Algebraic Equations Examples with Answers
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Algorithmic Factorization of Polynomials Over Number Fields
Rose-Hulman Institute of Technology Rose-Hulman Scholar Mathematical Sciences Technical Reports (MSTR) Mathematics 5-18-2017 Algorithmic Factorization of Polynomials over Number Fields Christian Schulz Rose-Hulman Institute of Technology Follow this and additional works at: https://scholar.rose-hulman.edu/math_mstr Part of the Number Theory Commons, and the Theory and Algorithms Commons Recommended Citation Schulz, Christian, "Algorithmic Factorization of Polynomials over Number Fields" (2017). Mathematical Sciences Technical Reports (MSTR). 163. https://scholar.rose-hulman.edu/math_mstr/163 This Dissertation is brought to you for free and open access by the Mathematics at Rose-Hulman Scholar. It has been accepted for inclusion in Mathematical Sciences Technical Reports (MSTR) by an authorized administrator of Rose-Hulman Scholar. For more information, please contact [email protected]. Algorithmic Factorization of Polynomials over Number Fields Christian Schulz May 18, 2017 Abstract The problem of exact polynomial factorization, in other words expressing a poly- nomial as a product of irreducible polynomials over some field, has applications in algebraic number theory. Although some algorithms for factorization over algebraic number fields are known, few are taught such general algorithms, as their use is mainly as part of the code of various computer algebra systems. This thesis provides a summary of one such algorithm, which the author has also fully implemented at https://github.com/Whirligig231/number-field-factorization, along with an analysis of the runtime of this algorithm. Let k be the product of the degrees of the adjoined elements used to form the algebraic number field in question, let s be the sum of the squares of these degrees, and let d be the degree of the polynomial to be factored; then the runtime of this algorithm is found to be O(d4sk2 + 2dd3). -
[Math.NA] 10 Jan 2001 Plctoso H Dmoetmti Ler Odsrt O Discrete to Algebra [9]– Matrix Theory
Idempotent Interval Analysis and Optimization Problems ∗ G. L. Litvinov ([email protected]) International Sophus Lie Centre A. N. Sobolevski˘ı([email protected]) M. V. Lomonosov Moscow State University Abstract. Many problems in optimization theory are strongly nonlinear in the traditional sense but possess a hidden linear structure over suitable idempotent semirings. After an overview of ‘Idempotent Mathematics’ with an emphasis on matrix theory, interval analysis over idempotent semirings is developed. The theory is applied to construction of exact interval solutions to the interval discrete sta- tionary Bellman equation. Solution of an interval system is typically NP -hard in the traditional interval linear algebra; in the idempotent case it is polynomial. A generalization to the case of positive semirings is outlined. Keywords: Idempotent Mathematics, Interval Analysis, idempotent semiring, dis- crete optimization, interval discrete Bellman equation MSC codes: 65G10, 16Y60, 06F05, 08A70, 65K10 Introduction Many problems in the optimization theory and other fields of mathe- matics are nonlinear in the traditional sense but appear to be linear over semirings with idempotent addition.1 This approach is developed systematically as Idempotent Analysis or Idempotent Mathematics (see, e.g., [1]–[8]). In this paper we present an idempotent version of Interval Analysis (its classical version is presented, e.g., in [9]–[12]) and discuss applications of the idempotent matrix algebra to discrete optimization theory. The idempotent interval analysis appears to be best suited for treat- ing problems with order-preserving transformations of input data. It gives exact interval solutions to optimization problems with interval un- arXiv:math/0101080v1 [math.NA] 10 Jan 2001 certainties without any conditions of smallness on uncertainty intervals. -
Solving Equations; Patterns, Functions, and Algebra; 8.15A
