Alphabeta Math
Pipeline-generated
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.

✓ 15 results · all verified · 11 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 4 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Minimax approximation and Remez algorithms

1 · Prerequisites

2 · Summary

For a continuous real target on a nondegenerate compact interval, the page proves existence of a best polynomial approximant, the n+2 alternating-extrema criterion for nonzero error, and uniqueness. It defines finite-budget polynomial Remez exchange with a distinct ordered reference set, an invertible alternation system, and an exact global-extrema oracle; a returned exact equioscillation certificate proves optimality. No iterative convergence claim is made.

The rational family uses real reduced numerator and denominator degrees at most m and n, a strictly positive continuous weight, and a denominator that is strictly positive on the interval. Its defect is d and its alternation count is m+n+2-d; the normal case d=0 gives m+n+2, while defective cases use the smaller count. The rational exchange procedure has an explicit nonlinear-solver, singularity, defect, oracle, and finite-budget status contract. No m+n+2 claim is copied into a defective case.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

Best uniform polynomial error on a compact interval

Definition

Let I=[a,b]⊂R with a<b, and let C(I,R) denote the real-valued continuous functions on I. For h∈C(I,R) set ∥h∥∞,I:=sup⁡x∈I∣h(x)∣. For n∈N0, let Pn(I) be the restrictions to I of real polynomials of degree at most n, including the zero polynomial, and define En(f;I):=inf⁡p∈Pn(I)∥f−p∥∞,I. When I=[−1,1], this agrees with the published definition Best uniform polynomial error and Chebyshev interpolation operators.

These quantities are finite and well-defined. The interval is compact by For a nonempty subset of Rn with n≥1, compactness, closedness and boundedness, pseudocompactness, and attainment of extrema by every continuous real-valued function are equivalent, so each continuous difference f−p has a finite maximum absolute value. The polynomial space contains 0, hence the set of errors is nonempty and bounded below by 0; completeness of R (Complete ordered field (least-upper-bound property)) supplies its infimum.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

A polynomial with the sign pattern of the active extrema

Statement

Let I=[a,b] with a<b, let e:I→R be continuous, and let E=∥e∥∞,I>0. Put S+={x∈I:e(x)=E} and S−={x∈I:e(x)=−E}. If there are no n+2 increasing points of S+∪S− with alternating signs, then there is a real polynomial h of degree at most n such that e(x)h(x)>0 for every x∈S+∪S−.

Facts & Assumptions

Given: I=[a,b] with a<b, a continuous real function e on I, E=∥e∥∞,I>0, and an integer n≥0.

[F3]

The reverse triangle inequality, The triangle inequality, and Basic properties of the absolute value: ∣∣u∣−∣v∣∣≤∣u−v∣, ∣u+v∣≤∣u∣+∣v∣, and ∣−u∣=∣u∣ for real u,v.

Proof

1.1givenF1F2construct

Continuity and attainment in [F2] show that S+∪S− is nonempty and compact: the maximum of ∣e∣ is attained and E>0, while each level set is closed in the compact interval [F1]. If one of S+ or S− is empty, take h=1 or h=−1 according to the sign of the nonempty set; this has degree zero and the required sign.

1.2givenF1F2F3constructalgebra

Suppose both sets are nonempty. Their product is a closed bounded subset of R2. For (x,y),(x′,y′)∈R2, the reverse and ordinary triangle inequalities in [F3] give ∣∣x−y∣−∣x′−y′∣∣≤∣(x−y)−(x′−y′)∣≤∣x−x′∣+∣y−y′∣≤2∥(x,y)−(x′,y′)∥2, so the distance function is continuous. By [F2] it attains a minimum separation δ=min⁡{∣x−y∣:x∈S+, y∈S−}. This minimum is positive because a minimizing pair at distance zero would give a point in both disjoint sets. Starting at the leftmost point of S+∪S−, repeatedly take the first point of the opposite-sign set to the right and the last current-sign point before it. These extrema exist because the level sets are compact, and each transition gives an open gap of length at least δ containing no point of S+∪S−. The gaps are pairwise disjoint subintervals of [a,b], so any k transitions satisfy kδ≤b−a; hence there are finitely many transitions, each with a distinct ordered gap.

