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\documentclass{article}
\usepackage{axiom}
\begin{document}
\title{\$SPAD/src/algebra rep2.spad}
\author{Holger Gollan, Johannes Grabmeier}
\maketitle
\begin{abstract}
\end{abstract}
\eject
\tableofcontents
\eject
\section{package REP2 RepresentationPackage2}
<<package REP2 RepresentationPackage2>>=
import Boolean
import Integer
import PositiveInteger
import List
import Vector
import Matrix
)abbrev package REP2 RepresentationPackage2
++ Authors: Holger Gollan, Johannes Grabmeier
++ Date Created: 10 September 1987
++ Date Last Updated: 20 August 1990
++ Basic Operations: areEquivalent?, isAbsolutelyIrreducible?,
++ split, meatAxe
++ Related Constructors: RepresentationTheoryPackage1
++ Also See: IrrRepSymNatPackage
++ AMS Classifications:
++ Keywords: meat-axe, modular representation
++ Reference:
++ R. A. Parker: The Computer Calculation of Modular Characters
++ (The Meat-Axe), in M. D. Atkinson (Ed.), Computational Group Theory
++ Academic Press, Inc., London 1984
++ H. Gollan, J. Grabmeier: Algorithms in Representation Theory and
++ their Realization in the Computer Algebra System Scratchpad,
++ Bayreuther Mathematische Schriften, Heft 33, 1990, 1-23.
++ Description:
++ RepresentationPackage2 provides functions for working with
++ modular representations of finite groups and algebra.
++ The routines in this package are created, using ideas of R. Parker,
++ (the meat-Axe) to get smaller representations from bigger ones,
++ i.e. finding sub- and factormodules, or to show, that such the
++ representations are irreducible.
++ Note: most functions are randomized functions of Las Vegas type
++ i.e. every answer is correct, but with small probability
++ the algorithm fails to get an answer.
RepresentationPackage2(R): public == private where
R : Ring
OF ==> OutputForm
I ==> Integer
L ==> List
SM ==> SquareMatrix
M ==> Matrix
NNI ==> NonNegativeInteger
V ==> Vector
PI ==> PositiveInteger
B ==> Boolean
RADIX ==> RadixExpansion
public ==> with
completeEchelonBasis : V V R -> M R
++ completeEchelonBasis(lv) completes the basis {\em lv} assumed
++ to be in echelon form of a subspace of {\em R**n} (n the length
++ of all the vectors in {\em lv}) with unit vectors to a basis of
++ {\em R**n}. It is assumed that the argument is not an empty
++ vector and that it is not the basis of the 0-subspace.
++ Note: the rows of the result correspond to the vectors of the basis.
createRandomElement : (L M R, M R) -> M R
++ createRandomElement(aG,x) creates a random element of the group
++ algebra generated by {\em aG}.
-- randomWord : (L L I, L M) -> M R
--++ You can create your own 'random' matrix with "randomWord(lli, lm)".
--++ Each li in lli determines a product of matrices, the entries in li
--++ determine which matrix from lm is chosen. Finally we sum over all
--++ products. The result "sm" can be used to call split with (e.g.)
--++ second parameter "first nullSpace sm"
if R has EuclideanDomain then -- using rowEchelon
cyclicSubmodule : (L M R, V R) -> V V R
++ cyclicSubmodule(lm,v) generates a basis as follows.
++ It is assumed that the size n of the vector equals the number
++ of rows and columns of the matrices. Then the matrices generate
++ a subalgebra, say \spad{A}, of the algebra of all square matrices of
++ dimension n. {\em V R} is an \spad{A}-module in the natural way.
++ cyclicSubmodule(lm,v) generates the R-Basis of {\em Av} as
++ described in section 6 of R. A. Parker's "The Meat-Axe".
++ Note: in contrast to the description in "The Meat-Axe" and to
++ {\em standardBasisOfCyclicSubmodule} the result is in
++ echelon form.
standardBasisOfCyclicSubmodule : (L M R, V R) -> M R
++ standardBasisOfCyclicSubmodule(lm,v) returns a matrix as follows.
++ It is assumed that the size n of the vector equals the number
++ of rows and columns of the matrices. Then the matrices generate
++ a subalgebra, say \spad{A},
++ of the algebra of all square matrices of
++ dimension n. {\em V R} is an \spad{A}-module in the natural way.
