On the Two Spectra Inverse Problem for Semi-Infinite Jacobi Matrices ∗† Luis O. Silva and Ricardo Weder ‡ 7 0 Departamento de Métodos Matemáticos y Numéricos 0 2 Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas n Universidad Nacional Autónoma de México a J México, D.F. C.P. 04510 2 2 silva@leibniz.iimas.unam.mx 2 weder@servidor.unam.mx v 8 7 0 1 1 5 Abstract 0 / h We present results on the unique reconstruction of a semi-infinite Jacobi operator p from the spectra of the operator with two different boundary conditions. This is - h the discrete analogue of the Borg-Marchenko theorem for Schrödinger operators t a on the half-line. Furthermore, we give necessary and sufficient conditions for two m real sequences to be the spectra of a Jacobi operator with different boundary : v conditions. i X r a ∗Mathematics Subject Classification(2000): 47B36, 49N45,81Q10,47A75,47B37,47B39. †Research partially supported by Universidad Nacional Autońoma de México under Project PAPIIT- DGAPA IN 105799,and by CONACYT under Project P42553F. ‡Fellow Sistema Nacional de Investigadores. 1 1 Introduction In the Hilbert space l (N) let us single out the dense subset l (N) of sequences which have 2 fin a finite number of non-zero elements. Consider the operator J defined for every f = f ∞ { k}k=1 in l (N) by means of the recurrence relation fin (Jf) := b f +q f +b f k N 1 (1.1) k k−1 k−1 k k k k+1 ∈ \{ } (Jf) := q f +b f , (1.2) 1 1 1 1 2 where, for every n N, b is positive, while q is real. J is symmetric, therefore closable, n n ∈ and in the sequel we shall consider the closure of J and denote it by the same letter. Notice that we have defined the Jacobi operator J in such a way that q b 0 0 1 1 ··· b q b 0  1 2 2 ··· 0 b2 q3 b3 (1.3) 0 0 b q ...  3 4   ... ... ... ...     is the matrix representation of J with respect to the canonical basis in l (N) (we refer the 2 reader to [2] for a discussion on matrix representation of unbounded symmetric operators). It is known that the symmetric operator J has deficiency indices (1,1) or (0,0) [1, Chap. 4, Sec. 1.2] and [23, Corollary 2.9]. In the case (1,1) we can always define a linear set D(g) Dom(J∗) parametrized by g R + such that ⊂ ∈ ∪{ ∞} J∗ ↾ D(g) =: J(g) is a self-adjoint extension of J. Moreover, for any self-adjoint extension (von Neumann extension) J of J, there exists a g R + such that ∈ ∪{ ∞} e e J(g) = J , [25,Lemma2.20]. Weshallshowlater(seetheAppeendix)thatg definesaboundarycondition e at infinity. To simplify the notation, even in the case of deficiency indices (0,0), we shall use J(g) to denote the operator J = J∗. Thus, throughout the paper J(g) stands either for a self-adjoint extension of the nonself-adjoint operator J, uniquely determined by g, or for the self-adjoint operator J. Inwhat follows weshall consider theinverse spectral problemfortheself-adjoint operator J(g). 2 It turns out that if J = J∗ (the case of indices (1,1)), then for all g R + the 6 ∈ ∪ { ∞} Jacobi operator J(g) has discrete spectrum with eigenvalues of multiplicity one, i.e., the spectrum consists of eigenvalues of multiplicity one that can accumulate only at , [25, ±∞ Lemma 2.19]. Throughout this work we shall always require that the spectrum of J(g), denoted σ(J(g)), be discrete, which is not an empty assumption only for the case J(g) = J. Notice that the discreteness of σ(J(g)) implies that J(g) has to be unbounded. FortheJacobioperatorsJ(g)onecandefineboundaryconditionsattheoriginincomplete analogy to those of the half-line Sturm-Liouville operator (see the Appendix). Different boundary conditions at the origin define different self-adjoint operators J (g), h R h ∈ ∪ + . J (g) corresponds