2.1givenstep 1.2constructalgebra∎

If there were at least n+1 transitions, choosing one extremal point from each successive sign run would give n+2 ordered alternating points, contrary to the hypothesis. Thus the number k of transitions is at most n. Choose one point ξj in each transition gap and set h(x)=c∏j=1k(x−ξj), where c∈{−1,1} is chosen so that h has the sign of e on the first run. The polynomial has degree k≤n, has no zero on S+∪S−, and changes sign exactly when the extremal sign changes. Hence e(x)h(x)>0 on the entire extremal set.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passOpen item page →

Alternating polynomial signs force the Haar zero-count contradiction

Statement

Let n≥0, let p be a nonzero real polynomial of degree at most n, and let x0<⋯<xn+1 be real numbers. The values p(xi) cannot all be nonzero with alternating signs.

Facts & Assumptions

Given: n≥0, a nonzero real polynomial p of degree at most n, and x0<⋯<xn+1 with each p(xi)≠0.

[F2]

Intermediate value theorem, by bisection with a canonical left-half rule: a continuous function on [a,b] takes every value between f(a) and f(b): if a continuous real function has endpoint values of opposite signs on a closed interval, it has a zero in the open interval.

[F3]

A nonzero real polynomial of degree n has no more than n distinct real roots: a nonzero real polynomial of degree at most n has at most n distinct real roots.

Proof

1.1givenF1F2construct

Suppose that the nonzero values p(xi) alternate in sign. By [F1], p is continuous on each [xi,xi+1]. Since the endpoint values are nonzero and have opposite signs, [F2] gives a root zi∈(xi,xi+1) for every 0≤i≤n. These open intervals are pairwise disjoint, so the zi are n+1 distinct real roots.

2.1givenF3step 1.1algebra∎

The n+1 distinct roots from step 1.1 contradict [F3], because p is nonzero and has degree at most n. Therefore the assumed alternating nonzero values cannot occur.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Polynomial coefficients are bounded by values at fixed distinct nodes

Statement

Let n≥0 and let t0,…,tn be distinct real numbers. For 0≤j≤n, define Lj(x):=∏k≠jx−tktj−tk. If p(x)=∑k=0nckxk has degree at most n, then p(x)=∑j=0np(tj)Lj(x). Consequently, writing Lj(x)=∑k=0nℓjkxk, every coefficient satisfies ∣ck∣≤(∑j=0n∣ℓjk∣)max⁡0≤j≤n∣p(tj)∣. The empty product convention gives L0=1 when n=0.

Facts & Assumptions

Given: An integer n≥0, distinct real nodes t0,…,tn, and a real polynomial p of degree at most n.

[F1]

Formal real polynomials, evaluation, degree, leading coefficient, and monic polynomials: a polynomial of degree at most n is a finite coefficient sum ∑k=0nckxk.

[F2]

A nonzero real polynomial of degree n has no more than n distinct real roots: a nonzero polynomial of degree at most n has at most n distinct real roots.

Proof

1.1F1F2givenconstructalgebra

Each denominator tj−tk is nonzero, so every Lj is a polynomial of degree at most n and Lj(ti) is 1 for i=j and 0 otherwise. The polynomial p−∑jp(tj)Lj has degree at most n and vanishes at the n+1 distinct nodes; [F2] makes it the zero polynomial. This also covers n=0, when L0=1.

2.1givenstep 1.1algebra∎

Comparing the coefficients of xk in the identity of step 1.1 gives ck=∑jp(tj)ℓjk. The triangle inequality yields the stated coefficient bound.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Alternating interpolation weights annihilate lower-degree polynomials

Statement

Let N≥0 and let x0<⋯<xN+1 be real nodes. Set ω(t)=∏j=0N+1(t−xj) and wi=∏j≠i(xi−xj). If g is a real polynomial of degree at most N, then ∑i=0N+1g(xi)wi=0. If, for one fixed ε∈{−1,1}, the values ε(−1)ig(xi) are all nonnegative, then g is the zero polynomial.