++ standardBasisOfCyclicSubmodule(lm,v) calculates a matrix whose
++ non-zero column vectors are the R-Basis of {\em Av} achieved
++ in the way as described in section 6
++ of R. A. Parker's "The Meat-Axe".
++ Note: in contrast to {\em cyclicSubmodule}, the result is not
++ in echelon form.
if R has Field then -- only because of inverse in SM
areEquivalent? : (L M R, L M R, B, I) -> M R
++ areEquivalent?(aG0,aG1,randomelements,numberOfTries) tests
++ whether the two lists of matrices, all assumed of same
++ square shape, can be simultaneously conjugated by a non-singular
++ matrix. If these matrices represent the same group generators,
++ the representations are equivalent.
++ The algorithm tries
++ {\em numberOfTries} times to create elements in the
++ generated algebras in the same fashion. If their ranks differ,
++ they are not equivalent. If an
++ isomorphism is assumed, then
++ the kernel of an element of the first algebra
++ is mapped to the kernel of the corresponding element in the
++ second algebra. Now consider the one-dimensional ones.
++ If they generate the whole space (e.g. irreducibility !)
++ we use {\em standardBasisOfCyclicSubmodule} to create the
++ only possible transition matrix. The method checks whether the
++ matrix conjugates all corresponding matrices from {\em aGi}.
++ The way to choose the singular matrices is as in {\em meatAxe}.
++ If the two representations are equivalent, this routine
++ returns the transformation matrix {\em TM} with
++ {\em aG0.i * TM = TM * aG1.i} for all i. If the representations
++ are not equivalent, a small 0-matrix is returned.
++ Note: the case
++ with different sets of group generators cannot be handled.
areEquivalent? : (L M R, L M R) -> M R
++ areEquivalent?(aG0,aG1) calls {\em areEquivalent?(aG0,aG1,true,25)}.
++ Note: the choice of 25 was rather arbitrary.
areEquivalent? : (L M R, L M R, I) -> M R
++ areEquivalent?(aG0,aG1,numberOfTries) calls
++ {\em areEquivalent?(aG0,aG1,true,25)}.
++ Note: the choice of 25 was rather arbitrary.
isAbsolutelyIrreducible? : (L M R, I) -> B
++ isAbsolutelyIrreducible?(aG, numberOfTries) uses
++ Norton's irreducibility test to check for absolute
++ irreduciblity, assuming if a one-dimensional kernel is found.
++ As no field extension changes create "new" elements
++ in a one-dimensional space, the criterium stays true
++ for every extension. The method looks for one-dimensionals only
++ by creating random elements (no fingerprints) since
++ a run of {\em meatAxe} would have proved absolute irreducibility
++ anyway.
isAbsolutelyIrreducible? : L M R -> B
++ isAbsolutelyIrreducible?(aG) calls
++ {\em isAbsolutelyIrreducible?(aG,25)}.
++ Note: the choice of 25 was rather arbitrary.
split : (L M R, V R) -> L L M R
++ split(aG, vector) returns a subalgebra \spad{A} of all
++ square matrix of dimension n as a list of list of matrices,
++ generated by the list of matrices aG, where n denotes both
++ the size of vector as well as the dimension of each of the
++ square matrices.
++ {\em V R} is an A-module in the natural way.
++ split(aG, vector) then checks whether the cyclic submodule
++ generated by {\em vector} is a proper submodule of {\em V R}.
++ If successful, it returns a two-element list, which contains
++ first the list of the representations of the submodule,
++ then the list of the representations of the factor module.
++ If the vector generates the whole module, a one-element list
++ of the old representation is given.
++ Note: a later version this should call the other split.
split: (L M R, V V R) -> L L M R
++ split(aG,submodule) uses a proper submodule of {\em R**n}
++ to create the representations of the submodule and of
++ the factor module.
if (R has Finite) and (R has Field) then
meatAxe : (L M R, B, I, I) -> L L M R
++ meatAxe(aG,randomElements,numberOfTries, maxTests) returns
++ a 2-list of representations as follows.
++ All matrices of argument aG are assumed to be square
++ and of equal size.
