-------------------------------------------------------------------------
-- PURPOSE : Compute the rees algebra of a module as it is defined in the
-- paper "What is the Rees algebra of a module?" by Craig Huneke,
-- David Eisenbud and Bernde Ulrich.
-- Also to compute many of the structures that require a Rees
-- algebra, including
-- analyticSpread
-- specialFiber
-- idealIntegralClosure
-- distinguished -- distinguished subvarieties of a variety
-- (components of the support of the normal cone)
-- PROGRAMMERs : Rees algebra code written by David Eisenbud,
-- Amelia Taylor, Sorin Popescu, and students (see the JSAG description)
-- UPDATE HISTORY : created 27 October 2006
-- updated 29 June 2008
-- updated 19-21 July 2017 (Berkeley M2 Workgroup)
-- updated November 2017
--
---------------------------------------------------------------------------
newPackage(
"ReesAlgebra",
Version => "2.2",
Date => "November 2017",
Authors => {{
Name => "David Eisenbud",
Email => "de@msri.org"},
{Name => "Amelia Taylor",
HomePage => "http://faculty1.coloradocollege.edu/~ataylor/",
Email => "amelia.taylor@coloradocollege.edu"},
{Name => "Sorin Popescu",
Email => "sorin@math.sunysb.edu"},
{Name => "Michael E. Stillman", Email => "mike@math.cornell.edu"}},
DebuggingMode => false,
Reload =>true,
Headline => "Rees algebras"
)
-*
restart
uninstallPackage "ReesAlgebra"
restart
installPackage "ReesAlgebra"
viewHelp ReesAlgebra
check "ReesAlgebra"
*-
export{
"analyticSpread",
"distinguished",
"intersectInP",
"isLinearType",
"minimalReduction",
"isReduction",
"multiplicity",
"normalCone",
"reductionNumber",
"reesIdeal",
"reesAlgebra",
"specialFiberIdeal",
"specialFiber",
"symmetricKernel",
"versalEmbedding",
"whichGm",
"Tries",
"jacobianDual",
"Jacobian",
"symmetricAlgebraIdeal",
"expectedReesIdeal",
"PlaneCurveSingularities",
--synonyms
"associatedGradedRing" => "normalCone",
"reesAlgebraIdeal" => "reesIdeal"
}
symmetricAlgebraIdeal = method(Options =>
{ VariableBaseName => "w",
})
symmetricAlgebraIdeal Module := Ideal => o -> M -> (
ideal presentation symmetricAlgebra(M, o))
symmetricAlgebraIdeal Ideal := Ideal => o -> M -> (
ideal presentation symmetricAlgebra(module M, o))
symmetricKernel = method(Options=>{Variable => "w"})
symmetricKernel(Matrix) := Ideal => o -> (f) -> (
if rank source f == 0 then return trim ideal(0_(ring f));
w := o.Variable;
if instance(w,String) then w = getSymbol w;
S := symmetricAlgebra(source f, VariableBaseName => w);
T := symmetricAlgebra target f;
trim ker symmetricAlgebra(T,S,f))
versalEmbedding = method()
versalEmbedding(Ideal) :=
versalEmbedding(Module) := Matrix => (M) -> (
if (class M) === Ideal then M = module M;
UE := transpose syz transpose presentation M;
map(target UE, M, UE)
)
fixupw = w -> if instance(w,String) then getSymbol w else w
reesIdeal = method(
Options => {
Jacobian =>false,
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
Variable => "w"
}
)
--the following uses a versal embedding
reesIdeal(Module) := Ideal => o -> M -> (
P := presentation minimalPresentation M;
UE := transpose syz transpose P;
symmetricKernel(UE,Variable => fixupw o.Variable)
)
--in the case of ideals we don't need a versal embedding; any embedding in the ring will do.
reesIdeal(Ideal) := Ideal => o-> (J) -> (
symmetricKernel(mingens J, Variable => fixupw o.Variable)
)
-- the following method, usually faster,
-- needs a user-provided non-zerodivisor a such that M[a^{-1}] is of linear type.
reesIdeal(Module,RingElement) := Ideal => o-> (I,I0) ->(
I' := trim I;
K' := if o.Jacobian == true then expectedReesIdeal I' else(
K' = symmetricAlgebraIdeal I';
R := ring K';
IR := substitute(I0, R);
trim saturate(K',IR))
)
reesIdeal(Ideal, RingElement) := Ideal => o -> (I,a) -> (
reesIdeal(module trim I, a)
)
reesAlgebra = method (TypicalValue=>Ring,
Options => {Jacobian => false,
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
Variable => "w"
}
)
-- accepts a Module, Ideal, or pair (depending on the method) and
-- returns the quotient ring isomorphic to the Rees Algebra rather
-- than just the defining ideal as in reesIdeal.
reesAlgebra Ideal :=
reesAlgebra Module := o-> M -> quotient reesIdeal(M, o)
reesAlgebra(Ideal, RingElement) :=
reesAlgebra(Module, RingElement) := o->(M,a)-> quotient reesIdeal(M,a,o)
isLinearType=method(TypicalValue =>Boolean,
Options => {
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null--,
--Variable => "w"
}
)
isLinearType(Ideal):=
isLinearType(Module):= o-> N->(
if class N === Ideal then N = module N;
M := prune N;
I := reesIdeal (M,o);
S := ring I;
P := promote(presentation M, S);
J := ideal((vars S) * P);
((gens I) % J) == 0)
isLinearType(Ideal, RingElement):=
isLinearType(Module, RingElement):= o-> (N,a)->(
if class N === Ideal then N = module N;
M := prune N;
I := reesIdeal(M,a,o);
S := ring I;
P := promote(presentation M, S);
J := ideal((vars S) * P);
((gens I) % J) == 0)
normalCone = method(TypicalValue => Ring,
Options => {
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
Variable => "w"
}
)
normalCone(Ideal) := o -> I -> (
RI := reesAlgebra(I,o);
RI/promote(I,RI)
)
normalCone(Ideal, RingElement) := o -> (I,a) -> (
RI := reesAlgebra(I,a,o);
RI/promote(I,RI)
)
multiplicity = method(
Options => {
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
Variable => "w"
}
)
multiplicity(Ideal) := ZZ => o -> I -> (
RI := normalCone (I,o);
J := ideal RI;
J1 := first flattenRing J;
S1 := newRing(ring J1, Degrees=>{numgens ring J1 : 1});
degree substitute(J1,S1)
)
multiplicity(Ideal,RingElement) := ZZ => o -> (I,a) -> (
RI := normalCone (I,a,o);
J := ideal RI;
J1 := first flattenRing J;
S1 := newRing(ring J1, Degrees=>{numgens ring J1 : 1});
degree substitute(J1,S1)
)
isEquigenerated = A -> (
if isHomogeneous A and
all(A_*, a->degree a == degree(A_*_0)) then true else false)
specialFiberIdeal=method(TypicalValue=>Ideal,
Options => {
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
Variable => "w",
Jacobian =>false
}
)
specialFiberIdeal(Ideal):= o-> I ->(
if isEquigenerated I then(
kk := ultimate(coefficientRing, ring I);
Z := symbol Z;
ker map(ring I, kk[Z_0..Z_(numgens I -1)], gens I)) else
specialFiberIdeal (module I, o))
specialFiberIdeal(Module):= o->i->(
Reesi:= reesIdeal(i, o);
S := ring Reesi;
kk := ultimate(coefficientRing, S);
T := kk[gens S];
minimalpres := map(T,S);
trim minimalpres Reesi
)
specialFiberIdeal(Ideal, RingElement):= o->(i,i0) ->(
if isEquigenerated i then return(
kk := ultimate(coefficientRing, ring i);
w := symbol w;
ker map(ring i, kk[w_0..w_(numgens i -1)], gens i));
specialFiberIdeal(module i, i0))
specialFiberIdeal(Module,RingElement):= o->(i,a)->(
Reesi:= reesIdeal(i, o);
S := ring Reesi;
kk := ultimate(coefficientRing, S);
T := kk[gens S];
minimalpres := map(T,S);
trim minimalpres Reesi
)
--The following returns a ring with just the new vars.
--The order of the generators is supposed to be the same as the order
--of the given generators of I.
