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ReesAlgebra.m2
------------------------------------------------------------------------- -- 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 => "2.3", Date => "November 2019", Authors => {{ Name => "David Eisenbud", Email => "de@msri.org"}, {Name => "Amelia Taylor", Email => "originalbrickhouse@gmail.com"}, {Name => "Sorin Popescu", Email => "sorin@math.sunysb.edu"}, {Name => "Michael E. Stillman", Email => "mike@math.cornell.edu"}}, DebuggingMode => false, Headline => "Rees algebras", Keywords => {"Commutative Algebra"}, Certification => { "journal name" => "The Journal of Software for Algebra and Geometry", "journal URI" => "https://msp.org/jsag/", "article title" => "The ReesAlgebra package in Macaulay2", "acceptance date" => "21 May 2018", "published article URI" => "https://msp.org/jsag/2018/8-1/p05.xhtml", "published article DOI" => "10.2140/jsag.2018.8.49", "published code URI" => "https://msp.org/jsag/2018/8-1/jsag-v8-n1-x05-ReesAlgebra.m2", "release at publication" => "0ccfca1d3d08d13ed0da78435b2106209fcee1b1", -- git commit number in hex "version at publication" => "2.2", "volume number" => "8", "volume URI" => "https://msp.org/jsag/2018/8-1/" } ) -* restart uninstallPackage "ReesAlgebra" restart installPackage "ReesAlgebra" viewHelp ReesAlgebra check "ReesAlgebra" *- export{ "analyticSpread", "associatedGradedRing", "distinguished", "intersectInP", "isLinearType", "minimalReduction", "isReduction", "multiplicity", "reductionNumber", "reesIdeal", "reesAlgebra", "specialFiberIdeal", "specialFiber", "symmetricKernel", "versalEmbedding", "whichGm", "jacobianDual", "symmetricAlgebraIdeal", "expectedReesIdeal", "PlaneCurveSingularities", --synonyms "reesAlgebraIdeal" => "reesIdeal", "Trim" -- option in 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", Trim => true } ) --the following uses a versal embedding reesIdeal(Module) := Ideal => o -> M -> ( if o.Trim == true then P := presentation minimalPresentation M else P = presentation 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) -> ( if o.Trim == true then J' := mingens J else J' = gens J; symmetricKernel(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) ->( if o.Trim == true then I' := trim I else I' = 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) -> ( if o.Trim == true then I' := trim I else I' = I; reesIdeal(module I', a, Trim => o.Trim) ) 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) normalConeOptions = { DegreeLimit => {}, BasisElementLimit => infinity, PairLimit => infinity, MinimalGenerators => true, Strategy => null, Variable => "w" } normalCone Ideal := Ring => normalConeOptions >> o -> I -> ( RI := reesAlgebra(I,o); RI/promote(I,RI) ) normalCone(Ideal, RingElement) := Ring => normalConeOptions >> o -> (I,a) -> ( RI := reesAlgebra(I,a,o); RI/promote(I,RI) ) associatedGradedRing = method(Options => normalConeOptions) associatedGradedRing Ideal := Ring => o -> I -> normalCone(I, o) associatedGradedRing(Ideal, RingElement) := Ring => o -> (I,a) -> normalCone(I, a, o) 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, Trim => true } ) 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(monoid [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, Trim => true } ) 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); <<o.Tries <<" iterations were not enough to randomly find a minimal reduction"; endl; error("not random enough") ) reductionNumber = method() reductionNumber (Ideal,Ideal) := (i,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 satisfies --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<d+1 and codim j > 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 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 Trim Headline Choose whether to trim (or find minimal generators) for the ideal or module. Usage reesIdeal(..., Trim => true) Description Text Note that when Trim=>true, the generators used will be the ones (and in the order) M2 likes, possibly not the original ones. 