Computer Algebra with LISP and REDUCE: An Introduction to Computer-aided Pure Mathematics

272 Pages·1991·18.151 MB·English

by  F. Brackx, D. Constales (auth.)

ComputerAlgebra withLISP and REDUCE
Mathematics and Its Applications
ManagingEditor:
M. HAZEWINKEL
CentreforMathematicsandComputerScience.Amsterdam.TheNetherlands
EditorialBoard:
F.CALOGERO.UniversitiidegliStudidiRoma.Italy
Yu. I.MANIN,SteklovInstituteofMathematics,Moscow, U.S.S.R.
M. NIVAT,UniversitedeParisVII,Paris,France
A. H.G.RINNOOY KAN,ErasmusUniversity.Rotterdam.TheNetherlands
G.-C.ROTA,M.l.T.•Cambridge, Mass., U.S.A.
Volume72
Computer Algebra
with LISP
andREDUCE
An Introduction to
Computer -aided Pure Mathematics
by
F. Brackx
Department of Mathematics, University ofGhent, Ghent, Belgium
and
D. Constales
Belgian National Fundfor Scientijic Research (NFWO), Belgium
~.
"
SPRINGER -SCIENCE+BUSINESS MEDIA, B.V.
Library of Congress Cataloging-in-Publication Data
Brackx, F.
Computer algebra with LISP and REDUCE an introductl0n to
computer-alded pure mathematlcs I by F. Brackx and D. Constales.
p. cm. -- (Mathematlcs and its appllcatlons , v. 72)
Includes bibll0graphlcal references and lndex.
ISBN 978-94-010-5549-9 ISBN 978-94-011-3502-3 (eBook)
DOI 10.1007/978-94-011-3502-3
1. Algeora--Data proeesslng. 2. LISP (Computer program language)
3. REDUCE (Computer program) I. Constales, D. II. Title.
III. Ser les, Mathemat les and ltS app I icatlons (Kluwer Academ le
Publishers) , v.72.
QA155.7.E4B72 1991
512' .0285--dc20 91-31211
ISBN 978-94-010-5549-9
Printed on aaid-free paper
All Rights Reserved
© 1991 Springer Science+Business Media Dordrecht
Originally published by Kluwer Academic Publishers in 1991
Softcover reprint ofthe hardcover Ist edition 1991
No part ofthe material protected by this copyright notice may be reproduced or
utilized in any form or by any means, electronic Of mechanical,
including photocopying, recording or by any information storage and
retrieval system, without written permission from the copyright owner.
SERIESEDITOR'S PREFACE
tEL moi,....sij'avait su commenten revenir. One service mathematics has rendered the
jen'yseraispointalle'.' human race. It has put common sense back
JulesVerne where it belongs, on the topmost shelfnext
tothedustycanisterlabelled 'discarded non
The series is divergent; thereforewemaybe sense',
abletodosomethingwithit. EricT. Bell
O.Heaviside
Mathematicsisa tool for thought. Ahighly necessary tool in a world whereboth feedback and non
linearitiesabound. Similarly, all kinds ofpartsofmathematicsserveas tools for other partsand for
other sciences.
Applying a simple rewriting rule to the quote on the right above one finds such statements as:
'One service topology has rendered mathematical physics ...'; 'One service logic has rendered com
puter science ...'; 'Oneservicecategory theory has rendered mathematics ,..'. All arguably true. And
allstatementsobtainable this way form partofthe raison d'elreofthisseries.
This series, Mathematics and Its Applications, started in 1977. Now that over one hundred
volumes haveappeared it seemsopportune to reexamine its scope. At the time I wrote
"Growing specialization and diversification have brought a host of monographs and
textbooks on increasingly specialized topics. However, the 'tree' of knowledge of
mathematics and related fields does not grow only by pUlling forth new branches. It
also happens, quite often in fact, that branches which were thought to be completely
disparate are suddenly seen to be related. Further, the kind and level ofsophistication
of mathematics applied in various sciences has changed drastically in recent years:
measure theory is used (non-trivially) in regional and theoretical economics; algebraic
geometry interacts with physics; the Minkowsky lemma,codingtheory and the structure
of water meet one another in packing and covering theory; quantum fields, crystal
defects and mathematical programming profit from homotopy theory; Lie algebras are
relevant to filtering; and prediction and electrical engineeringcan useStein spaces. And
in addition to this there are such new emerging subdisciplines as 'experimental
mathematics', 'CFD" 'completely integrable systems', 'chaos, synergetics and large-scale
order', which are almost impossible to fit into the existing classification schemes. They
draw upon widelydifferent sectionsofmathematics."