specialFiber=method(TypicalValue=>Ring,
Options => {
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
Variable => "w",
Jacobian => false
}
)
specialFiber(Ideal):=
specialFiber(Module):= o->i->(
spIdeal := specialFiberIdeal(i,o);
(ring spIdeal)/spIdeal
)
specialFiber(Ideal, RingElement):=
specialFiber(Module, RingElement):= o->(i,a)->(
spIdeal := specialFiberIdeal(i,a,o);
(ring spIdeal)/spIdeal
)
isReduction=method(TypicalValue=>Boolean,
Options => {
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
Variable => "w"
}
)
--test whether the SECOND arg is a reduction of the FIRST arg
isReduction(Module,Module):=
isReduction(Ideal,Ideal):= o->(I,J)->(
if isSubset(J, I) then (
I' := trim I;
Sfib:= specialFiber(I', o);
Ifib:=ideal presentation Sfib;
kk := coefficientRing Sfib;
M := sub(gens J // gens I', kk);
M = promote(M, Sfib);
L :=(vars Sfib)*M;
0===dim ideal L)
else false)
isReduction(Module,Module,RingElement):=
isReduction(Ideal,Ideal,RingElement):= o->(I,J,a)->(
if isSubset(J, I) then (
Sfib :=specialFiber(I, a, o);
Ifib:= ideal presentation Sfib;
kk := coefficientRing Sfib;
M := sub(gens J // gens I, kk);
M = promote(M, Sfib);
L :=(vars Sfib)*M;
0===dim ideal L)
else false)
analyticSpread = method(
Options => {
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null--,
--Variable => "w"
}
)
analyticSpread(Ideal) :=
analyticSpread(Module) := ZZ => o->(M) -> dim specialFiberIdeal(M,o)
analyticSpread(Ideal,RingElement) :=
analyticSpread(Module,RingElement) := ZZ => o->(M,a) -> dim specialFiberIdeal(M,a,o)
distinguished = method(Options => {
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
Variable => "w"
}
)
distinguished(RingMap, Ideal) := o -> (f,I) ->(
--f: S -> R, I\subset S, J\subset R, f(I)\subset J:
S := source f;
R := target f;
NI := normalCone (I,o);
NJ := normalCone(f I,o);
K := ker map(NJ,NI,(vars NJ));
L := decompose K;
M := apply(L,P->(Pcomponent := K:(saturate(K,P))));
--the P-primary component. The multiplicity is
--computed as (degree M_i)/(degree L_i)
prune NI;
mp := NI.minimalPresentationMap;
apply(#L, i -> {(degree mp(M_i))/(degree mp(L_i)),kernel(map(NI/L_i, S/I))})
)
distinguished(Ideal,Ideal) := o -> (I,J) -> (
--I,J ideals in the same ring S
S := ring I;
f := map(S/J,S);
distinguished(f,I)
)
distinguished(Ideal) := o -> I -> (
S := ring I;
f := map(S,S);
distinguished(f,I)
)
intersectInP = method(Options=>{
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
Variable => "w"
})
intersectInP(Ideal,Ideal) := o->(I,J) ->(
--I,J in a polynomial ring; intersection done with the diagonal, then pulled back
P := ring I;
kk := coefficientRing P;
n := numgens P;
if P =!=ring J then error"requires two ideals in the same ring";
if not isPolynomialRing P and isField kk then
error" ring should be a polynomial ring over a field";
X:=symbol X;
Y:=symbol Y;
PP := kk[X_0..X_(n-1),Y_0..Y_(n-1)];
diag := ideal apply(n, i-> X_i-Y_i);
toP := map(P,PP/diag,vars P | vars P);
inX := map(PP,P,apply(n,i->X_i));
inY := map(PP,P,apply(n,i->Y_i));
II := inX I + inY J;
L := distinguished(diag,II);
apply(L, l-> {l_0, trim toP l_1})
)
rand = method()
rand(Ideal, ZZ, ZZ) := (I,s,d) ->
--s elements of degree d chosen at random from I
ideal ((gens I)*random(source gens I, (ring I)^{s:-d}))
rand(Ideal, ZZ) := (I,s) ->(
--without the third argument d, the function takes
--random linear combinations of the generators, without
--regard for the degrees, thus sometimes inhomogeneous.
kk := ultimate(coefficientRing, ring I);
choose1 := I -> sum(I_*, i-> random(kk)*i);
ideal apply(s, i-> choose1 I))
rand(Module, ZZ) := (M,s) ->(
--random linear combinations of the generators, without
--regard for the degrees, thus sometimes inhomogeneous.
kk := ultimate(coefficientRing, ring M);
choose1 := M -> sum(M_*, i-> random(kk)*i);
map(M,(ring M)^s, matrix apply(s, i-> choose1 M))
)
minimalReduction = method(
Options => {
DegreeLimit => {},
BasisElementLimit => infinity,
PairLimit => infinity,
MinimalGenerators => true,
Strategy => null,
--Variable => "w",
Tries => 20
}
)
minimalReduction Ideal := Ideal => o -> i -> (
S:=ring i;
ell := analyticSpread(i,
DegreeLimit => o.DegreeLimit,
BasisElementLimit => o.BasisElementLimit,
PairLimit => o.PairLimit,
MinimalGenerators => true,
Strategy => o.Strategy
); -- the list is necessary because isReduction doesn't know about "Tries"
J:=null;
for b from 1 to o.Tries do(
J = rand(i, ell);
if isReduction(i,J,
DegreeLimit => o.DegreeLimit,
BasisElementLimit => o.BasisElementLimit,
PairLimit => o.PairLimit,
MinimalGenerators => true,
Strategy => o.Strategy
)
then return J);
< (
rN:=0;
I := (gens i)%j; -- will be a power of i
if isHomogeneous j then (
while I!=0 do (
j = trim(i*j);
I = (gens trim (i*ideal I))%j;
rN =rN+1))
else(
M:= ideal vars ring i; -- we're pretending to be in a local ring
while I!=0 do (
j = trim(i*j+M*ideal I);
I = (gens trim (i*ideal I))%j;
rN =rN+1));
rN)
whichGm = method()
whichGm Ideal := i -> (
--This *probabilistic* procedure returns the largest number m for which the ideal i satsifies
--the condition
--
--G_m: i_P is generated by <= codim P elements for all P with codim P < m.
--
f:=presentation module i;
S:=ring f;
if f==0 then "infinity" else(
q:=rank target f;
maxSource := (max degrees source f)_0;
minTarget := (min degrees target f)_0;
randomMinor := (f,t)->(
if t<=0 then ideal(1_S) else
if t >min(rank source f, rank target f) then ideal(0_S) else
ideal det (random(S^{t:-minTarget},target f)*f*random(source f, S^{t:-maxSource})));
d:=dim ring i;
m:=codim i;
j:=i+randomMinor(f,q-m);
while m m do (
m=m+1;
j=j+randomMinor(f, q-m));
if m<=d then m else "infinity"))
------------------------------------------------------------------
jacobianDual = method(Options=>{Variable => "w"})
jacobianDual Matrix := o-> phi ->(
S := ring phi;
X := vars S;
ST := symmetricAlgebra(target phi, VariableBaseName => fixupw o.Variable);
(vars ST * promote(phi, ST))//promote(X,ST)
)
jacobianDual(Matrix,Matrix, Matrix) := o -> (phi,X,T) -> (
--Suppose that T is a 1 x m matrix of variables in the ring ST = R[T_0..T_(m-1)],
--and phi is a matrix over ST that is defined over the subring R.
--Suppose also that X is a 1 x n matrix defined over ST whose
--entries generate ideal containing the entries of the matrix phi.
--the routine returns a matrix psi over ST such that
--T phi = X psi.
--Thus psi is a Jacobian dual of phi with respect to X.
if numcols T != numrows phi then error"if phi has m rows then T must have m cols.";
psi := (T * phi)//X;
--check that this worked:
if not T*phi == X*psi then error"requires
ideal flatten entries matrix phi subset ideal flatten entries X";
psi
)
expectedReesIdeal = method()
expectedReesIdeal Ideal := I -> expectedReesIdeal module I
expectedReesIdeal Module := Ideal => I -> (
S := ring I;
I1 := symmetricAlgebraIdeal I;
S1 := ring I1;
if numgens I < numgens S then return I1;
X := promote(vars ring I, S1);
jImat := jacobianDual (presentation I, X, vars S1);
I2 := minors(numrows jImat,jImat);
trim(I1+I2)
)
beginDocumentation()
///
restart
uninstallPackage "ReesAlgebra"
restart
installPackage "ReesAlgebra"
viewHelp ReesAlgebra
check "ReesAlgebra"
///
doc ///
Key
ReesAlgebra
Headline
Compute Rees algebras and their invariants
Description
Text
The Rees Algebra of an ideal is the
commutative algebra analogue of the blow up in algebraic
geometry. (In fact, the ``Rees Algebra''
is sometimes called the ``blowup algebra''.)
A great deal of modern
commutative algebra is devoted to studying them.
Classically the Rees algebra appeared as the bihomogeneous coordinate
ring of the blowup of a projective variety along a subvariety or
subscheme, used for resolution of singularities.
Though this is computationally slow on interesting examples,
we illustrate with some elementary cases of resolution of plane curve
singularities in @TO PlaneCurveSingularities@.
The Rees algebra was
studied in the commutative algebra context (in the case where M is an ideal of a ring R),
by David Rees in
a famous paper,
{\em On a problem of Zariski}, Illinois J. Math. (1958) 145-149).
In fact,
Rees mainly studied the ring
$R[It,t^{-1}]$, now also called the `extended Rees
Algebra' of I.
The original goal of this package, first written around 2002,
was to compute the Rees
algebra of a module as it is defined in the paper {\em What is the
Rees algebra of a module?}, by Craig Huneke, David Eisenbud and Bernd
Ulrich, Proc. Am. Math. Soc. 131, 701-708, 2002.
It has since expanded to include routines
for computing many of the invariants of an ideal or module
defined in terms of Rees algebras.
The Rees algebra, or more precisely the associated graded ring, which
we compute as a biproduct, plays a central role in modern intersection
theory: it is the basis of the Fulton-MacPherson definition of the
intersection product in the Chow ring. We illustrate this in
@TO distinguished@ and @TO intersectInP@.
The Rees algebra of a module M is defined
by a certain ideal in the symmetric
algebra $Sym(M)$ of $M$, or, as in this package,
by an ideal in the symmetric algebra of any
free module $F$ that maps onto $M$.
When $\phi: M \to G$ is the {\em versal embedding}
of $M$, then, by the definition of Huneke-Eisenbud-Ulrich,
the {\em Rees ideal of M} is the kernel of $Sym(\phi)$. Thus the
Rees Algebra of M is the image of $Sym(\phi)$.
In most cases the kernel of the
$Sym(\phi)$ is the same for any embedding $\phi$ of
$M$ into a free module:
{\bf Theorem (Eisenbud-Huneke-Ulrich, Thms 0.2 and 1.4):} Let R be a Noetherian ring
and let $M$ be a finitely generated R-module. Let $\phi: M \to G$
be a versal map of $M$ to a free module. Assume that $\phi$ is an inclusion, and let
$\psi: M \to G'$ be any inclusion. If $R$ is torsion-free over $\ZZ$
or $R$ is unmixed and generically Gorenstein, or $M$ is free locally
at each associated prime of $R$, or $G=R$, then the kernel of $Sym(\phi)$ and the
kernel of $Sym(\psi)$ are equal.
