Nilpotent matrices and spectrally arbitrary sign patterns

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Electronic Journal of Linear Algebra Volume 16 Article 21 2007 Nilpotent matrices and spectrally arbitrary sign patterns Rajesh J. Pereira rjxpereira@yahoo.com Follow this and additional works at: http://repository.uwyo.edu/ela Recommended Citation Pereira, Rajesh J.. (2007), "Nilpotent matrices and spectrally arbitrary sign patterns", Electronic Journal of Linear Algebra, Volume 16. DOI: https://doi.org/10.13001/1081-3810.1198 This Article is brought to you for free and open access by Wyoming Scholars Repository. It has been accepted for inclusion in Electronic Journal of Linear Algebra by an authorized editor of Wyoming Scholars Repository. For more information, please contact scholcom@uwyo.edu.

NILPOTENT MATRICES AND SPECTRALLY ARBITRARY SIGN PATTERNS RAJESH PEREIRA Abstract. It is shown that all potentially nilpotent full sign patterns are spectrally arbitrary. A related result for sign patterns all of whose zeros lie on the main diagonal is also given. Key words. Nilpotent matrices, Potentially nilpotent sign patterns, Spectrally arbitrary sign patterns. AMS subject classifications. 15A18. 1. Full Spectrally Arbitrary Patterns. In what follows, M n denotes the topological vector space of all n n matrices with real entries and P n denotes the set of all polynomials with real coefficients of degree n or less. The superdiagonal of an n n matrix consists of the n 1 elements that are in the ith row and (i +1)st column for some i, 1 i n 1. A sign pattern is a matrix with entries in {+, 0, }. Given two n n sign patterns A and B, we say that B is a superpattern of A if b ij = a ij whenever a ij 0. Note that a sign pattern is always a superpattern of itself. We define the function sign : R {+, 0, } in the obvious way: sign(x) =+ifx>0, sign(0) = 0, and sign(x) = if x<0. Given a real matrix A, sign(a) is the sign pattern with the same dimensions as A whose (i, j)th entry is sign(a ij ). For every sign pattern A, we define its associated sign pattern class to be the inverse image Q(A) =sign 1 (A). A sign pattern is said to be full if none of its entries are zero [8]. A sign pattern class Q(A) is an open set in the topology of M n if and only if A is a full sign pattern; this observation will be very useful in proving our first theorem. Recall that a square matrix N is nilpotent if there exists a k N such that N k = 0. We define the index of a nilpotent matrix N to be the smallest k N such that N k = 0. A sign pattern A is said to be potentially nilpotent if there exists a nilpotent matrix N Q(A). (Allows nilpotence is sometimes used in place of potentially nilpotent). Potentially nilpotent sign patterns were studied in [6] and [10]. An n n sign pattern matrix A is said to be spectrally arbitrary if every nth degree monic polynomial with real coefficients is a characteristic polynomial of some matrix in Q(A). The study of spectrally arbitrary sign patterns was initiated in [5]. It is clear that any spectrally arbitrary sign pattern is potentially nilpotent. The converse can easily be seen to be false. For instance, any potentially nilpotent sign pattern with only zeros on the main diagonal is not spectrally arbitrary. For n 3, these are the only counterexamples to the converse as any 2 2or3 3 potentially nilpotent sign pattern whose main diagonal does not consist entirely of zeros is spec- Received by the editors 21 May 2007. Accepted for publication 21 August 2007. Handling Editor: Michael J. Tsatsomeros. Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario N1G 2W1 (rjxpereira@yahoo.com). Supported by NSERC. 232

