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Consider the $N \times N$ matrix

$$A_{\alpha}=\begin{pmatrix} \lambda_1 & -1 & -\alpha & 0 & \cdots & 0\\ -1 & \lambda_2 & -1 & -\alpha & \cdots & 0\\ -\alpha & -1 & \ddots & \ddots & \cdots & 0\\ 0 & -\alpha & -1 & \lambda_{N-2} & -1 & -\alpha \\ 0 & \cdots & -\alpha & -1 &\lambda_{N-1} & -1 \\ 0 & \cdots & 0 & -\alpha &-1 &\lambda_N \\ \end{pmatrix}$$

The parameters $\lambda$ are defined such that the row sum or equivalently the column sum is equal to zero. This also means that $\lambda_3=\lambda_4 =...=\lambda_{N-2}=2(1+\alpha).$

If $\alpha \equiv 0$ the matrix $A_0$ is just the discrete Neumann Laplacian and it is well-known that all eigenvectors $v=(v_1,...,v_N) \in \mathbb C^N$ of $A_0$ have the property that the first entry $v_1$ and the last entry $v_N$ do not satisfy a Dirichlet condition, i.e. $v_1,v_N$ are not equal to zero, see e.g. here

I conjecture based on numerical experiments that there exists $\varepsilon>0$, independent of $N$ such that the same is true for $A_{\alpha} \in \mathbb C^{N \times N}$ with $\alpha \in (0,\varepsilon).$

To clarify: I do not claim that $v_1$ and $v_N$ are independent of $N$. I claim that there exists $\varepsilon>0$ independent of $N$ such that for all $\alpha \in (0,\varepsilon)$ both $v_1, v_N$ are non-zero!

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    $\begingroup$ did I miss something or in the case $\alpha=0$ the lower bound for the normalised eigenvector is $1/\sqrt N$ for $v_1$ or $v_N$ and therefore is not independent of $N$, in the link you provide? $\endgroup$
    – username
    Commented Feb 22, 2022 at 15:42
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    $\begingroup$ @username I do not claim that $v_1$ and $v_N$ are independent of $N$. I claim that there exists $\varepsilon>0$ independent of $N$ such that for all $\alpha \in (0,\varepsilon)$ both $v_1, v_N$ are non-zero! $\endgroup$
    – Guido Li
    Commented Feb 22, 2022 at 17:32
  • $\begingroup$ Can you set up a recurrence relation for the $v_i$, using $\lambda v_{i-2}=-\alpha v_{i-4}-v_{i-3}+2(1+\alpha)v_{i-2}-v_{i-1}-\alpha v_i$? You have two boundary conditions, and you can fix $v_2$ arbitrarily, so you should get some equation involving $\lambda$ and $\alpha$, and your constraints on $\lambda$ would give you constraints on $\alpha$. $\endgroup$
    – user7868
    Commented Feb 23, 2022 at 5:24

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