# Problem 2.10 of Boyd & Vandenberghe's Convex Optimization

Let C $$\subseteq$$ $$\Re^n$$ be the solution set of a quadratic inequality, $$C = \{x \in \Re^n \mid x^TAx +b^Tx + c \leq 0\}$$ where $$A \in \Re$$, b $$\in \Re^n$$ and c $$\in \Re$$. We want to show that $$C$$ is convex if $$A \succeq 0$$.

This is one of the problem of Convex Optimization. The solution is provided. But I want to prove it through another way in which we assume that if $$x_1$$ and $$x_2$$ are in the set then for $$0\leq \lambda\leq1$$ the point $$\lambda x_1+(1-\lambda)x_2$$ is also in the set.

I tried it and I end up with following equation $$\lambda^2x_1^TAx_1+\lambda x_1^TAx_2-\lambda^2 x_1^TAx_2+\lambda x_2^TAx_1-\lambda^2 x_2^TAx_1+(1-\lambda)^2x_2^TAx_2+b^T\lambda x_1+(1-\lambda)b^Tx_2+c$$ I do not know how to show that the above quantity is less than or equal to zero. Any help in this regard will be much appreciated. Thanks in advance.

• Which "Convex Optimization book" is it exactly ? There are plenty of such books. – Gabriel Romon May 4 '18 at 9:10
• Its convex optimization book by Stephen Boyd. – Frank Moses May 4 '18 at 9:11
• Group the terms related to the affine part and those related to the quadratic part. Then use the fact that $A \geq 0$. – LinAlg May 4 '18 at 11:32

If $f(x)=x^TAx+b^Tx+c$ and $\lambda_1+\lambda_2=1$ then I think
$$f(\lambda_1x_1+\lambda_2x_2) = \lambda_1f(x_1)+\lambda_2f(x_2)-\lambda_1\lambda_2(x_1-x_2)^TA(x_1-x_2)$$
• how can you not have a term with $\lambda_1^2$? – LinAlg May 4 '18 at 11:29
• @LinAlg On the right-hand side $x_1^TAx_1$ appears with coefficient $\lambda_1-\lambda_1\lambda_2=\lambda_1^2$. And I implicitly assumed $A$ is symmetric. – Michal Adamaszek May 4 '18 at 11:38
• Thank you for your answer. I think even if we do not assume $A$ to be symmetric the right side of your equation matches perfectly with my equation. But I do not know which steps you took to obtain the right side of your equation from my equation. – Frank Moses May 8 '18 at 2:38