Organisers: Jephian Lin (National Sun Yat-sen University, Taiwan) and Nand Polona Oblak (University of Ljubljiana)
A generalized adjacency matrix of a graph is a symmetric matrix whose off-diagonal entry is nonzero if and only if it corresponds to an edge of the graph, while the diagonal entries can be chosen as any real number. The inverse eigenvalue problem for graphs (IEPG) studies the generalized adjacency matrices of a given graph and aims to find the possible spectra of them.
Various related questions can be asked: What is the maximum nullity over all generalized adjacency matrices, and what is the minimum rank? What is the minimum number of distinct eigenvalues? Recently, new techniques, called the strong properties, are developed using the implicit function theorem and have found significant applications to the IEPG.
The minisymposium will present recent progress and open problems in IEPG.
- Mohammad Adm, Palestine Polytechnic University
- Wayne Barrett, Brigham Young University, USA
- Chassidy Bozeman, Mount Holyoke College, USA
- Boris Brimkov, Slippery Rock University, USA
- Bryan Curtis, University of Wyoming, USA
- Shaun Fallat, University of Regina, Canada
- Rupert Levene, University College Dublin, Ireland
- Shahla Nasserasr, Brandon University, Canada
- Polona Oblak, University of Ljubljana, Slovenia
- Carlos Saiago, Universidade NOVA de Lisboa, Portugal