To recall notation from last time, given a matrix we let denote the spectral radius, the modulus of the largest eigenvalue. We will let denote a Jordan block of a matrix, and will work with the convention that both the diagonal and super-diagonal have the eigenvalue (as opposed to the above-diagonal 1’s, as is standard). For example:

We define an ordering on the Jordan blocks of a matrix by considering the associated ordered pair (under the lexiographic order) where is the associated eigenvalue and is the size of the block.

Our goal here is to describe the behavior of projective transformations, by looking at iterations of them and qualitatively describing the dynamics. However first a few definitions are in order. Given a topological space and a continuous map we define the forward orbit of to be the set . The -limit set, denoted is the set of accumulation points of the forward orbit, where for a subset we define .

For the following defintions we will be considering positive projective space together with its projective transformations . Given a such projective transformation we may define to be the vector space spanned by the eigenvectors with largest modulus eigenvalue, more precisely . Using this we then define and as its projectivization.

As a quick example, consider the map and let be the triangle with vertices and . Here is the projective line containing and , and the forward orbit of any point in accumulates along this line; that is, .

There’s a very useful proposition from linear algebra which will help us understand the dynamics of projective transformations such as the example above which we will state here quickly. Given any there is a finite collection of (positive) projective subspaces such that if is a subset of their complement with nonempty interior, has nonempty interior, and the action of not only preserves but restricts to an orthogonal action on it.

The utility of this is best illustrated by considering another example: let be the following matrix

The eigenvalues of over the complex numbers are , and so . Also, is the (complex) span of the first three basis vectors, and so . The positive projectivization of is then a 2-sphere inside of the 3-sphere, the relevant subspaces are , , and the restriction of the action of to is simply

which is a rotation about the “”-axis (the overall constant factor of doesn’t matter under projectivization). Thus we may describe the dynamics of acting on as follows: there is a pair of two antipodal “repelling” fixed points and relative to them an equitorial 2-sphere . This sphere rotates under iterations of , and any other point of is attracted towards it.

This linear-algebra-inspired description of the dynamics on can be used to help us understand projective transformations preserving a more general properly convex subset . In fact; given a projective transformation we can say that the largest modulus of eigenvalue for actually occurs as a real eigenvalue, and out of all Jordan blocks for eigenvalues of that modulus, the largest occurs for the real one (In terms of the notation we have been developing, this says that there exists a most powerful Jordan block for with ). Furthermore, the fixed set for this must lie on the boundary.

To see this, let be the union of the projective subspaces furnished for us by the linear algebra proposition above, and consider the , which is then a subset of by the proposition. Intersecting this with gives a compact, convex set preserved by , and so by the Brower fixed point theorem, there is a fixed point . Interpreting this, we have , and so for some . But we already know that which means that , and so the radius is in fact achieved by a real eigenvalue. Also, because we began with a non-elliptic transformation, fixes no points in the interior of and so our fixed point must lie on the boundary.

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