How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced — the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted — a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated — a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Each is a norm on , and the induced metrics are exactly , and of the published metric-spaces page
Statement
Let and let with , with the norms of The -norms for rational , and . Then:
- is a norm on (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms).
- For , is a norm on .
- The dictionary. For and all , where , , are the metrics of the published as the set of functions , and , , are metrics on it. So the metric induced by each of these three norms (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms) is the correspondingly named published metric, not merely one equivalent to it.
Consequence, used repeatedly below and stated once here. By clause 3 at , the metric space of the published metric-spaces page and the metric space underlying the normed space of this page are the same object. Hence completeness ( and for with the Euclidean metric are complete, componentwise from the Cauchy criterion in clause 2), Heine-Borel (Heine-Borel in : with the Euclidean metric a subset of is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line clause 2) and the compactness equivalences (For a metric space, compact, countably compact, limit point compact, sequentially compact, and complete together with totally bounded are all equivalent, given countable choice and dependent choice) are statements about this page's normed space, with their hypothesis inherited unchanged and not weakened. Nothing below cites any of those three theorems for .
Why this lemma exists. Without it the library would hold a norm-induced metric on and a separately published metric on the same set with no recorded relation, and every later citation would have to guess which was meant. The proof of clause 3 is a comparison of two written expressions; the value is that the comparison is made and recorded.
Facts & Assumptions
Given: A natural number , a rational , vectors and a real ; write , so that (The -norms for rational , and , Finite sums and finite products, by recursion).
For clauses 2 and 3, , so that is a nonempty finite set of reals (The -norms for rational , and , as the set of functions , and , , are metrics on it).
Rational powers (Rational powers of a positive base, Laws of rational exponents): for and rationals one has , , , and when ; and for , and .
Monotonicity in the base (Monotonicity of and of clause 2): for a rational and reals one has ; hence implies , the case being trivial, and only for .
Laws of finite sums (Laws of finite sums and finite products, Finite sums and finite products, by recursion): additivity, scaling, monotonicity; a sum of nonnegative terms is nonnegative, each single term is at most such a sum, and a sum of nonnegative terms that vanishes has every term .
Minkowski's inequality for finite sums at rational (Minkowski's inequality for finite sums (rational exponent)): .
Absolute value (Basic properties of the absolute value, Absolute value in an ordered field, The triangle inequality): ; exactly when ; ; ; and .
Maxima (Every nonempty finite set of reals has a maximum and a minimum, Maximum and minimum of a set): a nonempty finite set of reals has a maximum, the maximum belongs to the set and bounds it above, and a set with an upper bound belonging to it has that element as its maximum.
Order arithmetic: multiplying an inequality by a nonnegative real preserves it (Sign rules for products and monotonicity of multiplication in its strict form, together with the case of equality settled by totality), and is transitive (Ordered field).
The norm axioms (N1), (N2), (N3) (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms); agrees with the Euclidean norm of The Euclidean inner product on , and is a norm by Cauchy-Schwarz with its equality case, the triangle inequality for , the parallelogram law and polarisation; square roots are the rational power at exponent (Square roots exist: a unique with ; the positives are , The -norms for rational , and ).
The published metrics on for are , and , and each is a metric ( as the set of functions , and , , are metrics on it, Metric space: iff , symmetry, and the triangle inequality; pseudometric and ultrametric, The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement).
Proof
Every term is nonnegative, so and is defined and nonnegative.
holds exactly when for every , a vanishing sum of nonnegative terms having every term ; and exactly when , that is exactly when .
For every , , so by scaling of finite sums.
Instantiating [L4] at and , and using , gives , which is axiom (N3) for .
Under [A1] the set is nonempty and finite, so exists, is one of the , and satisfies for every ; in particular .
Under [A1], by the case of the definition, and that is the written expression for .
Under [A1], , using and the identification of the exponent with the nonnegative square root, and that is the written expression for .
Under [A1], by definition, and that is the written expression for .
holds exactly when , since would give and .
Under [A1]: forces and for every , hence ; and . This is (N1) for .
Under [A1]: for every , , and choosing with gives ; so belongs to the set and bounds it above, whence . This is (N2) for .
Under [A1]: for every , ; choosing with gives , which is (N3) for .
By steps 2.1 and 1.2, exactly when for every , that is exactly when ; this is axiom (N1) for .
Steps 2.2, 2.3 and 2.4 are (N1), (N2) and (N3) for under [A1], so clause 2 holds.
If then and both sides of (N2) are by step 3.1; if then , and step 1.3 with the power laws gives ; this is axiom (N2).
Steps 3.1, 4.1 and 1.4 are (N1), (N2) and (N3) for , so clause 1 holds.
Steps 1.6, 1.7 and 1.8 give clause 3, and with steps 5.1 and 3.2 all three clauses are proved; in particular the metric induced by on for is the published , which is the consequence recorded in the Statement.
Remarks
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What the consequence does and does not license. Because the two metric spaces are literally the same, a published theorem about may be quoted here verbatim. It may not be quoted with a weaker hypothesis: and for with the Euclidean metric are complete, componentwise from the Cauchy criterion in , Heine-Borel in : with the Euclidean metric a subset of is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line and as the set of functions , and , , are metrics on it are all stated for only, because is a maximum over an empty index set at , and every item on this page that uses one of them carries in its own statement.
