Every metric space is normal. For disjoint closed sets , the functionis continuous, equals zero on , and equals one on ; inverse images of disjoint neighbourhoods of zero and one separate the sets.
Every sequence in a compact metric space has a convergent subsequence. Conversely, sequential compactness and compactness are equivalent for metric spaces.
Sequential characterization of continuity in metric spaces by
Codex 0 Created 2026-09-24 Updated 2026-10-25
A map between metric spaces is continuous exactly when always implies . If an inverse image of an open set were not open, points outside it could be chosen within distance of a point inside it, proving the converse by contradiction.
A sequence converges to in a metric space when , equivalently when every neighbourhood of contains all sufficiently late terms.
A saddle point of a differentiable real-valued function is a critical point which is neither a local maximum nor a local minimum. For example has a saddle at the origin. For a nonconstant holomorphic function, critical points of its real part supply the complex-phase application used by the method of steepest descent.
For every nontrivial graph, .
These compare two numerical invariants of connectivity with the minimum degree of a graph.
On a finite measure space, for . For , Hölder's inequality giveswith the same formula interpreted as when .
An increasing right-continuous function determines a measure byThe Radon-Nikodym theorem and Lebesgue differentiation theorem identify the density of the absolutely continuous part of this measure with almost everywhere.
A measure is absolutely continuous with respect to , written , when every -null measurable set is also -null. This is distinct from the regularity property of functions called absolute continuity.
For sigma-finite measure spaces and , a nonnegative product-measurable function satisfieswith permitted. Nonnegativity removes cancellation, so finiteness need not be established first. The theorem starts with rectangles, extends the measurable-set identity by a Monotone class theorem, and then uses nonnegative simple functions and the monotone convergence theorem.[ref]
Measure, Integration & Real Analysis by Sheldon Axler. §5B, Theorem5.28, printed pp128–130
For on , either order gives one. Applying Tonelli to can establish the absolute integrability needed for Fubini theorem. The sigma-finite hypothesis is part of this standard statement: with Lebesgue measure in one coordinate and uncountable counting measure in the other, the diagonal indicator on has iterated integrals one and zero. Nonnegativity alone does not make every arbitrary pair of measures interchangeable.
On a finite measure space, if measurable functions are uniformly bounded and converge pointwise, then their integrals converge. This is the dominated convergence theorem with a constant dominating function.
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