Mathematics Enhanced Scope and Sequence – Grade 8 Solving Equations Reporting Category Patterns, Functions, and Algebra Topic Solving equations in one variable Primary SOL 8.15a The student will solve multistep linear equations in one variable with the variable on one and two sides of the equation. Materials • Sets of algebra tiles • Equation-Solving Balance Mat (attached) • Equation-Solving Ordering Cards (attached) • Be the Teacher: Solving Equations activity sheet (attached) • Student whiteboards and markers Vocabulary equation, variable, coefficient, constant (earlier grades) Student/Teacher Actions (what students and teachers should be doing to facilitate learning) 1. Give each student a set of algebra tiles and a copy of the Equation-Solving Balance Mat. Lead students through the steps for using the tiles to model the solutions to the following equations. As you are working through the solution of each equation with the students, point out that you are undoing each operation and keeping the equation balanced by doing the same thing to both sides. Explain why you do this. When students are comfortable with modeling equation solutions with algebra tiles, transition to writing out the solution steps algebraically while still using the tiles. Eventually, progress to only writing out the steps algebraically without using the tiles. • x + 3 = 6 • x − 2 = 5 • 3x = 9 • 2x + 1 = 9 • −x + 4 = 7 • −2x − 1 = 7 • 3(x + 1) = 9 • 2x = x − 5 Continue to allow students to use the tiles whenever they wish as they work to solve equations. 2. Give each student a whiteboard and marker. Provide students with a problem to solve, and as they write each step, have them hold up their whiteboards so you can ensure that they are completing each step correctly and understanding the process. -
Some Properties of the Discriminant Matrices of a Linear Associative Algebra*
570 R. F. RINEHART [August, SOME PROPERTIES OF THE DISCRIMINANT MATRICES OF A LINEAR ASSOCIATIVE ALGEBRA* BY R. F. RINEHART 1. Introduction. Let A be a linear associative algebra over an algebraic field. Let d, e2, • • • , en be a basis for A and let £»•/*., (hjik = l,2, • • • , n), be the constants of multiplication corre sponding to this basis. The first and second discriminant mat rices of A, relative to this basis, are defined by Ti(A) = \\h(eres[ CrsiCij i, j=l T2(A) = \\h{eres / ,J CrsiC j II i,j=l where ti(eres) and fa{erea) are the first and second traces, respec tively, of eres. The first forms in terms of the constants of multi plication arise from the isomorphism between the first and sec ond matrices of the elements of A and the elements themselves. The second forms result from direct calculation of the traces of R(er)R(es) and S(er)S(es), R{ei) and S(ei) denoting, respectively, the first and second matrices of ei. The last forms of the dis criminant matrices show that each is symmetric. E. Noetherf and C. C. MacDuffeeJ discovered some of the interesting properties of these matrices, and shed new light on the particular case of the discriminant matrix of an algebraic equation. It is the purpose of this paper to develop additional properties of these matrices, and to interpret them in some fa miliar instances. Let A be subjected to a transformation of basis, of matrix M, 7 J rH%j€j 1,2, *0). -
Diffman: an Object-Oriented MATLAB Toolbox for Solving Differential Equations on Manifolds
Applied Numerical Mathematics 39 (2001) 323–347 www.elsevier.com/locate/apnum DiffMan: An object-oriented MATLAB toolbox for solving differential equations on manifolds Kenth Engø a,∗,1, Arne Marthinsen b,2, Hans Z. Munthe-Kaas a,3 a Department of Informatics, University of Bergen, N-5020 Bergen, Norway b Department of Mathematical Sciences, NTNU, N-7491 Trondheim, Norway Abstract We describe an object-oriented MATLAB toolbox for solving differential equations on manifolds. The software reflects recent development within the area of geometric integration. Through the use of elements from differential geometry, in particular Lie groups and homogeneous spaces, coordinate free formulations of numerical integrators are developed. The strict mathematical definitions and results are well suited for implementation in an object- oriented language, and, due to its simplicity, the authors have chosen MATLAB as the working environment. The basic ideas of DiffMan are presented, along with particular examples that illustrate the working of and the theory behind the software package. 2001 IMACS. Published by Elsevier Science B.V. All rights reserved. Keywords: Geometric integration; Numerical integration of ordinary differential equations on manifolds; Numerical analysis; Lie groups; Lie algebras; Homogeneous spaces; Object-oriented programming; MATLAB; Free Lie algebras 1. Introduction DiffMan is an object-oriented MATLAB [24] toolbox designed to solve differential equations evolving on manifolds. The current version of the toolbox addresses primarily the solution of ordinary differential equations. The solution techniques implemented fall into the category of geometric integrators— a very active area of research during the last few years. The essence of geometric integration is to construct numerical methods that respect underlying constraints, for instance, the configuration space * Corresponding author. -