Facts & Assumptions

Given: N≥0, strictly increasing real nodes x0,…,xN+1, and g∈PN(R).

[F1]

A nonzero real polynomial of degree n has no more than n distinct real roots: a nonzero polynomial of degree at most N+1 cannot vanish at N+2 distinct nodes; a nonzero polynomial of degree at most N cannot vanish at N+1 distinct nodes.

Proof

1.1givenF1constructalgebra

Each wi≠0. The Lagrange polynomial Li(t):=ω(t)/((t−xi)wi) has degree N+1 and values Li(xj)=1 for j=i and 0 otherwise. Thus H(t):=∑ig(xi)Li(t) has degree at most N+1 and agrees with g at all N+2 nodes. By [F1], H−g=0, so H=g.

2.1givenstep 1.1algebra

The coefficient of tN+1 in Li is 1/wi, while that coefficient in g is 0. Comparing the tN+1 coefficients in H=g from step 1.1 proves the displayed sum identity.

3.1givenstep 2.1algebra

The sign of wi is (−1)N+1−i, since exactly the N+1−i factors with j>i are negative. Hence all terms g(xi)/wi have one common weak sign when ε(−1)ig(xi)≥0. Their sum is 0 by step 2.1, so every term is 0, and all N+2 values g(xi) vanish.

4.1givenF1step 3.1algebra∎

Since g has degree at most N, its N+2 distinct roots in step 3.1 force g=0 by [F1].

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Reduced real rational representations are unique up to scale

Statement

Call a pair (p,q) of real polynomials reduced when q≠0 and no nonconstant polynomial divides both entries. We identify p/q and p′/q′ as the same rational function exactly when pq′=p′q. Every quotient with nonzero denominator has a reduced representation, and any two reduced representations of the same nonzero rational function differ by a common nonzero real scalar. The zero rational function has reduced pair (0,1) up to a nonzero scalar. For q(x)=∑j=0dqjxj, define ∥q∥coef,2:=(∑j=0dqj2)1/2, unchanged by appending zero coefficients. If I is a nonempty interval, two reduced representations of the same rational function with denominators strictly positive on I and coefficient norm 1 are equal.

Facts & Assumptions

Given: Real polynomials p,q with q≠0.

[F1]

Bézout identity and the Euclidean algorithm for polynomials over a field: polynomial division over R gives a monic gcd d and polynomials A,B with Ap+Bq=d; d divides both inputs, and every common divisor divides d.

Proof

1.1givenF1constructalgebra

For a nonzero quotient, let d=gcd⁡(p,q) from [F1] and put p0=p/d, q0=q/d. Then Ap+Bq=d implies Ap0+Bq0=1, so no nonconstant polynomial divides both p0 and q0. For the zero quotient, p=0 and division by the monic gcd⁡(0,q) gives (0,lc⁡(q)); scaling by 1/lc⁡(q) gives (0,1). Any reduced pair representing zero has zero numerator and a nonzero constant denominator.

2.1F1step 1.1algebra

Suppose p0/q0=p1/q1 are nonzero reduced representations. By the stated equality convention, p0q1=p1q0. The Bézout identity Ap0+Bq0=1 from step 1.1, multiplied by p1, shows p0 divides p1; multiplying the same identity by q1 shows q0∣q1. Write p1=hp0 and q1=kq0. The nonzero real leading coefficients of p0 and q0 have nonzero product, so p0q0≠0; cross-multiplication then gives (h−k)p0q0=0 and hence h=k. If h were nonconstant, it would divide both p1 and q1, contradicting reduction. Thus h=k is a nonzero real constant. The zero case is the reduced pair already identified in step 1.1.