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] 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 maximal 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 Finally, 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] [reesIdeal,Trim] 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 A = reesAlgebra M A = 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 A: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, Ideal, RingElement)@, @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 associatedGradedRing (associatedGradedRing, Ideal) (associatedGradedRing, Ideal, RingElement) (normalCone, Ideal) (normalCone, Ideal, RingElement) Headline The normal cone of a subscheme Usage normalCone I normalCone(I,f) associatedGradedRing I associatedGradedRing(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 "MultiplicitySequence::grGr" /// 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) [specialFiberIdeal, Jacobian] [specialFiberIdeal, Trim] 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 $I$. With the default Trim => true, the computation begins by computing minimal generators, which may result in a change of generators of M 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] [specialFiber, Trim] 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 $I$. With the default Trim => true, the computation begins by computing minimal generators, which may result in a change of generators of M 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 multiplicity 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 [minimalReduction, 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 information, 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 $0<k<m$, the ideal $I_P$ in $S_P$ can be generated by at most $k$ elements. The command {\tt whichGm I} returns the largest $m$ such that $I$ satisfies $G_m$, or infinity if $I$ satisfies $G_m$ for every $m$. This condition arises frequently in work of Vasconcelos and Ulrich and their schools on Rees algebras and powers of ideals. See for example Morey, Susan; Ulrich, Bernd: Rees algebras of ideals with low codimension. Proc. Amer. Math. Soc. 124 (1996), no. 12, 3653--3661. Example kk=ZZ/101; S=kk[a..c]; m=ideal vars S i=(ideal"a,b")*m+ideal"c3" whichGm i SeeAlso analyticSpread minimalReduction reductionNumber /// doc /// Key jacobianDual (jacobianDual, Matrix) (jacobianDual, Matrix, Matrix, Matrix) Headline Computes the 'jacobian dual', part of a method of finding generators for Rees Algebra ideals Usage psi = jacobianDual phi psi = jacobianDual(phi, X, T) Inputs phi:Matrix presentation matrix of an ideal X:Matrix row matrix generating an ideal that contains the entries of phi T:Matrix row matrix of variables that will be generators of the Rees algebra of I Outputs psi:Matrix the `Jacobian Dual', which satisfies $T*phi = X*psi$ Description Text Let I be an ideal of R and let phi be the presentation matrix of I as a module. The symmetric algebra of I has the form $Sym_R(I) = R[T_0..T_m]/ideal(T*phi)$ where the T_i correspond to the generators of I. If $X = matrix\{\{x_1..x_n\}\}$, with x_i \in{} R, and ideal X contains the entries of the matrix phi, then there is a matrix psi defined over R[T_0..T_m], called the Jacobian Dual of phi with respect to X, such that $T*phi = X*psi$. (the matrix psi is generally not unique; Macaulay2 computes it using Groebner division with remainder.) In the form {\tt psi = jacobianDual phi}, a new ring ST := S[T_0..T_m] is created, and the vector X is set to the variables of R. The result is returned as a matrix over ST. To do the computation in a ring previously defined computed, use the form {\tt psi = jacobianDual(phi, X,T)}; in this case, the matrices phi, X, T should all be defined over the same ring ST, the matrix T should be a row of variables of ST, and the matrix phi should have entries in a subring not involving the entries of T. If I is an ideal of grade >=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 r<ell, the conditions must all be satisfied. We first check that reesAlgebra I is Cohen-Macaulay: Example reesI = reesIdeal I; codim reesI betti res reesI Text Finally, we wish to see that reesIdeal I is generated by the ideal of the symmetric algebra together with the jacobian dual: Example psi = jacobianDual phi Text We now compute the ideal J of the symmetric algebra; the call symmetricAlgebra I would return the ideal over a different ring, so we do it by hand: Example ST = ring psi T = vars ST J = ideal(T*promote(phi, ST)) betti res J J1 = minors(ell, psi) betti (G = res trim (J+J1)) betti res reesIdeal I Text The name Jacobian Dual comes from the case where phi is a matrix of linear forms the x_i are