By and large, all this still applies today. It is still true that at first sight mathematics seems rather
fragmented and that to find, see, and exploit the deeper underlying interrelations more effort is
needed and so are books that can help mathematicians and scientists do so. Accordingly MIA will
continueto try to makesuch booksavailable,
If anything, the description I gave in 1977 is now an understatement. To the examples of
interaction areas one should add string theory where Riemann surfaces, algebraic geometry, modu
lar functions, knots, quantum field theory, Kac-Moody algebras, monstrous moonshine (and more)
all come together. And to the examplesofthings which can be usefully applied let meadd the topic
'finite geometry'; a combination of words which sounds like it might not even exist, let alone be
applicable. And yet it is beingapplied: to statistics via designs, to radar/sonar detection arrays (via
finite projective planes), and to bus connectionsofVLSI chips (via difference sets). Thereseems to
be no part of(so-called pure) mathematics that is not in immediate danger ofbeing applied. And,
accordingly, the applied mathematician needs to be aware of much more. Besides analysis and
numerics, the traditional workhorses, he may need all kinds ofcombinatories, algebra, probability,
and soon.
In addition, the applied scientist needs to cope increasingly with the nonlinear world and the
vi SERIESEDITOR'SPREFACE
extra mathematical sophistication that this requires. For that is where the rewards are. Linear
models are honest and a bit sad and depressing: proportional efforts and results. It is in the non
linear world that infinitesimal inputs may result in macroscopic outputs (or vice versa). To appreci
ate what I am hintingat: ifelectronicswere linear we would have no fun with transistors and com
puters; we would have noTV; in fact you would not bereading these lines.
There is also no safety in ignoring such outlandish things as nonstandard analysis, superspace
and anticommuting integration, p-adic and ultrametric space. AU three have applications in both
electrical engineering and physics. Once, complex numbers were equaUy outlandish, but they fre
quently proved the shortest path between 'real' results. Similarly, the first two topics named have
already provided a number of 'wormhole' paths. There is no teUing where aU this is leading
fortunately.
Thus the original scopeof the series, which for various (sound) reasons now comprises five sub
series: white (Japan), yeUow (China), red (USSR), blue (Eastern Europe), and green (everything
else), stiU applies. It has been enlarged a bit to include books treatingofthe tools from one subdis
cipline which are used in others.Thus theseries stil1aims at booksdealing with:
a central concept which plays an important role in several different mathematical and!or
scientific specialization areas;
new applicationsoftheresults and ideas from onearea ofscientificendeavour into another;
- influences which the results, probJcms and concepts ofone field of enquiry have, and have had,
on thedevelopmentofanother.
In spite of its name, a computer is a data-processing device and not necessarily a calculating
machine. One aspect of its scientific uses that is rapidly allracting more and more attention is the
useofthese machines for symbolic rather than numerical calculation.
For this kind of use, the programming LISP and general purpose computer algebra systems, of
which REDUCE isoneofthe wel1-known ones,offer critical advantages when compared toclassical
high-level programming languages such as FORTRAN,PASCAL,and C.
This volume, based on a set ofERASMUS courses, offers a selfcontained, and accessible treat
ment ofLISP and REDUCE for symbolic manipulations.
The shortest path between two truths in the Never lend books, for no one ever returns
real domain passes through the complex them; the only books I have in my library
domain. arebooksthatotherfolk havelentme.
J.Hadamard Anatole France
La physique ne nous donne pas seulement Thefunction ofan expert is not to be more
I'occasion de resoudre des problcmes ... cUe right than other people, but to be wrongfor
DOUSfait pressentirlasolution. moresophisticated reasons.
