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P ON THE MATRIX EQUATION XA−AX=X DIETRICH BURDE Abstract. We study the matrix equation XA − AX = Xp in M (K) for 1 < p < n. It is n shown that every matrix solution X is nilpotent and that the generalized eigenspaces of A are X-invariant. For A being a full Jordan block we describe how to compute all matrix solutions. m ℓ ℓ m ℓ Combinatorial formulas for A X ,X A and (AX) are given. The case p = 2 is a special case of the algebraic Riccati equation. 1. Introduction Let p be a positive integer. The matrix equation XA−AX=Xp arises from questions in Lie theory. In particular, the quadratic matrix equation XA−AX = X2 plays a role in the study of affine structures on solvable Lie algebras. An affine structure on a Lie algebra g over a field K is a K-bilinear product g × g → g, (x,y) 7→ x · y such that x·(y·z)−(x·y)·z =y·(x·z)−(y·x)·z [x,y] = x · y − y · x for all x,y,z ∈ g where [x,y] denotes the Lie bracket of g. Affine structures on Lie algebras correspond to left-invariant affine structures on Lie groups. They are important for affine manifolds and for affine crystallographic groups, see [1], [3], [5]. We want to explain how the quadratic matrix equations XA − AX = X2 arise from affine structures. Let g be a two-step solvable Lie algebra. This means we have an exact sequence of Lie algebras ι π 0 →a−→g−→b→0 with the following data: a and b are abelian Lie algebras, ϕ : b 7→ End(a) is a Lie algebra representation, Ω ∈ Z2(b,a) is a 2-cocycle, and the Lie bracket of g = a × b is given by [(a,x),(b,y)] := (ϕ(x)b − ϕ(y)a + Ω(x,y),0). Let ω : b × b → a be a bilinear map and ϕ1, ϕ2 : b 7→ End(a) Lie algebra representations. A natural choice for a left-symmetric product on g is the bilinear product given by (a,x)◦(b,y) := (ϕ1(y)a+ϕ2(x)b+ω(x,y),0). One of the necessary conditions for the product to be left-symmetric is the following: ϕ1(x)ϕ(y)−ϕ(y)ϕ1(x) = ϕ1(y)ϕ1(x). Date: January 27, 2006. 1991 Mathematics Subject Classification. Primary 15A24. Key words and phrases. Algebraic Riccati equation, weighted Stirling numbers. I thank Joachim Mahnkopf for helpful remarks. 1 2 D. BURDE Let (e ,...e ) be a basis of b and write X := ϕ (e ) and A := ϕ(e ) for the linear operators. 1 m i 1 i j j Weobtain the matrix equations XA −AX =XX i j j i j i for all 1 ≤ i,j ≤ m. In particular we have matrix equations of the type XA − AX = X2. 2. General results Let K be an algebraically closed field of characteristic zero. In general it is quite difficult to determine the matrix solutions of a nonlinear matrix equation. Even the existence of solutions is a serious issue as illustrated by the quadratic matrix equation X2 = 0 1 0 0 which has no solution. On the other hand our equation XA−AX = Xp always has a solution, for any given A, namely X = 0. However, if A has a multiple eigenvalue, then we have a lot of nontrivial solutions and there is no easy way to describe the solution set algebraically. A special set of solutions is obtained by the matrices X satisfying XA−AX = 0 = Xp. First one can determine the matrices X commuting with A and then pick out those satisfying Xp = 0. Let E denote the n × n identity. We will assume most of time that p ≥ 2 since for p = 1 we obtain the linear matrix equation AX +X(E −A) = 0 which is a special case of the Sylvester matrix equation AX + XB = C. Let S : Mn(K) → Mn(K) with S(X) = AX +XB be the Sylvester operator. It is well known that the linear operator S is singular if and only if A and −Bhave a common eigenvalue, see [4]. For B = E −A we obtain the following result. Proposition 2.1. The matrix equation XA−AX = X has a nonzero solution if and only if Aand A−E have a common eigenvalue. The general solution of the matrix equation AX = XB is given in [2]. We have the following results on the solutions of our general equation. Proposition 2.2. Let A ∈ M (K). Then every matrix solution X ∈ M (K) of XA−AX = Xp n n is nilpotent and hence satisfies Xn = 0. Proof. We have Xk(XA−AX) = Xk+p for all k ≥ 0. Taking the trace on both sides we obtain tr(Xk+p) = 0 for all k ≥ 0. Let λ ,...,λ be the pairwise distinct eigenvalues of X. For s ≥ 1 1 r we have r tr(Xs) = Xmiλs. i i=1 For s ≥ p we have tr(Xs) = 0 and hence r X(miλp)λk =0 i i i=1 for all k ≥ 0. This is a system of linear equations in the unknowns x = m λp for i = 1,2,...,r. i i i The determinant of its coefficients is a Vandermonde determinant. It is nonzero since the λi are pairwise distinct. Hence it follows m λp = 0 for all i = 1,2,...,r. This means λ = λ = i i 1 2 · · · = λ = 0 so that X is nilpotent with Xn = 0. r XA−AX=Xp 3 Since for p = n our equation reduces to Xn = 0 and the linear matrix equation XA = AX, we may assume that p < n. Proposition 2.3. Let K be an