3.1givenstep 2.1algebra∎

Since I is nonempty, choose x∈I. If the common scalar from step 2.1 is c, then q1(x)=cq0(x) and both denominators are positive, so c>0. Homogeneity of the coefficient norm and ∥q0∥coef,2=∥q1∥coef,2=1 give c=1, so the numerators agree as well.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

Weighted rational minimax families and defect

Definition

Let I=[a,b] with a<b, let m,n∈N0, and let f,w∈C(I,R) with w(x)>0 for every x∈I. A normalized reduced pair is a pair of real polynomials p,q such that q>0 on I, deg⁡p≤m, deg⁡q≤n, p and q have no nonconstant common divisor, and ∥q∥coef,2:=(∑j=0nqj2)1/2=1when q(x)=∑j=0nqjxj. The zero rational function is represented by (p,q)=(0,1). By Reduced real rational representations are unique up to scale, each rational function admissible under these conditions has exactly one normalized reduced pair. Define Rm,n+(I):={p/q:(p,q) is a normalized reduced pair} and Em,n(f,w;I):=inf⁡r∈Rm,n+(I)∥w(f−r)∥∞,I. The family is nonempty because it contains r=0. For each admissible r=p/q, q>0 on I makes r continuous by 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, so w(f−r) is continuous and bounded on compact I. The infimum is therefore finite, bounded below by zero, and exists as a real number by completeness of R.

For r=p/q≠0 in reduced form, put dm,n(r):=min⁡{m−deg⁡p, n−deg⁡q},Nm,n(r):=m+n−dm,n(r). For r=0, define dm,n(0):=n and hence Nm,n(0):=m. The integer dm,n(r) is the defect. A candidate is normal when dm,n(r)=0 and defective when dm,n(r)>0. The alternation count associated with the candidate is Nm,n(r)+2; it equals m+n+2 only in the normal case.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

The Remez alternation linear system has a unique solution

Statement

Let n≥0, let I=[a,b] with a<b, let f:I→R be any function, and let x0<⋯<xn+1 be distinct nodes in I. There is a unique pair (p,λ)∈Pn(I)×R satisfying p(xi)+(−1)iλ=f(xi),0≤i≤n+1.

Facts & Assumptions

Given: n≥0, I=[a,b] with a<b, a real function f defined at the nodes, and ordered distinct nodes x0,…,xn+1 in I.

[F1]

Alternating polynomial signs force the Haar zero-count contradiction: a nonzero polynomial of degree at most n cannot take nonzero alternating signs at n+2 ordered real nodes.

[F2]

Rank-nullity: dim⁡FV=nullity⁡T+rank⁡T: for a linear map between finite-dimensional vector spaces, the domain dimension is the sum of its kernel dimension and image dimension.

[F3]

Best uniform polynomial error on a compact interval: Pn(I) is the space of restrictions to I of real polynomials of degree at most n.

[F4]

Formal real polynomials, evaluation, degree, leading coefficient, and monic polynomials: every real polynomial of degree at most n is represented by a coefficient sum ∑j=0ncjxj.

[F5]

A nonzero real polynomial of degree n has no more than n distinct real roots: a nonzero real polynomial of degree at most n has at most n distinct real roots.

Proof

1.1givenF1F3F4F5construct

Define the linear map T:Pn(I)×R→Rn+2 by T(p,λ)i=p(xi)+(−1)iλ. Choose a polynomial representative P of p using [F3] and [F4]. If T(p,λ)=0 and λ=0, then P vanishes at all n+2 distinct nodes, so [F5] forces P=0 and hence p=0. If λ≠0, then P(xi)=−(−1)iλ are nonzero alternating values, so P is nonzero and [F1] rules this out. Thus ker⁡T={(0,0)}.

