Complex eigenvalues of real matrices mean rotations
The real vector space can be seen as in several ways: it depends on what we set as the (fixed a complex structure, is identified with and reciprocally, is determined by the choice of the analogous of ). When you have an -linear operator in with complex eigenvalues (that must be conjugate of each other) you can look for the appropriate way of see as in such a manner that becomes like multiplying by a complex number. Which one? The eigenvalue!! (one of them to your choice). Formally:
Lemma
Let be a -linear operator in . If has two conjugate complex eigenvalues and , then we can find a complex structure in in such a way that is like multiplication by in . Proof
The complex structure must be a such that , where is an eigenvalue of with by hypothesis . To see that we use the complexification of :
Assume the eigenvalues have module one. In the picture above we see in red the real vector space , with the usual base in red. If we take the complexified we extend and not as a line, but each one as a plane (the solid orange plane and the blue one). The whole system is a four dimensional real space (two dimensional complex space), the complex plane . The map has eigenvectors and (the black ones in the picture). When we apply this eigenvectors rotate inside their complex line y (the yellow and the blue transparent planes in the picture). This rotations (one of angle and other of since they are conjugates eigenvalues) compensate'' each other in such a way that they produce a rotation in the original real plane (the transparent red one).
This rotation of the original plane induces a complex structure in which is, in some sense, transversal: the red transparent plane is not a complex line, so it has no natural complex structure...