It follows that in the good cases above the Rees
ideal is equal to the saturation
of the defining ideal of symmetric
algebra of $M$ with respect to any
element f of the ground ring such
that $M[f^{-1}]$ is free, or is simply {\em of linear type},
meaning that $Sym(\phi)$ is a monomorphism. This is the case,
for example, when M is an ideal and $M[f^{-1}]$ is generated
by a regular sequence.
This fact often leads to
a faster computation than computing the
kernel of $Sym(\phi)$ directly.
Here is an example of the pathological case of
inclusions $\phi: M \to G$ and $\psi: M \to G'$ where $ker(\phi) \neq ker(\psi)$.
In the following, any finite characteristic would work as well.
Example
p = 5;
R = ZZ/p[x,y,z]/(ideal(x^p,y^p)+(ideal(x,y,z))^(p+1));
M = module ideal(z);
Text
It is easy to check that M \cong R^1/(x,y,z)^p.
We write iota: M\to R^1 for the embedding as an ideal
and psi for the embedding M \to R^2 sending z to (x,y).
Example
iota = map(R^1,M,matrix{{z}});
psi = map(R^2,M,matrix{{x},{y}});
Text
Finally, a versal embedding is M \to R^3,
sending z to (x,y,z):
Example
phi = versalEmbedding(M);
Text
We now compute the kernels of the three maps
on symmetric algebras:
Example
Iiota = symmetricKernel iota;
Ipsi = symmetricKernel psi;
Iphi = symmetricKernel phi;
Text
and check that the ones corresponding to phi and iota
are equal, whereas the ones corresponding to psi and phi
are not:
Example
Iiota == Iphi
Ipsi == Iphi
Text
In fact, they differ in degree p:
Example
numcols basis(p,Iphi)
numcols basis(p,Ipsi)
SeeAlso
PlaneCurveSingularities
distinguished
intersectInP
///
doc ///
Key
symmetricAlgebraIdeal
(symmetricAlgebraIdeal,Ideal)
(symmetricAlgebraIdeal,Module)
[symmetricAlgebraIdeal,VariableBaseName]
Headline
Ideal of the symmetric algebra of an ideal or module
Usage
I = symmetricAlgebraIdeal J
Inputs
I:Ideal
I: Module
Outputs
J:Ideal
Description
Text
Uses the built-in function @TO symmetricAlgebra@. The function returns J an ideal in a
new ring, with generators corresponding to those of th eideal or module I. The name
of the new generators may be set, for example to T, with the form
symmetricAlgebraIdeal(J, VariableBaseName =>"T")
SeeAlso
reesIdeal
///
{*
viewHelp symmetricAlgebra
*}
doc ///
Key
symmetricKernel
(symmetricKernel,Matrix)
Headline
Compute the Rees ring of the image of a matrix
Usage
I = symmetricKernel f
Inputs
f:Matrix
Outputs
:Ideal
the defining ideal of the image of $Sym(f)$
Description
Text
Given a map between free modules $f: F \to G$ this function computes the
kernel of the induced map of symmetric algebras, $Sym(f): Sym(F) \to
Sym(G)$ as an ideal in $Sym(F)$. When $f$ defines a versal embedding
of $Im f$ then by the definition
of Huneke-Eisenbud-Ulrich) this is equal to the defining ideal of the Rees
algebra of the module Im f, the Rees ideal of M.
When $M$ is an ideal (and in general in characteristic 0) then, by a
theorem of Eisenbud-Huneke-Ulrich,
any embedding of M into a free module may be used,
and it follows that the Rees ideal is equal to the saturation
of the defining ideal of symmetric algebra of M with respect to any
element f of the ground ring such that M[f^{-1}] is free. And this
often gives a faster computation.
Most users will prefer to use one of the front
end commands @TO reesAlgebra@, @TO reesIdeal@ to compute the ideal.
Example
R = QQ[a..e]
J = monomialCurveIdeal(R, {1,2,3})
symmetricKernel (gens J)
Text
Let I be the ideal returned and let S be the ring it lives in
(also printed). The ring S/I is isomorphic to
the Rees algebra R[Jt]. We can get the same information
above using {\tt reesIdeal(J)}, see @TO reesIdeal@. Note that the degree length
of S is one more than the degree length of R; the old variables
now have first degree 0, while the new variables have first degree 1.
Example
S = ring oo;
(monoid S).Options.Degrees
Text
The function {\tt symmetricKernel} can also be computed over a quotient ring.
Example
R = QQ[x,y,z]/ideal(x*y^2-z^9)
J = ideal(x,y,z)
symmetricKernel(gens J)
Text
The many ways of working with this function allows the system
to compute both the classic Rees algebra of an ideal over a ring
(polynomial or quotient) and to compute the the Rees algebra of a
module or ideal using a versal embedding as described in the paper
of Eisenbud, Huneke and Ulrich. It also allows different ways of
setting up the quotient ring.
SeeAlso
reesIdeal
reesAlgebra
versalEmbedding
///
doc ///
Key
Jacobian
[reesAlgebra, Jacobian]
Headline
Choose whether to use the Jacobian dual in the computation
Usage
reesIdeal(..., Jacobian => true)
SeeAlso
reesIdeal
reesAlgebra
specialFiberIdeal
specialFiber
expectedReesIdeal
///
///
Description
Text
When searching for a minimal reduction of an ideal over a field with
a small number of elements, random choices of generators are often
not good enough. This option controls how many times the routine
will try new random choices before giving up and reporting an error.
Example
setRandomSeed(314159268)
kk=ZZ/2
S = kk[a,b,c,d];
I = monomialCurveIdeal(S, {1,3,4});
minimalReduction(I, Tries=>30);
///
doc ///
Key
[minimalReduction, Tries]
Tries
Headline
Set the number of random tries to compute a minimal reduction
Usage
minimalReduction(..., Tries => 20)
Description
Text
When searching for a minimal reduction of an ideal over a field with
a small number of elements, random choices of generators are often
not good enough. This option controls how many times the routine
will try new random choices before giving up and reporting an error.
Example
setRandomSeed(314159268)
kk=ZZ/2
S = kk[a,b,c,d];
I = monomialCurveIdeal(S, {1,3,4});
minimalReduction(I, Tries=>30);
///
doc ///
Key
versalEmbedding
(versalEmbedding,Ideal)
(versalEmbedding,Module)
Headline
Compute a versal embedding
Usage
u = versalEmbedding M
Inputs
M:Module
or @ofClass Ideal@
Outputs
u:Matrix
a matrix that induces a versal embedding of the R-module M
into a free R-module.
Description
Text
For any module M over a Noetherian ring R there is a map $u: M \to H$
that is versal for maps from M to free modules; that is,
such that any map from M to a free module factors through u. Such a map
may be constructed by choosing a set of s generators for Hom(M,R), and using
them as the components of a map $u: M \to H := R^s$.
(NOTE: In the paper of Eisenbud, Huneke and Ulrich
cited below, the versal map is described with the
term ``universal'', which is misleading, since the induced map
from H is generally not unique.)
Suppose that $M$ has a free presentation $F \to G$, and let $u1$ be the
map $u1: G\to H$ induced by composing $u$ with the surjection $p: G \to
M$. By definition, the Rees algebra of $M$ is the image of the induced
map $Sym(u1): Sym(G)\to Sym(H)$, and thus can be computed with
symmetricKernel(u1). The map u is computed from the dual of the first
syzygy map of the dual of the presentation of $M$.
We first give a simple example looking at the syzygy matrix of the cube of
the maximial ideal of a polynomial ring.
Example
S = ZZ/101[x,y,z];
FF=res ((ideal vars S)^3);
M=coker (FF.dd_2)
versalEmbedding M
Text
A more complicated example.
Example
x = symbol x;
R=QQ[x_1..x_8];
m1=genericMatrix(R,x_1,2,2); m2=genericMatrix(R,x_5,2,2);
m=m1*m2
d1=minors(2,m1); d2=minors(2,m2);
M=matrix{{0,d1_0,m_(0,0),m_(0,1)}, {0,0,m_(1,0),m_(1,1)}, {0,0,0,d2_0}, {0,0,0,0}}
M=M-(transpose M);
N= coker(res coker transpose M).dd_2
versalEmbedding(N)
Text
Here is an example from the paper "What is the Rees Algebra of a
Module" by David Eisenbud, Craig Huneke and Bernd Ulrich,
Proc. Am. Math. Soc. 131, 701-708, 2002. The example shows that one
cannot, in general, define the Rees algebra of a module by using *any*
embedding of that module, even when the module is isomorphic to an ideal;
this is the reason for using the map provided by the routine
versalEmbedding. Note that the same paper shows that such problems do
not arise when the ring is torsion-free as a ZZ-module, or when one takes
the natural embedding of the ideal into the ring.
Example
p = 3;
S = ZZ/p[x,y,z];
R = S/((ideal(x^p,y^p))+(ideal(x,y,z))^(p+1))
I = module ideal(z)
Text
As a module (or ideal), $Hom(I,R^1)$ is minimally generated by 3 elements,
and thus a versal embedding of $I$ into a free module is into $R^3$.
Example
betti Hom(I,R^1)
ui = versalEmbedding I
Text
it is injective:
Example
kernel ui
Text
It is easy to make two other embeddings of $I$ into free modules. One is
the natural inclusion of $I$ into $R$ as an ideal:
Example
inci = map(R^1,I,matrix{{z}})
kernel inci
Text
Another is the map defined by multiplication by x and y.
Example
gi = map(R^2, I, matrix{{x},{y}})
kernel gi
Text
We can compose $ui, inci$ and $gi$ with a surjection $R\to i$ to get maps
$u:R^1 \to R^3, inc: R^1 \to R^1$ and $g:R^1 \to R^2$ having image $i$.