Spectrally Arbitrary Sign Patterns 233 trally arbitrary [2]. For n 4, there exist potentially nilpotent sign patterns whose main diagonals do not consist entirely of zeros yet are still not spectrally arbitrary. The following example is given in [3]. Example 1.1. The following 4 4 nilpotent matrix belongs to a sign pattern which is not spectrally arbitrary: (1.1) 1 1 1 0 1 1 1 0 0 0 0 1 1 1 0 0. It is noted in both [3] and [4] that it is the location of the zero entries in (1.1) which prevents this sign pattern from being spectrally arbitrary. (In the sense that any other sign pattern with zeros in the exact same locations would not be spectrally arbitrary). Another collection of potentially nilpotent but not spectrally arbitrary sign patterns can be obtained by following an argument of [4] and noting that any reducible sign pattern having all of its irreducible blocks being potentially nilpotent and at least two of its irreducible blocks being of odd order would be potentially nilpotent but not spectrally arbitrary (since it would require two real eigenvalues). Note that in this case as well it is the location of the zero entries which prevent the sign patterns in this collection from being spectrally arbitrary. This would suggest that one should look at sign patterns with no or few zero entries to see if potential nilpotence implies being spectrally arbitrary in these cases. In page 14 of [1] (Question 2.14), it was asked whether any potentially nilpotent full sign pattern is spectrally arbitrary. We answer this question in the affirmative. Theorem 1.2. Any potentially nilpotent full sign pattern is spectrally arbitrary. Proof. Let A be an n n full sign pattern and let N Q(A) be a nilpotent matrix. Let N = PJP 1 be the Jordan decomposition of N. SinceJ is a direct sum of Jordan blocks; it is a matrix with ones and zeros on the superdiagonal and zero entries everywhere else. We now show that there is a nilpotent matrix of index n in Q(A). If all the elements on the superdiagonal of J are one, then N is nilpotent of index n. Otherwise, let J ɛ be the n n matrix obtained by replacing all of the zeros on the superdiagonal of J by ɛ and leaving all other entries unchanged. Then N ɛ = PJ ɛ P 1 is a nilpotent matrix of index n for ɛ 0andfurtherN ɛ Q(A) for some non-zero ɛ sufficiently small. Since N ɛ is a nilpotent matrix of index n, ithas a Jordan decomposition N ɛ = SJ 1 S 1 where S is an invertible matrix and J 1 is the matrix with ones along the superdiagonal and zeros everywhere else. Now consider matrices of the form SC p S 1 where C p is the companion matrix with characteristic polynomial p(x) =x n + a n 1 x n 1 +... + a 1 x + a 0. 0 1 0... 0 0 0 1... 0 C p =........ 0 0 0... 1 a 0 a 1 a 2... a n 1

234 R. Pereira There exists an ɛ>0, such that if a i <ɛfor 0 i n 1, SC p S 1 Q(A). Now let p(x) be an arbitrary nth degree monic polynomial with real coefficients, Then there exists a positive k R such that the polynomial q(x) =k n p(x/k) isa monic polynomial all of whose nonleading coefficients have modulus less than ɛ. Then 1 k SC qs 1 is in Q(A) and has characteristic polynomial p(x). Hence A is spectrally arbitrary. An n n sign pattern A is called p-striped if it has p columns with only positive entries and n p columns with only negative entries. In [9], it was shown that all n np-striped sign patterns where 1 p n 1 are spectrally arbitrary. Since it is easy to construct a rank-one nilpotent matrix in any n np-striped sign pattern class with 1 p n 1, we now have an alternate and shorter proof of this result. Theorem 1.2 suggests the following random algorithm to find most (or possibly even all) of the full spectrally arbitrary n n sign patterns for small n. Randomly choose an invertible P M n,calculatepj 1 P 1.IfalltheentriesofPJ 1 P 1 are far enough from zero to avoid sign errors, add the sign pattern containing PJ 1 P 1 to the list of n n spectrally arbitrary full sign patterns to generate a (not necessarily complete) list of full spectrally arbitrary sign patterns. 2. Patterns with zeros only on the main diagonal. In this section we give a variant of Theorem 1.2 in the case of a sign pattern whose zeros are restricted to the main diagonal. The adjugate of an n n matrix A, denoted adj(a) isthen n matrix whose (i, j)th entry is ( 1) i+j det(a[j i]) where A[j i] isthe(n 1) (n 1) matrix obtained by deleting the jth row and ith column of A. IfA is invertible then A 1 = adj(a) If the (i, j)th entry of A, a ij, is considered to be a variable; then det(a) a ij det(a). is equal to the (j, i)th entry of adj(a). More about the adjugate can be found in [7]. We also will use D n to denote the subspace of M n consisting of the n n diagonal matrices; M n /D n is the quotient vector space. One of the most useful tools in finding spectrally arbitrary sign patterns is the Nilpotent-Jacobian method first used in [5] but first explicitly stated as Lemma 2.1 of [2]. We state it here as follows: Lemma 2.1. [2] Let A be a n n sign pattern, and suppose there exists some nilpotent A Q(A) with at least n non-zero entries, say a i1j 1,a i2j 2,..., a inj n. Let X be the matrix obtained by replacing these entries in A by the variables x 1,..., x n and let det(xi X) =x n + α 1 x n 1 + α 2 x n 2 +... + α n 1 x + α n. If the Jacobian (α1,α2,...,αn) (x 1,x 2,...,x n) is invertible at (x 1,x 2,..., x n )=(a i1j 1,a i2j 2,..., a inj n ), then every superpattern of A is a spectrally arbitrary. We will now prove a result for sign patterns whose zeros lie solely on the main diagonal. Since any sign pattern with less than two non-zero elements on the main diagonal is not spectrally arbitrary, we will restrict the statement of our theorem to patterns which have at least two non-zero elements on the main diagonal. Theorem 2.2. Let A be a n n sign pattern having at most n 2 zero entries all of which are on the main diagonal. If there exists a nilpotent matrix of index n in Q(A), then every superpattern of A is a spectrally arbitrary sign pattern.

