A real-valued function attains a global minimum at whenThe point is a global minimizer; is the minimum value. A global maximum reverses the inequality throughout the same domain of a function. Unlike a local minimum or local maximum, a global minimum or global maximum compares every permitted input, however distant. The domain of a function is part of the claim.
For on , completing the square giveswith equality exactly at . This proves that is the global minimum and that the two global minimizers are and . Neither is a strict global minimizer, because the other attains the same value; both are strict local minima. There is no global maximum on , whereas on the global maximum is , attained at zero.
Finding critical points supplies candidates rather than a global certificate. The squared expression above is beautiful because one inequality compares infinitely many inputs at once. A global minimum is always a local minimum under the relative-neighbourhood convention; the converse fails. For example, has a strict local minimum at , but as , so it has no global minimum on the real line.
Existence also matters: on has infimum zero and supremum one but attains neither a global minimum nor a global maximum. By the extreme value theorem, a continuous function on a nonempty closed interval attains both. To find those values, compare all interior critical numbers, including points where the derivative does not exist, and both endpoints. Checking only stationary points can miss a corner or an endpoint. [ref]
https://openstax.org/books/calculus-volume-1/pages/4-3-maxima-and-minima. Gilbert Strang and Edwin Herman, OpenStax Calculus Volume 1, §4.3: locating absolute extrema
A global minimizer is a point attaining the infimum of an objective. For an extended-real functional, it is usual to require a finite objective value; this excludes points outside its effective domain. A convention allowing as the attained value gives every point as a formal minimizer of the identically infinite function.
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