Abstract:The direct and inverse scattering problems are analyzed for a first-order discrete system associated with the semidiscrete version of the derivative nonlinear Schrödinger (NLS) system. The Jost solutions, the scattering coefficients, the bound-state dependency and norming constants are investigated and related to the corresponding quantities for two particular discrete linear systems associated with the semi-discrete version of the NLS system. The bound-state data set with any multiplicities is described in an… Show more
“…As the bound-state norming constants, we use the double-indexed quantities c jk for 1 ≤ j ≤ N and 0 ≤ k ≤ (m j − 1) and the double-indexed quantities cjk for 1 ≤ j ≤ N and 0 ≤ k ≤ ( mj − 1). The construction of the bound-state norming constants c jk from the transmission coefficient T (ζ) and the Jost solutions φ(ζ, x) and ψ(ζ, x) and the construction of the bound-state norming constants cjk from the transmission coefficient T (ζ) and the Jost solutions φ(ζ, x) and ψ(ζ, x) are analogous to the constructions presented for the discrete version of (1.1), and we refer the reader to [9] for the details. Such a construction involves the determination of the double-indexed "residues" t jk with 1 ≤ j ≤ N and 1 ≤ k ≤ m j and the the double-indexed "residues" tjk with 1 ≤ j ≤ N and 1 ≤ k ≤ mj , respectively, by using the expansions of the transmission coefficients at the bound-state poles, which are given by…”
Section: The Bound Statesmentioning
confidence: 99%
“…We then recursively obtain (3.3). For the details of the procedure, we refer the reader to [9]. Similarly, the double-indexed dependency constants γjk with 1 ≤ j ≤ N and 0 ≤ k ≤ ( mj − 1) appear in the coefficients when we express at λ = λj the value of each…”
Section: The Bound Statesmentioning
confidence: 99%
“…, and this procedure is explained in the proof of Theorem 4.2 and it is similar to the procedure described in Theorem 15 of [9]. In a similar manner, the norming constants cjk are formed by using the set of residues { tjk } mj k=1 and the set of dependency constants {γ jk } mj −1 k=0 .…”
Section: The Bound Statesmentioning
confidence: 99%
“…For simplicity and clarity, we outline the main steps of the procedure by omitting the details. We refer the reader to [9] where the details of the procedure are presented for the discrete version of (1.1). The steps presented in [9] are general enough to apply to (1.1) and other linear systems.…”
Section: The Bound Statesmentioning
confidence: 99%
“…We present the Marchenko method for (1.1) in such a way that the method can be applied on other linear systems and also on their discrete versions. We have already developed [9] the Marchenko method for the discrete analog of the linear system (1.1), and hence our emphasis in this paper is the development of the Marchenko method for the linear system (1.1).…”
The Marchenko method is developed in the inverse scattering problem for a linear system of first-order differential equations containing potentials proportional to the spectral parameter. The corresponding Marchenko system of integral equations is derived in such a way that the method can be applied to some other linear systems for which a Marchenko method is not yet available. It is shown how the potentials and the scattering solutions to the linear system are constructed from the solution to the Marchenko system. The bound-state information for the linear system with any number of bound states and any multiplicities is described in terms of a pair of constant matrix triplets. When the potentials in the linear system are reflectionless, some explicit solution formulas are presented in closed form for the potentials and for the scattering solutions to the linear system. The theory is illustrated with some explicit examples.
