 2016 2 / 29 Computer differential geometry and tensor calculus Outline 1 Computer differential geometry and tensor calculus 2 The SageManifolds project 3 Let us practice! 4 Other examples 5 Conclusion and perspectives Eric´ Gourgoulhon (LUTH) GR computations with SageManifolds NewCompStar, Coimbra, 6 Sept. 2016 3 / 29 In 1965, J.G. Fletcher developed the GEOM program, to compute the Riemann tensor of a given metric In 1969, during his PhD under Pirani supervision, 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 yielded to the discovery of 6 errors in the original paper [J.E.F. Skea, Applications of SHEEP (1994)] Since then, many softwares for tensor calculus have been developed... Computer differential geometry and tensor calculus Introduction Computer algebra system (CAS) started to be developed in the 1960's; for instance Macsyma (to become Maxima in 1998) was initiated in 1968 at MIT Eric´ Gourgoulhon (LUTH) GR computations with SageManifolds NewCompStar, Coimbra, 6 Sept. -
The Process of Urban Systems Integration
THE PROCESS OF URBAN SYSTEMS An integrative approach towards the institutional process of systems integration in urban area development INTEGRATION MSc Thesis Eva Ros MSc Thesis November 2017 Eva Ros student number # 4188624 MSc Architecture, Urbanism and Building Sciences Delft University of Technology, department of Management in the Built Environment chair of Urban Area Development (UAD) graduation laboratory Next Generation Waterfronts in collaboration with the AMS institute First mentor Arie Romein Second mentor Ellen van Bueren This thesis was printed on environmentally friendly recycled and unbleached paper 2 THE PROCESS OF URBAN SYSTEMS INTEGRATION An integrative approach towards the institutional process of systems integration in urban area development 3 MANAGEMENT SUMMARY (ENG) INTRODUCTION Today, more than half of the world’s population lives in cities. This makes them centres of resource consumption and waste production. Sustainable development is seen as an opportunity to respond to the consequences of urbanisation and climate change. In recent years the concepts of circularity and urban symbiosis have emerged as popular strategies to develop sustainable urban areas. An example is the experimental project “Straat van de Toekomst”, implementing a circular strategy based on the Greenhouse Village concept (appendix I). This concept implements circular systems for new ways of sanitation, heat and cold storage and greenhouse-house symbiosis. Although many technological artefacts have to be developed for these sustainable solutions, integrating infrastructural systems asks for more than just technological innovation. A socio-cultural change is needed in order to reach systems integration. The institutional part of technological transitions has been underexposed over the past few years.