Is the Converse of Polynomial Convexity True in Complex Analysis?

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In summary, Gunning and Rossi's book on complex analysis in several variables defines "polynomial convexity" for a domain D, which is a connected open set. The purpose of this concept is to show that if D is polynomially convex, then an analytic function on D can be approximated by polynomials with uniform convergence on compact subsets of D. However, the converse is not true in C^n, n >1, but it is true in C. This was confirmed in a discussion on the sci.math group."
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lark
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I've been reading Gunning and Rossi's book on complex analysis in several variables (good book!).
They define something called "polynomial convexity" for a domain D. "domain" = connected open set, I think.
The point of polynomial convexity is that if D [tex]\subset C^n[/tex] is polynomially convex, then an analytic function on D can be approximated by polynomials, and the approximation is uniform on compact subsets of D.
Is the converse true? i.e. if D isn't polynomially convex, is there a function that's analytic on D that can't be approximated by polynomials uniformly on compact subsets?
If D isn't polynomially convex, that means there's a compact subset K of D and a point w [tex]\notin[/tex] D such that
|p(w)| [tex]\leq[/tex] max(|p(z)|, z [tex]\in[/tex] K), for all polynomials p.
Laura
 
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What is polynomial convexity?

Polynomial convexity is a mathematical concept that refers to the shape of a polynomial function. A polynomial function is considered convex if it is always increasing or decreasing, and its graph has no "dips".

How is polynomial convexity different from polynomial concavity?

Polynomial convexity and concavity are two sides of the same coin. A polynomial function is considered concave if it is always decreasing or increasing, and its graph has no "bumps". In other words, a convex polynomial has a "smile" shape, while a concave polynomial has a "frown" shape.

What are the applications of polynomial convexity?

Polynomial convexity has many applications in various fields, including economics, physics, and engineering. In economics, it is used to analyze production functions and cost curves. In physics, it is used to model the behavior of particles. In engineering, it is used to optimize designs and analyze systems.

How can polynomial convexity be determined?

There are several methods for determining polynomial convexity. One way is to graph the polynomial function and visually inspect if it has a "smile" shape. Another way is to calculate the second derivative of the function. If the second derivative is always positive, the function is convex. If it is always negative, the function is concave.

What are the properties of a convex polynomial?

A convex polynomial has several important properties. It has a unique minimum value, and any local minimum is also the global minimum. It is also continuous and differentiable everywhere. In addition, the tangent line at any point on the graph of a convex polynomial lies above the curve.

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