Example
u= map(R^3,R^{-1},ui)
inc=map(R^1, R^{-1}, matrix{{z}})
g=map(R^2, R^{-1}, matrix{{x},{y}})
Text
We now form the symmetric kernels of these maps and compare them. Note
that since symmetricKernel defines a new ring, we must bring them to the
same ring to make the comparison. First the map u, which would be used
by reesIdeal:
Example
A=symmetricKernel u
Text
Next the inclusion:
Example
B1=symmetricKernel inc
B=(map(ring A, ring B1)) B1
Text
Finallly, the map g1:
Example
C1 = symmetricKernel g
C=(map(ring A, ring C1)) C1
Text
The following test yields ``true'', as implied by the theorem of
Eisenbud, Huneke and Ulrich.
Example
A==B
Text
But the following yields ``false'', showing that one must take care
in general, which inclusion one uses.
Example
A==C
SeeAlso
reesIdeal
reesAlgebra
symmetricKernel
///
doc ///
Key
reesIdeal
(reesIdeal,Ideal)
(reesIdeal, Module)
(reesIdeal,Ideal, RingElement)
(reesIdeal,Module, RingElement)
[reesIdeal,Jacobian]
Headline
Compute the defining ideal of the Rees Algebra
Usage
reesIdeal M
reesIdeal(M,f)
Inputs
M:Module
or @ofClass Ideal@ of a quotient polynomial ring $R$
f:RingElement
any non-zerodivisor in ideal or the first Fitting ideal of the module. Optional
Outputs
:Ideal
defining the Rees algebra of M
Description
Text
This routine gives the user a choice between two methods for finding the
defining ideal of the Rees algebra of an ideal or module $M$ over a ring
$R$: The command {\tt reesIdeal(M)}
computes a versal embedding $g: M\to G$ and a surjection $f: F\to M$
and returns the result of symmetricKernel(gf).
When M is an ideal (the usual case) or in characteristic 0, the same
ideal can be computed by an alternate method that is often faster.
If the
user knows a non-zerodivisor $a\in{} R$ such that $M[a^{-1}$ is a free
module (for example, when M is an ideal, any non-zerodivisor $a \in{} M$
then it is often much faster to compute
{\tt reesIdeal(M,a)}
which computes the saturation of the defining ideal of the symmetric algebra
of M with respect to a. This
gives the correct answer even under the slightly weaker hypothesis that
$M[a^{-1}]$ is {\em of linear type}. (See also @TO isLinearType@.)
Example
kk = ZZ/101;
S=kk[x_0..x_4];
i= trim monomialCurveIdeal(S,{2,3,5,6})
time V1 = reesIdeal i;
time V2 = reesIdeal(i,i_0);
Text
The following example shows how we handle degrees
Example
S=kk[a,b,c]
m=matrix{{a,0},{b,a},{0,b}}
i=minors(2,m)
time I1 = reesIdeal i;
time I2 = reesIdeal(i,i_0);
transpose gens I1
transpose gens I2
Text
{\bf Investigating plane curve singularities:}
Proj of the Rees algebra of I \subset{} R
is the blowup of I in spec R. Thus the Rees algebra is a basic construction in
resolution of singularities. Here we work out a simple case:
Example
R = ZZ/32003[x,y]
I = ideal(x,y)
cusp = ideal(x^2-y^3)
RI = reesIdeal(I)
S = ring RI
totalTransform = substitute(cusp, S) + RI
D = decompose totalTransform -- the components are the strict transform of the cuspidal curve and the exceptional curve
totalTransform = first flattenRing totalTransform
L = primaryDecomposition totalTransform
apply(L, i -> (degree i)/(degree radical i))
Text
The total transform of the cusp contains the exceptional divisor with
multiplicity two. The strict transform of the cusp is a smooth curve but
is tangent to the exceptional divisor
Example
use ring L_0
singular = ideal(singularLocus(L_0));
SL = saturate(singular, ideal(x,y));
saturate(SL, ideal(w_0,w_1))
Text
This shows that the strict transform is smooth.
SeeAlso
symmetricKernel
reesAlgebra
///
doc ///
Key
reesAlgebra
(reesAlgebra,Ideal)
(reesAlgebra, Module)
(reesAlgebra,Ideal, RingElement)
(reesAlgebra,Module, RingElement)
Headline
Compute the defining ideal of the Rees Algebra
Usage
reesAlgebra M
reesAlgebra(M,f)
Inputs
M:Module
or @ofClass Ideal@ of a quotient polynomial ring $R$
f:RingElement
any non-zerodivisor in ideal or the first Fitting ideal of the module. Optional
Outputs
:Ring
defining the Rees algebra of M
Description
Text
If $M$ is an ideal or module over a ring $R$, and $F\to M$ is a
surjection from a free module, then reesAlgebra(M) returns the ring
$Sym(F)/J$, where $J = reesIdeal(M)$.
In the following example, we find the Rees Algebra of a monomial curve
singularity. We also demonstrate the use of @TO reesIdeal@, @TO symmetricKernel@,
@TO isLinearType@, @TO normalCone@, @TO associatedGradedRing@, @TO specialFiberIdeal@.
Example
S = QQ[x_0..x_3]
i = monomialCurveIdeal(S,{3,7,8})
I = reesIdeal i;
reesIdeal(i, Variable=>v)
I=reesIdeal(i,i_0);
(J=symmetricKernel gens i);
isLinearType(i,i_0)
isLinearType i
reesAlgebra (i,i_0)
trim ideal normalCone (i, i_0)
trim ideal associatedGradedRing (i,i_0)
trim specialFiberIdeal (i,i_0)
SeeAlso
reesIdeal
symmetricKernel
///
doc ///
Key
isLinearType
(isLinearType, Module)
(isLinearType, Ideal)
(isLinearType,Module, RingElement)
(isLinearType, Ideal, RingElement)
Headline
Determine whether module has linear type
Usage
isLinearType M
isLinearType(M,f)
Inputs
M:Module
or @ofClass Ideal@
f:RingElement
any non-zero divisor modulo the ideal or module. Optional
Outputs
:Boolean
true if M is of linear type, false otherwise
Description
Text
A module or ideal $M$ is said to be ``of linear type'' if the natural map
from the symmetric algebra of $M$ to the Rees algebra of $M$ is an
isomorphism. It is known, for example, that any complete intersection
ideal is of linear type.
This routine computes the @TO reesIdeal@ of M. Giving the element f
computes the @TO reesIdeal@ in a different manner, which is sometimes
faster, sometimes slower.
Example
S = QQ[x_0..x_4]
i = monomialCurveIdeal(S,{2,3,5,6})
isLinearType i
isLinearType(i, i_0)
I = reesIdeal i
select(I_*, f -> first degree f > 1)
Example
S = ZZ/101[x,y,z]
for p from 1 to 5 do print isLinearType (ideal vars S)^p
SeeAlso
reesIdeal
monomialCurveIdeal
///
doc ///
Key
isReduction
(isReduction, Ideal, Ideal)
(isReduction, Ideal, Ideal, RingElement)
(isReduction, Module, Module)
(isReduction, Module, Module, RingElement)
Headline
Determine whether an ideal is a reduction
Usage
t=isReduction(I,J)
t=isReduction(I,J,f)
Inputs
I:Ideal
J:Ideal
f:RingElement
an optional element, which is a non-zerodivisor modulo M and the ring of M
Outputs
t:Boolean
true if J is a reduction of I, false otherwise
Description
Text
For an ideal $I$, a subideal $J$ of $I$ is said to be a {\bf reduction}
of $I$ if there exists a nonnegative integer n such that
$JI^{n}=I^{n+1}$.
This function returns true if $J$ is a reduction of $I$ and returns false
if $J$ is not a subideal of $I$ or $J$ is a subideal but not a reduction of $I$.
Example
S = ZZ/5[x,y]
I = ideal(x^3,x*y,y^4)
J = ideal(x*y, x^3+y^4)
isReduction(I,J)
isReduction(J,I)
isReduction(I,I)
g = I_0
isReduction(I,J,g)
isReduction(J,I,g)
isReduction(I,I,g)
SeeAlso
minimalReduction
reductionNumber
///
doc ///
Key
normalCone
(normalCone, Ideal)
(normalCone, Ideal, RingElement)
Headline
The normal cone of a subscheme
Usage
normalCone I
normalCone(I,f)
Inputs
I:Ideal
f:RingElement
optional argument, if given it should be a non-zero divisor in the ideal I
Outputs
:Ring
the ring $R[It] \otimes{} R/I$ of the normal cone of $I$
Description
Text
The normal cone of an ideal $I\subset{} R$ is the ring $R/I \oplus{} I/I^2
\oplus \ldots$, also called the associated graded ring of $R$ with
respect to $I$. If $S$ is the Rees algebra of $I$, then this ring is
isomorphic to $S/IS$, which is how it is computed here.
SeeAlso
reesAlgebra
associatedGradedRing
normalCone
///
doc ///
Key
multiplicity
(multiplicity, Ideal)
(multiplicity, Ideal, RingElement)
Headline
Compute the Hilbert-Samuel multiplicity of an ideal
Usage
multiplicity I
multiplicity(I,f)
Inputs
I:Ideal
f:RingElement
optional argument, if given it should be a non-zero divisor in the ideal I
Outputs
:ZZ
the normalized leading coefficient of the Hilbert-Samuel polynomial of $I$
Description
Text
Given an ideal $I\subset{} R$, ``multiplicity I'' returns the degree of the
normal cone of $I$. When $R/I$ has finite length this is the sum of the
Samuel multiplicities of $I$ at the various localizations of $R$. When $I$
is generated by a complete intersection, this is the length of the ring
$R/I$ but in general it is greater. For example,
Example
R=ZZ/101[x,y]
I = ideal(x^3, x^2*y, y^3)
multiplicity I
degree I
Caveat
The normal cone is computed using the Rees algebra, thus may be slow.
