Liz Balsam Advisor: Bahman Kalantari.  Term coined by Dr. Kalantari  Polynomial + graph  Definition: the art and science of visualization in the approximation.

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Presentation transcript:

Liz Balsam Advisor: Bahman Kalantari

 Term coined by Dr. Kalantari  Polynomial + graph  Definition: the art and science of visualization in the approximation of zeroes of complex polynomials  Each image is called a “polynomiograph”

 How do we find the solutions to a complex polynomial equation?  Classic question  Not at all an easy question  We only have closed formulas for polynomials of degree n < 5  The rest is left up to approximations

 Best known method for approximating roots  Formula:  Where z can be either a real or complex input, in which case z = x + iy  Makes use of an iteration function

 Machine into which you input the output and eventually hope that the terms converge to some value  Definition: if θ is a root of the polynomial p, then it is a fixed point of the iteration function F  If p(θ) = 0, then F(θ) = θ

 Want to approximate √2  i.e. solve f(x) = x 2 – 2  Newton’s formula for this f(x) results in an iteration function nxnxn 01 1N(x 0 ) N(x 1 ) N(x 2 ) N(x 3 ) N(x 4 )

 Did it work?  True value of √2 =  Indeed our expectations hold:  Newton’s method seems to converge at i.e. it is a fixed point of N(x)  is a root of f(x) = x 2 – 2

 Formally: Given a set of n Euclidean points, find a point in their convex hull that maximizes the product of the distances to the n given points.  Informally: In an art gallery with, say, 3 paintings, what is the optimal position for a camera?

 Consider three points in the plane  Their convex hull (the minimal set containing all the points) is naturally a triangle  Would the camera be somewhere along the edges of the triangle or inside the triangle?

 Answer: the point that would maximize the product of the distances is at the boundary

 Why is the optimal point at the boundary?  Is it unique?  How do you find the optimal point?

 We will use geometry, polynomial root- finding methods, and polynomiography to solve these problems  How you find roots of polynomial equations ≈ how you find the optimal point  Why and how this is so… To Be Discovered  Consider the Algebraic Art Gallery Problem in 3D  Explore other geometric problems related to root-finding