algebraically closed field and p be a positive integer. If X,A ∈ M(K)satisfy XA−AX =Xp then X and A can be simultaneously triangularized. n Proof. Let V be the vector space generated by A and all Xi. Since X is nilpotent we can choose a minimal m ∈ N such that Xm = 0. Then V = span{A,X,X2,...,Xm−1}. We define a Lie bracket on V by taking commutators. Using induction on ℓ we see that for all ℓ ≥ 1 (1) XℓA−AXℓ=ℓXp+ℓ−1 Hence the Lie brackets are defined by [A,A] = 0 [A,Xi] = AXi −XiA = −iXp+i−1 [Xi,Xj] = 0. It follows that V is a finite-dimensional Lie algebra. The commutator Lie algebra [V,V] is abelian and V/[V,V] is 1-dimensional. Hence V is solvable. By Lie’s theorem V is triangular- izable. Hence there is a basis such that X and A are simultaneously upper triangular. p i k j Corollary 2.4. Let X,A ∈ Mn(K) satisfy the matrix equation XA−AX = X . Then A X A is nilpotent for all k ≥ 1 and i,j ≥ 0. So are linear combinations of such matrices. Proof. We mayassumethatX andAaresimultaneouslyuppertriangular. SinceX isnilpotent, Xk is strictly upper triangular. The product of such a matrix with an upper triangular matrix i j A or A is again strictly upper triangular. Moreover a linear combination of strictly upper triangular matrices is again strictly upper triangular. Proposition 2.5. Let p ≥ 2 and A ∈ Mn(K). If A has no multiple eigenvalue then X = 0 is the only matrix solution of XA − AX = Xp. Conversely if A has a multiple eigenvalue then there exists a nontrivial solution X 6= 0. Proof. Assume first that A has no multiple eigenvalue. Let B = (e ,...,e ) be a basis of Kn 1 n such that A = (a ) and X = (x ) are upper triangular relative to B. In particular a =0for ij ij ij i > j and xij = 0 for i ≥ j. Since all eigenvalues of A are distinct, A is diagonalizable. We can diagonalize A by a base change of the form e 7→ µ e +µ e +···+µ e which also keeps i 1 1 2 2 i i X strictly upper triangular. Hence we may assume that A is diagonal and X is strictly upper triangular. Then the coefficients of the matrix XA−AX = (cij) satisfy c =x (a −a ), x =0fori≥j. ij ij jj ii ij Consider the lowest nonzero line parallel to the main diagonal in X. Since α −α 6=0for all jj ii i 6= j this line stays also nonzero in XA−AX, but not in Xp because of p ≥ 2. It follows that X=0. Now assume that A has a multiple eigenvalue. There exists a basis of Kn such that A has canonical Jordan block form. Each Jordan block is an matrix of the form λ 1 ... 0 0 0 λ ... 0 0 . . . . . J(r,λ) = . . .. . . ∈ Mr(K). . . . . 0 0 . . . λ 1 0 0 . . . 0 λ 4 D. BURDE For λ = 0 we put J(r) = J(r,0). It is J(r,λ) = J(r) + λE. Consider the matrix equation XJ(r,λ)−J(r,λ)X =Xp in M (K). It is equivalent to the equation XJ(r)−J(r)X = Xp. If r r ≥ 2 it has a nonzero solution, namely the r × r matrix 0 . . . 1 . . . X= . .. . . . . 0 . . . 0 Indeed, XJ(r) − J(r)X = 0 = Xp in that case. Since A has a multiple eigenvalue, it has a Jordan block of size r ≥ 2. After permutation we may assume that this is the first Jordan block of A. Let X ∈ Mr(K) be the above matrix and extend it to an n×n-matrix by forming a block matrix with X and the zero matrix in Mn−r(K). This will be a nontrivial solution of XA−AX=XpinM (K). n Lemma 2.6. Let A,X ∈ M (K) and A = SAS−1, X = SXS−1 for some S ∈ GL (K). n 1 1 n Then XA−AX =Xp if and only if X A −A X =Xp. 1 1 1 1 1 Proof. The equation Xp = XA−AX is equivalent to p −1 p p −1 X =(SXS ) =SX S 1 =(SXS−1)(SAS−1)−(SAS−1)(SXS−1) =XA −AX. 1 1 1 1 The lemma says that we may choose a basis of Kn such that A has canonical Jordan form. Denote by C(A) = {S ∈ Mn(K) | SA = AS} the centralizer of A ∈ Mn(K). Applying the lemma with A = SAS−1 = A, where S ∈ C(A)∩GL (K), we obtain the following corollary. 1 n Corollary 2.7. If X is a matrix solution of XA−AX = Xp then so is X = SX S−1 for any 0 0 S ∈ C(A)∩GLn(K). Let B = (e ,...,e ) be a basis of Kn such that A has canonical Jordan form. Then A is a 1 n block matrix A=diag(A ,A ,...,A ) 1 2 k with A ∈ M (K) and A leaves invariant the corresponding subspaces of Kn. Let X satisfy i ri XA−AX = Xp. Does it follow that X is also a block matrix X = diag(X ,...,X ) with 1 r X ∈M (K)relative to the basis B ? In general this is not the case. i ri Example 2.8. The matrices 0 0 0 −1 0 1 A= 0 0 1 , X= −1 0 0 0 0 0 −1 0 1 satisfy XA−AX =X2. Here A = diag(J(1),J(2)) leaves invariant the subspaces span{e } and span{e ,e } corre- 1 2 3 sponding to the Jordan blocks J(1) and J(2), but X does not. Also the subspace kerA is not X-invariant. This shows that the eigenspaces E = {x ∈ Kn | Ax = λx} of A need not λ be X-invariant. However, we have the following result concerning the generalized eigenspaces n k H ={x∈K |(A−λE) x=0forsomek≥0}ofA. λ
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