Represent the quadratic form by the symmetric matrixThe spectral theorem for real symmetric matrices gives an orthogonal matrix and real eigenvalues such that . In the orthogonal change of coordinates , the equation becomes .
If both eigenvalues are positive, this is an ellipse with semiaxes and . Conversely, a zero eigenvalue makes the set either empty or unbounded along that coordinate, while two negative eigenvalues give the empty set. Opposite signs give an unbounded hyperbola. A negative eigenvalue together with a zero one also gives the empty set. None of those cases is an ellipse. Therefore the exact condition is that be a symmetric positive-definite matrix.
The sum and product of its eigenvalues are its matrix trace and determinant:Two real numbers are both positive precisely when their sum and product are positive. ThusAn orthogonal transformation preserves area. Using i gives the quadratic-form ellipse area
Eliminate using the plane equation. The orthogonal projection consists exactly of the points satisfyingsince each such lifts uniquely to on the intersection. Translating to the center of an ellipse with and givesThe symmetric matrix of this quadratic form is , whose eigenvalues are and . Thus it is a symmetric positive-definite matrix, and the projected curve is an ellipse. The quadratic-form ellipse area, with the right-hand side scaled by , isFor example, the orthogonal change of coordinates , gives semiaxes and , with the same product.
Let be the filled projected ellipse. The part of the plane bounded by is the parametrized surfaceIts tangent vectors satisfyThe surface area is thereforeThis also illustrates the orthogonal projection area formula: the unit normal to the plane has vertical component , so projection multiplies area by .
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