“…As the bound-state norming constants, we use the double-indexed quantities c jk for 1 ≤ j ≤ N and 0 ≤ k ≤ (m j − 1) and the double-indexed quantities cjk for 1 ≤ j ≤ N and 0 ≤ k ≤ ( mj − 1). The construction of the bound-state norming constants c jk from the transmission coefficient T (ζ) and the Jost solutions φ(ζ, x) and ψ(ζ, x) and the construction of the bound-state norming constants cjk from the transmission coefficient T (ζ) and the Jost solutions φ(ζ, x) and ψ(ζ, x) are analogous to the constructions presented for the discrete version of (1.1), and we refer the reader to [9] for the details. Such a construction involves the determination of the double-indexed "residues" t jk with 1 ≤ j ≤ N and 1 ≤ k ≤ m j and the the double-indexed "residues" tjk with 1 ≤ j ≤ N and 1 ≤ k ≤ mj , respectively, by using the expansions of the transmission coefficients at the bound-state poles, which are given by…”
Section: The Bound Statesmentioning
confidence: 99%
“…We then recursively obtain (3.3). For the details of the procedure, we refer the reader to [9]. Similarly, the double-indexed dependency constants γjk with 1 ≤ j ≤ N and 0 ≤ k ≤ ( mj − 1) appear in the coefficients when we express at λ = λj the value of each…”
Section: The Bound Statesmentioning
confidence: 99%
“…, and this procedure is explained in the proof of Theorem 4.2 and it is similar to the procedure described in Theorem 15 of [9]. In a similar manner, the norming constants cjk are formed by using the set of residues { tjk } mj k=1 and the set of dependency constants {γ jk } mj −1 k=0 .…”
Section: The Bound Statesmentioning
confidence: 99%
“…For simplicity and clarity, we outline the main steps of the procedure by omitting the details. We refer the reader to [9] where the details of the procedure are presented for the discrete version of (1.1). The steps presented in [9] are general enough to apply to (1.1) and other linear systems.…”
Section: The Bound Statesmentioning
confidence: 99%
“…We present the Marchenko method for (1.1) in such a way that the method can be applied on other linear systems and also on their discrete versions. We have already developed [9] the Marchenko method for the discrete analog of the linear system (1.1), and hence our emphasis in this paper is the development of the Marchenko method for the linear system (1.1).…”
The Marchenko method is developed in the inverse scattering problem for a linear system of first-order differential equations containing potentials proportional to the spectral parameter. The corresponding Marchenko system of integral equations is derived in such a way that the method can be applied to some other linear systems for which a Marchenko method is not yet available. It is shown how the potentials and the scattering solutions to the linear system are constructed from the solution to the Marchenko system. The bound-state information for the linear system with any number of bound states and any multiplicities is described in terms of a pair of constant matrix triplets. When the potentials in the linear system are reflectionless, some explicit solution formulas are presented in closed form for the potentials and for the scattering solutions to the linear system. The theory is illustrated with some explicit examples.
A system of linear integral equations is presented, which is the analog of the system of Marchenko integral equations, to solve the inverse scattering problem for the linear system associated with the DNLS (derivative nonlinear Schrödinger) equations. The corresponding direct and inverse scattering problems are analyzed, and the recovery of the potentials and the Jost solutions from the solution to the Marchenko system is described. When the reflection coefficients are zero, some explicit solution formulas are provided for the potentials and the Jost solutions in terms of a pair of constant matrix triplets representing the bound-state information for any number of bound states and any multiplicities. In the reduced case, when the two potentials in the linear system are related to each other through complex conjugation, the corresponding reduced Marchenko integral equation is obtained. The solution to the DNLS equation is obtained from the solution to the reduced Marchenko integral equation. The theory presented is illustrated with some explicit examples.
We are revisiting the problem of solving a discrete nonlinear Schrödinger equation by the inverse scattering transform method, by use of the recently developed ExactMPF package within MAPLE Software. ExactMPF allows for an
exact
Wiener–Hopf factorization of matrix polynomials regardless of the partial indices of the matrix. The package can be widely used in various problems, where Wiener–Hopf factorization as one of the effective mathematical tools is required, as its code has already been disclosed. The analysis presented in this paper contains not only numerical examples of its use, but is also supported by appropriate and accurate
a priori
estimations. The procedure itself guarantees that the ExactMPF package produces all computations arithmetically
exactly
, and a detailed numerical analysis of various aspects of the computational algorithm and approximation strategies is provided in the case of a finite initial impulse.
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