Teaching Strategies for Improving Algebra Knowledge in Middle and High School Students
EDUCATOR’S PRACTICE GUIDE A set of recommendations to address challenges in classrooms and schools WHAT WORKS CLEARINGHOUSE™ Teaching Strategies for Improving Algebra Knowledge in Middle and High School Students NCEE 2015-4010 U.S. DEPARTMENT OF EDUCATION About this practice guide The Institute of Education Sciences (IES) publishes practice guides in education to provide edu- cators with the best available evidence and expertise on current challenges in education. The What Works Clearinghouse (WWC) develops practice guides in conjunction with an expert panel, combining the panel’s expertise with the findings of existing rigorous research to produce spe- cific recommendations for addressing these challenges. The WWC and the panel rate the strength of the research evidence supporting each of their recommendations. See Appendix A for a full description of practice guides. The goal of this practice guide is to offer educators specific, evidence-based recommendations that address the challenges of teaching algebra to students in grades 6 through 12. This guide synthesizes the best available research and shares practices that are supported by evidence. It is intended to be practical and easy for teachers to use. The guide includes many examples in each recommendation to demonstrate the concepts discussed. Practice guides published by IES are available on the What Works Clearinghouse website at http://whatworks.ed.gov. How to use this guide This guide provides educators with instructional recommendations that can be implemented in conjunction with existing standards or curricula and does not recommend a particular curriculum. Teachers can use the guide when planning instruction to prepare students for future mathemat- ics and post-secondary success. -
Step-By-Step Solution Possibilities in Different Computer Algebra Systems
Step-by-Step Solution Possibilities in Different Computer Algebra Systems Eno Tõnisson University of Tartu Estonia E-mail: [email protected] Introduction The aim of my research is to compare different computer algebra systems, and specifically to find out how the students could solve problems step-by-step using different computer algebra systems. The present paper provides the preliminary comparison of some aspects related to step-by-step solution in DERIVE, Maple, Mathematica, and MuPAD. The paper begins with examples of one-step solutions of equations. This is followed by a cursory survey of useful commands, entering commands, programming etc. I hope that a more detailed and complete review will be composed quite soon. Suggestions for complementing the comparison are welcome. It is necessary to know which concrete versions are under consideration. In alphabetical order: DERIVE for Windows. Version 4.11 (1996) Maple V Release 5. Student Version 5.00 (1998) Mathematica for Students. Version 3.0 (1996) MuPAD Light. Version 1.4.1 (1998) Only pure systems (without additional packages, etc.) are under consideration. I believe that there may be more (especially interface-sensitive) possibilities in MuPAD Pro than in MuPAD Light. My paper is not the first comparison, of course. I found several previous ones in the Internet. For example, 1. Michael Wester. A review of CAS mathematical capabilities. 1995 There are 131 short problems covering a broad range of symbolic mathematics. http://math.unm.edu/~wester/cas/Paper.ps (One of the profoundest comparisons is probably M. Wester's book Practical Guide to Computer Algebra Systems.) 1 2. -
A Historical Survey of Methods of Solving Cubic Equations Minna Burgess Connor