SeeAlso
///
doc ///
Key
specialFiberIdeal
(specialFiberIdeal, Module)
(specialFiberIdeal, Ideal)
(specialFiberIdeal, Module, RingElement)
(specialFiberIdeal, Ideal, RingElement)
Headline
Special fiber of a blowup
Usage
specialFiberIdeal M
specialFiberIdeal(M,f)
Inputs
M:Module
or @ofClass Ideal@
f:RingElement
a non-zerodivisor such that $M[f^{-1}]$ is a free module when $M$ is a module, an element in $M$ when $M$ is an ideal
Outputs
:Ideal
Description
Text
Let $M$ be an $R = k[x_1,\ldots,x_n]/J$-module (for example an ideal), and
let $mm=ideal vars R = (x_1,\ldots,x_n)$, and suppose that $M$ is a
homomorphic image of the free module $F$. Let $T$ be the Rees algebra of
$M$. The call specialFiberIdeal(M) returns the ideal $J\subset{} Sym(F)$
such that $Sym(F)/J \cong{} T/mm*T$; that is, $specialFiberIdeal(M) =
reesIdeal(M)+mm*Sym(F).$
The name derives from the fact that $Proj(T/mm*T)$ is the special fiber of
the blowup of $Spec R$ along the subscheme defined by $I$.
Example
R=QQ[a..h]
M=matrix{{a,b,c,d},{e,f,g,h}}
analyticSpread minors(2,M)
specialFiberIdeal minors(2,M)
Text
If M is an n x n+1 matrix in n variables, and all generators have the
same degree d, with ell = n as expected,
then the special fiber is a rational hypersurface of degree $D := d^n$, and
the reduction number is D-1.
Example
n = 2
x = symbol x
S = ZZ/32003[x_1..x_n]
M = matrix{{x_1,x_2,0},{0,x_1,x_2}}
I = minors(n,M)
specialFiber(I,I_0)
Caveat
Special fiber is here defined to be the fiber of the blowup over the
subvariety defined by the vars of the original ring. Note that if the
original ring is a tower ring, this might not be the fiber over the
closed point! To get the closed
fiber, flatten the base ring first.
SeeAlso
reesIdeal
///
doc ///
Key
specialFiber
(specialFiber, Module)
(specialFiber, Ideal)
(specialFiber, Module, RingElement)
(specialFiber, Ideal, RingElement)
[specialFiber, Jacobian]
Headline
Special fiber of a blowup
Usage
specialFiber M
specialFiber(M,f)
Inputs
M:Module
or @ofClass Ideal@
f:RingElement
an optional element, which is a non-zerodivisor such that $M[f^{-1}]$ is a free module when $M$ is a module, an element in $M$ when $M$ is an ideal
Outputs
:Ring
Description
Text
Let $M$ be an $R = k[x_1,\ldots,x_n]/J$-module (for example an ideal), and
let $mm=ideal vars R = (x_1,\ldots,x_n)$, and suppose that $M$ is a
homomorphic image of the free module $F$ with $m+1$ generators. Let $T$ be the Rees algebra of
$M$. The call specialFiber(M) returns the ideal $J\subset{} k[w_0,\dots,w_m]$
such that $k[w_0,\dots,w_m]/J \cong{} T/mm*T$; that is, $specialFiber(M) =
reesIdeal(M)+mm*Sym(F)$. This routine differs from @TO specialFiberIdeal@ in that
the ambient ring of the output ideal is $k[w_0,\dots,w_m]$ rather than
$R[w_0,\dots,w_m]$.
The coefficient ring $k$ used is always the
@TO ultimate@ @TO2 {coefficientRing, "coefficient ring"} @ of $R$.
The name derives from the fact that $Proj(T/mm*T)$ is the special fiber of
the blowup of $Spec R$ along the subscheme defined by $I$.
Example
R=QQ[a..h]
M=matrix{{a,b,c,d},{e,f,g,h}}
analyticSpread minors(2,M)
specialFiber minors(2,M)
SeeAlso
reesIdeal
specialFiberIdeal
///
doc ///
Key
analyticSpread
(analyticSpread, Module)
(analyticSpread, Ideal)
(analyticSpread, Module, RingElement)
(analyticSpread, Ideal, RingElement)
Headline
Compute the analytic spread of a module or ideal
Usage
analyticSpread M
analyticSpread(M,f)
Inputs
M:Module
or @ofClass Ideal@
f:RingElement
an optional element, which is a non-zerodivisor such that $M[f^{-1}]$ is a free module when $M$ is a module, an element in $M$ when $M$ is an ideal
Outputs
:ZZ
the analytic spread of a module or an ideal $M$
Description
Text
The analytic spread of a module is the dimension of its special fiber
ring. When $I$ is an ideal (and more generally, with the right
definitions) the analytic spread of $I$ is the smallest number of
generators of an ideal $J$ such that $I$ is integral over $J$. See for
example the book Integral closure of ideals, rings, and modules. London
Mathematical Society Lecture Note Series, 336. Cambridge University Press,
Cambridge, 2006, by Craig Huneke and Irena Swanson.
Example
R=QQ[a..h]
M=matrix{{a,b,c,d},{e,f,g,h}}
analyticSpread minors(2,M)
specialFiberIdeal minors(2,M)
R=QQ[a,b,c,d]
M=matrix{{a,b,c,d},{b,c,d,a}}
analyticSpread minors(2,M)
specialFiberIdeal minors(2,M)
SeeAlso
specialFiberIdeal
reesIdeal
///
doc ///
Key
distinguished
(distinguished, RingMap, Ideal)
(distinguished, Ideal, Ideal)
(distinguished, Ideal)
Headline
Compute the distinguished subvarieties of a pullback, intersection or cone
Usage
L = distinguished(f,I)
L = distinguished(I,J)
L = distinguished(I)
Inputs
f:RingMap
I:Ideal
J:Ideal
Outputs
L:List
Description
Text
Suppose that f:S\to R is a map of rings, and I is an ideal of S.
Let K be the kernel of the map of associated graded rings
gr_I(S) \to gr_(fI)R.
The distinguished primes p_i in S/I are the intersections of the
minimal primes P_i over K with S/I \subset{} gr_IS, that is,
the minimal primes of the support in R/I of the normal cone of f(I).
The multiplicity associated
with p_i is by definition the the multiplicities of P_i in the primary
decomposition of K.
Distinguished subvarieties and their multiplicity
(defined by the distinguished primes, usually
in the global case of a quasi-projective variety and its sheaf of rings)
play a central role in the Fulton-MacPherson
construction of refined intersection products. See William Fulton, Intersection Theory,
Section 6.1 for the geometric context and the general case, and the explanation
in the article Rees Algebras in JSAG (submitted).
This application is illustrated in the code for @TO intersectInP@.
We allow the special cases
{\tt distinguished(I,J) := distinguished(f,I)}, with f:S\to S/J the projection
and
{\tt distinguished(I) := distinguished(f,I)}, with f:S\to S the identity.
which computes the distinguished primes in the support of the normal cone gr_IS
itself.
An interesting application is given in the paper
``A geometric effective Nullstellensatz,''
Invent. Math. 137 (1999), no. 2, 427--448 by
Ein and Lazarsfeld.
Here is an example showing that associated primes need not be distinguished primes:
Example
R = ZZ/101[a,b]
I = ideal(a^2, a*b)
ass I
Text
There is one minimal associated prime (a thick line in $P^3$) and one
embedded prime.
Example
distinguished I
intersectInP(I,I)
SeeAlso
intersectInP
saturate
///
doc ///
Key
intersectInP
(intersectInP, Ideal, Ideal)
Headline
Compute distinguished varieties for an intersection in A^n or P^n
Usage
L = intersectInP(I,J)
Inputs
I:Ideal
of a polynomial ring P over a field
J:Ideal
of the same ring
Outputs
L:List
Description
Text
This function applies the technology of @TO distinguished @ to compute
the distinguished subvarieties, with their multiplicities, for an intersection
in affine or projective space. The function @TO distinguished @ is actually applied
to the diagonal ideal in P**P and the ideal I**P + P**I, and the answer is
pulled back to P.
Example
kk = ZZ/101
P = kk[x,y]
I = ideal"x2-y";J=ideal y
intersectInP(I,J)
I = ideal"x4+y3+1"
intersectInP(I,J)
I = ideal"x2y";J=ideal"xy2"
intersectInP(I,J)
intersectInP(I,I)
Text
Note that in the last two cases, which are improper intersections of
two cubics, the total multiplicity is 9 = 3*3. But this is not always the case
(in the actual definition of the intersection product, the multiplicity is
multiplied by the class of a certain cycle supported on the distinguished subvariety).
Example
I = ideal"y-x2"
intersectInP(I,I)
Caveat
SeeAlso
distinguished
///
doc ///
Key
[intersectInP,BasisElementLimit]
[intersectInP,DegreeLimit]
[intersectInP,MinimalGenerators]
[intersectInP,PairLimit]
[intersectInP,Strategy]
[intersectInP,Variable]
[multiplicity,Variable]
Headline
Option for intersectInP
Description
Text
see the options for @TO saturate@.
SeeAlso
intersectInP
distinguished
saturate
///
doc ///
Key
minimalReduction
(minimalReduction, Ideal)
Headline
Find a minimal reduction of an ideal
Usage
J = minimalReduction I
Inputs
I:Ideal
Outputs
:Ideal
A minimal reduction of I (defined below)
Description
Text
{\tt minimalReduction} takes an ideal I that is homogeneous or inhomogeneous
(in the latter case the ideal is to be regarded as an ideal in the
localization of the polynomial ring at the origin.). It returns an ideal $J$
contained in $I$, with a minimal number of generators
such that $I$ is integrally dependent on $J$. This minimal number is called
the analyticSpread of $I$.
This routine is probabilistic: $J$ is computed as the ideal generated by the
right number of random linear combinations of the generators of $I$. However, the
routine checks rigorously that the output ideal is a reduction, and tries
probabilistically again if it is not. If it cannot find a minimal reduction after
a certain number of tries, it returns an error. The number of tries defaults
to 20, but can be set with the optional argument @TO Tries@.
To say that $I$ is integrally dependent on $J$ means that
$JI^k = I^{k+1}$ for some non-negative integer $k$. The smallest $k$ with this
property is called the reduction number of $I$, and can be computed
with @TO reductionNumber@ i.
