Suleĭmanova Spectra & Realization Theorems
The definitive solvable class of spectra with a single positive eigenvalue: trace nonnegativity, Hazel Perfect's companion matrix proof, Fiedler's symmetric tridiagonal realization, and Soules bases.
1. Definition & The Suleĭmanova Condition
In the spectral theory of nonnegative matrices, the most thoroughly understood family of spectra consists of real multisets possessing exactly one positive eigenvalue (the Perron root), with all remaining eigenvalues being nonpositive.
Definition 1.1 (Suleĭmanova Spectrum)
DefinitionA multiset of real numbers $\sigma = \{\lambda_0, \lambda_1, \dots, \lambda_{n-1}\} \subset \mathbb{R}$ is called a Suleĭmanova spectrum if:
$$\lambda_0 > 0 \ge \lambda_1 \ge \lambda_2 \ge \cdots \ge \lambda_{n-1}$$and the first trace condition (trace nonnegativity) is satisfied:
$$s_1 = \sum_{i=0}^{n-1} \lambda_i = \lambda_0 - \sum_{j=1}^{n-1} |\lambda_j| \ge 0$$For general candidate spectra, spectral nonnegativity requires verifying infinitely many nonlinear power-sum inequalities ($s_k = \operatorname{Tr}(A^k) \ge 0$), Newton-Girard relations, and Johnson-Loewy-London constraints. However, when all secondary eigenvalues are nonpositive:
- Even powers ($k = 2m$): Every term satisfies $\lambda_i^{2m} \ge 0$, ensuring $s_{2m} = \sum_{i=0}^{n-1} \lambda_i^{2m} > 0$ holds unconditionally.
- Odd powers ($k = 2m+1$): Because $\lambda_0 \ge |\lambda_j|$ for all $j \ge 1$, we have $\lambda_0^{2m+1} \ge \sum_{j=1}^{n-1} |\lambda_j|^{2m+1}$ whenever $\lambda_0 \ge \sum_{j=1}^{n-1} |\lambda_j|$. Hence all odd power sums $s_{2m+1} \ge 0$ are satisfied simultaneously.
Consequently, all higher-order trace obstructions vanish identically. The linear condition $\operatorname{Tr}(A) = s_1 \ge 0$ is the sole necessary obstacle.
2. Historical Development & Hazel Perfect's Proof
In 1949, the Soviet mathematician
In 1953 and 1955, the British mathematician
Theorem 2.1 (Suleĭmanova's Realization Theorem; Suleĭmanova 1949, Perfect 1953/1955)
TheoremLet $\sigma = \{\lambda_0, \lambda_1, \dots, \lambda_{n-1}\}$ be a multiset of real numbers such that:
$$\lambda_0 > 0 \ge \lambda_1 \ge \cdots \ge \lambda_{n-1} \quad \text{and} \quad \lambda_0 + \sum_{j=1}^{n-1} \lambda_j \ge 0$$Then $\sigma$ is realizable as the spectrum of an entrywise nonnegative matrix $A \in \mathcal{M}_n(\mathbb{R}_{\ge 0})$. If the inequality is strict ($s_1 > 0$), $A$ can be chosen strictly positive ($A > 0$).
Perfect established this by considering the monic polynomial $p(t) = \prod_{i=0}^{n-1} (t - \lambda_i) = t^n - c_1 t^{n-1} - \cdots - c_n$. She constructed an explicit similarity transformation:
$$A = S C(p) S^{-1} \ge 0$$
where $C(p)$ is the Frobenius companion matrix and $S$ is a lower-triangular matrix whose entries are derived from partial products of the nonpositive eigenvalues $\lambda_1, \dots, \lambda_{n-1}$. While constructive, the resulting matrix $A$ was generally asymmetric. Direct algebraic companion constructions were later simplified by
3. Fiedler's Theorem: Symmetric Realizability (1974)
For more than two decades following Perfect's work, it remained open whether a Suleĭmanova spectrum could always be realized by a symmetric nonnegative matrix ($A = A^T \ge 0$).
In 1974,
Theorem 3.1 (Fiedler's Symmetric Realization Theorem, 1974)
TheoremLet $\sigma = \{\lambda_0, \lambda_1, \dots, \lambda_{n-1}\}$ with $\lambda_0 > 0 \ge \lambda_1 \ge \dots \ge \lambda_{n-1}$. If $\sum_{i=0}^{n-1} \lambda_i \ge 0$, then there exists a symmetric, tridiagonal nonnegative matrix $A = A^T \ge 0$ having spectrum $\sigma$.
