In recent years, there are some researches on eigenvalue estimates for quadratic polynomial operator of Laplacian:
where $\Omega$ is a bounded domain in an $n$-dimensional complete Riemannian manifold $M, v$ denotes the outwards unit normal vector field of $\partial \Omega$, the constants $p, q \geq0$, $\Delta(=-{\rm div}\nabla)$ is the Laplacian and $\Delta^{2}$ is the biharmonic operator on $M$. In 2011, Sun and Qi [3] obtained universal eigenvalue inequalities of problem (1.1),
where $H_{0}$ is a constant which only depends on the mean curvature of $M$ and
For other related results, one can see [2, 4, 5, 7, 8].
Let $(M^{n}, \langle, \rangle)$ be an $n(\geq2)$-dimensional complete Riemannian manifold isometrically immersed in the Euclidean space $\mathbb{R}^{N}$ by $\Psi$, $\Omega$ is a bounded domain in $M^{n}$. In this paper, we are interested in extrinsic upper bounds for the lower order eigenvalues of following operator defined on $\Omega$:
where $A$ is a positive definite symmetric (1, 1)-tensor on $M^{n}$, the eigenvalues of $A$ on $\Omega$ are bounded below by a positive constant $b$, ${\rm tr}(A)|_{\Omega}\leq c$ (i.e., $A$ can also be viewed as a smooth symmetric and positive defined section of the bundle of all endomorphisms of $T(M^{n})$, $\Delta(={\rm div}\nabla)$ is the Laplacian, $\nabla$ is the gradient operator on $M$ and $a$ is a nonnegative constant.
It is well known that problem (1.2) has a real and discrete spectrum
where each eigenvalue is repeated according to its multiplicity. Our results are stated as follows.
Theorem 1.1 Let $(M^{n}, \langle, \rangle)$ be an $n(\geq 2)$-dimensional complete Riemannian manifold isometrically immersed in the Euclidean space $\mathbb{R}^{N}$ by $\Psi$, $\Omega$ is a bounded domain in $M^{n}$. $A$ is a positive definite symmetric (1, 1)-tensor on $M^{n}$. Assume that the eigenvalues of $A$ on $\Omega$ are bounded below by a positive constant $b$ (that is, $\bar{\lambda}(A)|_{\Omega}\geq b)$ and that ${\rm tr}(\hbox{A})|_{\Omega}\leq c$. Then for the eigenvalues of problem (1.2),
where $B=-b+\sqrt{b^2+4(\lambda_{1}-a)}$ and $H$ is the mean curvature vector of the immersion $\Psi$.
First, we give the following lemma.
Lemma 2.1 Let $\lambda_{i}$ be the $i$-th eigenvalue of problem (1.2) and $u_{i}$ the orthonormal eigenfunction corresponding to $\lambda_{i}$ $({\rm i.e.} \displaystyle\int_{\Omega}u_{i}u_{j}=\delta_{ij})$. For any function $m_{\alpha}\in C^2(\bar{\Omega})$ satisfying
we have for any positive constant $\delta$,
where $||f||^2=\int_{\Omega}f^2$.
Proof We consider the function $T_{\alpha}=m_{\alpha}u_{1}-u_{1}\displaystyle\int_{\Omega} m_{\alpha}u_{1}^2$. Then, it is easy to check that $T_{\alpha}|_{\partial \Omega}=0$ and
Hence
It follows from the Rayleigh-Ritz inequality(or min-max principle) that
By virtue of (2.3), a direct calculation yields
Substituting (2.6) into inequality (2.5) and utilizing the Green's formula, we have
From the divergence theorem, we get
Then, putting (2.8)-(2.10) into (2.7), one get
Utilizing the divergence theorem again, it holds
By virtue of (2.11), (2.13) and the Cauchy's inequality, it is not difficult to get
Now we give the proof of Theorem 1.1:
Proof of Theorem 1.1 Let $x^1, x^2, \cdots, x^{N}$ be the standard coordinate functions on $\mathbb{R}^{N}$. We consider the $N\times N$ matrix
From the orthogonalization of Gram-Schmidt (QR-factorization theorem), we know that $D$ can be written by $ R=QD, $ where $Q=(q_{\alpha\beta})$ is an orthogonal $N\times N$ matrix and $R=(r_{\alpha\beta})$ is an upper triangular matrix. Hence, we have
Taking $m_{\alpha}=\sum\limits_{\gamma=1}^N q_{\alpha\gamma}x^{\gamma}$, thus $\displaystyle\int_{\Omega}m_{\alpha}u_{1}u_{l}=0 \quad {\rm for} \ l=2, \cdots, \alpha$. Applying Lemma 2.1 to $m_{\alpha}=\sum\limits_{\gamma=1}^N q_{\alpha\gamma}x^{\gamma}$ and summing on $\alpha$ from $1$ to $N$, we get
where
see [1, Lemma 2.1]. Since
Then, we obtain
where $B=-b+\sqrt{b^2+4(\lambda_{1}-a)}$ and $H$ is the mean curvature vector of its immersion $\Psi$.
Minimizing the right hand side of (2.17), one get
It is easy to get $\sum\limits_{\alpha=1}^{N}|\nabla m_{\alpha}|^2=n$ and $|\nabla m_{\alpha}|^2\leq 1 \ {\rm for}\ \alpha=1, \cdots, n$, see [6]. Therefore,
From (2.18) and (2.19), we have
This completes the proof of Theorem 1.1.
Corollary 2.2 Let $(M^{n}, \langle, \rangle)$ be an $n(\geq 2)$-dimensional complete Riemannian manifold isometrically immersed in the Euclidean space $\mathbb{R}^{N}$ by $\Psi$, $\Omega$ is a bounded domain in $M^{n}$. For the lower order eigenvalues of problem (1.1), where $p>0$, it holds that
where $C=\sqrt{p^2+4(\lambda_{1}-q)}$ and $H$ is the mean curvature vector of its immersion $\Psi$.
Corollary 2.3 Let $\Omega$ be a bounded domain in an $n(\geq 2)$-dimensional unit sphere $\mathbb{S}^{n}(1)$. For the lower order eigenvalues of problem (1.1), where $p>0$, It holds that
where $C=\sqrt{p^2+4(\lambda_{1}-q)}$.
Remark For the unit sphere $\mathbb{S}^{n}(1)$, by taking $\Omega=\mathbb{S}^{n}(1)$, $\partial \Omega=\emptyset$, we know that eigenvalues of problem (1.1) satisfy $\lambda_{1}=q$ and $\lambda_{2}=\cdots=\lambda_{n+1}=n^2+pn+q$. Then inequality in (2.21) become equality. So inequality (2.21) is sharp.