++ Then \spad{aG} generates a subalgebra, say \spad{A}, of the algebra
++ of all square matrices of dimension n. {\em V R} is an A-module
++ in the usual way.
++ meatAxe(aG,numberOfTries, maxTests) creates at most
++ {\em numberOfTries} random elements of the algebra, tests
++ them for singularity. If singular, it tries at most {\em maxTests}
++ elements of its kernel to generate a proper submodule.
++ If successful, a 2-list is returned: first, a list
++ containing first the list of the
++ representations of the submodule, then a list of the
++ representations of the factor module.
++ Otherwise, if we know that all the kernel is already
++ scanned, Norton's irreducibility test can be used either
++ to prove irreducibility or to find the splitting.
++ If {\em randomElements} is {\em false}, the first 6 tries
++ use Parker's fingerprints.
meatAxe : L M R -> L L M R
++ meatAxe(aG) calls {\em meatAxe(aG,false,25,7)} returns
++ a 2-list of representations as follows.
++ All matrices of argument \spad{aG} are assumed to be square
++ and of
++ equal size. Then \spad{aG} generates a subalgebra,
++ say \spad{A}, of the algebra
++ of all square matrices of dimension n. {\em V R} is an A-module
++ in the usual way.
++ meatAxe(aG) creates at most 25 random elements
++ of the algebra, tests
++ them for singularity. If singular, it tries at most 7
++ elements of its kernel to generate a proper submodule.
++ If successful a list which contains first the list of the
++ representations of the submodule, then a list of the
++ representations of the factor module is returned.
++ Otherwise, if we know that all the kernel is already
++ scanned, Norton's irreducibility test can be used either
++ to prove irreducibility or to find the splitting.
++ Notes: the first 6 tries use Parker's fingerprints.
++ Also, 7 covers the case of three-dimensional kernels over
++ the field with 2 elements.
meatAxe: (L M R, B) -> L L M R
++ meatAxe(aG, randomElements) calls {\em meatAxe(aG,false,6,7)},
++ only using Parker's fingerprints, if {\em randomElemnts} is false.
++ If it is true, it calls {\em meatAxe(aG,true,25,7)},
++ only using random elements.
++ Note: the choice of 25 was rather arbitrary.
++ Also, 7 covers the case of three-dimensional kernels over the field
++ with 2 elements.
meatAxe : (L M R, PI) -> L L M R
++ meatAxe(aG, numberOfTries) calls
++ {\em meatAxe(aG,true,numberOfTries,7)}.
++ Notes: 7 covers the case of three-dimensional
++ kernels over the field with 2 elements.
scanOneDimSubspaces: (L V R, I) -> V R
++ scanOneDimSubspaces(basis,n) gives a canonical representative
++ of the {\em n}-th one-dimensional subspace of the vector space
++ generated by the elements of {\em basis}, all from {\em R**n}.
++ The coefficients of the representative are of shape
++ {\em (0,...,0,1,*,...,*)}, {\em *} in R. If the size of R
++ is q, then there are {\em (q**n-1)/(q-1)} of them.
++ We first reduce n modulo this number, then find the
++ largest i such that {\em +/[q**i for i in 0..i-1] <= n}.
++ Subtracting this sum of powers from n results in an
++ i-digit number to basis q. This fills the positions of the
++ stars.
-- would prefer to have (V V R,.... but nullSpace results
-- in L V R
private ==> add
-- import of domain and packages
import OutputForm
-- declarations and definitions of local variables and
-- local function
blockMultiply: (M R, M R, L I, I) -> M R
-- blockMultiply(a,b,li,n) assumes that a has n columns
-- and b has n rows, li is a sublist of the rows of a and
-- a sublist of the columns of b. The result is the
-- multiplication of the (li x n) part of a with the
-- (n x li) part of b. We need this, because just matrix
-- multiplying the parts would require extra storage.
blockMultiply(a, b, li, n) ==
matrix([[ +/[a(i,s) * b(s,j) for s in 1..n ] _
for j in li ] for i in li])
fingerPrint: (NNI, M R, M R, M R) -> M R
-- is local, because one should know all the results for smaller i
fingerPrint (i : NNI, a : M R, b : M R, x :M R) ==
-- i > 2 only gives the correct result if the value of x from
-- the parameter list equals the result of fingerprint(i-1,...)
