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These labels describe origin, not correctness: citations and verification chips remain separate evidence.
The -norms for rational , and
Definition
Let and let be the function space of The Euclidean inner product on , with for .
The -norm, for a rational exponent
Let with . For put
where is the absolute value (Absolute value in an ordered field), the sum is the finite sum of Finite sums and finite products, by recursion, and both powers are the rational powers of Rational powers of a positive base.
Every power written here is defined. Each base is a nonnegative real and , so is given by Rational powers of a positive base for and by its supplementary clause for ; the sum of these nonnegative terms is nonnegative (Laws of finite sums and finite products clause 4), and is a positive rational, so the outer power is defined for the same two reasons. The value does not depend on which representative of or of is used (Rational powers do not depend on the representative).
The exponent is a rational, and that is not a matter of taste. Rational powers of a positive base supplies for a nonnegative base and a rational exponent only; real exponents do not exist at this point in the reading order, and Why real exponents are deferred on the rational-powers page records exactly why. This is also why the published Minkowski inequality Minkowski's inequality for finite sums (rational exponent), which is what makes the triangle inequality work below, is itself stated for rational . No statement on this page is written for ranging over a real interval.
The maximum norm
For and put
the maximum of a nonempty finite set of reals, which exists and is one of its elements (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set).
The hypothesis is required and propagates. At the set is empty and has no maximum (Maximum and minimum of a set). This is the same restriction the published as the set of functions , and , , are metrics on it carries, for the same reason, and every statement on this page that mentions inherits it. The -norms for rational carry no such restriction: at each is the empty sum raised to a positive rational power, hence .
The three cases the rest of the page uses
- , since for (Laws of rational exponents, and by the supplementary clause).
- , which is exactly the Euclidean norm of The Euclidean inner product on : the exponent agrees with the integer power, so (Basic properties of the absolute value), and is the unique nonnegative square root of , which is (Rational powers of a positive base, Square roots exist: a unique with ; the positives are ). The two notations denote the same function and no second Euclidean norm is introduced.
- as above, for .
That each of these is a norm in the sense of A norm on a real vector space, the induced metric, and the dictionary with the metric axioms, and that the metrics they induce are exactly the published , and of as the set of functions , and , , are metrics on it, is Each is a norm on , and the induced metrics are exactly , and of the published metric-spaces page; it is proved there and is not assumed here.
Remarks
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Why . The triangle inequality for is Minkowski's inequality, and Minkowski's inequality for finite sums (rational exponent) is stated for rational . For the displayed expression is still defined but is not a norm on for ; nothing on this page asserts anything about that range, and the expression is never written with such an exponent.
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Monotonicity in the base is what makes the comparisons below work. For a fixed positive rational the map is strictly increasing on the positive reals (Monotonicity of and of clause 2), so an inequality between nonnegative sums passes through the outer power. That is the only property of rational powers used in the comparison chain of The finite and reverse triangle inequalities for a norm; and for every norm on satisfies and is Lipschitz, hence continuous, for .
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The subscript is a name, not a number. No arithmetic is performed with it, and is not for any exponent; it is a separately defined function that happens to sit at the end of the family. This is the same refusal to extend silently that Intervals of : the nine order-convex forms, nondegeneracy, and length records for the interval notation.
