We solve by Chebyshev spectral collocation some genuinely nonlinear Liouville-Bratu-Gelfand type, 1D and a 2D boundary value problems. The problems are formulated on the square domain $[-1, 1]\times[-1, 1]$ and the boundary condition attached is a homogeneous Dirichlet one. We pay a particular attention to the bifurcation branch on which a solution is searched and try to estimate empirically the attraction basin for each bifurcation variety. The first eigenvector approximating the corresponding the first eigenfunction of the linear problem is used as an initial guess in solving the non-linear algebraic system of Chebyshev collocation to find the "small" solution. For the same value of the bifurcation parameter we use another initial guess, namely lowest basis function (1 point approximation), to find the "big" solution. The Newton-Kantorovich method solves very fast the non-linear algebraic system in no more than eight iterations. Beyond being exact, the method is numerically stable, robust and easy to implement. Actually, the MATLAB code essentially contains three programming lines. It by far surpasses in simplicity and accuracy various methods used to solve some well-known problems. We end up by providing some numerical and graphical outcomes in order to underline the validity and the effectiveness of our method, i.e., norms of Newton updates in solving the algebraic systems and the decreasing rate of Chebyshev coeffcients of solution.
翻译:我们通过Chebyshev 光谱同化来解决一些真正非线性Liouville-Bratu-Gelfand 类型、 1D 和 2D 边界值问题。 问题是在 $[ 1, 1] 时间[ 1] 平方域 $1, 附带的边界条件是同质的 Dirichlet 之一。 我们特别关注搜索解决方案所基于的两面分解分支, 并尝试根据经验来估计每个两面形的吸引区 。 第一次对相应的线性问题首个直线性功能进行比对准的 。 在解决 Chebyshev 交点的非线性代谢系统非线性代谢性值系统寻找“ 小” 解决方案时, 问题在最初的两面值参数值相同, 即最低基函数(1 点近似) 找到“ 大” 解决方案。 Newton- Kantorov 方法在8 的代号中非常迅速地解决非线性平面性高位系统 。 不仅准确, 而且, 这种方法在数字化的解法中, 也以数字稳定、 坚固化和易化方法 提供了我们最精确的精确的精确的精确、 的精确性、 的精确性、 的精确性、 和精确性、 和精确性地的精确性- 和精确性- 的系统。