See the book
Huneke, Craig; Swanson, Irena: Integral closure of ideals, rings, and modules.
London Mathematical Society Lecture Note Series, 336. Cambridge University Press, Cambridge, 2006.
for further information.
Example
kk = ZZ/101;
S = kk[a..c];
m = ideal vars S;
i = (ideal"a,b")*m+ideal"c3"
analyticSpread i
minimalReduction i
Text
Note that this is inhomogeneous--
it is generated by 3 random linear combinations
of the generators of i.
There is no homogeneous ideal with just 3 generators
on which i is integrally dependent.
Example
f = gens i
for a from 0 to 3 do(jhom:=ideal (f*random(source f, S^{3-a:-2,a:-3})); print(i^6 == (i^5)*jhom))
Caveat
It is possible that the ideal returned is not a minimal reduction,
due to the probabilistic nature of the routine. This will be addressed in a future version
of the package. The larger the size of the base field, the less likely this is to happen.
SeeAlso
analyticSpread
reductionNumber
whichGm
///
doc ///
Key
reductionNumber
(reductionNumber, Ideal, Ideal)
Headline
Reduction number of one ideal with respect to another
Usage
k = reductionNumber(I,J)
Inputs
I:Ideal
J:Ideal
Outputs
:ZZ
the reduction number of $I$ (defined below)
Description
Text
The function {\tt reductionNumber} takes a pair of ideals $I,J$, homogeneous or inhomogeneous
(in the latter case $I$ and $J$ are to be regarded as ideals in the
localization of the polynomial ring at the origin.).
The ideal $J$ must be a reduction of $I$ (that is, $J\subset{} I$
and $I$ is integrally dependent on $J$. This condition is checked by
the function @TO isReduction@. It returns the smallest integer $k$ such that
$JI^k = I^{k+1}$.
For further informaion, see the book:
Huneke, Craig; Swanson, Irena: Integral closure of ideals, rings, and modules,
London Mathematical Society Lecture Note Series, 336. Cambridge University Press,
Cambridge, 2006.
Example
setRandomSeed()
kk = ZZ/32003;
S = kk[a..c];
m = ideal vars S;
i = (ideal"a,b")*m+ideal"c3"
analyticSpread i
j=minimalReduction i
reductionNumber (i,j)
Caveat
It is possible for the routine to not finish in reasonable time, due to the
probabilistic nature of the routine. What happens is that
the routine @TO minimalReduction@ occasionally, but rarely, returns an ideal
which is not a minimal reduction. In this case, the routine goes into an infinite loop.
This will be addressed in a future version
of the package. In the meantime, simply interrupt the routine, and restart the
computation.
SeeAlso
analyticSpread
minimalReduction
whichGm
///
doc ///
Key
whichGm
(whichGm, Ideal)
Headline
Largest Gm satisfied by an ideal
Usage
whichGm I
Inputs
I:Ideal
Outputs
:ZZ
what it does
Description
Text
An ideal $I$ in a ring $S$ is said to satisfy the condition $G_m$ if, for every prime ideal $P$ of
codimension $0=1 and ideal X contains a nonzerodivisor of R
(which will be automatic if I has finite projective dimension) then
ideal X has grade >= 1 on the Rees algebra. Since ideal(T*phi) is contained in the
defining ideal of the Rees algebra, the vector X is annihilated by the matrix
psi when regarded over the Rees algebra. If also the number of relations of I
is >= the number of generators of I, this implies that the maximal minors of
psi annihilate the x_i as elements of the Rees algebra, and thus that the maximal
minors of psi are inside the ideal of the Rees algebra. In very favorable circumstances,
one may even have the equality reesIdeal I = ideal(T*phi)+ideal minors(psi): For example:
Theorem (S. Morey and B. Ulrich, Rees Algebras of Ideals with Low Codimension, Proc. Am. Math.
Soc. 124 (1996) 3653--3661):
Let R be a local Gorenstein ring with infinite residue field, let I be a perfect ideal
of grade 2 with n generators, and let phi be the presentation matrix of I. Let
ell = ell(I) be the analytic spread. Suppose that
I satisfies the condition G_{ell} or, equivalently, that the n-p sized minors of phi
have codimension >p for 1<= p < ell. The following conditions are equivalent:
1) reesAlgebra I is Cohen-Macaulay and I_(n-ell)(phi) = I_1(phi)^{n-ell}
2) reductionNumber I < ell and I_(n+1-ell)(phi) = I_1(phi)^{n+1-ell}
3) reesIdeal I = symmetricAlgebraIdeal I + minors(n, jacobianDual phi)
We start with the presentation matrix phi of an (n+1)-generator perfect ideal
Such that the first row consists of the n
variables of the ring, and the rest of whose rows are reasonably general (in this
case random quadrics):
Example
setRandomSeed 0
n=3;
kk = ZZ/101;
S = kk[a_0..a_(n-2)];
phi' = map(S^(n),S^(n-1), (i,j) -> if i == 0 then a_j else random(2,S));
I = minors(n-1,phi');
betti (F = res I)
phi = F.dd_2;
jphi = jacobianDual phi
Text
We first compute the analytic spread ell and the reduction number r
Example
ell = analyticSpread I
r = reductionNumber(I, minimalReduction I)
Text
Now we can check the condition G_{ell}, first probabilistically
Example
whichGm I >= ell
Text
and now deterministically
Example
apply(toList(1..ell-1), p-> {p+1, codim minors(n-p, phi)})
Text
We now check the three equivalent conditions of the Morey-Ulrich Theorem.
Note that since ell = n-1 in this case, the second part of conditions
1,2 is vacuously satisfied, and since rw)
reesIdeal(...,Variable=>w)
reesAlgebra(...,Variable=>w)
specialFiberIdeal(...,Variable=>w)
specialFiber(...,Variable=>w)
distinguished(...,Variable=>w)
isReduction(...,Variable=>w)
jacobianDual(...,Variable=>w)
Description
Text
Each of these functions creates a new ring of the form R[w_0,\ldots, w_r]
or R[w_0,\ldots, w_r]/J, where R is the ring of the input ideal or module
(except for @TO specialFiber@, which creates a ring $K[w_0,\ldots, w_r]$,
where $K$ is the ultimate coefficient ring of the input ideal or module.)
This option allows the user to change the names of the new variables in this ring.
The default variable is w.
Example
R = QQ[x,y,z]/ideal(x*y^2-z^9)
J = ideal(x,y,z)
I = reesIdeal(J, Variable => p)
Text
To lift the result to an ideal in a flattened ring, use @TO flattenRing@:
Example
describe ring I
I1 = first flattenRing I
describe ring oo
Text
Note that the rings of I and I1 both have bigradings. Use @TO newRing@ to
make a new ring with different degrees.
Example
S = newRing(ring I1, Degrees=>{numgens ring I1:1})
describe S
I2 = sub(I1,vars S)
res I2
SeeAlso
flattenRing
newRing
substitute
///
doc ///
Key
[reesIdeal, Strategy]
[reesAlgebra,Strategy]
[isLinearType,Strategy]
[isReduction, Strategy]
[normalCone, Strategy]
[multiplicity, Strategy]
[specialFiberIdeal, Strategy]
[specialFiber, Strategy]
[analyticSpread, Strategy]
[distinguished,Strategy]
[minimalReduction, Strategy]
Headline
Choose a strategy for the saturation step
Usage
reesIdeal(...,Strategy => X)
Description
Text
where X is is one of @TO Iterate@, @TO Linear@, @TO Bayer@, @TO Eliminate@.
These are described in the documentation node for @TO saturate@.
The Rees algebra S(M) of a submodule M of a free module (most importantly,
an ideal in the ring), is equal to the symmetric algebra Sym_k(M) mod torsion.
computing this torsion is the slow link in most of the programs in this
package. The fastest way to compute it is usually by saturating the ideal
defining the symmetric algebra with respect
to an element in that ideal.
SeeAlso
reesIdeal
reesAlgebra
isLinearType
isReduction
normalCone
multiplicity
specialFiberIdeal
specialFiber
analyticSpread
distinguished
minimalReduction
saturate
///
doc ///
Key
[reesIdeal, PairLimit]
[minimalReduction, PairLimit]
[distinguished,PairLimit]
[analyticSpread, PairLimit]
[specialFiber, PairLimit]
[specialFiberIdeal, PairLimit]
[multiplicity, PairLimit]
[normalCone, PairLimit]
[isReduction, PairLimit]
[isLinearType,PairLimit]
[reesAlgebra,PairLimit]
Headline
Bound the number of s-pairs considered in the saturation step
Usage
reesIdeal(...,PairLimit => X)
Description
Text
Here X is a positive integer. Each of these functions computes the Rees
Algebra using a saturation step, and the optional argument causes the saturation
process to stop after that number of s-pairs is found.
This is described in the documentation node for @TO saturate@.
SeeAlso
reesIdeal
reesAlgebra
isLinearType
isReduction
normalCone
multiplicity
specialFiberIdeal
specialFiber
analyticSpread
distinguished
minimalReduction
saturate
///
doc ///
Key
[reesIdeal, MinimalGenerators]
[minimalReduction, MinimalGenerators]
[distinguished,MinimalGenerators]
[analyticSpread, MinimalGenerators]
[specialFiber, MinimalGenerators]
[specialFiberIdeal, MinimalGenerators]
[multiplicity, MinimalGenerators]
[normalCone, MinimalGenerators]
[isReduction, MinimalGenerators]
[isLinearType,MinimalGenerators]
[reesAlgebra,MinimalGenerators]
Headline
Whether the saturation step returns minimal generators
Usage
reesIdeal(...,MinimalGenerators => X)
Description
Text
Here X is of type boolean. Each of these functions involves the
computation of a Rees algebra, which may involve a saturation step.
This optional argument determines whether or not
the output of the saturation step will be forced to have a minmimal generating set.
This is described in the documentation node for @TO saturate@.
