Inequality proof - for determining convex set

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Discussion Overview

The discussion revolves around proving that a specific set defined by the inequality $\Omega = \{ \textbf{x} \in \mathbb{R}^2 | x_1^2 - x_2 \leq 6 \}$ is convex. Participants explore the necessary conditions for convexity and how to demonstrate that a linear combination of points in the set also lies within the set.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant expresses difficulty in proving the convexity of the set by expanding the left-hand side of the inequality after substituting a linear combination of two points.
  • Another participant suggests that the problem can be approached graphically, indicating that any weighted mean of two points above the parabola defined by the inequality will also be above that parabola.
  • A later reply proposes a reformulation of the problem, leading to the need to prove that a specific expression involving $x_1$ and $y_1$ is non-negative.
  • One participant claims to have simplified the expression and shows that it can be represented as a square, which is non-negative, thus supporting the argument for convexity.

Areas of Agreement / Disagreement

Participants do not reach a consensus, as there are varying approaches and methods proposed to tackle the proof of convexity. Some participants agree on the steps taken, while others continue to seek clarification or alternative methods.

Contextual Notes

Participants rely on assumptions about the properties of the functions involved and the definitions of convexity, which may not be explicitly stated. The discussion includes unresolved mathematical steps and simplifications that are not universally accepted.

numbersense
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I am stuck at the inequality proof of this convext set problem.

$\Omega = \{ \textbf{x} \in \mathbb{R}^2 | x_1^2 - x_2 \leq 6 \}$

The set should be a convex set, meaning for $\textbf{x}, \textbf{y} \in \mathbb{R}^2$ and $\theta \in [0,1]$, $\theta \textbf{x} + (1-\theta)\textbf{y}$ also belong to $\Omega$.

How can I show that $(\theta x_1 + (1-\theta)y_1)^2 - (\theta x_2 + (1-\theta)y_2) \leq 6$?

I am stuck after expanding the LHS.
\begin{align*}
& (\theta x_1 + (1-\theta)y_1)^2 - (\theta x_2 + (1-\theta)y_2) \\
=& \theta^2 x_1^2 + 2\theta(1 - \theta)x_1 y_1 + (1 - \theta)^2 y_1^2 - \theta x_2 - (1 - \theta) y_2
\end{align*}

Any hints or pointers are welcome. Thanks in advance.
 
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numbersense said:
I am stuck at the inequality proof of this convext set problem.

$\Omega = \{ \textbf{x} \in \mathbb{R}^2 | x_1^2 - x_2 \leq 6 \}$

The set should be a convex set, meaning for $\textbf{x}, \textbf{y} \in \mathbb{R}^2$ and $\theta \in [0,1]$, $\theta \textbf{x} + (1-\theta)\textbf{y}$ also belong to $\Omega$.

How can I show that $(\theta x_1 + (1-\theta)y_1)^2 - (\theta x_2 + (1-\theta)y_2) \leq 6$?

I am stuck after expanding the LHS.
\begin{align*}
& (\theta x_1 + (1-\theta)y_1)^2 - (\theta x_2 + (1-\theta)y_2) \\
=& \theta^2 x_1^2 + 2\theta(1 - \theta)x_1 y_1 + (1 - \theta)^2 y_1^2 - \theta x_2 - (1 - \theta) y_2
\end{align*}

Any hints or pointers are welcome. Thanks in advance.

Welcome to MHB, numbersense! :)

Graphically, your problem is that any weighted mean of 2 points above the parabola $x^2-6$ is also above that parabola.
Something like this:

View attachment 721

Summarized, your problem is that:
$$\text{Given} \\
\qquad x_2 \ge x_1^2 - 6 \qquad (1) \\
\qquad y_2 \ge y_1^2 - 6 \qquad (2) \\
\text{Proof that: } \theta x_2 + (1-\theta)y_2 \ge (\theta x_1 + (1-\theta)y_1)^2 - 6 \qquad (3)$$

Starting with the LHS of (3), we get with (1) and (2) that:
$$\theta x_2 + (1-\theta)y_2 \ge \theta (x_1^2 - 6) + (1-\theta)(y_1^2 - 6) = \theta x_1^2 + (1-\theta)y_1^2 - 6 \qquad (4)$$

So we're left to proof that:
$$(\theta x_1^2 + (1-\theta)y_1^2) - (\theta x_1 + (1-\theta)y_1)^2 \overset{?}{\ge} 0 \qquad (5)$$

Can you simplify that?
 

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Thank you I like Serena! I think I managed to simplify that.

\begin{align*}
& \theta x_1^2 + (1 - \theta) y_1^2 - (\theta x_1 + (1-\theta) y_1)^2 \\
=& \theta x_1^2 + (1-\theta)y_1^2 - ( \theta^2 x_1^2 + 2 (\theta - \theta^2) x_1 y_1 + (1-2\theta + \theta^2) y_1^2)\\
=& (\theta - \theta^2) x_1^2 - 2(\theta - \theta^2)x_1 y_1 + (\theta - \theta^2) y_1^2\\
=& \left((\theta - \theta^2)^\frac{1}{2} x_1 - (\theta - \theta^2)^\frac{1}{2} y_1\right)^2\\
\geq & 0
\end{align*}

$\theta - \theta^2 \geq 0$ as $\theta \in [0,1]$.
 
numbersense said:
Thank you I like Serena! I think I managed to simplify that.

\begin{align*}
& \theta x_1^2 + (1 - \theta) y_1^2 - (\theta x_1 + (1-\theta) y_1)^2 \\
=& \theta x_1^2 + (1-\theta)y_1^2 - ( \theta^2 x_1^2 + 2 (\theta - \theta^2) x_1 y_1 + (1-2\theta + \theta^2) y_1^2)\\
=& (\theta - \theta^2) x_1^2 - 2(\theta - \theta^2)x_1 y_1 + (\theta - \theta^2) y_1^2\\
=& \left((\theta - \theta^2)^\frac{1}{2} x_1 - (\theta - \theta^2)^\frac{1}{2} y_1\right)^2\\
\geq & 0
\end{align*}

$\theta - \theta^2 \geq 0$ as $\theta \in [0,1]$.

Yep! ;)
 

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