2.1givenF2F3F4F5step 1.1algebra∎

The restrictions of 1,x,…,xn span Pn(I) by [F3] and [F4]. If a linear combination of them restricts to zero on I, its representing polynomial vanishes at x0,…,xn. These are n+1 distinct roots, so [F5] makes that polynomial zero; the coefficient representation then makes every coefficient zero. Thus the restrictions are linearly independent and form a basis, so dim⁡Pn(I)=n+1. Therefore (1,0),(x,0),…,(xn,0),(0,1) is a basis of the domain, while the standard coordinate vectors form a basis of the codomain; both dimensions are n+2. By [F2] and step 1.1, T has image dimension n+2 and is therefore bijective. Its equation T(p,λ)i=f(xi) has exactly one solution.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Best uniform polynomial approximants exist

Statement

Let I=[a,b] with a<b, let n≥0, and let f∈C(I,R). There is a polynomial p∗∈Pn(I) such that ∥f−p∗∥∞,I=En(f;I).

Facts & Assumptions

Given: I=[a,b] with a<b, an integer n≥0, and f∈C(I,R).

[F1]

Best uniform polynomial error on a compact interval: Pn(I) consists of restrictions of real polynomials of degree at most n, and En(f;I)=inf⁡p∈Pn(I)∥f−p∥∞,I.

[F3]

For a nonempty subset of Rn with n≥1, compactness, closedness and boundedness, pseudocompactness, and attainment of extrema by every continuous real-valued function are equivalent: closed bounded subsets of Rk are compact, and continuous real-valued functions on nonempty compact subsets attain minima and maxima.

[F4]

Polynomial coefficients are bounded by values at fixed distinct nodes: on any fixed n+1 distinct nodes, each polynomial coefficient is a fixed linear combination of the sampled values.

Proof

1.1F1F2F3givenalgebra

Write pc(x)=∑j=0ncjxj for c=(c0,…,cn)∈Rn+1 and set F(c)=∥f−pc∥∞,I. For 0≤j≤n, compactness of I and [F2] give Mj:=max⁡x∈I∣x∣j<∞. For every x∈I, the triangle inequality gives ∣f(x)−pc(x)∣≤∣f(x)−pd(x)∣+∣pd(x)−pc(x)∣; taking suprema and then exchanging c,d yields ∣F(c)−F(d)∣≤∥pc−pd∥∞,I≤∑j=0n∣cj−dj∣Mj. Thus F is continuous. The sublevel set K:={c:F(c)≤∥f∥∞,I} is closed and contains 0.

2.1F1F4step 1.1algebra

If c∈K, then ∥pc∥∞,I≤∥f∥∞,I+F(c)≤2∥f∥∞,I. For n=0, take τ0=a; for n≥1, take distinct nodes τj=a+j(b−a)/n, 0≤j≤n. Each ∣pc(τj)∣≤2∥f∥∞,I, so [F4] bounds every coefficient ck uniformly on K. Hence K is bounded.

3.1F1F3step 1.1step 2.1construct∎

By [F3], the nonempty closed bounded set K is compact, so the continuous function F attains a minimum α on K. Since 0∈K, α≤∥f∥∞,I; every coefficient vector outside K has F(c)>∥f∥∞,I≥α. Therefore α is the minimum over all of Rn+1, which by [F1] is En(f;I). The attaining polynomial is the required p∗.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Exact polynomial equioscillation certifies best approximation

Statement

Let n≥0, let f∈C([a,b],R) with a<b, and let p∈Pn([a,b]). If E:=∥f−p∥∞,[a,b]>0 and there are n+2 ordered nodes x0<⋯<xn+1 in [a,b] and a sign σ∈{−1,1} such that f(xi)−p(xi)=σ(−1)iE(0≤i≤n+1), then no polynomial in Pn([a,b]) has smaller uniform error than p. Thus the displayed residual values are an a posteriori optimality certificate.

Facts & Assumptions

Given: n≥0, a nondegenerate closed interval [a,b], a continuous real function f, a polynomial p of degree at most n, its positive error E=∥f−p∥∞,[a,b], and the stated ordered alternation nodes in [a,b].

[F1]

Best uniform polynomial error on a compact interval: the comparison class is Pn([a,b]) and its error is the uniform norm on that interval.

