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arXiv 2402.12136math-phmath.MP
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半线矩阵薛定谔算子移除或添加束缚态的变换

The transformations to remove or add bound states for the half-line matrix Schrödinger operator

Tuncay Aktosun, Ricardo Weder

AI总结:

本文针对半线矩阵薛定谔算子,提出了在不改变连续谱的情况下移除或添加束缚态及调整其重数的变换方法,并给出了相关量的构造与渐近估计。

摘要:

我们提出了对于具有一般自伴边界条件的半线矩阵值薛定谔算子,在不改变算子连续谱的情况下,移除或添加束缚态,或减少或增加任何现有束缚态重数的变换。当矩阵值势是自伴的、可积的且具有有限一阶矩时,相关变换是通过发展相应的薛定谔算子的Gel'fand-Levitan方法来构造的。特别地,对于任何重数的束缚态,在每个束缚态处构造了束缚态归一化矩阵。变换是针对所有相关量获得的,包括矩阵势、Jost解、正则解、Jost矩阵、散射矩阵和边界条件。对于每个束缚态,通过连接Gel'fand-Levitan方法中使用的归一化矩阵和逆散射Marchenko方法中使用的归一化矩阵,引入了相应的依赖矩阵。提供了各种估计来描述当束缚态被移除或添加或其重数被修改时势的变化的大空间渐近行为。提供了一个显式例子,表明文献中在标量情况下关于势增量的渐近估计是不正确的。

英文摘要:

We present the transformations to remove or add bound states or to decrease or increase the multiplicities of any existing bound states for the half-line matrix-valued Schrödinger operator with the general selfadjoint boundary condition, without changing the continuous spectrum of the operator. When the matrix-valued potential is selfadjoint, is integrable, and has a finite first moment, the relevant transformations are constructed through the development of the Gel'fand-Levitan method for the corresponding Schrödinger operator. In particular, the bound-state normalization matrices are constructed at each bound state for any multiplicity. The transformations are obtained for all relevant quantities, including the matrix potential, the Jost solution, the regular solution, the Jost matrix, the scattering matrix, and the boundary condition. For each bound state, the corresponding dependency matrix is introduced by connecting the normalization matrix used in the Gel'fand-Levitan method and the normalization matrix used in the Marchenko method of inverse scattering. Various estimates are provided to describe the large spacial asymptotics for the change in the potential when the bound states are removed or added or their multiplicities are modified. An explicit example is provided showing that an asymptotic estimate available in the literature in the scalar case for the potential increment is incorrect.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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