(i::PI) = 1 => x := a + b + a*b
(i::PI) = 2 => x := (x + a*b)*b
(i::PI) = 3 => x := a + b*x
(i::PI) = 4 => x := x + b
(i::PI) = 5 => x := x + a*b
(i::PI) = 6 => x := x - a + b*a
error "Sorry, but there are only 6 fingerprints!"
x
-- definition of exported functions
--randomWord(lli,lm) ==
-- -- we assume that all matrices are square of same size
-- numberOfMatrices := #lm
-- +/[*/[lm.(1+i rem numberOfMatrices) for i in li ] for li in lli]
completeEchelonBasis(basis) ==
dimensionOfSubmodule : NNI := #basis
n : NNI := # basis.1
indexOfVectorToBeScanned : NNI := 1
row : NNI := dimensionOfSubmodule
completedBasis : M R := zero(n, n)
for i in 1..dimensionOfSubmodule repeat
completedBasis := setRow_!(completedBasis, i, basis.i)
if #basis <= n then
newStart : NNI := 1
for j in 1..n
while indexOfVectorToBeScanned <= dimensionOfSubmodule repeat
if basis.indexOfVectorToBeScanned.j = 0 then
completedBasis(1+row,j) := 1 --put unit vector into basis
row := row + 1
else
indexOfVectorToBeScanned := indexOfVectorToBeScanned + 1
newStart : NNI := j + 1
for j in newStart..n repeat
completedBasis(j,j) := 1 --put unit vector into basis
completedBasis
createRandomElement(aG,algElt) ==
numberOfGenerators : NNI := #aG
-- randomIndex := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
algElt := algElt * aG.randomIndex
-- randomIndxElement := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
algElt + aG.randomIndex
if R has EuclideanDomain then
cyclicSubmodule (lm : L M R, v : V R) ==
basis : M R := rowEchelon matrix list entries v
-- normalizing the vector
-- all these elements lie in the submodule generated by v
furtherElts : L V R := [(lm.i*v)::V R for i in 1..maxIndex lm]
--furtherElts has elements of the generated submodule. It will
--will be checked whether they are in the span of the vectors
--computed so far. Of course we stop if we have got the whole
--space.
while (not null furtherElts) and (nrows basis < #v) repeat
w : V R := first furtherElts
nextVector : M R := matrix list entries w -- normalizing the vector
-- will the rank change if we add this nextVector
-- to the basis so far computed?
addedToBasis : M R := vertConcat(basis, nextVector)
if rank addedToBasis ~= nrows basis then
basis := rowEchelon addedToBasis -- add vector w to basis
updateFurtherElts : L V R := _
[(lm.i*w)::V R for i in 1..maxIndex lm]
furtherElts := append (rest furtherElts, updateFurtherElts)
else
-- the vector w lies in the span of matrix, no updating
-- of the basis
furtherElts := rest furtherElts
vector [row(basis, i) for i in 1..maxRowIndex basis]
standardBasisOfCyclicSubmodule (lm : L M R, v : V R) ==
dim : NNI := #v
standardBasis : L L R := list(entries v)
basis : M R := rowEchelon matrix list entries v
-- normalizing the vector
-- all these elements lie in the submodule generated by v
furtherElts : L V R := [(lm.i*v)::V R for i in 1..maxIndex lm]
--furtherElts has elements of the generated submodule. It will
--will be checked whether they are in the span of the vectors
--computed so far. Of course we stop if we have got the whole
--space.
while (not null furtherElts) and (nrows basis < #v) repeat
w : V R := first furtherElts
nextVector : M R := matrix list entries w -- normalizing the vector
-- will the rank change if we add this nextVector
-- to the basis so far computed?