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Clause 1 holds at and clause 2 does not apply there. At every is the zero function on the one-element space , which is the unique norm on the zero space (A norm on a real vector space, the induced metric, and the dictionary with the metric axioms); is not defined there at all.
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The route to (N3) differs between the two families, and that is not an accident. For the triangle inequality is Minkowski's inequality, a genuine theorem about rational powers; for it is the elementary argument of step 2.4, that a maximum of sums is at most the sum of the maxima. The second argument is the one that needs a nonempty index set.
Depends on
- The $p$-norms $\lVert x\rVert_p$ for rational $p \ge 1$, and $\lVert x\rVert_\infty$
- 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 $\mathbb{R}^n$
- Cauchy-Schwarz $\lvert\langle x,y\rangle\rvert \le \lVert x\rVert_2\lVert y\rVert_2$ with its equality case, the triangle inequality for $\lVert\cdot\rVert_2$, the parallelogram law and polarisation
- Minkowski's inequality for finite sums (rational exponent)
- Laws of rational exponents
- Monotonicity of $r \mapsto a^{r}$ and of $a \mapsto a^{r}$
- Laws of finite sums and finite products
- Finite sums and finite products, by recursion
- $\mathbb{R}^n$ as the set of functions $n \to \mathbb{R}$, and $d_1$, $d_2$, $d_\infty$ are metrics on it
- Metric space: $d(x,y) = 0$ iff $x = y$, symmetry, and the triangle inequality; pseudometric and ultrametric
- The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement
- $\mathbb{R}$ and $\mathbb{R}^n$ for $n \ge 1$ with the Euclidean metric are complete, componentwise from the Cauchy criterion in $\mathbb{R}$
- Heine-Borel in $\mathbb{R}^n$: with the Euclidean metric a subset of $\mathbb{R}^n$ is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line
- For a metric space, compact, countably compact, limit point compact, sequentially compact, and complete together with totally bounded are all equivalent, given countable choice and dependent choice
- Every nonempty finite set of reals has a maximum and a minimum
- Maximum and minimum of a set
- Rational powers $a^r$ of a positive base
- Basic properties of the absolute value
- Absolute value in an ordered field
- The triangle inequality
- Sign rules for products and monotonicity of multiplication
- Ordered field
- Square roots exist: a unique $\sqrt{a} \ge 0$ with $(\sqrt{a})^2 = a$; the positives are $\{x^2 : x \neq 0\}$
Used by
- At m=1, cube-nullity and cube-content-zero are exactly the published interval-cover notions Corollary
- At m=1, nondegenerate multidimensional rectangles, grid sums and the integral are exactly the published one-dimensional notions 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
- ‖·‖₁ on ℝ² violates the parallelogram law, so no symmetric bilinear form induces it 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
- Equivalent norms, and the dictionary with equivalent metrics Definition
- Grid partitions of a rectangle in ℝᵐ, their cells, refinements and mesh Definition
- Oscillation of a real function on subsets of ℝᵐ and at a point Definition
- Series of vectors in ℝⁿ, absolute convergence, rearrangement, and the set of rearrangement sums Definition
- The Euclidean metric, convergence, Cauchy sequences, and continuity on the complex plane Definition
- Vector-valued functions f : A → ℝᵐ, their limits and continuity, with the dictionary to the metric notions Definition
- Every convex subset of ℝⁿ, in particular every ball and ℝⁿ itself, is path-connected and hence connected 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
- FALSE: a sequence in ℝⁿ whose coordinate sequences are each bounded converges False statement
- A C¹ map uniformly close to the identity derivative sandwiches a cube between contracted and expanded cubes Lemma
- A function on a subset of ℝᵐ is continuous at x iff its oscillation there is 0, and every oscillation superlevel set is closed Lemma
- Conjugation laws, zoverline z=|z|², multiplicativity of modulus, and the triangle inequality Lemma
- The finite and reverse triangle inequalities for a norm; and for n ≥ 1 every norm N on ℝⁿ satisfies N(x) ≤ C‖ x‖₁ and is Lipschitz, hence continuous, for d₂ Lemma
- Conventions of this page, the standing n ≥ 1 hypothesis, and what is taken up elsewhere in the reading order Remark
- A Lipschitz map ℝᵐ→ℝᵐ sends null sets to null sets Theorem
- A vector-valued function has a limit, or is continuous, if and only if each of its components does; with the algebra of continuous vector-valued functions Theorem
- An absolutely convergent series in ℝⁿ converges, and every rearrangement converges to the same sum Theorem
- Every continuous function on a closed nondegenerate rectangle in ℝᵐ is Riemann integrable Theorem
- For n ≥ 1 a sequence in ℝⁿ converges iff each coordinate sequence converges, is Cauchy iff each coordinate sequence is Cauchy, and ℝⁿ is complete in every norm Theorem
- For n ≥ 1 all norms on ℝⁿ are equivalent Theorem
- Steinitz's polygonal confinement theorem: finitely many vectors of norm at most 1 summing to 0 can be ordered so that every partial sum has norm at most n Theorem
- The graph of a continuous function on a closed nondegenerate rectangle in ℝᵐ has content zero in ℝᵐ⁺¹ Theorem
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 181 results over 30 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- Lp space (Wikipedia) (standard reference, not scraped)
- Minkowski inequality (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)