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.
Uncertainty analysis: bounded-error data confine the parameter of a prediction along a declared unit direction in
Statement
Let , let be open, let , and let satisfy (The Euclidean inner product on ). Let be an open interval with and such that for every . Let be of class ( Euclidean maps and diffeomorphisms) with , and suppose that for every the directional derivative of along satisfies
(Directional derivatives and partial derivatives of a map , The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case, For a differentiable scalar field, and the unit direction of steepest ascent is the normalized gradient). Let a recorded scalar satisfy with , and let a calibration-error bound with hold for at a candidate . Then
and the corresponding configuration displacement has Euclidean length . The conclusion is a deterministic conditional statement about the stated bounds; it is not a sampling law, a statistical inference, or a claim about any historical report, and the parameters are supplied by the user of the statement rather than estimated from data here.
Facts & Assumptions
Given: a natural ; an open set ; a point ; a vector with ; an open interval with and for every ; a function of class with and for every ; a recorded scalar with , ; a calibration bound , , for at a candidate .
The intervals that are open in the sense of Intervals of : the nine order-convex forms, nondegeneracy, and length are the four forms , , and , and a set is open when every has a real with , where is the neighbourhood of Open subset of (every point has a neighbourhood inside it), closed subset (complement open), and clopen.
The punctured neighbourhood is never empty: the element satisfies , which is and (The -neighbourhood and the punctured -neighbourhood of a point of ).
Every point of a nondegenerate interval is a limit point of it (The derivative of at a point that is a limit point of , and differentiability on a set).
A limit point of is a point with for every real (Limit point, isolated point, adherent point, derived set, and dense subset of ).
The derivative of at a limit point of is , the limit of the difference quotient, and is differentiable at when that limit exists (The derivative of at a point that is a limit point of , and differentiability on a set).
If , if is a limit point of and if is differentiable at , then the restriction is differentiable at with (The derivative of at a point that is a limit point of , and differentiability on a set).
For a natural number the function is differentiable at every real, with derivative at when the natural number is read as a real number, and the constant function is differentiable at every real with derivative (For a natural the function is differentiable everywhere with derivative ; for it is the constant , with derivative ; for a natural the function is differentiable at every with derivative ; consequently every polynomial function is differentiable at every real, with the derivative computed term by term).
If are differentiable at a limit point of and , then and are differentiable at with and (Sums, scalar multiples, products and quotients: , , , and when , claims 1 and 2).
For , , and , if the line map is defined near , its derivative at is the directional derivative , and for a standard basis vector one writes (Directional derivatives and partial derivatives of a map ). For one-dimensional domains and codomains we identify with by the bijection , the function on with value ; it is isometric because (The Euclidean inner product on ). Under this identification the only standard basis vector is (The standard list with and for is an ordered basis of ; hence , and is the zero space with basis and dimension ).
For with and a limit point of , the statement means: for every real there is a real such that every with satisfies (The - limit of at a limit point of ).
For , a limit point of , and , one has if and only if for every (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, clause 2).
A vector-valued on is continuous at when for every real there is a real such that every with satisfies (Vector-valued functions , their limits and continuity, with the dictionary to the metric notions).
A map on an open is totally differentiable at when there is a linear map with as , and then is written (The total (Fréchet) derivative as the linear first-order approximation with remainder).
If every partial derivative of exists on a neighbourhood of and is continuous at , then is totally differentiable at and is the linear map with matrix (If all partial derivatives exist on a neighbourhood and are continuous at a point, then the map is totally differentiable there with Jacobian derivative).
If is totally differentiable at , then exists for every and equals ; in particular (A total derivative computes every directional derivative, and its matrix is the Jacobian).
A map is of class when each component is; for a scalar function on an open set this means that the function and each of its first coordinate partial derivatives exist and are continuous on the domain ( Euclidean maps and diffeomorphisms, maps and multi-index derivative notation in Euclidean space).
If a scalar-valued is totally differentiable at , then for every (For a differentiable scalar field, and the unit direction of steepest ascent is the normalized gradient).
For scalar whose partial derivatives exist at , the gradient is (The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case).
The Euclidean inner product is with norm ; for one has ; and two elements of are equal exactly when they agree at every (The Euclidean inner product on ).
