Introduces the strong inner product property to construct infinite families of sign patterns allowing row orthogonality and develops algorithmic verification techniques.
The inverse eigenvalue problem of a graph: Multiplicities and minors
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
The inverse eigenvalue problem of a given graph $G$ is to determine all possible spectra of real symmetric matrices whose off-diagonal entries are governed by the adjacencies in $G$. Barrett et al. introduced the Strong Spectral Property (SSP) and the Strong Multiplicity Property (SMP) in [8]. In that paper it was shown that if a graph has a matrix with the SSP (or the SMP) then a supergraph has a matrix with the same spectrum (or ordered multiplicity list) augmented with simple eigenvalues if necessary, that is, subgraph monotonicity. In this paper we extend this to a form of minor monotonicity, with restrictions on where the new eigenvalues appear. These ideas are applied to solve the inverse eigenvalue problem for all graphs of order five, and to characterize forbidden minors of graphs having at most one multiple eigenvalue.
fields
math.CO 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Sign Patterns of Orthogonal Matrices and the Strong Inner Product Property
Introduces the strong inner product property to construct infinite families of sign patterns allowing row orthogonality and develops algorithmic verification techniques.