 Gradient descent preserves an eigenline for a cubic product

Let $A$ be real symmetric, let $b$ be a unit eigenvector satisfying $Ab=\lambda b$, and use scalar step sizes ${\alpha }_n$. The gradient of the displayed cubic polynomial function isOn the eigenline, $\nabla h(tb)=3\lambda t^{2}b$, so a gradient descent update remains on that same line and obeys the scalar recurrence in the title. Induction proves invariance for every iterate starting on the line, including an iterate that reaches zero. This is a statement about the geometry of the updates, not a convergence theorem: when $\lambda \ne 0$, the restriction $h(tb)=\lambda t^3$ is unbounded below in one direction.