[F2]

Alternating polynomial signs force the Haar zero-count contradiction: no nonzero polynomial of degree at most n can have nonzero alternating signs at n+2 ordered nodes.

Proof

1.1givenF1algebra

Suppose q∈Pn([a,b]) has ∥f−q∥∞,[a,b]<E. At a node with f(xi)−p(xi)=σ(−1)iE, the strict inequality gives ∣f(xi)−q(xi)∣<E, so q(xi)−p(xi)=(f(xi)−p(xi))−(f(xi)−q(xi)) has the same nonzero sign as σ(−1)i.

2.1givenF2step 1.1algebra∎

The polynomial q−p has degree at most n and, by step 1.1, has nonzero alternating signs at n+2 ordered nodes. This contradicts [F2]. Therefore no such q exists, and p is a best approximant.

AlgorithmAlgorithm: Literature-sourcedProof: Not applicableOpen item page →

Finite-budget polynomial Remez exchange with an exact extrema oracle

Definition

Inputs. A nondegenerate interval I=[a,b], a degree n≥0, a continuous real function f on I, an integer exchange budget B∈N0, and an initial reference X=(x0,…,xn+1) with a≤x0<⋯<xn+1≤b. Also supply an exact extrema oracle for a polynomial candidate p. On each call it returns one of:

  • alternation(E,y0,…,yn+1), only when E=∥f−p∥∞,I and the returned ordered distinct nodes lie in I and satisfy f(yi)−p(yi)=σ(−1)iE for one fixed sign σ;
  • maximum(E,y), only when y∈I, E=∥f−p∥∞,I and ∣f(y)−p(y)∣=E; or
  • inconclusive, when neither exact certificate can be returned.

Procedure. For k=0,…,B, solve the unique real linear system pk(xi)+(−1)iλk=f(xi),0≤i≤n+1, for pk∈Pn(I) and λk∈R, using The Remez alternation linear system has a unique solution. Query the oracle for pk. If it returns alternation(0,Y) or maximum(0,y), return exact(pk), since either response certifies zero uniform error. If it returns alternation(E,Y) with E>0, return certified(pk,E,Y); the optimality claim is discharged by Exact polynomial equioscillation certifies best approximation. If it returns inconclusive, return oracle-inconclusive. If it returns maximum(E,y) with E>0 and E=∣λk∣, return certified(pk,E,X), because the solved equations make X an alternating set and the oracle certifies the global norm. If λk=0<E, return zero-level-no-exchange. If k=B, return budget-exhausted with pk and the current reference X before attempting an exchange.

In the remaining case, let s=sgn⁡(f(y)−pk(y)). Find the smallest index i for which s=sgn⁡(λk)(−1)i and replacing xi by y preserves a strictly increasing reference tuple under these tests: for i=0, require a≤y<x1; for i=n+1, require xn<y≤b; and for 0<i<n+1, require xi−1<y<xi+1. Thus a global maximum at an endpoint may replace the corresponding endpoint reference node, while distinctness and strict ordering are retained. Replace xi by y and continue. If no such index exists, return no-order-preserving-exchange.

Outputs. The procedure returns an exact best-approximation certificate, an exact zero-error candidate, or one of the explicit inconclusive, zero-level, no-exchange, or budget statuses. It asserts no convergence of the iterates. Any implementation must ensure each exact solve and oracle call terminates.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

The rational first-variation space has dimension set by defect

Statement

Let r=p/q∈Rm,n+(I) be nonzero, with its reduced pair and defect d=dm,n(r), and put N=m+n−d. Then {uq−pv:u∈Pm, v∈Pn}=PN. For r=0 with the convention p=0,q=1,d=n,N=m, the same equality holds.

Facts & Assumptions

Given: A nondegenerate interval I, nonnegative degrees m,n, and a normalized admissible rational function r=p/q with the reduced convention of Weighted rational minimax families and defect.

