Lebesgue spaces
E87728
Lebesgue spaces are function spaces, denoted \(L^p\), that consist of measurable functions whose absolute values raised to the \(p\)-th power are integrable, forming a fundamental framework in modern analysis and probability theory.
All labels observed (4)
| Label | Occurrences |
|---|---|
| Lebesgue space | 2 |
| Lebesgue spaces canonical | 2 |
| L^p spaces | 1 |
| Lebesgue space L^p | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T736587 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: Lebesgue spaces Context triple: [Minkowski inequality, holdsIn, Lebesgue spaces]
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A.
Lebesgue integration
Lebesgue integration is a foundational measure-theoretic framework for defining and analyzing integrals, particularly suited to handling limits, convergence, and more general functions than those allowed by Riemann integration.
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B.
Hilbert spaces
Hilbert spaces are complete inner product spaces that provide the fundamental framework for modern functional analysis and many areas of mathematical physics.
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C.
Minkowski functional
The Minkowski functional is a mathematical tool in functional analysis that assigns a nonnegative real number to each vector in a vector space based on its position relative to a given convex, balanced, absorbing set, generalizing the notion of a norm.
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D.
Cameron–Martin theorem
The Cameron–Martin theorem is a fundamental result in probability theory and functional analysis that characterizes how Gaussian measures on infinite-dimensional spaces change under shifts by elements of a special Hilbert subspace (the Cameron–Martin space).
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E.
Riemann–Lebesgue lemma
The Riemann–Lebesgue lemma is a fundamental result in Fourier analysis stating that the Fourier coefficients (or transform) of an integrable function vanish at infinity.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Lebesgue spaces Target entity description: Lebesgue spaces are function spaces, denoted \(L^p\), that consist of measurable functions whose absolute values raised to the \(p\)-th power are integrable, forming a fundamental framework in modern analysis and probability theory.
-
A.
Lebesgue integration
Lebesgue integration is a foundational measure-theoretic framework for defining and analyzing integrals, particularly suited to handling limits, convergence, and more general functions than those allowed by Riemann integration.
-
B.
Hilbert spaces
Hilbert spaces are complete inner product spaces that provide the fundamental framework for modern functional analysis and many areas of mathematical physics.
-
C.
Minkowski functional
The Minkowski functional is a mathematical tool in functional analysis that assigns a nonnegative real number to each vector in a vector space based on its position relative to a given convex, balanced, absorbing set, generalizing the notion of a norm.
-
D.
Cameron–Martin theorem
The Cameron–Martin theorem is a fundamental result in probability theory and functional analysis that characterizes how Gaussian measures on infinite-dimensional spaces change under shifts by elements of a special Hilbert subspace (the Cameron–Martin space).
-
E.
Riemann–Lebesgue lemma
The Riemann–Lebesgue lemma is a fundamental result in Fourier analysis stating that the Fourier coefficients (or transform) of an integrable function vanish at infinity.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
Banach space family
ⓘ
function space family ⓘ mathematical concept ⓘ |
| alsoKnownAs | Lp spaces ⓘ |
| application |
Fourier analysis
ⓘ
ergodic theory ⓘ harmonic analysis ⓘ interpolation theory ⓘ partial differential equations ⓘ probability theory ⓘ |
| basedOn |
Lebesgue measure
ⓘ
measure space ⓘ |
| definedOn | measure space (X, Σ, μ) ⓘ |
| definingCondition |
f is essentially bounded for p = ∞
ⓘ
|f|^p is integrable ⓘ ∫ |f|^p dμ < ∞ for 1 ≤ p < ∞ ⓘ |
| duality | (L^p)* ≅ L^q for 1 < p < ∞ and 1/p + 1/q = 1 ⓘ |
| elementType | equivalence classes of measurable functions ⓘ |
| equivalenceRelation | equality almost everywhere ⓘ |
| field |
functional analysis
ⓘ
measure theory ⓘ probability theory ⓘ |
| inequality |
Hölder inequality holds in L^p spaces
ⓘ
Minkowski inequality holds in L^p spaces ⓘ |
| introducedBy | Henri Lebesgue ⓘ |
| L1Definition | integrable functions ⓘ |
| L1Dual | L^∞ in many standard measure spaces ⓘ |
| L2Definition | square-integrable functions ⓘ |
| L2InnerProduct | ∫ f·conjugate(g) dμ ⓘ |
| L2Is | Hilbert space ⓘ |
| LInfinityDefinition | essentially bounded measurable functions ⓘ |
| LInfinityDual | larger than L^1 in general ⓘ |
| LpDefinition | p-integrable functions ⓘ |
| LpInclusion | L^q ⊆ L^p under suitable measure conditions when q > p ⓘ |
| norm |
(∫ |f|^p dμ)^{1/p} for 1 ≤ p < ∞
ⓘ
essential supremum norm for p = ∞ ⓘ |
| notation | L^p ⓘ |
| parameter | p ⓘ |
| parameterRange | 1 ≤ p ≤ ∞ ⓘ |
| property |
Banach spaces for 1 ≤ p ≤ ∞
ⓘ
complete normed spaces ⓘ |
| relatedConcept |
Banach spaces
ⓘ
surface form:
Banach function spaces
Orlicz spaces ⓘ Sobolev spaces ⓘ |
| role |
fundamental framework in modern analysis
ⓘ
standard setting for random variables in probability theory ⓘ |
| specialCase | Hilbert space when p = 2 ⓘ |
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Subject: Lebesgue spaces Description of subject: Lebesgue spaces are function spaces, denoted \(L^p\), that consist of measurable functions whose absolute values raised to the \(p\)-th power are integrable, forming a fundamental framework in modern analysis and probability theory.
Referenced by (6)
Full triples — surface form annotated when it differs from this entity's canonical label.