Fiedler's inductive proof constructs a sequence of symmetric matrices $A_1, A_2, \dots, A_n = A$ where at step $k$:
$$A_k = \begin{pmatrix} A_{k-1} & \mathbf{v}_k \\ \mathbf{v}_k^T & \alpha_k \end{pmatrix}$$By selecting the coupling vector $\mathbf{v}_k \ge 0$ and the diagonal scalar $\alpha_k \ge 0$, the eigenvalues of $A_k$ interlace precisely with those of $A_{k-1}$, adjoining $\lambda_k \le 0$ without shifting the previous spectrum. Fiedler's theorem established that there is no symmetry gap for Suleĭmanova spectra:
$$\sigma \text{ is Sule\u012dmanova} \implies \sigma \in \operatorname{SNIEP} \iff \sigma \in \operatorname{RNIEP} \iff \sum_{i=0}^{n-1} \lambda_i \ge 0$$4. Soules Bases & Simplicial Spectral Geometry
In 1983,
Definition 4.1 (Soules Matrices and Bases; Soules 1983)
DefinitionAn orthogonal matrix $R = [\mathbf{r}_0, \mathbf{r}_1, \dots, \mathbf{r}_{n-1}] \in \mathbb{R}^{n \times n}$ is called a Soules matrix if:
- The first column is strictly positive: $\mathbf{r}_0 = \frac{1}{\sqrt{n}} \mathbf{1} = \frac{1}{\sqrt{n}}(1, 1, \dots, 1)^T$.
- For any Suleĭmanova spectrum $\Lambda = \operatorname{diag}(\lambda_0, \lambda_1, \dots, \lambda_{n-1})$, the reconstructed matrix: $$A = R \Lambda R^T = \sum_{i=0}^{n-1} \lambda_i \mathbf{r}_i \mathbf{r}_i^T$$ is entrywise nonnegative ($A \ge 0$).
In 1998,
Theorem 4.1 (Simplicial Geometry via Soules Bases; Elsner, Nabben, & Neumann 1998)
TheoremThe cone of Suleĭmanova spectra forms an extremal simplicial cone within the trace polytope of symmetric nonnegative matrices. Every Soules matrix acts as a universal geometric embedding of this cone into the positive semidefinite affine cone of matrices.
5. Generalizations Beyond Suleĭmanova Spectra
Because Suleĭmanova's condition is an exact criterion for single-positive spectra, researchers have extended its mechanisms to broader configurations:
Theorem 5.1 (Soto's Partition Theorem; Soto 2003)
TheoremLet $\sigma = \Gamma_1 \cup \cdots \cup \Gamma_k$ be a partition of a real spectrum into disjoint sub-multisets. If each $\Gamma_j$ satisfies a localized Suleĭmanova condition relative to an auxiliary positive eigenvalue, then $\sigma$ is realizable by a block-partitioned nonnegative matrix.
Complex Spectra (Monov 2005 )
Extended the Suleĭmanova framework to complex conjugate pairs whose non-Perron eigenvalues have nonpositive real parts: $\lambda_0 > 0$ and $\operatorname{Re}(\lambda_j) \le 0$, under modulus and trace bounds.
Negative Real Parts (Laffey & Šmigoc 2007 )
Established constructive realization theorems for spectra whose non-Perron eigenvalues have strictly negative real parts, exploiting companion matrix pencils and similarity reductions.
Multiple Positive Roots
When a spectrum has two positive eigenvalues $\{\lambda_0, \lambda_1 > 0 \ge \lambda_2 \ge \cdots \ge \lambda_{n-1}\}$, the trace $s_1$ alone is no longer sufficient; higher-order traces $s_3, s_5$ generate nonlinear semi-algebraic boundaries.
6. Interactive Solver & Matrix Synthesis
The Spectra Realizer tool on this research hub allows live synthesis of both asymmetric companion realizations and symmetric Fiedler/Soules matrices for any valid Suleĭmanova spectrum:
Interactive Spectra Realizer
Input your candidate eigenvalues, verify the Suleĭmanova trace condition, and generate the realization matrix live.
7. Key Literature & Academic Citations
Pioneering and foundational publications on Suleĭmanova spectra, Fiedler tridiagonal matrices, and Soules basesThe publications below are sourced directly from the global NIEP Comprehensive Bibliography. Each record provides academic metadata, research notes, links to primary literature, and one-click BibTeX exports:
8. See Also & Related Theory Articles
Symmetric NIEP (SNIEP)
Orthogonal eigenspaces, Fiedler theorems, Soules bases, and trace polytopes.
Real NIEP (RNIEP)
Investigating general real spectra and the Laffey-Loewy separation spectrum $\{4, 2, 2, -4, -4\}$.
Karpelevič Region
Kolmogorov's problem, Farey boundary arcs, and algebraic polynomials $\mathcal{K}_n$.
NIEP Theoretical Survey
The master theoretical survey covering Perron-Frobenius theory, trace inequalities, and modern semi-algebraic cones.