Depends on
- A norm on a real vector space, the induced metric, and the dictionary with the metric axioms
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
- Rational powers $a^r$ of a positive base
- Rational powers do not depend on the representative
- Laws of rational exponents
- Monotonicity of $r \mapsto a^{r}$ and of $a \mapsto a^{r}$
- Why real exponents are deferred on the rational-powers page
- Minkowski's inequality for finite sums (rational exponent)
- Finite sums and finite products, by recursion
- Laws of finite sums and finite products
- Every nonempty finite set of reals has a maximum and a minimum
- Maximum and minimum of a set
- $\mathbb{R}^n$ as the set of functions $n \to \mathbb{R}$, and $d_1$, $d_2$, $d_\infty$ are metrics on it
- Absolute value in an ordered field
- Basic properties of the absolute value
- Square roots exist: a unique $\sqrt{a} \ge 0$ with $(\sqrt{a})^2 = a$; the positives are $\{x^2 : x \neq 0\}$
Used by
- A Lebesgue measurable subgroup of (ℝⁿ,+) of positive measure is all of ℝⁿ Corollary
- For n ≥ 1 every bounded sequence in ℝⁿ has a convergent subsequence Corollary
- If f : [a,b] → ℝᵐ is differentiable with integrable f' then ∫ₐᵇ f' = f(b)-f(a); and a bounded derivative makes f Lipschitz Corollary
- If f is continuous on [a,b], differentiable on (a,b), and f' extends continuously to [a,b], then the graph of f has length ∫ₐᵇ√1+f'(t)² dt Corollary
- ‖·‖₁ on ℝ² violates the parallelogram law, so no symmetric bilinear form induces it Counterexample
- A curve for which the mean value inequality is an equality, showing the constant cannot be improved Counterexample
- f(t) = (t², t³) on [0,1]: no ξ satisfies f(1)-f(0) = f'(ξ) Counterexample
- g(x,y) = xy/(x²+y²), extended by g(0,0)=0, is continuous in each variable separately and not continuous at the origin Counterexample
- The circular curve defeats the equality form of the vector-valued mean value theorem Counterexample
- x↦-√1-‖x‖₂² has empty subdifferential on the unit-sphere boundary Counterexample
- Axis-parallel rectangles in ℝᵐ and their volume Definition
- Circular arcs, circumference as arc length, and diameter Definition
- Equivalent norms, and the dictionary with equivalent metrics Definition
- Grid partitions of a rectangle in ℝᵐ, their cells, refinements and mesh Definition
- Paths in ℝⁿ, inscribed polygonal sums, arc length as their supremum, and rectifiability Definition
- Radian angle by unit-circle arc length Definition
- Series of vectors in ℝⁿ, absolute convergence, rearrangement, and the set of rearrangement sums Definition
- The derivative and the Riemann integral of a vector-valued function: an intrinsic derivative and a componentwise integral Definition
- The Euclidean metric, convergence, Cauchy sequences, and continuity on the complex plane Definition
- The matrix norm induced by a published vector p-norm Definition
- The subspace Γ of directions along which a series converges absolutely, and its orthogonal complement Γ^⊥ Definition
- Vector-valued functions f : A → ℝᵐ, their limits and continuity, with the dictionary to the metric notions Definition
- A convergent sequence in ℝ³ and the integral ∫₀¹ (1, t, t²), computed componentwise Example
- A convergent series in ℝ² with Γ a line and Γ^⊥ a line, computed from the definition Example
- A Euclidean sphere is a regular level set with tangent hyperplanes Example
- Every convex subset of ℝⁿ, in particular every ball and ℝⁿ itself, is path-connected and hence connected Example
- Explicit comparison constants for the standard norms on Kⁿ Example
- Finite counting measure on n points recovers ℝⁿ p-norms Example
- r² sin(1/r) is differentiable at the origin with a discontinuous gradient Example
- Steinitz's confinement bound realised on an explicit list of six unit vectors in ℝ² summing to zero Example
- The comparison constants between ‖·‖₁, ‖·‖₂ and ‖·‖_∞ on ℝ², and vectors attaining each Example
- The Euclidean norm and its square are convex, with a ball of subgradients at zero for the norm Example
- The family sin(nx)sin(ny) is uniformly bounded but not equicontinuous Example
- Two constraints on a sphere-plane circle, where one multiplier solution is only a local maximum Example
- xy sin(1/(x²+y²)) is differentiable at the origin with unbounded partial derivatives nearby Example
- FALSE: a sequence in ℝⁿ whose coordinate sequences are each bounded converges False statement
- FALSE: if a convergent series in ℝⁿ does not converge absolutely, then every point of ℝⁿ is the sum of some rearrangement of it False statement
- A convex function is bounded above and below on a smaller interior cube Lemma
- A shear sends the unit cube to a set of Lebesgue measure one Lemma
- Each ‖·‖ₚ is a norm on ℝⁿ, and the induced metrics are exactly d₁, d₂ and d_∞ of the published metric-spaces page Lemma
…and 29 more results.
Dependency tree · two levels
64 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Lp space (Wikipedia) (standard reference, not scraped)
- Norm (mathematics) (Wikipedia) (standard reference, not scraped)
- J. Demmel, MA221 Lecture 3: Vector Norms (standard reference, not scraped)
- G. Zitelli, Math 641 Functional Analysis, Part I (standard reference, not scraped)