If is totally differentiable at and is totally differentiable at , then is totally differentiable at with (The chain rule for total derivatives: ).
Real continuity (Continuity of at a point of and on : the - condition, its agreement with at a limit point, and continuity at an isolated point), metric continuity (Continuity of a map between metric spaces, at a point and globally, in the - form), the choice-free equivalence of continuity with openness of preimages (Metric continuity characterisations, with countable choice for the sequential converse, conditions (a) and (b)), the agreement of the real and metric notions on subsets of (Dictionary: for with the metric , continuity and uniform continuity of agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of is compact in the open-cover sense of exactly when it is a compact metric subspace), and continuity of sums and scalar multiples at a point of a common domain (Sums, scalar multiples, products, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, as are constants, the identity and every polynomial function, claim 1).
For every norm on a real vector space and all in one has (axiom (N2) of A norm on a real vector space, the induced metric, and the dictionary with the metric axioms), and is a norm on for every natural number , inducing the metric whenever (Cauchy-Schwarz with its equality case, the triangle inequality for , the parallelogram law and polarisation, clause 2).
Images and preimages of sets under a function are those of the induced relation, and denotes the preimage of under (Injection, surjection, bijection).
The bounded-error model comparison: for an interval with at least two elements, and of class with and on , every candidate for which a recorded scalar satisfies , , and satisfies , , obeys (Bounded-error model comparison: a derivative lower bound confines compatible parameters).
Proof
The interval is one of the four open forms of [F1], hence an open subset of ; fix a real with . By [F2] the punctured neighbourhood is a nonempty subset of , so contains and at least one further point and is therefore nondegenerate; by [F3] every point of is a limit point of , that is, by [F4], for every and every real .
The function is totally differentiable at , and : as is of class , each first partial derivative exists and is continuous on the open set by [F16], so [F14] gives total differentiability of at , and [F17] gives .
The path is continuous at every : given a real take ; for with one has , by [F19], the homogeneity axiom (N2) of [F22] and ; this is continuity in the metric sense of [F21].
The configuration displacement has Euclidean length , by the Euclidean norm of [F19], the homogeneity axiom (N2) of [F22] and .
For every the components of the path satisfy for every real with , since by field arithmetic; on the functions , constantly , and , the identity, are differentiable at with derivatives and , because the power functions and have those derivatives at every real by [F7] and is a limit point of by step 1.1, so [F6] restricts; since on , the sum and scalar rules of [F8] give that is differentiable at with .
Each composite is continuous: for open the preimage is, by [F23], the preimage ; the set is open in the domain of the continuous by the choice-free equivalence (a)(b) of [F21], and its preimage under the continuous is therefore open in ; the same equivalence then gives continuity of on .
For every the partial derivative of in the direction equals its ordinary derivative, so : by [F9] the directional derivative is the limit at of , while by [F5] the derivative of step 2.1 is the limit at of ; the substitution carries one punctured domain bijectively onto the other and the two - conditions of [F10] are the same condition, so .
For every the partial derivative of the path is the vector : the quotient on its domain is identically by the component identity in step 2.1, so its limit exists and defines by [F9], the -th component of is with limit , and step 3.1 gives ; by the componentwise limit criterion [F11] the -th coordinate of equals for every , and two vectors in with equal coordinates are equal by [F19], so .
The only partial derivative of is the constant on by step 4.1 applied at every , and it is continuous at : given a real , every serves for the continuity condition of [F12], because for every .
The path is totally differentiable at with : the partial derivative exists on the neighbourhood of in the open domain and is continuous at by step 5.1, so exists by [F14]; moreover by [F15] and step 4.1.
The composite is totally differentiable at every with by the chain rule [F20], applied to the totally differentiable of step 6.1 and of step 1.2; consequently for every , where the first equality identifies the ordinary derivative with the total derivative applied to (the limits of [F9] and [F5] coincide as in step 3.1) and the remaining equalities are step 6.1, [F15] and step 1.2.
The derivative is continuous on : on one has by step 7.1, the gradient definition [F18] and the inner product of [F19]; the composites are continuous by step 2.2, the dictionary of [F21] transfers this to the real reading, and finite sums and scalar multiples of functions continuous at each point of are continuous there by the algebra clause of [F21]; in particular is continuous on in the sense required by [F24].
