import { GraphSpec } from '../spec';
import { SeededRandom, TestEdge, TestNode } from './types';
/**
 * Compute and store full spectrum of graph adjacency matrix.
 * Uses power iteration for dominant eigenvalue approximation.
 * @param nodes - Graph nodes
 * @param edges - Graph edges
 * @param spec - Graph specification
 * @param _rng - Random number generator (unused, kept for interface consistency)
 */
export declare const computeAndStoreSpectrum: (nodes: TestNode[], edges: TestEdge[], spec: GraphSpec, _rng: SeededRandom) => void;
/**
 * Compute and store algebraic connectivity (Fiedler value, λ₂ of Laplacian).
 * Algebraic connectivity measures how well-connected the graph is.
 * Uses Fiedler value bounds and approximation.
 * @param nodes - Graph nodes
 * @param edges - Graph edges
 * @param spec - Graph specification
 * @param _rng - Random number generator (unused, kept for interface consistency)
 */
export declare const computeAndStoreAlgebraicConnectivity: (nodes: TestNode[], edges: TestEdge[], spec: GraphSpec, _rng: SeededRandom) => void;
/**
 * Compute and store spectral radius (largest eigenvalue).
 * Spectral radius relates to graph expansion and mixing rate.
 * Uses power iteration for approximation.
 * @param nodes - Graph nodes
 * @param edges - Graph edges
 * @param spec - Graph specification
 * @param _rng - Random number generator (unused, kept for interface consistency)
 */
export declare const computeAndStoreSpectralRadius: (nodes: TestNode[], edges: TestEdge[], spec: GraphSpec, _rng: SeededRandom) => void;
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