Code for Ubiquity of synonymity: almost all large binary trees are not uniquely identified by their spectra or their immanantal polynomials by Matsen and Evans
[Link to paper] (http://arxiv.org/abs/q-bio/0512010)
There are several common ways to encode a tree as a matrix, such as the adjacency matrix, the Laplacian matrix (that is, the infinitesimal generator of the natural random walk), and the matrix of pairwise distances between leaves. Such representations involve a specific labeling of the vertices or at least the leaves, and so it is natural to attempt to identify trees by some feature of the associated matrices that is invariant under relabeling. An obvious candidate is the spectrum of eigenvalues (or, equivalently, the characteristic polynomial). We show for any of these choices of matrix that the fraction of binary trees with a unique spectrum goes to zero as the number of leaves goes to infinity. We investigate the rate of convergence of the above fraction to zero using numerical methods. For the adjacency and Laplacian matrices, we show that that the a priori more informative immanantal polynomials have no greater power to distinguish between trees.
immanantal/check_results
- checks to make sure that the trees in Figure 1(b) have the exchange property with respect to the immanantal polynomialsimmanantal/coimm_results
- coimmanantal pairs of treesimmanantal/n_spectra_results
- number of immanantal polynomials
This empty diff shows that the hypotheses of Lemma 3 are satisfied for the trees in Figure 1(b):
diff immanantal/check_results/a immanantal/check_results/b
distance/check_results
- checks to make sure that the trees in Figure 1(b) have the exchange property with respect to the distance matrix spectrumdistance/n_spectra_results
- the number of spectra
This empty diff shows that the hypotheses of Lemma 4 are satisfied for the trees in Figure 1(b):
diff distance/check_results/dist_poly1.txt distance/check_results/dist_poly2.txt