The value of at the centre is , and has at least two elements with by step 1.1; the function is differentiable at every point of with continuous derivative by steps 7.1 and 8.1, and on by step 7.1.
The bounded-error model comparison [F24] now applies to on with centre and the recorded scalar , , of the statement, because a model value at the candidate is exactly the quantity the calibration bound constrains; its conclusion is , that is , and the equivalent contrapositive form says that a proposed violating this bound is incompatible with the two stated bounds; with the displacement identity of step 1.4 the statement is proved.
Remarks
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What the statement does not assert. The bounds are parameters of the statement, not estimates: no sampling distribution, likelihood, confidence level or measurement precision is introduced or claimed, and the conclusion is the deterministic conditional inequality alone. The consumer on the empirical-testing page must supply and qualify , and from an explicit detector and calibration model before any physical reading.
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Where the hypotheses are used. The unit length of gives the exact distance identity in the continuity estimate of step 1.3 and the displacement identity of step 1.4; the lower bound enters through the bounded-error lemma and is exactly the hypothesis the companion example shows cannot be dropped; the openness of and make every point of a limit point of and nondegenerate, which is what lets the one-variable and total-differential machinery apply on .
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No choice principle is used. The proof invokes only the choice-free parts of Metric continuity characterisations, with countable choice for the sequential converse, namely the equivalence of continuity with openness of preimages, and nothing is selected from a family of nonempty sets. The single application of the bounded-error lemma inherits no choice assumption.
Depends on
Bounded-error model comparison: a derivative lower bound confines compatible parameters
Euclidean maps and diffeomorphisms
maps and multi-index derivative notation in Euclidean space
The Euclidean inner product on
Directional derivatives and partial derivatives of a map
The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case
The derivative of at a point that is a limit point of , and differentiability on a set
Intervals of : the nine order-convex forms, nondegeneracy, and length
Limit point, isolated point, adherent point, derived set, and dense subset of
The -neighbourhood and the punctured -neighbourhood of a point of
Open subset of (every point has a neighbourhood inside it), closed subset (complement open), and clopen
The - limit of at a limit point of
Vector-valued functions , their limits and continuity, with the dictionary to the metric notions
The total (Fréchet) derivative as the linear first-order approximation with remainder
Continuity of at a point of and on : the - condition, its agreement with at a limit point, and continuity at an isolated point
A norm on a real vector space, the induced metric, and the dictionary with the metric axioms
Injection, surjection, bijection
The standard list with and for is an ordered basis of ; hence , and is the zero space with basis and dimension
For a natural the function is differentiable everywhere with derivative ; for it is the constant , with derivative ; for a natural the function is differentiable at every with derivative ; consequently every polynomial function is differentiable at every real, with the derivative computed term by term
Sums, scalar multiples, products and quotients: , , , and when
The chain rule for total derivatives:
If all partial derivatives exist on a neighbourhood and are continuous at a point, then the map is totally differentiable there with Jacobian derivative
A total derivative computes every directional derivative, and its matrix is the Jacobian
For a differentiable scalar field, and the unit direction of steepest ascent is the normalized gradient
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
Continuity of a map between metric spaces, at a point and globally, in the - form
Metric continuity characterisations, with countable choice for the sequential converse
Cauchy-Schwarz with its equality case, the triangle inequality for , the parallelogram law and polarisation
Dictionary: for with the metric , continuity and uniform continuity of agree with the metric-space notions, the Lipschitz and Hölder conditions are the metric ones instantiated, and a subset of is compact in the open-cover sense of exactly when it is a compact metric subspace
Sums, scalar multiples, products, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, as are constants, the identity and every polynomial function
Dependency tree · 2 levels
Sources
- J. Lebl, Basic Analysis I: Introduction to Real Analysis, Volume I (open textbook), Chapter 4 'The Derivative', sections 4.1.1 to 4.2.5, printed pp. 154-168, version 6.3 (May 15, 2026)
- G. L. Luke, Notes of lectures on Multivariable Calculus (University of Oxford course notes hosted at people.maths.ox.ac.uk/~tillmann), sections 2 'The Total Derivative', 3 'Properties of Total Derivatives' and 7 'Mean Value Theorem', PDF pp. 5-6 and 9-13