Solve the Global Minima Problem in Two Variable Functions

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Homework Help Overview

The discussion revolves around determining global minima for two-variable functions, particularly focusing on the challenges of identifying convexity and local minima.

Discussion Character

  • Exploratory, Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants discuss the relationship between local and global minima, with one noting the difficulty in establishing convexity. There are suggestions to calculate partial derivatives and consider the Hessian matrix. Some participants express uncertainty about how to proceed.

Discussion Status

The conversation is ongoing, with various approaches being explored. Some participants have offered guidance on calculating derivatives and analyzing minima, while others are questioning assumptions about convexity and the nature of the function being discussed.

Contextual Notes

There is mention of the need to identify local minima and analyze them to find global minima, as well as a discussion about the implications of convexity on the uniqueness of global minima.

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Homework Statement
Let ##f(x,y)=\arctan(4\sin^2(y)+3\ln(x^2+1))## show that it has ##\infty## global minima
Relevant Equations
No relevant equations
I'm always struggling understand how to determine if a two variable function has global minima, I know that if I find a local minima and the function is convex than the local minima is also a global minima, in this case is really difficult to determine if the function is convex.

Sorry if I don't post any attempt but I got no clue how to do this.
 
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I'm afraid you will have to calculate the partial derivatives and consider where they vanish. Also look up the Hesse matrix.
 
Archimedess said:
no clue how to do this.
Not good enough per the PF guidelines !
Least you could do is find and discuss a few minima, remark that ##\sin^2## is periodical, etc ...
 
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No, it is not convex. A convex function has a UNIQUE global minimum.

Edit: OK, I'm going to back off on that statement. That's true for a strictly convex function. But you could imagine a convex function whose set of global minima was a finite flat region. For instance, a function with ##f(x,y) = 0## on the circle of radius 1, and positive elsewhere. That would qualify as a convex function with infinitely many global minima.

But that's not the reason for infinitely many minima here. @BvU has already identified the reason in comment #3.

To find the global minima, you're going to have to identify all the local minima. Then analyze them and find which subset of those have minimal values of ##f(x, y)##.
 

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