[F1]

Weighted rational minimax families and defect: for r≠0, p,q are coprime, deg⁡p≤m, deg⁡q≤n, and d=min⁡(m−deg⁡p,n−deg⁡q); for r=0, (p,q,d)=(0,1,n).

[F2]

Bézout identity and the Euclidean algorithm for polynomials over a field: if p,q are coprime, there are polynomials A,B with Ap+Bq=1.

[F3]

Rank-nullity: dim⁡FV=nullity⁡T+rank⁡T: domain dimension is kernel dimension plus image dimension for a linear map of finite-dimensional vector spaces.

[F4]

Over an integral domain, degrees add under multiplication of nonzero polynomials: for nonzero polynomials over R, product degrees add.

[F5]

Formal real polynomials, evaluation, degree, leading coefficient, and monic polynomials: Pk has basis 1,x,…,xk and dimension k+1.

Proof

1.1F1F5construct

Define Φ:Pm×Pn→R[x] by Φ(u,v)=uq−pv. It is linear. If r=0, [F1] gives p=0,q=1,d=n,N=m, so Φ(u,v)=u and its image is exactly Pm=PN.

2.1F1F2F4step 1.1algebra

Suppose r≠0. If (u,v)∈ker⁡Φ, then uq=pv. Multiply the Bézout identity in [F2] by u: u=Apu+Bqu=Apu+Bpv=p(Au+Bv), so u=hp for h:=Au+Bv. Substitution into uq=pv and cancellation of the nonzero polynomial p give v=hq. Conversely, every (hp,hq) lies in the kernel.

3.1F1F3F4F5step 2.1algebra

The degree bounds on u=hp and v=hq, together with [F4], are equivalent to deg⁡h≤min⁡(m−deg⁡p,n−deg⁡q)=d; the zero polynomial h is included. Thus the kernel has basis (p,q),(xp,xq),…,(xdp,xdq) and dimension d+1. By [F3] and [F5], the image dimension is (m+n+2)−(d+1)=m+n+1−d=N+1.

4.1F1F4F5step 3.1algebra∎

For all u,v, the degree of uq−pv is at most max⁡(m+deg⁡q,n+deg⁡p)=m+n−d=N by [F1] and [F4]. Hence the image is a subspace of PN, whose dimension is N+1 by [F5]. Its dimension from step 3.1 is also N+1, so the two spaces are equal.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Best weighted rational approximants exist

Statement

For I=[a,b] with a<b, m,n≥0, f∈C(I,R), and a strictly positive continuous weight w, there is r∗∈Rm,n+(I) such that ∥w(f−r∗)∥∞,I=Em,n(f,w;I).

Facts & Assumptions

Given: A nondegenerate compact interval I=[a,b], integers m,n≥0, f,w∈C(I,R), and w>0 on I.

[F1]

Weighted rational minimax families and defect: candidates have reduced degrees at most (m,n), a denominator q>0 normalized by coefficient Euclidean norm 1, and error ∥w(f−p/q)∥∞,I.

[F2]

Reduced real rational representations are unique up to scale: for a nonempty interval, two reduced representations of the same rational function with denominators positive on I and coefficient norm 1 are equal.

[F3]

For a nonempty subset of Rn with n≥1, compactness, closedness and boundedness, pseudocompactness, and attainment of extrema by every continuous real-valued function are equivalent: continuous functions on nonempty compact intervals attain extrema; closed bounded subsets of finite-dimensional Euclidean space are compact and continuous functions on them attain minima.

[F4]

A nonzero real polynomial of degree n has no more than n distinct real roots: a nonzero polynomial has finitely many roots in I.

[F5]

A real polynomial vanishing at a is divisible by x−a: if a polynomial vanishes at c, it is divisible by x−c.

[F7]

Polynomial coefficients are bounded by values at fixed distinct nodes: for fixed distinct nodes, bounded polynomial values give a fixed bound on all coefficients.

[F8]

Over an integral domain, degrees add under multiplication of nonzero polynomials: degrees add for products of nonzero real polynomials.