addedToBasis : M R := vertConcat(basis, nextVector)
if rank addedToBasis ~= nrows basis then
standardBasis := cons(entries w, standardBasis)
basis := rowEchelon addedToBasis -- add vector w to basis
updateFurtherElts : L V R := _
[lm.i*w for i in 1..maxIndex lm]
furtherElts := append (rest furtherElts, updateFurtherElts)
else
-- the vector w lies in the span of matrix, therefore
-- no updating of matrix
furtherElts := rest furtherElts
transpose matrix standardBasis
if R has Field then -- only because of inverse in Matrix
-- as conditional local functions, *internal have to be here
splitInternal: (L M R, V R, B) -> L L M R
splitInternal(algebraGenerators : L M R, vector: V R,doSplitting? : B) ==
n : I := # vector -- R-rank of representation module =
-- degree of representation
submodule : V V R := cyclicSubmodule (algebraGenerators,vector)
rankOfSubmodule : I := # submodule -- R-Rank of submodule
submoduleRepresentation : L M R := nil()
factormoduleRepresentation : L M R := nil()
if n ~= rankOfSubmodule then
messagePrint " A proper cyclic submodule is found."
if doSplitting? then -- no else !!
submoduleIndices : L I := [i for i in 1..rankOfSubmodule]
factormoduleIndices : L I := [i for i in (1+rankOfSubmodule)..n]
transitionMatrix : M R := _
transpose completeEchelonBasis submodule
messagePrint " Transition matrix computed"
inverseTransitionMatrix : M R := _
autoCoerce(inverse transitionMatrix)$Union(M R,"failed")
messagePrint " The inverse of the transition matrix computed"
messagePrint " Now transform the matrices"
for i in 1..maxIndex algebraGenerators repeat
helpMatrix : M R := inverseTransitionMatrix * algebraGenerators.i
-- in order to not create extra space and regarding the fact
-- that we only want the two blocks in the main diagonal we
-- multiply with the aid of the local function blockMultiply
submoduleRepresentation := cons( blockMultiply( _
helpMatrix,transitionMatrix,submoduleIndices,n), _
submoduleRepresentation)
factormoduleRepresentation := cons( blockMultiply( _
helpMatrix,transitionMatrix,factormoduleIndices,n), _
factormoduleRepresentation)
[reverse submoduleRepresentation, reverse _
factormoduleRepresentation]
else -- represesentation is irreducible
messagePrint " The generated cyclic submodule was not proper"
[algebraGenerators]
irreducibilityTestInternal: (L M R, M R, B) -> L L M R
irreducibilityTestInternal(algebraGenerators,_
singularMatrix,split?) ==
algebraGeneratorsTranspose : L M R := [transpose _
algebraGenerators.j for j in 1..maxIndex algebraGenerators]
xt : M R := transpose singularMatrix
messagePrint " We know that all the cyclic submodules generated by all"
messagePrint " non-trivial element of the singular matrix under view are"
messagePrint " not proper, hence Norton's irreducibility test can be done:"
-- actually we only would need one (!) non-trivial element from
-- the kernel of xt, such an element must exist as the transpose
-- of a singular matrix is of course singular. Question: Can
-- we get it more easily from the kernel of x = singularMatrix?
kernel : L V R := nullSpace xt
result : L L M R := _
splitInternal(algebraGeneratorsTranspose,first kernel,split?)
if null rest result then -- this means first kernel generates
-- the whole module
if 1 = #kernel then
messagePrint " Representation is absolutely irreducible"
else
messagePrint " Representation is irreducible, but we don't know "
messagePrint " whether it is absolutely irreducible"
else
if split? then
messagePrint " Representation is not irreducible and it will be split:"
-- these are the dual representations, so calculate the
-- dual to get the desired result, i.e. "transpose inverse"
-- improvements??
for i in 1..maxIndex result repeat
for j in 1..maxIndex (result.i) repeat
mat : M R := result.i.j
result.i.j := _
transpose autoCoerce(inverse mat)$Union(M R,"failed")
else
messagePrint " Representation is not irreducible, use meatAxe to split"
-- if "split?" then dual representation interchange factor
-- and submodules, hence reverse
reverse result
-- exported functions for FiniteField-s.
areEquivalent? (aG0, aG1) ==
areEquivalent? (aG0, aG1, true, 25)
areEquivalent? (aG0, aG1, numberOfTries) ==
areEquivalent? (aG0, aG1, true, numberOfTries)
areEquivalent? (aG0, aG1, randomelements, numberOfTries) ==
result : B := false
transitionM : M R := zero(1, 1)
numberOfGenerators : NNI := #aG0
-- need a start value for creating random matrices:
-- if we switch to randomelements later, we take the last
-- fingerprint.
if randomelements then -- random should not be from I
--randomIndex : I := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
x0 : M R := aG0.randomIndex
x1 : M R := aG1.randomIndex
n : NNI := #row(x0,1) -- degree of representation
foundResult : B := false
for i in 1..numberOfTries until foundResult repeat
-- try to create a non-singular element of the algebra
-- generated by "aG". If only two generators,
-- i < 7 and not "randomelements" use Parker's fingerprints
-- i >= 7 create random elements recursively:
-- x_i+1 :=x_i * mr1 + mr2, where mr1 and mr2 are randomly
-- chosen elements form "aG".
if i = 7 then randomelements := true
if randomelements then
--randomIndex := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
x0 := x0 * aG0.randomIndex
x1 := x1 * aG1.randomIndex
--randomIndex := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
x0 := x0 + aG0.randomIndex
x1 := x1 + aG1.randomIndex
else
x0 := fingerPrint (i, aG0.0, aG0.1 ,x0)
x1 := fingerPrint (i, aG1.0, aG1.1 ,x1)
-- test singularity of x0 and x1
rk0 : NNI := rank x0
rk1 : NNI := rank x1
rk0 ~= rk1 =>
messagePrint "Dimensions of kernels differ"
foundResult := true
result := false
-- can assume dimensions are equal
rk0 ~= n - 1 =>
-- not of any use here if kernel not one-dimensional
if randomelements then
messagePrint "Random element in generated algebra does"
messagePrint " not have a one-dimensional kernel"
else
messagePrint "Fingerprint element in generated algebra does"
messagePrint " not have a one-dimensional kernel"
-- can assume dimensions are equal and equal to n-1
if randomelements then
messagePrint "Random element in generated algebra has"
messagePrint " one-dimensional kernel"
else
messagePrint "Fingerprint element in generated algebra has"
messagePrint " one-dimensional kernel"
kernel0 : L V R := nullSpace x0
kernel1 : L V R := nullSpace x1
baseChange0 : M R := standardBasisOfCyclicSubmodule(_
aG0,kernel0.1)
baseChange1 : M R := standardBasisOfCyclicSubmodule(_
aG1,kernel1.1)
(ncols baseChange0) ~= (ncols baseChange1) =>
messagePrint " Dimensions of generated cyclic submodules differ"
foundResult := true
result := false
-- can assume that dimensions of cyclic submodules are equal
(ncols baseChange0) = n => -- full dimension
transitionM := baseChange0 * _
autoCoerce(inverse baseChange1)$Union(M R,"failed")
foundResult := true
result := true
for j in 1..numberOfGenerators while result repeat
if (aG0.j*transitionM) ~= (transitionM*aG1.j) then
result := false
transitionM := zero(1 ,1)
messagePrint " There is no isomorphism, as the only possible one"
messagePrint " fails to do the necessary base change"
-- can assume that dimensions of cyclic submodules are not "n"
messagePrint " Generated cyclic submodules have equal, but not full"
messagePrint " dimension, hence we can not draw any conclusion"
-- here ends the for-loop
if not foundResult then
messagePrint " "
messagePrint "Can neither prove equivalence nor inequivalence."
messagePrint " Try again."
else
if result then
messagePrint " "
messagePrint "Representations are equivalent."
else
messagePrint " "
messagePrint "Representations are not equivalent."
transitionM
isAbsolutelyIrreducible?(aG) == isAbsolutelyIrreducible?(aG,25)
isAbsolutelyIrreducible?(aG, numberOfTries) ==
result : B := false
numberOfGenerators : NNI := #aG
-- need a start value for creating random matrices:
-- randomIndex : I := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
x : M R := aG.randomIndex
n : NNI := #row(x,1) -- degree of representation
foundResult : B := false
for i in 1..numberOfTries until foundResult repeat
-- try to create a non-singular element of the algebra
-- generated by "aG", dimension of its kernel being 1.
-- create random elements recursively:
-- x_i+1 :=x_i * mr1 + mr2, where mr1 and mr2 are randomly
-- chosen elements form "aG".
