Quadratic Forms, An Introduction

Introduction

A quadratic equation has a variable x that is squared, and possibly a linear term, and possibly a constant term.  (Quad often means 4 in English, as in quadrilateral or quadruplets, but in latin, quad meant square, and the word quadratic reflects this early etimology.)  In general, a quadratic form has many variables, and each term has degree 2 or less.  An example is shown below.

7x2 + 13y2 - 17z2 + 11xy - 5xz + 9x + 4y - 67 = 0

This is a 3 dimensional example; it defines a quadratic surface in 3 space.  You are probably more familiar with quadratic forms in two variables.  These generate the conic sections in the plane: parabola, ellipse, and hyperbola.  We'll get to all this later, but first, let's talk about quadratic forms and matrices.

Let M be a fixed matrix of real numbers and let x be an unspecified vector in Rn.  The components of x are indeterminants, i.e. variables.  The quadratic form associated with M is x*M*xT, using standard matrix multiplication.  Expand this all out, and the coefficient on the squared term xi2 is Mi,i, while the coefficient on the mixed term xixj is Mi,j+Mj,i.

Note that there are different matrices that produce the same quadratic form.  We could subtract 1 from Mi,j and add 1 to Mj,i, and the result would be the same.  By convention, M is assumed to be symmetric.

Conversely, every quadratic form comes from a symmetric matrix M.  Take the coefficient on xi2 and place it in Mi,i.  Take half the coefficient of xixj and place this in Mi,j and Mj,i.

If M is diagonal, the result is a diagonal form.  There are no mixed terms, no linear terms, no constant terms; just a series of squared terms.  If we can characterize the diagonal forms, we're halfway home.  This is because a rigid rotation turns the quadratic form into a diagonal form.  More on this later.