Proof

1.1F1F3F6givenconstruct

Let γ:=min⁡x∈Iw(x)>0 and M:=∥wf∥∞,I. Positivity of γ follows because the continuous positive function w attains its minimum on compact I by [F3]. In the coefficient space for pairs (p,q) of degrees at most (m,n) and an extra scalar t, define K by ∥q∥coef,2=1, q(x)≥0 on I, 0≤t≤M, and ∣w(x)(f(x)q(x)−p(x))∣≤tq(x) for every x∈I. The triple (0,1,M) lies in K, so K is nonempty.

2.1F1F3F7step 1.1algebra

The coefficient norm equation, the interval for t, and each pointwise inequality defining K are closed conditions on the finite coefficient vector, so K is closed. Its denominator coefficients have norm 1, and for every (p,q,t)∈K, ∣p(x)∣≤(∣f(x)∣+M/γ)q(x) on I. The coefficient norm bound gives ∥q∥∞,I≤∑j=0nmax⁡(∣a∣,∣b∣)j, hence ∥p∥∞,I is uniformly bounded. For m=0, evaluation at one node bounds the sole coefficient of p. For m≥1, evaluate at the m+1 distinct nodes τj=a+j(b−a)/m; each value is bounded by ∥p∥∞,I, so [F7] bounds every coefficient. Thus K is bounded.

3.1F1F2F3step 1.1step 2.1construct

By [F3], K is compact, so its coordinate function (p,q,t)↦t has a minimum t∗ at some (p∗,q∗,t∗)∈K. For every admissible rational r=p/q with error at most M, [F1] supplies a normalized positive reduced representing pair, unique by [F2]; with t=∥w(f−r)∥∞,I this triple belongs to K. Candidates with larger error exceed M≥t∗. Therefore t∗≤Em,n(f,w;I).

3.2F1F4F5F6F8step 2.1algebra

For the minimizing pair, q∗ is a nonzero nonnegative polynomial because its coefficient norm is 1. Its zero set in I is finite by [F4]. The defining inequality of K and w≥γ give ∣p∗(x)∣≤(∥f∥∞,I+M/γ)q∗(x) for every x∈I. At any zero c of q∗, repeated use of [F5] writes q∗(x)=(x−c)su(x) with u(c)≠0 and, if p∗≠0, writes p∗(x)=(x−c)rv(x) with v(c)≠0. If p∗≠0 and r<s, then [F8] and [F4] give q∗(x)>0 on a punctured one-sided neighborhood of c inside I. By continuity in [F6] and u(c)v(c)≠0, ∣v(x)∣/∣u(x)∣ is bounded below by a positive constant on a sufficiently small such neighborhood, so ∣p∗(x)∣/q∗(x)=∣x−c∣r−s∣v(x)∣/∣u(x)∣ is unbounded as x→c from within I, contradicting the displayed bound. Hence p∗ is divisible by the factor of q∗ at every interval zero; this is automatic if p∗=0. Thus every interval zero of q∗ cancels from the quotient.

4.1F1F2F6F9step 3.1step 3.2algebra∎

For each interior zero c of q∗, its multiplicity is even: an odd multiplicity would make q∗ change sign across c, contradicting q∗≥0 on I. Form H from the factors (x−c)s at interior zeros (where s is even), (x−a)sa at a if it is a zero, and (b−x)sb at b if it is a zero. Then H≥0 on I and H>0 off the finite zero set of q∗. Step 3.2 shows that H divides both p∗ and q∗. Write p∗=Hpˉ and q∗=Hqˉ. The exact multiplicities included in H make qˉ nonzero at every zero of q∗; elsewhere, q∗>0 and H>0, so qˉ>0. Since qˉ is continuous by [F6], positivity off the finite zero set makes it nonnegative at each removed zero; its nonvanishing there makes it positive on all of I. At every point outside those zeros, divide the defining inequality ∣w(fq∗−p∗)∣≤t∗q∗ by H to obtain ∣w(fqˉ−pˉ)∣≤t∗qˉ. