# Convex Functions: Proving g(x) is Convex

• russel.arnold
In summary, the conversation discusses a function f(X) defined on a convex set S that is a subset of Rn. It is assumed that f is positive throughout and then a new function g(x) is defined as the square of f(x). The main point of the conversation is to prove that if f(x) is convex, then g(x) is also convex. It is suggested that this topic be posted in the Calculus and Beyond Homework forum with an attempt at a solution.
russel.arnold
let f(X) : Rn --> R be a function defined on convex set S s.t S is a subset of
Rn (real space n-dim). Let f is positive throughout. Then define g(x) = (f(x))^2. Prove that if f(x) is convex then g(x) is also convex.

russel.arnold said:
let f(X) : Rn --> R be a function defined on convex set S s.t S is a subset of
Rn (real space n-dim). Let f is positive throughout. Then define g(x) = (f(x))^2. Prove that if f(x) is convex then g(x) is also convex.

This needs to be posted in the Calculus and Beyond Homework forum with your attempt at a solution.

## 1. What is a convex function?

A convex function is a mathematical function where any line segment connecting two points on the graph of the function lies above or on the graph. In other words, the function is always "curving up" and never "curving down".

## 2. How do you prove that a function is convex?

To prove that a function is convex, you must show that the second derivative of the function is always positive. This means that the function is always "curving up" and never "curving down".

## 3. What is the significance of proving that a function is convex?

Proving that a function is convex is important because convex functions have many desirable properties, such as having a unique global minimum and being easy to optimize. They are also commonly used in various fields of mathematics and science, such as economics and physics.

## 4. Can a function be both convex and concave?

No, a function cannot be both convex and concave at the same time. A convex function always curves up, while a concave function always curves down. However, a function can be neither convex nor concave, in which case it is considered a non-convex function.

## 5. How can I use convexity to solve optimization problems?

Convexity can be used to simplify and solve optimization problems. This is because convex functions have a unique global minimum, meaning that the optimal solution can be easily identified. Additionally, convexity allows for the use of efficient optimization algorithms.

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