to the Dirichlet boundary condition, while the operator J (g) 0 ∞ { ∞} has Neumann boundary condition. If J(g) has discrete spectrum, the same is true for J (g), h h R + (for the case of h finite see Section 2 and for h = , Section 4). ∀ ∈ ∪{ ∞} ∞ In this work we prove that a Jacobi operator J(g) with discrete spectrum is uniquely determined by σ(J (g)), σ(J (g)), with h ,h R and h = h , and either h or h . If h , h1 h2 1 2 ∈ 1 6 2 1 2 1 respectively, h is given, the reconstruction method also gives h , respectively, h . Saying 2 2 1 that J(g) is determined means that we can recover the matrix (1.3) and the boundary condition g at infinity, in the case of deficiency indices (1,1). We will also establish (the precise statement is in Theorem 3.4) that if two infinite real sequences λ and µ that k k k k { } { } can accumulate only at satisfy ±∞ a) λ and µ interlace, i.e., between two elements of a sequence there is one and only k k k k { } { } one element of the other. Thus, we assume below that λ < µ < λ . k k k+1 b) The series (µ λ ) converges, so k k − k P (µ λ ) =: ∆ < . k k − ∞ k X µ λ k n By b) the product − is convergent, so define λ λ k n k6=n − Y µ λ µ λ τ−1 := n − n k − n . n ∆ λ λ k n k6=n − Y c) The sequence τ is such that, for m = 0,1,2,..., n n { } λ2m k converges. τ k k X d) For a sequence of complex numbers β , such that the series k k { } β 2 k | | converges τ k k X 3 and β λm k k = 0, m = 0,1,2,... τ k k X it must hold true that β = 0 for all k. k Then, for any real number h , there exists a unique Jacobi operator J, a unique h > h , 1 2 1 and if J = J∗, a unique g R + , such that σ(J (g)) = λ and σ(J (g)) = µ . 6 ∈ ∪{ ∞} h2 { k}k h1 { k}k Moreover, we show that ifthesequences λ and µ arethe spectra of aJacobioperator k k k k { } { } J(g) with two different boundary conditions h < h (h R), then a), b), c), d) hold for 1 2 2 ∈ ∆ = h h . 2 1 − Necessary and sufficient conditions for two sequences to be the spectra of a Jacobi operator J(g) with Dirichlet and Neumann boundary conditions are also given. Conditions b) and c) differ in this case (see Section 4). Our necessary and sufficient conditions give a characterization of the spectral data for our two spectra inverse problem. Our proofs are constructive and they give a method for the unique reconstruction of the operator J, the boundary condition at infinity, g, and either h or h . 1 2 The two-spectra inverse problem for Jacobi matrices has also been studied in several papers [10, 14, 15, 24]. There are also results on this problem in [9]. We shall comment on these results in the following sections. Theproblemthatwesolvehereisthediscreteanalogueofthetwo-spectrainverseproblem for Sturm-Liouville operators on the half-line. The classical result is the celebrated Borg- Marchenko theorem [6, 20]. Let us briefly explain this result. Consider the self-adjoint Schrödinger operator, f = f′′(x)+Q(x)f(x), x R , (1.4) + B − ∈ where Q(x) is real-valued and locally integrable on [0, ), and the following boundary con- ∞ dition at zero is satisfied, cosαf(0)+sinαf′(0) = 0, α [0,π). ∈ Moreover, the boundary condition at infinity, if any, is considered fixed. Suppose that the spectrum isdiscrete forone(andthenforall)α, anddenote by λk(α) k∈N thecorresponding { } eigenvalues. The Borg-Marchenko theorem asserts that the sets λk(α1) k∈N and λk(α2) k∈N for { } { } some α = α uniquely determine α ,α , and Q. Thus, the differential expression and the 1 2 1 2 6 boundary conditions are determined by two spectra. Other results here are the necessary 4 and sufficient conditions for a pair of sequences to be the eigenvalues of a Sturm-Liouville equation with