In mathematics, an equaliser is a set of arguments where two or more functions have equal values.
An equaliser is the solution set of an equation.
In certain contexts, a difference kernel is the equaliser of exactly two functions.
Let X and Y be sets.
Let f and g be functions, both from X to Y.
Then the equaliser of f and g is the set of elements x of X such that f(x) equals g(x) in Y.
Symbolically:
The equaliser may be denoted Eq(f, g) or a variation on that theme (such as with lowercase letters "eq").
In informal contexts, the notation {f = g} is common.
The definition above used two functions f and g, but there is no need to restrict to only two functions, or even to only finitely many functions.
In general, if F is a set of functions from X to Y, then the equaliser of the members of F is the set of elements x of X such that, given any two members f and g of F, f(x) equals g(x) in Y.
Symbolically:
This equaliser may be written as Eq(f, g, h, ...) if is the set {f, g, h, ...}.
In the latter case, one may also find {f = g = h = ···} in informal contexts.
As a degenerate case of the general definition, let F be a singleton {f}.
Since f(x) always equals itself, the equaliser must be the entire domain X.
As an even more degenerate case, let F be the empty set. Then the equaliser is again the entire domain X, since the universal quantification in the definition is vacuously true.
A binary equaliser (that is, an equaliser of just two functions) is also called a difference kernel. This may also be denoted DiffKer(f, g), Ker(f, g), or Ker(f − g). The last notation shows where this terminology comes from, and why it is most common in the context of abstract algebra: The difference kernel of f and g is simply the kernel of the difference f − g. Furthermore, the kernel of a single function f can be reconstructed as the difference kernel Eq(f, 0), where 0 is the constant function with value zero.
Of course, all of this presumes an algebraic context where the kernel of a function is the of zero under that function; that is not true in all situations.