University of Richmond UR Scholarship Repository Master's Theses Student Research 7-1-1956 A historical survey of methods of solving cubic equations Minna Burgess Connor Follow this and additional works at: http://scholarship.richmond.edu/masters-theses Recommended Citation Connor, Minna Burgess, "A historical survey of methods of solving cubic equations" (1956). Master's Theses. Paper 114. This Thesis is brought to you for free and open access by the Student Research at UR Scholarship Repository. It has been accepted for inclusion in Master's Theses by an authorized administrator of UR Scholarship Repository. For more information, please contact [email protected]. A HISTORICAL SURVEY OF METHODS OF SOLVING CUBIC E<~UATIONS A Thesis Presented' to the Faculty or the Department of Mathematics University of Richmond In Partial Fulfillment ot the Requirements tor the Degree Master of Science by Minna Burgess Connor August 1956 LIBRARY UNIVERStTY OF RICHMOND VIRGlNIA 23173 - . TABLE Olf CONTENTS CHAPTER PAGE OUTLINE OF HISTORY INTRODUCTION' I. THE BABYLONIANS l) II. THE GREEKS 16 III. THE HINDUS 32 IV. THE CHINESE, lAPANESE AND 31 ARABS v. THE RENAISSANCE 47 VI. THE SEVEW.l'EEl'iTH AND S6 EIGHTEENTH CENTURIES VII. THE NINETEENTH AND 70 TWENTIETH C:BNTURIES VIII• CONCLUSION, BIBLIOGRAPHY 76 AND NOTES OUTLINE OF HISTORY OF SOLUTIONS I. The Babylonians (1800 B. c.) Solutions by use ot. :tables II. The Greeks·. cs·oo ·B.c,. - )00 A~D.) Hippocrates of Chios (~440) Hippias ot Elis (•420) (the quadratrix) Archytas (~400) _ .M~naeobmus J ""375) ,{,conic section~) Archimedes (-240) {conioisections) Nicomedea (-180) (the conchoid) Diophantus ot Alexander (75) (right-angled tr~angle) Pappus (300) · III. -
501 Algebra Questions 2Nd Edition
501 Algebra Questions 501 Algebra Questions 2nd Edition ® NEW YORK Copyright © 2006 LearningExpress, LLC. All rights reserved under International and Pan-American Copyright Conventions. Published in the United States by LearningExpress, LLC, New York. Library of Congress Cataloging-in-Publication Data: 501 algebra questions.—2nd ed. p. cm. Rev. ed. of: 501 algebra questions / [William Recco]. 1st ed. © 2002. ISBN 1-57685-552-X 1. Algebra—Problems, exercises, etc. I. Recco, William. 501 algebra questions. II. LearningExpress (Organization). III. Title: Five hundred one algebra questions. IV. Title: Five hundred and one algebra questions. QA157.A15 2006 512—dc22 2006040834 Printed in the United States of America 98765432 1 Second Edition ISBN 1-57685-552-X For more information or to place an order, contact LearningExpress at: 55 Broadway 8th Floor New York, NY 10006 Or visit us at: www.learnatest.com The LearningExpress Skill Builder in Focus Writing Team is comprised of experts in test preparation, as well as educators and teachers who specialize in language arts and math. LearningExpress Skill Builder in Focus Writing Team Brigit Dermott Freelance Writer English Tutor, New York Cares New York, New York Sandy Gade Project Editor LearningExpress New York, New York Kerry McLean Project Editor Math Tutor Shirley, New York William Recco Middle School Math Teacher, Grade 8 New York Shoreham/Wading River School District Math Tutor St. James, New York Colleen Schultz Middle School Math Teacher, Grade 8 Vestal Central School District Math Tutor -
The Evolution of Equation-Solving: Linear, Quadratic, and Cubic
California State University, San Bernardino CSUSB ScholarWorks Theses Digitization Project John M. Pfau Library 2006 The evolution of equation-solving: Linear, quadratic, and cubic Annabelle Louise Porter Follow this and additional works at: https://scholarworks.lib.csusb.edu/etd-project Part of the Mathematics Commons Recommended Citation Porter, Annabelle Louise, "The evolution of equation-solving: Linear, quadratic, and cubic" (2006). Theses Digitization Project. 3069. https://scholarworks.lib.csusb.edu/etd-project/3069 This Thesis is brought to you for free and open access by the John M. Pfau Library at CSUSB ScholarWorks. It has been accepted for inclusion in Theses Digitization Project by an authorized administrator of CSUSB ScholarWorks. For more information, please contact [email protected]. THE EVOLUTION OF EQUATION-SOLVING LINEAR, QUADRATIC, AND CUBIC A Project Presented to the Faculty of California State University, San Bernardino In Partial Fulfillment of the Requirements for the Degre Master of Arts in Teaching: Mathematics by Annabelle Louise Porter June 2006 THE EVOLUTION OF EQUATION-SOLVING: LINEAR, QUADRATIC, AND CUBIC A Project Presented to the Faculty of California State University, San