the variables of R, and the generators of I are forms, all of the same degree D; in this case Euler's formula sum(df_i/dx_j*xj) = Df can be used to express the entries of psi in terms of the derivatives of the entries of phi, at least when the degrees of the columns of phi are nonzero in the coefficient field. Explicitly, let x_1,...,x_n be the variables of R, and let phi be a presentation matrix for I. Since all the f_i have the same degree, if follows that, for each j, the entries phi_(i,j) will all have the same degree, say D_j = deg phi_(i,j). Let ST be the polynomial ring R[T_0..T_m], where the T_i correspond to f_i, and let X=matrix{{x_1,...,x_n}}, and T=matrix{{T_0,...,T_m}} be row matrices over ST. In this case, by Euler's formula, we may take psi_{k,j}=(1/D_j)*sum_i(d phi_{i,j}/d x_k*T_i), Caveat The division with remainder step is usually fast, but if this ever becomes a bottleneck it would be possible to test for the degree condition and use Euler's formula in the case where it applies. SeeAlso whichGm expectedReesIdeal reesAlgebra reesAlgebraIdeal reesIdeal specialFiberIdeal /// doc /// Key [symmetricKernel, Variable] [reesIdeal, Variable] [reesAlgebra, Variable] [associatedGradedRing, Variable] [(normalCone, Ideal), Variable] [(normalCone, Ideal, RingElement), Variable] [specialFiberIdeal, Variable] [specialFiber, Variable] [distinguished, Variable] [isReduction, Variable] [jacobianDual, Variable] Headline Choose name for variables in the created ring Usage symmetricKernel(...,Variable=>w) 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] [multiplicity, Strategy] [associatedGradedRing, Strategy] [(normalCone, Ideal), Strategy] [(normalCone, Ideal, RingElement), 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 associatedGradedRing multiplicity specialFiberIdeal specialFiber analyticSpread distinguished minimalReduction saturate /// doc /// Key [reesIdeal, PairLimit] [minimalReduction, PairLimit] [distinguished,PairLimit] [analyticSpread, PairLimit] [specialFiber, PairLimit] [specialFiberIdeal, PairLimit] [multiplicity, PairLimit] [associatedGradedRing, PairLimit] [(normalCone, Ideal), PairLimit] [(normalCone, Ideal, RingElement), 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 associatedGradedRing multiplicity specialFiberIdeal specialFiber analyticSpread distinguished minimalReduction saturate /// doc /// Key [reesIdeal, MinimalGenerators] [minimalReduction, MinimalGenerators] [distinguished,MinimalGenerators] [analyticSpread, MinimalGenerators] [specialFiber, MinimalGenerators] [specialFiberIdeal, MinimalGenerators] [multiplicity, MinimalGenerators] [associatedGradedRing, MinimalGenerators] [(normalCone, Ideal), MinimalGenerators] [(normalCone, Ideal, RingElement), 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 minimal generating set. This is described in the documentation node for @TO saturate@. SeeAlso reesIdeal reesAlgebra isLinearType isReduction associatedGradedRing multiplicity specialFiberIdeal specialFiber analyticSpread distinguished minimalReduction saturate /// doc /// Key [minimalReduction, BasisElementLimit] [reesIdeal, BasisElementLimit] [distinguished,BasisElementLimit] [analyticSpread, BasisElementLimit] [specialFiber, BasisElementLimit] [multiplicity, BasisElementLimit] [associatedGradedRing, BasisElementLimit] [(normalCone, Ideal), BasisElementLimit] [(normalCone, Ideal, RingElement), 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 associatedGradedRing multiplicity specialFiberIdeal specialFiber analyticSpread distinguished minimalReduction saturate /// doc /// Key [reesIdeal, DegreeLimit] [minimalReduction, DegreeLimit] [distinguished,DegreeLimit] [analyticSpread, DegreeLimit] [specialFiber, DegreeLimit] [multiplicity, DegreeLimit] [associatedGradedRing, DegreeLimit] [(normalCone, Ideal), DegreeLimit] [(normalCone, Ideal, RingElement), 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 associatedGradedRing 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 algebra. 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) doublePoint = saturate(D_0+D_1, irrelB) codim doublePoint degree doublePoint 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 exceptional = 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) == {{5, ideal (y, x)}, {2, ideal y}, {2, ideal x}}) 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 ----