1·In math, when you see multiple value solutions, these are eigenvalues.
在数学中，当你看到许多值的解法时，这些就是特征值。
2·These are termed the eigenvalues.
这些被称为特征值。
3·For example, no function returns the eigenvalues of a matrix.
例如，它没有返回矩阵的特征值的函数。
4·If the operator's spectrum is discrete, the observable can only attain those discrete eigenvalues.
假如操作者光谱是发散的，可见仅能获得那些离散特征值。
5·Such technique pursues, through the study of the eigenvalues, the reduction of the dimensionality in the representation space.
这种方法是通过对特征值的研究，追求表征空间的维数压缩。
1·We prove the relativistic virial theorem, which gives simple criteria for the absence of embedded eigenvalues in certain regions of the continuous spectrum.
我们证明相对论维里定理，这定理对于连续谱空间里本征值的缺乏给出了简单的标准。
2·By using linear operator theory in L2 space, we proved that the operators of this kind has not more than denumerable positive eigenvalues.
运用L2空间上的线性算子理论，我们证明了这类算子存在至多可数个正的本征值。
3·The corresponding energy eigenvalues and exact electron eigenfunctions are deduced.
给出了相应的能量本征值和严格的电子波函数。
4·Through transforming the equations of motion of the system into state equations, the eigenvalues of the system can be solved to obtain the eigenvectors.
将运动方程化为状态方程，求解本征值问题获得结构系统的特征向量解。