/**
 * The MIT License (MIT)
 *
 * Copyright (c) 2013 Mikola Lysenko
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 * THE SOFTWARE.
 */
/**
 * The reverse Cuthill-Mckee method is a fast and effective preconditioner for reducing the bandwidth of sparse linear systems.
 * When solving a positive semidefinite linear system using Cholesky factorization, it greatly reduces fill-in.
 * It is a direct conversion to TS from {@link github.com/mikolalysenko/cuthill-mckee}
 * @param list - lower triangular non zeros from a symmetric sparse matrix.
 * @param dimension - matrix dimension
 * @returns A Float64Array where the value at each index represents the new position of the node
 *          in the bandwidth-reduced ordering.
 */
export declare function matrixCuthillMckee(list: number[][], dimension: number): Float64Array<ArrayBuffer>;
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