Is Set M1 Convex? A Proof Using Mathematical Induction

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In summary, the conversation was about checking if a set is convex given a function and a set of points. The set was defined as the set of points where the function output is greater than 1. The process involved showing that the function satisfies the definition of convexity and using a theorem about convex functions to conclude that the set is convex.
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mathmari
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Hey! :eek:

We have the function $\displaystyle{y=f(x_1, x_2)=x_1\cdot x_2^2}$ and the set $M_1=\{x\in [0, \infty)^2 \mid f(x_1, x_2)>1\}$.

I want to check if the set is convex. Let $x=(x_1, x_2) , y=(y_1, y_2)\in M_1$, then $x_1\cdot x_2^2>1$ and $y_1\cdot y_2^2>1$.

We want to show that \begin{equation*}\lambda x+(1-\lambda )y=\lambda (x_1, x_2)+(1-\lambda )(y_1, y_2)=(\lambda x_1+(1-\lambda )y_1, \lambda x_2 +(1-\lambda )y_2)\in M_1\end{equation*} so we have to show that \begin{equation*}f\left (\lambda x_1+(1-\lambda )y_1, \lambda x_2 +(1-\lambda )y_2\right )>1\end{equation*}

We have the following:
\begin{align*}f&\left (\lambda x_1+(1-\lambda )y_1, \lambda x_2 +(1-\lambda )y_2\right )=(\lambda x_1+(1-\lambda )y_1)\cdot( \lambda x_2 +(1-\lambda )y_2)^2 \\ &=(\lambda x_1+(1-\lambda )y_1)\cdot( \lambda^2 x_2^2+2\lambda x_2(1-\lambda )y_2 +(1-\lambda )^2y_2^2)\\ &= \lambda x_1\cdot( \lambda^2 x_2^2+2\lambda (1-\lambda )x_2y_2 +(1-\lambda )^2y_2^2)+(1-\lambda )y_1\cdot( \lambda^2 x_2^2+2\lambda (1-\lambda )x_2y_2 +(1-\lambda )^2y_2^2) \\ & = \lambda^3 x_1x_2^2+2\lambda^2 (1-\lambda )x_1 x_2y_2 +\lambda (1-\lambda )^2x_1 y_2^2+ \lambda^2 (1-\lambda )x_2^2y_1+2\lambda (1-\lambda )^2x_2y_1y_2 +(1-\lambda )^3y_1y_2^2 \\ & > \lambda^3 +2\lambda^2 (1-\lambda )x_1 x_2y_2 +\lambda (1-\lambda )^2x_1 y_2^2+ \lambda^2 (1-\lambda )x_2^2y_1+2\lambda (1-\lambda )^2x_2y_1y_2 +(1-\lambda )^3\end{align*}

Is this correct so far? (Wondering)

How could we continue? (Wondering)
 
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mathmari said:
We have the function $\displaystyle{y=f(x_1, x_2)=x_1\cdot x_2^2}$ and the set $M_1=\{x\in [0, \infty)^2 \mid f(x_1, x_2)>1\}$.
I want to check if the set is convex.
Let $x=(x_1, x_2) , y=(y_1, y_2)\in M_1$, then $x_1\cdot x_2^2>1$ and $y_1\cdot y_2^2>1$.
We want to show that \begin{equation*}\lambda x+(1-\lambda )y=\lambda (x_1, x_2)+(1-\lambda )(y_1, y_2)=(\lambda x_1+(1-\lambda )y_1, \lambda x_2 +(1-\lambda )y_2)\in M_1\end{equation*} so we have to show that \begin{equation*}f\left (\lambda x_1+(1-\lambda )y_1, \lambda x_2 +(1-\lambda )y_2\right )>1\end{equation*}
We have the following:
\begin{align*}f&\left (\lambda x_1+(1-\lambda )y_1, \lambda x_2 +(1-\lambda )y_2\right )=(\lambda x_1+(1-\lambda )y_1)\cdot( \lambda x_2 +(1-\lambda )y_2)^2 \\ &=(\lambda x_1+(1-\lambda )y_1)\cdot( \lambda^2 x_2^2+2\lambda x_2(1-\lambda )y_2 +(1-\lambda )^2y_2^2)\\ &= \lambda x_1\cdot( \lambda^2 x_2^2+2\lambda (1-\lambda )x_2y_2 +(1-\lambda )^2y_2^2)+(1-\lambda )y_1\cdot( \lambda^2 x_2^2+2\lambda (1-\lambda )x_2y_2 +(1-\lambda )^2y_2^2) \\ & = \lambda^3 x_1x_2^2+2\lambda^2 (1-\lambda )x_1 x_2y_2 +\lambda (1-\lambda )^2x_1 y_2^2+ \lambda^2 (1-\lambda )x_2^2y_1+2\lambda (1-\lambda )^2x_2y_1y_2 +(1-\lambda )^3y_1y_2^2 \\ & > \lambda^3 +2\lambda^2 (1-\lambda )x_1 x_2y_2 +\lambda (1-\lambda )^2x_1 y_2^2+ \lambda^2 (1-\lambda )x_2^2y_1+2\lambda (1-\lambda )^2x_2y_1y_2 +(1-\lambda )^3\end{align*}

Is this correct so far? (Wondering)
It may be correct, but it's too complicated to be helpful. I would be surprised if you could solve this problem by working directly from the definition of convexity.

The condition for $(x,y)$ to be in $M_1$ is $xy^2>1.$ If you write that as $y > \dfrac1{\sqrt x}$, it says that $(x,y)$ lies above the graph of the function $y = \dfrac1{\sqrt x}$. But that function is a convex function (because its second derivative is positive), and there is then a theorem to say that the region above its graph is a convex set.
 
  • #3
I got it! (Nerd)

Thank you very much! (Smile)
 

Related to Is Set M1 Convex? A Proof Using Mathematical Induction

1. What is a convex set?

A convex set is a set in which any line segment connecting two points in the set lies entirely within the set. In other words, a convex set is a set that does not have any indentations or holes.

2. How do you determine if a set is convex?

To determine if a set is convex, you can use the definition of a convex set or the convexity criterion. The convexity criterion states that a set is convex if, for any two points in the set, all points on the line segment connecting them are also in the set.

3. What is the difference between a convex set and a non-convex set?

The main difference between a convex set and a non-convex set is that a convex set has no indentations or holes, while a non-convex set may have one or more of these features. Additionally, all points on a line segment connecting two points in a convex set will also be in the set, while this may not be true for a non-convex set.

4. Why is it important to check if a set is convex?

Checking if a set is convex is important because it can help in solving optimization problems and determining the properties and behaviors of a set. Convex sets have many useful properties, such as all local minima being global minima, and can simplify mathematical calculations and proofs.

5. Can a set be both convex and non-convex?

No, a set cannot be both convex and non-convex. By definition, a set is either convex or non-convex. It is possible for a set to have both convex and non-convex subsets, but the set as a whole can only be one or the other.

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