different boundary conditions found by Levitan and Gasymov in [19]. Other settings for two-spectra inverse problems can be found in [3, 4, 11]. A resonance inverse problem for Jacobi matrices is considered in[7]. Recent local Borg-Marchenko results for Schrödinger operators and Jacobi matrices [13, 27] are also related to the problem we discuss here. Jacobi matrices appear in several fields of quantum mechanics and condensed matter physics (see for example [8]). The paper is organized as follows. In Section 2 we present some preliminary results that we need. In Section 3 we prove our results of uniqueness, reconstruction, and necessary and sufficient conditions (characterization) in the case where h and h are real numbers. 1 2 In Section 4 we obtain similar results for the Dirichlet and Neumann boundary conditions. Finally, in theAppendix we briefly describe –forthe reader’s convenience– howthe boundary conditions are interpreted when J is considered as a difference operator. 2 Preliminaries Let us denote by γ the second order symmetric difference expression (see (1.1), (1.2)) such that γ : f = fk k∈N (γf)k k∈N, by { } 7→ { } (γf) := b f +q f +b f , k N 1 , (2.1) k k−1 k−1 k k k k+1 ∈ \{ } (γf) := q f +b f . (2.2) 1 1 1 1 2 Then, it is proven in Section 1.1, Chapter 4 of [1] and in Theorem 2.7 of [23] that Dom(J∗) = f l (N) : γf l (N) , J∗f = γf, f Dom(J∗). 2 2 { ∈ ∈ } ∈ The solution of the difference equation, (γf) = ζf , ζ C, (2.3) ∈ is uniquely determined if one gives f = 1. For the elements of this solution the following 1 notation is standard [1, Chap. 1, Sec. 2.1] P (ζ) := f , n N, n−1 n ∈ where the polynomial P (ζ) (of degree k) is referred to as the k-th orthogonal polynomial of k the first kind associated with the matrix (1.3). 5 The sequence P (ζ) ∞ is not in l (N) but it may happen that { k }k=0 fin ∞ P (ζ) 2 < , (2.4) k | | ∞ k=0 X in which case ζ is an eigenvalue of J∗ and f(ζ) the corresponding eigenvector. Since the eigenspace is always one-dimensional, the eigenvalue of J∗ is of multiplicity one . Moreover, since the (von Neumann) self-adjoint extensions of J,J(g), are restrictions of J∗, it follows that the point spectrum of J(g), g R + , has multiplicity one. ∈ ∪{ ∞} The polynomials of the second kind Q (ζ) ∞ associated with the matrix (1.3) are { k }k=0 defined as the solutions of b f +q f +b f = ζf , k N 1 , k−1 k−1 k k k k+1 k ∈ \{ } under the assumption that f = 0 and f = b−1. Then 1 2 1 Q (ζ) := f , n N. n−1 n ∈ Q (ζ) is a polynomial of degree k 1. k − By construction the Jacobi operator J is a closed symmetric operator. It is well known, [1, Chap. 4, Sec. 1.2] and [23, Corollary 2.9], that this operator has either deficiency indices (1,1) or (0,0). In terms of the polynomials of the first kind, J has deficiency indices (1,1) when ∞ P (ζ) 2 < , for ζ C R k | | ∞ ∈ \ k=0 X (this holds for all ζ C R if and only if it holds for one ζ C R), and deficiency ∈ \ ∈ \ indices (0,0) otherwise. Since J is closed, deficiency indices (0,0) mean that J = J∗. The symmetric operator J with deficiency indices (1,1) has always self-adjoint extensions, which are restrictions of J∗. When studying the self-adjoint extensions of J in a more general context the self-adjoint restrictions of J∗ are called von Neumann self-adjoint extensions of J [2, 23]. All self-adjoint extensions considered in this paper are von Neumann. Let us now introduce a convenient way of parametrizing the self-adjoint extensions of J in the nonself-adjoint case. We first define the Wronskian associated with J for any pair of sequences ϕ = ϕ ∞ and ψ = ψ ∞ in l (N) as follows { k}k=1 { k}k=1 2 W (ϕ,ψ) := b (ϕ ψ ψ ϕ ), k N. k k k k+1 k