Spectrally Arbitrary Sign Patterns 235 Proof. LetN be a nilpotent matrix of index n in Q(A). We have span{adj(xi N) :x 0} = span{(xi N) 1 : x 0} = span{n k } n 1 k=0 where the latter equality follows from the Neumann series for N which gives us the identity (xi N) 1 = n 1 k=0 x k 1 N k.letv be the image of span{n k } n 1 k=0 in M n/d n.sincei = N 0 gets mapped to 0, dim(v )isatmostn 1. If dim(v ) <n 1, then there would exist real numbers {c k } n 1 i=1 not all zero such that D = n 1 k=1 c kn k is a diagonal matrix. Since D would also be nilpotent, it must be zero which is impossible since the index of N is n. So the dimension of V is exactly n 1. Now let p ij (x) bethe(j, i)th entry of adj(xi N). (Taking the (j, i)th entry is intentional and not a misprint; this choice makes the notation simpler later on.) Each polynomial p ij is of degree n 1ifi = j and of degree n 2 otherwise. The result of the previous paragraph implies that dim(span{p ij (x) :1 i, j n; i j}) =n 1 and hence {p ij (x) :1 i, j n; i j} spans P n 2. We can obtain a basis of P n 2 from the elements {p ij (x) :1 i, j n; i j}. Now choose any i such that the (i, i)th entry of Q(A) is nonzero. By adjoining p ii (x) to the basis of P n 2,wegeta basis of P n 1 which we will write as {p ik j k } n k=1. We now apply the Nilpotent-Jacobian method to N. Let X(x 1,x 2,..., x n )be the n n matrix obtained by replacing the (i k,j k )th entry of N by the variable x k for 1 k n. Let x =(x 1,x 2,..., x n ), and η be the n-vector whose kth entry is the (i k,j k )th entry of N and let p(x, x 1,x 2,..., x n )=det(xi X(x 1,x 2,..., x n )). Then p x k x= η = p ik j k (x). The kth column of the required Jacobian consists of the coefficients of the polynomial p ik j k (x) for all k where 1 k n and the invertibility of the Jacobian follows from the linear independence of these polynomials. It should be noted that the 4 4 nilpotent matrix in Example 1.1 is of index 4; hence Theorem 2.2 becomes false if we allow too many additional zeros outside of the main diagonal. Acknowledgment. The author would like to thank the organizers of the 2006 Western Canada Linear Algebra meeting where the author first learned about spectrally arbitrary sign patterns. The author would also like to acknowledge NSERC support. REFERENCES [1] R. Brualdi, L. Hogben, and B. Shader. AIM Workshop: spectra of families of matrices described by graphs, digraphs and sign patterns; Final Report: Mathematical Results (revised) (March 30, 2007). (Available at http://aimath.org/pastworkshops/matrixspectrumrep.pdf) [2] T. Britz, J. J. McDonald, D. D. Olesky, and P. van den Driessche. Minimally spectrally arbitrary sign patterns. SIAM Journal on Matrix Analysis and Applications, 26:257 271, 2004. [3] L. Corpuz and J. J. McDonald. Spectrally arbitrary zero-nonzero patterns of order 4. Linear and Multilinear Algebra, 55:249 273, 2007. [4] L. M. DeAlba, I. R. Hentzel, L. Hogben, J. McDonald, R. Mikkelson, O. Pryporova, B. Shader, and K. N. van der Meulen. Spectrally arbitrary patterns: Reducibility and the 2n conjecture for n =5. Linear Algebra and its Applications, 423:262 276, 2007. [5] J.H.Drew,C.R.Johnson,D.D.Olesky,andP.vandenDriessche.Spectrallyarbitrarypatterns. Linear Algebra and its Applications, 308:121 137, 2000. [6] C. Eschenbach and Z. Li. Potentially nilpotent sign pattern matrices. Linear Algebra and its Applications, 299:81 99, 1999.

236 R. Pereira [7] R. D. Hill and E. E. Underwood. On the matrix adjoint (adjugate). SIAM Journal on Algebraic and Discrete Methods, 6:731 737, 1985. [8] C. R. Johnson, W. D. McCuaig, and D. P. Stanford. Sign patterns that allow minimal semipositivity. Linear Algebra and its Applications, 223-224:363 373, 1995. [9] J.J.McDonald,D.D.Olesky,M.J.Tsatsomeros,andP.vandenDriessche.Onthespectraof striped sign patterns. Linear and Multilinear Algebra, 51:39 48, 2003. [10] L. Yeh. Sign pattern matrices that allow a nilpotent matrix. Bulletin of the Australian Mathematical Society, 53:189 196, 1996.