-- randomIndex := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
x := x * aG.randomIndex
--randomIndex := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
x := x + aG.randomIndex
-- test whether rank of x is n-1
rk : NNI := rank x
if rk = n - 1 then
foundResult := true
messagePrint "Random element in generated algebra has"
messagePrint " one-dimensional kernel"
kernel : L V R := nullSpace x
if n=#cyclicSubmodule(aG, first kernel) then
result := (irreducibilityTestInternal(aG,x,false)).1 ~= nil()$(L M R)
-- result := not null? first irreducibilityTestInternal(aG,x,false) -- this down't compile !!
else -- we found a proper submodule
result := false
--split(aG,kernel.1) -- to get the splitting
else -- not of any use here if kernel not one-dimensional
messagePrint "Random element in generated algebra does"
messagePrint " not have a one-dimensional kernel"
-- here ends the for-loop
if not foundResult then
messagePrint "We have not found a one-dimensional kernel so far,"
messagePrint " as we do a random search you could try again"
--else
-- if not result then
-- messagePrint "Representation is not irreducible."
-- else
-- messagePrint "Representation is irreducible."
result
split(algebraGenerators: L M R, vector: V R) ==
splitInternal(algebraGenerators, vector, true)
split(algebraGenerators : L M R, submodule: V V R) == --not zero submodule
n : NNI := #submodule.1 -- R-rank of representation module =
-- degree of representation
rankOfSubmodule : I := (#submodule) :: I --R-Rank of submodule
submoduleRepresentation : L M R := nil()
factormoduleRepresentation : L M R := nil()
submoduleIndices : L I := [i for i in 1..rankOfSubmodule]
factormoduleIndices : L I := [i for i in (1+rankOfSubmodule)..(n::I)]
transitionMatrix : M R := _
transpose completeEchelonBasis submodule
messagePrint " Transition matrix computed"
inverseTransitionMatrix : M R :=
autoCoerce(inverse transitionMatrix)$Union(M R,"failed")
messagePrint " The inverse of the transition matrix computed"
messagePrint " Now transform the matrices"
for i in 1..maxIndex algebraGenerators repeat
helpMatrix : M R := inverseTransitionMatrix * algebraGenerators.i
-- in order to not create extra space and regarding the fact
-- that we only want the two blocks in the main diagonal we
-- multiply with the aid of the local function blockMultiply
submoduleRepresentation := cons( blockMultiply( _
helpMatrix,transitionMatrix,submoduleIndices,n), _
submoduleRepresentation)
factormoduleRepresentation := cons( blockMultiply( _
helpMatrix,transitionMatrix,factormoduleIndices,n), _
factormoduleRepresentation)
cons(reverse submoduleRepresentation, list( reverse _
factormoduleRepresentation)::(L L M R))
-- the following is "under" "if R has Field", as there are compiler
-- problems with conditinally defined local functions, i.e. it
-- doesn't know, that "FiniteField" has "Field".
-- we are scanning through the vectorspaces
if (R has Finite) and (R has Field) then
meatAxe(algebraGenerators, randomelements, numberOfTries, _
maxTests) ==
numberOfGenerators : NNI := #algebraGenerators
result : L L M R := nil()$(L L M R)
q : PI := size()$R:PI
-- need a start value for creating random matrices:
-- if we switch to randomelements later, we take the last
-- fingerprint.
if randomelements then -- random should not be from I
--randomIndex : I := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
x : M R := algebraGenerators.randomIndex
foundResult : B := false
for i in 1..numberOfTries until foundResult repeat
-- try to create a non-singular element of the algebra
-- generated by "algebraGenerators". If only two generators,
-- i < 7 and not "randomelements" use Parker's fingerprints
-- i >= 7 create random elements recursively:
-- x_i+1 :=x_i * mr1 + mr2, where mr1 and mr2 are randomly
-- chosen elements form "algebraGenerators".