H. Poincare David Butler
Amsterdam, August 1991 Michiel Hazewinkel
Contents
Series Editor's Preface v
Preface xi
1 Introduction 1
1.1 Computers, mathematics and computer algebra 1
1.2 Requirements for a computer algebra system . 4
1.3 Why REDUCE? . 8
1.4 Classical high-level programming languages vs. REDUCE. 10
2 Standard LISP and RLISP 17
2.1 Computer programming 17
2.2 A model for LISP memory 19
2.3 Basic Standard LISP .. 21
2.4 An overview of Standard LISP functions 27
2.4.1 Fundamental functions 27
2.4.2 Structural predicates 46
2.4.3 Equality........ 52
2.4.4 Membership...... 54
2.4.5 Functions related to identifiers. 56
2.4.6 Function definition 62
2.4.7 Logical functions 67
2.4.8 Vectors. .... 70
2.4.9 Program constructs 72
2.4.10 Numerical functions 74
2.4.11 Evaluation ..... 81
2.4.12 Mapping functions 83
2.4.13 Association lists .. 85
2.4.14 Non-local jumps and error handling 86
2.4.15 Variable binding .. . . 88
2.4.16 Other Standard LISP functions 91
2.5 RLISP and Standard LISP. 97
2.6 Standard LISP vs. Common LISP . . . 102
viii CONTENTS
3 REDUCE algebraic mode 105
3.1 Numbers. . . 105
3.1.1 Integers . 105
3.1.2 Rational numbers 106
3.1.3 Algebraic numbers 108
3.1.4 Transcendental numbers 109
3.1.5 Complex numbers .... 110
3.1.6 Floating-point numbers. 111
3.2 Variables. 113
3.3 Lists... 115
3.4 Arrays .. 119
3.5 Matrices. 121
3.6 Operators 127
3.6.1 The built-in infix operators 127
3.6.2 The built-in prefix operators. 128
3.6.3 User-defined operators 136
3.7 Expressions and statements 142
3.7.1 Expressions. 142
3.7.2 Statements.. 146
3.8 Commands . 152
3.8.1 bye and quit. 153
3.8.2 define. 153
3.8.3 write ... 153
3.8.4 Substitution commands. 154
3.9 Special prefix operators. 161
3.9.1 Differentiation. 161
3.9.2 Finding primitives 163
3.9.3 Solving equations . 166
3.9.4 The mkid operator 171
3.9.5 The pf operator .. 172
3.9.6 The length operator 173
3.9.7 The coeff operator. 174
3.10 Polynomials. . .... 175
3.10.1 Factorization of polynomials and rational functions 176
3.10.2 The functions gcd, lcm and mcd.. 178
3.10.3 resultant. 180
3.10.4 remainder. 181
3.10.5 decompose. 181
3.10.6 interpol . 182
3.10.7 deg ..... 182
3.10.8 den and num 183
3.10.9 leaf, lterm and reduct 183
CONTENTS ix
3.10.10mainvar . 184
3.10.11Rational coefficients . 184
3.10.12Floating-point coefficients 185
3.10.13Complex coefficients 186
3.11 Structure. 188
3.11.1 output. 188
3.11.2 pri .. 189
3.11.3 exp ... 189
3.11.4 order . 189
3.11.5 korder. 190
3.11.6 factor. 191
3.11.7 allfac. 191
3.11.8 div. 192
3.11.9 list .. 192
3.11.10rat ... 193
3.11.11ratpri . 193
3.11.12revpri. 194
3.11.13nero .. 195
3.12 Internal representation 195
3.12.1 The share command 195
3.12.2 The part operator 195
3.13 Files . 197
4 Applications 201
4.1 A functional equation. . . . . . . . . . . . . . . . . 201
4.2 An algebra of one-dimensional projection operators 204
4.3 Grebner bases . . . . . . . . . . . . . . . 208
4.3.1 Systems of polynomial equations 208
4.3.2 Polynomial ideals . . . . . . . . . 209
4.3.3 The ideal associated to a system of polynomial equations 210
4.3.4 Reduction of a polynomial . . . . . . 210
4.3.5 Complete reduction of a polynomial. 212
4.3.6 Grebner bases. . . . . . 213
4.3.7 Buchberger's algorithm. 214
4.3.8 The radical ideal . . . . 215
4.3.9 Euler's nine-point circle 217
5 A package for three-dimensional euclidean geometry 219
5.1 Vectors............. 219
5.2 Clifford algebra . . . . . . . . . . . . . . . . . . . . . . 220
5.3 Groups in the Clifford algebra . . . . . . . . . . . . . . 225
5.4 The geometric meaning ofelements of the Clifford group 229
x CONTENTS
5.5 Objects 233
5.5.1 233
5.5.2 235
5.5.3 237
5.6 Incidence and coincidence of objects. 239
5.7 Union and intersection of objects 240
5.8 Orthogonality of objects 241
5.8.1 241
5.8.2 242
5.8.3 242
5.8.4 243
5.9 Distance and objects 243
5.10 Parallelism ofobjects 244
5.10.1 . 244
5.10.2 . 245
5.11 Orthogonal transformation of objects 245
5.12 Figures. 245
5.12.1 246
5.12.2 246
5.12.3 246
5.12.4 247
5.12.5 247
5.12.6 248
5.12.7 249
5.13 Conditions. 249
5.14 Applications. 254
5.14.1 Desargues's Theorem verified 254
5.14.2 Problem 2 . 254
Bibliography 257
Index 259