Bernardino by Annabelle Louise Porter June 2006 Approved by: Shawnee McMurran, Committee Chair Date Laura Wallace, Committee Member , (Committee Member Peter Williams, Chair Davida Fischman Department of Mathematics MAT Coordinator Department of Mathematics ABSTRACT Algebra and algebraic thinking have been cornerstones of problem solving in many different cultures over time. Since ancient times, algebra has been used and developed in cultures around the world, and has undergone quite a bit of transformation. This paper is intended as a professional developmental tool to help secondary algebra teachers understand the concepts underlying the algorithms we use, how these algorithms developed, and why they work. -
Algebraic Division by Zero Implemented As Quasigeometric Multiplication by Infinity in Real and Complex Multispatial Hyperspaces
Available online at www.worldscientificnews.com WSN 92(2) (2018) 171-197 EISSN 2392-2192 Algebraic division by zero implemented as quasigeometric multiplication by infinity in real and complex multispatial hyperspaces Jakub Czajko Science/Mathematics Education Department, Southern University and A&M College, Baton Rouge, LA 70813, USA E-mail address: [email protected] ABSTRACT An unrestricted division by zero implemented as an algebraic multiplication by infinity is feasible within a multispatial hyperspace comprising several quasigeometric spaces. Keywords: Division by zero, infinity, multispatiality, multispatial uncertainty principle 1. INTRODUCTION Numbers used to be identified with their values. Yet complex numbers have two distinct single-number values: modulus/length and angle/phase, which can vary independently of each other. Since values are attributes of the algebraic entities called numbers, we need yet another way to define these entities and establish a basis that specifies their attributes. In an operational sense a number can be defined as the outcome of an algebraic operation. We must know the space where the numbers reside and the basis in which they are represented. Since division is inverse of multiplication, then reciprocal/contragradient basis can be used to represent inverse numbers for division [1]. Note that dual space, as conjugate space [2] is a space of functionals defined on elements of the primary space [3-5]. Although dual geometries are identical as sets, their geometrical structures are different [6] for duality can ( Received 18 December 2017; Accepted 03 January 2018; Date of Publication 04 January 2018 ) World Scientific News 92(2) (2018) 171-197 form anti-isomorphism or inverse isomorphism [7]. -
Interactive Mathematics Program Curriculum Framework
Interactive Mathematics Program Curriculum Framework School: __Delaware STEM Academy________ Curricular Tool: _IMP________ Grade or Course _Year 1 (grade 9) Unit Concepts / Standards Alignment Essential Questions Assessments Big Ideas from IMP Unit One: Patterns Timeline: 6 weeks Interpret expressions that represent a quantity in terms of its Patterns emphasizes extended, open-ended Can students use variables and All assessments are context. CC.A-SSE.1 exploration and the search for patterns. algebraic expressions to listed at the end of the Important mathematics introduced or represent concrete situations, curriculum map. Understand that a function from one set (called the domain) reviewed in Patterns includes In-Out tables, generalize results, and describe to another set (called the range) assigns to each element of functions, variables, positive and negative functions? the domain exactly one element of the range. If f is a function numbers, and basic geometry concepts Can students use different and x is an element of its domain, then f(x) denotes the output related to polygons. Proof, another major representations of functions— of f corresponding to the input x. The graph of f is the graph theme, is developed as part of the larger symbolic, graphical, situational, of the equation y = f(x). CC.F-IF.1 theme of reasoning and explaining. and numerical—and Students’ ability to create and understand understanding the connections Recognize that sequences are functions, sometimes defined proofs will develop over their four years in between these representations? recursively, whose domain is a subset of the integers. For IMP; their work in this unit is an important example, the Fibonacci sequence is defined recursively by start.