k+1 − ∈ Now, consider the sequences v(g) = v (g) ∞ such that k N { k }k=1 ∀ ∈ v (g) := P (0)+gQ (0), g R (2.5) k k−1 k−1 ∈ 6 and v (+ ) := Q (0). (2.6) k k−1 ∞ All the self-adjoint extensions J(g) of the nonself-adjoint operator J are restrictions of J∗ to the set [25, Lemma 2.20] D(g) := f = f ∞ Dom(J∗) : lim W v(g),f = 0 = { k}k=1 ∈ n→∞ n (2.7) = (cid:8)f l (N) : γf l (N), lim W v(g(cid:0)),f =(cid:1)0 . (cid:9) 2 2 n ∈ ∈ n→∞ (cid:8) (cid:0) (cid:1) (cid:9) Different values of g imply different self-adjoint extensions. If J is self-adjoint, we define J(g) := J, for all g R + ; otherwise J(g) is a self-adjoint extension of J uniquely ∈ ∪ { ∞} determined by g. We have defined the domains D(g) in such a way that g defines a boundary condition at infinity (see the Appendix). It is worth mentioning that if J = J∗ then, for all g R + , J(g) has discrete 6 ∈ ∪ { ∞} spectrum. This follows from the fact that the resolvent of J(g) turns out to be a Hilbert- Schmidt operator [25, Lemma 2.19]. Let us now define the self-adjoint operator J (g) by h J (g) := J(g) h ,e e , h R, h 1 1 − h· i ∈ where e ∞ is the canonical basis in l (N) and , denotes the inner product in this { k}k=1 2 h· ·i space. Clearly, J (g) = J(g). 0 We define J (g) as follows. First consider the space l (2, ) of square summable ∞ 2 ∞ sequences f ∞ and the sequence v(g) = v (g) ∞ given by (2.5) and (2.6) with g fixed. { n}n=2 { k }k=1 (cid:0) (cid:1) Let us denote J (g) the operator in l (2, ) such that ∞ 2 ∞ (cid:0) (cid:1) J (g)f = γf , ∞ where (γf) is considered for any k 2 and f = 0 in the definition of (γf) , with domain k 1 2 ≥ given by Dom(J (g)) := f l (2, ) : γf l (2, ) , lim W v(g),f = 0 . ∞ 2 2 n ∈ ∞ ∈ ∞ n→∞ (cid:8) (cid:0) (cid:1) (cid:0) (cid:1) (cid:0) (cid:1) (cid:9) Clearly, the matrix q b 0 0 2 2 ··· b q b 0  2 3 3 ··· 0 b3 q4 b4 , 0 0 b q ...  4 5   ... ... ... ...     7 which is our original matrix (1.3) with the first column and row removed, is the matrix representation of J (g) with respect to the canonical basis in l (2, ) . ∞ 2 ∞ It follows easily from the definition of J (g) that if J(g) has d(cid:0)iscrete(cid:1)spectrum, the same h is true for J (g) (h R + ). Indeed, for h R this is a consequence of the invariance h ∈ ∪{ ∞} ∈ of the essential spectrum –that is empty in our case– under a compact perturbation [22]. We shall show in Section 4 that it is also true that J (g) has discrete spectrum provided that ∞ σ(J(g)) is discrete. For the self-adjoint operator J (g), we can introduce the right-continuous resolution of h the identity E (t), such that J (g) = tdE (t). Let us define the function ρ(t) as Jh(g) h R Jh(g) follows: R ρ(t) := E (t)e ,e , t R. (2.8) h Jh(g) 1 1i ∈ Consider the function (see [24] and [25, Chap. 2, Sec. 2.1]) m (ζ,g) := (J (g) ζI)−1e ,e , ζ σ(J (g)). (2.9) h h 1 1 h h − i 6∈ m (ζ,g) is called the Weyl m-function of J (g). We shall use below the simplified notation h h m(ζ,g) := m (ζ,g). The functions ρ(t) and m (ζ,g) are related by the Stieltjes transform 0 h (also called Borel transform): dρ(t) m (ζ,g) = . h t ζ R Z − It follows from the definition that the Weyl m-function is a Herglotz function, i.e., Imm (ζ,g) h > 0, Imζ > 0. Imζ Using the Neumann expansion for the resolvent (cf.