SeeAlso
reesIdeal
reesAlgebra
isLinearType
isReduction
normalCone
multiplicity
specialFiberIdeal
specialFiber
analyticSpread
distinguished
minimalReduction
saturate
///
doc ///
Key
[minimalReduction, BasisElementLimit]
[reesIdeal, BasisElementLimit]
[distinguished,BasisElementLimit]
[analyticSpread, BasisElementLimit]
[specialFiber, BasisElementLimit]
[multiplicity, BasisElementLimit]
[normalCone, BasisElementLimit]
[isReduction, BasisElementLimit]
[isLinearType,BasisElementLimit]
[reesAlgebra,BasisElementLimit]
[specialFiberIdeal, BasisElementLimit]
Headline
Bound the number of Groebner basis elements to compute in the saturation step
Usage
reesIdeal(...,BasisElementLimit => X)
Description
Text
Here X is a positive integer. Each of these functions computes the Rees
Algebra using a saturation step, and the optional argument causes the saturation
process to stop after that number of s-pairs is found.
This is described in the documentation node for @TO saturate@.
SeeAlso
reesIdeal
reesAlgebra
isLinearType
isReduction
normalCone
multiplicity
specialFiberIdeal
specialFiber
analyticSpread
distinguished
minimalReduction
saturate
///
doc ///
Key
[reesIdeal, DegreeLimit]
[minimalReduction, DegreeLimit]
[distinguished,DegreeLimit]
[analyticSpread, DegreeLimit]
[specialFiber, DegreeLimit]
[normalCone, DegreeLimit]
[multiplicity, DegreeLimit]
[isReduction, DegreeLimit]
[isLinearType,DegreeLimit]
[reesAlgebra,DegreeLimit]
[specialFiberIdeal, DegreeLimit]
Headline
Bound the degrees considered in the saturation step. Defaults to infinity
Usage
reesIdeal(...,DegreeLimit => X)
Description
Text
where X is a non-negative integer. Stop computation at degree X.
This is described in the documentation node for @TO saturate@.
Here X is a positive integer. Each of these functions computes the Rees
Algebra using a saturation step, and the optional argument causes the saturation
process to stop after that number of s-pairs is found.
This is described in the documentation node for @TO saturate@.
SeeAlso
reesIdeal
reesAlgebra
isLinearType
isReduction
normalCone
multiplicity
specialFiberIdeal
specialFiber
analyticSpread
distinguished
minimalReduction
saturate
///
doc ///
Key
expectedReesIdeal
(expectedReesIdeal, Ideal)
(expectedReesIdeal, Module)
Headline
symmetric algebra ideal plus jacobian dual
Usage
J = expectedReesIdeal M
Inputs
M:Ideal
M:Module
Outputs
J:Ideal
Description
Text
Let M be an R-module with g generators and free presentation phi: R^h \to R^g. The symmetric algebra of M
can be written as R[T_1,\dots,T_g]/J, where J is the ideal generated by the entries of the 1 x h matrix
T*m, where T = (T_1..T_g). If the entries of m are all contained in an ideal (X_1..X_n) (for example, when
m is a minimal presentation and the X_i generate the maximal ideal, there is a matrix psi: R[Z]^h \to R[Z]^n
such that T*phi = X*psi. Under reasonable hypotheses (eg when R is a domain) the relation
X*psi = 0 in the Rees algebra implies that the n x n minors of psi are 0. Thus these minors lie in the ideal
defining the Rees algebra. The expectedReesIdeal is the sum of the ideals (T*phi) and the ideal of nxn minors of psi.
Under particularly good circumstances this sum is known to be equal to the ideal of the Rees algrebra. More generally,
it may speed computations of @TO reesIdeal@ to start with this sum rather than with the ideal T*phi, as in the following
example. (This can be turned off with the Jacobian=>false option.)
The term 'Expected Rees Ideal' for the sum of
of the ideal of the symmetric algebra of I with
the ideal of maximal minors of the Jacobian dual matrix of a presentation of I
is derived from the paper
"Rees Algebras of Ideals of Low Codimension", Proc. Am. Math. Soc. 1996
of Colley and Ulrich. Building on the paper
"Ideals with Expected Reduction Number", Am. J. Math 1996,
they prove that this ideal is in fact equal to the
ideal of the Rees algebra of I when I is a codimension 2 perfect ideal whose
Hilbert-Burch matrix has a special form. See @TO jacobianDual@ for an example.
Example
setRandomSeed 0
n = 5
S = ZZ/101[x_0..x_(n-2)];
M1 = random(S^(n-1),S^{n-1:-2});
M = M1||vars S
I = minors(n-1, M);
time rI = expectedReesIdeal I; -- n= 5 case takes < 1 sec.
--time rrI = reesIdeal(I,I_0); -- n = 5 case ~20 sec
--time rrrI = reesIdeal I; -- n = 4 case > 1 minute; I didn't wait to see!
--assert(rI == (map(ring rI, ring rrI, vars ring rI)) rrI)
kk = ZZ/101;
S = kk[x,y,z];
m = random(S^3, S^{4:-2});
I = minors(3,m);
time reesIdeal (I, I_0);
time reesIdeal (I, I_0, Jacobian =>false);
SeeAlso
symmetricAlgebraIdeal
jacobianDual
///
///
///
///
uninstallPackage "ReesAlgebra"
restart
installPackage "ReesAlgebra"
check "ReesAlgebra"
viewHelp PlaneCurveSingularities
restart
loadPackage("ReesAlgebra", Reload=>true)
///
doc ///
Key
PlaneCurveSingularities
Headline
Using the Rees Algebra to resolve plane curve singularities
Description
Text
The Rees Algebra of an ideal I appeared classically as
the bihomogeneous coordinate ring of the
blow up of the ideal I, used in resolution of singularities. Though the general
case is still out of reach, we illustrate with some simple examples of plane
curve singularities.
First the cusp in the affine plane
Example
R = ZZ/32003[x,y]
cusp = ideal(x^2-y^3)
mm = radical ideal singularLocus cusp
Text
The cusp is singular at the maximal ideal (x,y), so we blow that up,
and examine the ``total transform'', that is, the ideal generated by the
x^2-y^3 in the Rees algebra.
Example
B = first flattenRing reesAlgebra(mm)
Text
Application of {\tt first flattenRing} serves to make B a quotient of the polynomial
ring T in 4 variables; otherwise it would be a quotient of R[w_0,w_1], which
Macaulay2 treats as a polynomial ring in 2 variables, and the calculation of
the singular locus later on would be wrong.
Example
vars B
proj = map(B,R,{x,y})
totalTransform = proj cusp
D = decompose totalTransform
D/codim
Text
We see that the reduced preimage consists of two codimension 1 components,
the `exceptional divisor', which is the pullback of the point we blew up, (x,y),
and the `strict transform'.
The two components meet in a double point in the 2 dimensional variety
B \subset{} A^2\times P^1. We have to saturate with respect to the irrelevant
ideal to understand what's going on.
Example
irrelB = ideal(B_0,B_1)
intersection = saturate(D_0+D_1, irrelB)
codim intersection
degree intersection
Text
We can see the multiplicities of these components by comparing their degrees to the
degrees of the reduced components
Example
divisors = primaryDecomposition totalTransform
strictTransform = divisors_0
exeptional = divisors_1
divisors/(i-> degree i/degree radical i)
Text
That is, the exceptional component occurs with multiplicity 2 (in general we'd
get the exceptional component with multiplicity equal to the multiplicity of the
singular point we blew up.)
We next investigate the singularity of the strict transform. We want to see
it as a curve in P^1 x A^2, that is, as an ideal of T = kk[w_0,w_1,x,y]
Example
T = ring ideal B
irrelT = ideal(w_0,w_1)
sing = saturate(ideal singularLocus strictTransform, irrelT)
Text
We see that the singular locus of the strict transform is empty; that is, the curve is smooth.
We could have made the computation in B as well:
Example
jacobianMatrix = diff(vars B, transpose gens strictTransform)
codim strictTransform
jacobianIdeal = strictTransform+ minors(1,jacobianMatrix)
sing1 = saturate(jacobianIdeal, irrelB)
Text
Next we look at the desingularization of a tacnode; it will take two blowups.
Example
R = ZZ/32003[x,y]
tacnode = ideal(x^2-y^4)
sing = ideal singularLocus tacnode
mm = radical sing
B1 = first flattenRing reesAlgebra mm
proj1 = map(B1,R,{x,y})
irrelB1 = ideal(w_0,w_1)
totalTransform1 = proj1 tacnode
netList (D1 = decompose totalTransform1)
strictTransform1 = saturate(totalTransform1,proj1 mm )
Text
Here proj1 mm is the ideal of the exceptional divisor.
The strict transform is, by definition, obtained by saturating it away,
The strict transform of the tacnode is not yet smooth: it consists of
two smooth branches, meeting transversely at a point:
Example
strictTransform1 == intersect(D1_1,D1_2)
degree (D1_1+D1_2)
Text
We compute the singular point of the strict transform:
Example
mm1 = sub(radical ideal singularLocus strictTransform1, B1)
Text
...and blow up B1, getting a variety in P^2 x P^1 x A^2
Example
B2 = first flattenRing reesAlgebra(mm1, Variable => p)
vars B2
proj2 = map(B2,B1,{w_0,w_1,x,y})
irrelB2 = ideal(p_0,p_1,p_2)
irrelTot = (proj2 irrelB1) *irrelB2
totalTransform2 = saturate(proj2 proj1 tacnode, irrelTot)
exceptional2 = saturate(proj2 proj1 mm, irrelTot)
netList(D2 = decompose totalTransform2)
netList(E2 = decompose exceptional2)
strictTransform2 = saturate(totalTransform2, exceptional2)
Text
We compute the singular locus once again:
Example
time sing2 = ideal singularLocus strictTransform2;
saturate(sing2, sub(irrelTot, ring sing2))
Text
The answer, {\tt ideal 1} shows that the second blowup desingularizes the tacnode.
