File:WX20211209-162608@2x.png

Figure 1. A comparison of the convergence of gradient descent (in green) and conjugate vector (in red) for minimizing a quadratic function. In theory, the conjugate gradient method converges in at most ${\displaystyle n}$ steps, where ${\displaystyle n}$ is the size of the matrix of the system (here ${\displaystyle n=2}$)