In mathematics, a homogeneous function is one with multiplicative scaling behaviour: if all its arguments are multiplied bya factor, then its value is multiplied by some power of this factor. For example, a homogeneous real-valued function of two variables x and y is a real-valued function that satisfies the condition for some constant k and all real numbers α. The constant k is called the degree of homogeneity. More generally, if is a function between two vector spaces over a fieldF, and k is an integer, then ƒ is said to be homogeneous of degree k if for all nonzero and. When the vector spaces involved are over the real numbers, a slightly less general form of homogeneity is often used, requiring only that hold for all α > 0. Homogeneous functions can also be defined for vector spaces with the origin deleted, a fact that is used in the definition of sheaves on projective space in algebraic geometry. More generally, if S ⊂ V is any subset that is invariant under scalar multiplication by elements of the field, then a homogeneous function from S to W can still be defined by.
Examples
Example 1
The function is homogeneous of degree 2: For example, suppose x = 2, y = 4 and t = 5. Then
, and
.
Linear functions
Any linear map is homogeneous of degree 1 since by the definition of linearity for all and. Similarly, any multilinear function is homogeneous of degree n since by the definition of multilinearity for all and,,...,. It follows that the n-th differential of a function between two Banach spacesX and Y is homogeneous of degree n.
in n variables define homogeneous functions . For example, is homogeneous of degree 10 since The degree is the sum of the exponents on the variables; in this example, 10 = 5+2+3. A homogeneous polynomial is a polynomial made up of a sum of monomials of the same degree. For example, is a homogeneous polynomial of degree 5. Homogeneous polynomials also define homogeneous functions. Given a homogeneous polynomial of degree k, it is possible to get a homogeneous function of degree 1 by raising to the power 1/k. So for example, for every k the following function is homogeneous of degree 1:
Min/max
For every set of weights, the following functions are homogeneous of degree 1:
Polarization
A multilinear function from the n-th Cartesian product of V with itself to the underlying field F gives rise to a homogeneous function by evaluating on the diagonal: The resulting function ƒ is a polynomial on the vector spaceV. Conversely, if F has characteristic zero, then given a homogeneous polynomial ƒ of degree n on V, the polarization of ƒ is a multilinear function on the n-th Cartesian product of V. The polarization is defined by: These two constructions, one of a homogeneous polynomial from a multilinear form and the other of a multilinear form from a homogeneous polynomial, are mutually inverse to one another. In finite dimensions, they establish an isomorphism of graded vector spaces from the symmetric algebra of V∗ to the algebra of homogeneous polynomials on V.
Rational functions
s formed as the ratio of two homogeneous polynomials are homogeneous functions off of the affine cone cut out by the zero locus of the denominator. Thus, if f is homogeneous of degree m and g is homogeneous of degree n, then f/g is homogeneous of degree m − n away from the zeros of g.
Non-examples
Logarithms
The natural logarithm scales additively and so is not homogeneous. This can be demonstrated with the following examples:,, and. This is because there is no k such that.
Affine functions
s do not scale multiplicatively.
Positive homogeneity
In the special case of vector spaces over the real numbers, the notion of positive homogeneity often plays a more important role than homogeneity in the above sense. A function is positively homogeneous of degree k if for all. Here k can be any real number. A continuous function which is homogeneous of degree k on Rn \ extends continuously to Rn if and only if. Positively homogeneous functions are characterized by Euler's homogeneous function theorem. Suppose that the function is continuously differentiable. Then ƒ is positively homogeneous of degree k if and only if This result follows at once by differentiating both sides of the equation with respect to α, applying the chain rule, and choosing to be 1. The converse holds by integrating. Specifically, let Since, Thus,. This implies. Therefore, : ƒ is positively homogeneous of degree k. As a consequence, suppose that is differentiable and homogeneous of degree k. Then its first-order partial derivatives are homogeneous of degree k − 1. The result follows fromEuler's theorem by commuting the operator with the partial derivative. One can specialise the theorem to the case of a function of a single real variable, in which case the function satisfies the ordinary differential equation This equation may be solved using an integrating factor approach, with solution, where.
A continuous function ƒ on Rn is homogeneous of degree k if and only if for all compactly supportedtest functions ; and nonzero real t. Equivalently, making a change of variable, ƒ is homogeneous of degree k if and only if for all t and all test functions. The last display makes it possible to define homogeneity of distributions. A distribution S is homogeneous of degree k if for all nonzero real t and all test functions. Here the angle brackets denote the pairing between distributions and test functions, and is the mapping of scalar division by the real number t.