[25, Chap. 6, Sec. 6.1]) N−1 (J (g))k (J (g))N (J (g) ζI)−1 = h + h (J (g) ζI)−1, h − − ζk+1 ζN h − k=0 X where ζ C σ(J(g)), one can easily obtain the following asymptotic formula ∈ \ 1 q h b2 +(q h)2 m (ζ,g) = 1 − 1 1 − +O(ζ−4), (2.10) h −ζ − ζ2 − ζ3 as ζ (Imζ ǫ, ǫ > 0). → ∞ ≥ An important result in the theory of Jacobi operators is the fact that m(ζ,g) completely determines J(g) (the same is of course true for the pair m (ζ,g) and J (g)). There are two h h ways for recovering the operator from the Weyl m-function. One way consists in obtaining 8 first ρ(t) from m(ζ,g) by means of the inverse Stieltjes transform (cf. [25, Appendix B]), namely, 1 b+δ ρ(b) ρ(a) = limlim (Imm(x+iǫ,g))dx. − δ↓0 ǫ↓0 π Za+δ The function ρ is such that all the moments of the corresponding measure are finite [1, 23]. Hence, all the elements of the sequence tk ∞ are in L (R,dρ) and one can apply, { }k=0 2 in this Hilbert space, the Gram-Schmidt procedure of orthonormalization to the sequence tk ∞ . One, thus, obtains a sequence of polynomials P (t) ∞ normalized and orthogonal { }k=0 { k }k=0 in L (R,dρ). These polynomials satisfy a three term recurrence equation [23] 2 tP (t) = b P (t)+q P (t)+b P (t) k N 1 (2.11) k−1 k−1 k−2 k k−1 k k ∈ \{ } tP (t) = q P (t)+b P (t), (2.12) 0 1 0 1 1 where all the coefficients b (k N) turn out to be positive and q (k N) are real numbers. k k ∈ ∈ The system (2.11) and (2.12) defines a matrix which is the matrix representation of J. We shall refer to this procedure for recovering J as the method of orthogonal polynomials. The other method for determining J from m(ζ,g)was developed in [12] (see also [24]). It is based on the asymptotic behavior of m(ζ,g) and the Ricatti equation [24], 1 b2m(n)(ζ,g) = q ζ , n N, (2.13) n n − − m(n−1)(ζ,g) ∈ where m(n)(ζ,g) is the Weyl m-function of the Jacobi operator associated with the matrix (1.3) with the first n columns and n rows removed. After obtaining the matrix representation of J, one can easily obtain the boundary condition at infinity which defines the domain of J(g) in the nonself-adjoint case. Indeed, take an eigenvalue, λ, of J(g), i.e., λ is a pole of m(ζ,g). Since the corresponding eigenvector f(λ) = f (λ) ∞ is in Dom(J(g)), it must be that { k }k=1 lim W v(g),f(λ) = 0. n n→∞ (cid:0) (cid:1) This implies that either lim W Q (0) ∞ ,f(λ) = 0, which means that g = + , n→∞ n { k−1 }k=1 ∞ or (cid:0) (cid:1) lim W P (0) ∞ ,f(λ) g = n→∞ n { k−1 }k=1 . −lim W Q (0) ∞ ,f(λ) n→∞ n(cid:0){ k−1 }k=1 (cid:1) (cid:0) (cid:1) If the spectrum of J (g) is discrete, say σ(J (g)) = λ , the function ρ(t) defined by h h k k { } (2.8) can be written as follows 1 ρ(t) = , α k λXk≤t 9 where the coefficients α are called the normalizing constants and are given by k k { } ∞ α = P (λ ) 2 . (2.14) n k n | | k=0 X Thus, √α equals the l norm of the eigenvector f(λ ) := P (λ ) ∞ corresponding to λ . n 2 n { k n }k=0 n The eigenvector f(λ ) is normalized in such a way that f (λ ) = 1. n 1 n Clearly, 1 1 = e ,e = dρ = . (2.15) 1 1 h i α R k Z k X The Weyl m-function in this case is given by 1 m (ζ,g) = . (2.16) h α (λ ζ) k k k − X From this we have that 1 λ ζ 1 n (λ ζ)m (ζ,g) = (λ ζ) = − + . n h n − − α (λ ζ) α (λ ζ) α k k k k n k − k6=n − X X Therefore, α−1 = lim (λ ζ)m(ζ,g) = Res m(ζ,g). (2.17) n ζ→λn n − −ζ=λn Let us now introduce an appropriate way for enumerating sequences that we shall use. Consider a pair of infinite real sequences λ and µ that have no finite accumulation k k k k { } { } points and that interlace, i.e., between two elements of one sequence there is one and only one element of the other. We use M, a subset of Z to be defined below, for enumerating the sequences as follows k M λ < µ < λ , (2.18) k k k+1 ∀ ∈ where a) If inf λ = and sup λ = , k{ k}k −∞ k{ k}k ∞ M := Z and we require µ < 0 < λ . (2.19) −1 1 b) If 0 < sup λ < , k{ k}k ∞ M := k kmax , (k 1) and we require µ < 0 < λ . (2.20) { }k=−∞ max ≥ −1 1 c) If sup λ 0, k{ k}k ≤ M := k 0 . (2.21) { }k=−∞ 10

On the Two Spectra Inverse Problem for Semi-Infinite Jacobi Matrices

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