if i = 7 then randomelements := true
if randomelements then
--randomIndex := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
x := x * algebraGenerators.randomIndex
--randomIndex := randnum numberOfGenerators
randomIndex := 1+(random()$Integer rem numberOfGenerators)
x := x + algebraGenerators.randomIndex
else
x := fingerPrint (i, algebraGenerators.1,_
algebraGenerators.2 , x)
-- test singularity of x
n : NNI := #row(x, 1) -- degree of representation
if (rank x) ~= n then -- x singular
if randomelements then
messagePrint "Random element in generated algebra is singular"
else
messagePrint "Fingerprint element in generated algebra is singular"
kernel : L V R := nullSpace x
-- the first number is the maximal number of one dimensional
-- subspaces of the kernel, the second is a user given
-- constant
numberOfOneDimSubspacesInKernel : I := (q**(#kernel)-1)quo(q-1)
numberOfTests : I := _
min(numberOfOneDimSubspacesInKernel, maxTests)
for j in 1..numberOfTests repeat
--we create an element in the kernel, there is a good
--probability for it to generate a proper submodule, the
--called "split" does the further work:
result := _
split(algebraGenerators,scanOneDimSubspaces(kernel,j))
-- we had "not null rest result" directly in the following
-- if .. then, but the statment there foundResult := true
-- didn't work properly
foundResult := not null rest result
if foundResult then
leave -- inner for-loop
-- finish here with result
else -- no proper submodule
-- we were not successfull, i.e gen. submodule was
-- not proper, if the whole kernel is already scanned,
-- Norton's irreducibility test is used now.
if (j+1)>numberOfOneDimSubspacesInKernel then
-- we know that all the cyclic submodules generated
-- by all non-trivial elements of the kernel are proper.
foundResult := true
result : L L M R := irreducibilityTestInternal (_
algebraGenerators,x,true)
leave -- inner for-loop
-- here ends the inner for-loop
else -- x non-singular
if randomelements then
messagePrint "Random element in generated algebra is non-singular"
else
messagePrint "Fingerprint element in generated algebra is non-singular"
-- here ends the outer for-loop
if not foundResult then
result : L L M R := [nil()$(L M R), nil()$(L M R)]
messagePrint " "
messagePrint "Sorry, no result, try meatAxe(...,true)"
messagePrint " or consider using an extension field."
result
meatAxe (algebraGenerators) ==
meatAxe(algebraGenerators, false, 25, 7)
meatAxe (algebraGenerators: L M R, randomElements?: Boolean) ==
randomElements? => meatAxe (algebraGenerators, true, 25, 7)
meatAxe(algebraGenerators, false, 6, 7)
meatAxe (algebraGenerators:L M R, numberOfTries:PI) ==
meatAxe (algebraGenerators, true, numberOfTries, 7)
scanOneDimSubspaces(basis,n) ==
-- "dimension" of subspace generated by "basis"
dim : NNI := #basis
-- "dimension of the whole space:
nn : NNI := #(basis.1)
q : NNI := size()$R
-- number of all one-dimensional subspaces:
nred : I := n rem ((q**dim -1) quo (q-1))
pos : I := nred
i : I := 0
for i in 0..dim-1 while nred >= 0 repeat
pos := nred
nred := nred - (q**i)
i := if i = 0 then 0 else i-1
coefficients : V R := new(dim,0$R)
coefficients.(dim-i) := 1$R
iR : L I := wholeRagits(pos::RADIX q)
for j in 1..(maxIndex iR) repeat
coefficients.(dim-((#iR)::I) +j) := index((iR.j+(q::I))::PI)$R
result : V R := new(nn,0)
for i in 1..maxIndex coefficients repeat
newAdd : V R := coefficients.i * basis.i
for j in 1..nn repeat
result.j := result.j + newAdd.j
result
@
\section{License}
<<license>>=
--Copyright (c) 1991-2002, The Numerical ALgorithms Group Ltd.
--All rights reserved.
--
--Redistribution and use in source and binary forms, with or without
--modification, are permitted provided that the following conditions are
--met:
--
-- - Redistributions of source code must retain the above copyright
-- notice, this list of conditions and the following disclaimer.
--
-- - Redistributions in binary form must reproduce the above copyright
-- notice, this list of conditions and the following disclaimer in
-- the documentation and/or other materials provided with the
-- distribution.
--
-- - Neither the name of The Numerical ALgorithms Group Ltd. nor the
-- names of its contributors may be used to endorse or promote products
-- derived from this software without specific prior written permission.
--
--THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
--IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
--TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
--PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER
--OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
--EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
--PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
--PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
--LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
--NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
--SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
@
<<*>>=
<<license>>
<<package REP2 RepresentationPackage2>>
@
\eject
\begin{thebibliography}{99}
\bibitem{1} nothing
\end{thebibliography}
\end{document}
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