Text
It is not necessary to repeatedly blow up closed points: there is always a
single ideal that can be blown up to desingularize
(Hartshorne, Algebraic Geometry,Thm II.7.17).
In this case, blowing-up (x,y^2) desingularizes the tacnode x^2-y^4 in a single step.
Example
R = ZZ/32003[x,y];
tacnode = ideal(x^2-y^4);
mm = ideal(x,y^2);
B = first flattenRing reesAlgebra mm;
irrelB = ideal(w_0,w_1);
proj = map(B,R,{x,y});
totalTransform = proj tacnode
netList (D = decompose totalTransform)
exceptional = proj mm
strictTransform = saturate(totalTransform, exceptional);
netList decompose strictTransform
sing0 = sub(ideal singularLocus strictTransform, B);
sing = saturate(sing0,irrelB)
Text
So this single blowup is already nonsingular.
///
///
uninstallPackage "ReesAlgebra"
restart
installPackage "ReesAlgebra"
check "ReesAlgebra"
viewHelp ReesAlgebra
///
-----TESTS-----
TEST///
--TEST for jacobianDual
setRandomSeed 0
d=2
S = ZZ/101[a_0..a_(d-1)]
kk = ZZ/101
mlin = transpose vars S
mquad = random(S^d, S^{-1,-4,d-2:-2})
Irand = minors(d,mlin|mquad)
X = vars S
phi = syz gens Irand;
psi = jacobianDual phi
T = symbol T
ST = kk[T_0..T_d, x_0..x_(d-1)]
X = matrix{toList(x_0..x_(d-1))}
Ts = matrix{{T_0,T_1..T_d}}
phi1 = (map(ST,S,X)) phi
psi1 = jacobianDual(phi1, X, Ts)
f = map(ST, ring psi, vars ST)
assert(f psi - psi1 == 0)
m = matrix {{-15*T_1-8*T_2, T_0*x_0^3+14*T_0*x_0*x_1^2-24*T_0*x_1^3+18*T_2},
{T_0*x_0^3-16*T_0*x_0^2*x_1+2*T_0*x_0*x_1^2+32*T_0*x_1^3+45*T_1+40*T_2,
-11*T_0*x_1^3-11*T_1+43*T_2}}
f psi - m
///
TEST///
--test for expectedReesIdeal
setRandomSeed 0
n = 3
S = ZZ/101[x_0..x_(n-2)];
M1 = random(S^(n-1),S^{n-1:-2});
M = M1||vars S
I = minors(n-1, M);
time rI = expectedReesIdeal I
time rrI = reesIdeal I;
time rrI = reesIdeal(I,I_0); -- ~20 sec
assert(betti rrI == betti rI)
///
///
restart
uninstallPackage "ReesAlgebra"
installPackage "ReesAlgebra"
check "ReesAlgebra"
///
TEST///
--TEST for versalEmbedding
p=3
S=ZZ/p[x,y,z]
R=S/((ideal(x^p,y^p))+(ideal(x,y,z))^(p+1))
i=module ideal(z)
ui=versalEmbedding i
assert(kernel ui == ideal(0_R))
inci=map(R^1,i,matrix{{z}})
assert(kernel inci == 0)
gi=map(R^2, i, matrix{{x},{y}})
assert(kernel gi == 0)
u= map(R^3,R^{-1},ui)
inc=map(R^1, R^{-1}, matrix{{z}})
g=map(R^2, R^{-1}, matrix{{x},{y}})
A=symmetricKernel u
B1=symmetricKernel inc
B=(map(ring A, ring B1)) B1
C1 = symmetricKernel g
C=(map(ring A, ring C1)) C1
assert((A==B)==true)
assert((A==C)==false)
///
--- A very basic tests of reesIdeal - a few more after this.
TEST///
S=ZZ/101[x,y]
i=ideal"x5,y5, x3y2"
V1 = reesIdeal(i)
use ring V1
assert(V1 == ideal(x^2*w_1-y^2*w_2,y*w_1^2-x*w_0*w_2,x^3*w_0-y^3*w_1,x*w_1^3-y*w_0*w_2^2,w_1^5-w_0^2*w_2^3))
V2 = reesIdeal(i,i_0)
use ring V2
assert(V2 == ideal(x^2*w_1-y^2*w_2,y*w_1^2-x*w_0*w_2,x^3*w_0-y^3*w_1,x*w_1^3-y*w_0*w_2^2,w_1^5-w_0^2*w_2^3))
///
-- 3 very simple tests. The first tests just reesIdeal, the second
-- just reesAlgebra and the third tests both.
TEST///
S = ZZ/101[x,y]
M = module ideal(x,y)
V = reesIdeal M
use ring V
assert(V == ideal (-w_0*y+w_1*x))
use S
M = module (ideal(x,y))^2
R = reesAlgebra M
assert(numgens R + numgens coefficientRing R == 5)
use ambient R
assert(ideal R == ideal (-w_1*y+w_2*x, -w_0*y + w_1*x, w_1^2 - w_0*w_2))
use S
M = module (ideal (x,y))^3
V = reesIdeal M
use ring V
assert(V == ideal (-w_2*y+w_3*x,-w_1*y+w_2*x,-w_0*y+w_1*x,w_2^2-w_1*w_3,w_1*w_2-w_0*w_3,w_1^2-w_0*w_2))
R = reesAlgebra M
assert(numgens R + numgens coefficientRing R == 6)
use ambient R
assert(ideal R == ideal (-w_2*y+w_3*x,-w_1*y+w_2*x,-w_0*y+w_1*x,w_2^2-w_1*w_3,w_1*w_2-w_0*w_3,w_1^2-w_0*w_2))
///
--- Checking that the two methods for getting a Rees Ideal yields the
--- same answer. This is now an example as well.
TEST///
x = symbol x
S=ZZ/101[x_0..x_4]
i=monomialCurveIdeal(S,{4,5,6,7})
M1 = gens gb reesIdeal i;
M2 = gens gb reesIdeal(i,i_0);
M1 = substitute(M1, ring M2);
assert(M2 == M1)
///
///
restart
loadPackage ("ReesAlgebra", Reload =>true)
S=ZZ/101[x_0..x_4]
i=monomialCurveIdeal(S,{5,8,9,11})
time M1 = gens gb reesIdeal i;
time M2 = gens gb reesIdeal(i,i_0);
time M3 = gens gb reesIdeal(i,i_0, Strategy => Bayer);
time M4 = gens gb reesIdeal(i, Strategy => Bayer);
M1 = substitute(M1, ring M2);
M4 = substitute(M4, ring M2);
assert(M2 == M1)
assert(M2 == M4)
///
--- Testing analyticSpread
TEST ///
R=QQ[a,b,c,d,e,f]
M=matrix{{a,c,e},{b,d,f}}
assert(analyticSpread image M == 3)
///
---Testing specialFiberIdeal
TEST///
R=ZZ/23[a,b,c,d]
msq=ideal(a^2, a*b, b^2,a*c,b*c, c^2,a*d, b*d, c*d, d^2)
sfi=specialFiberIdeal(msq)
S=ring sfi
T=ZZ/23[S_0,S_1,S_2,S_3,S_4,S_5,S_6,S_7,S_8,S_9]
M=matrix{{S_0,S_1,S_3,S_6},{S_1,S_2,S_4,S_7},{S_3,S_4,S_5,S_8},{S_6,S_7,S_8,S_9}}
i=minors(2,M)
assert(sfi == i)
///
---Testing minimalReduction, isReduction, reductionNumber
TEST///
S = ZZ/5[x,y]
I = ideal(x^3,x*y,y^4)
J = ideal(x*y, x^3+y^4)
assert(isReduction(I,J)==true)
assert(isReduction(J,I)==false)
K= minimalReduction I
assert(reductionNumber(I,J)==1)
assert(isReduction(I,K)==true)
assert(reductionNumber(I,K)==1)
///
--testing multiplicity
TEST///
R=ZZ/101[x,y]
I = ideal(x^3, x^2*y, y^3)
assert(multiplicity I==9)
R = ZZ/101[x,y]/ideal(x^3-y^3)
I = ideal(x^2,y^2)
assert(multiplicity I==6)
///
--Testing which Gm
TEST///
kk=ZZ/101;
S=kk[a..c];
m=ideal vars S
i=(ideal"a,b")*m+ideal"c3"
assert(whichGm i==3)
///
TEST///
--Test for isLinearType
S = ZZ/101[x,y]
M = module ideal(x,y)
E = {true, false, false, false, false}
assert({true, false, false, false, false} ==
for p from 1 to 5 list(isLinearType (ideal vars S)^p))
///
TEST///
--Associated Graded ring and Normal Cone very basic test
R=ZZ/23[x]
I=ideal(x)
A=associatedGradedRing I
S=ring ideal A
assert(dim S==2)
assert(codim A==1)
N=normalCone I
s=ring ideal N
assert(dim s==2)
assert(codim N==1)
///
TEST///
--Test for distinguished
R=ZZ/101[x,y,u,v]
I=ideal(x^2, x*y*u^2+2*x*y*u*v+x*y*v^2,y^2)
p = map(R/I,R)
assert(distinguished I == {{2, p ideal(x,y)}})
///
TEST///
kk = ZZ/101
S = kk[x,y]
I = ideal"x2y";J=ideal"xy2"
assert(intersectInP(I,J) == {{2, ideal x}, {5, ideal (y, x)}, {2, ideal y}})
I = ideal"y-x2";J=ideal y
assert(intersectInP(I,J) == {{2, ideal (y, x)}})
///
TEST///
--Test for symmetricAlgebraIdeal
R=ZZ/101[x,y,u,v]
I=ideal vars R
J = symmetricAlgebraIdeal I
S = ring J
m = promote(vars R,S)||vars S
assert(J == minors(2,m))
///
end--
restart
uninstallPackage "ReesAlgebra"
restart
installPackage "ReesAlgebra"
check "ReesAlgebra"
viewHelp ReesAlgebra
----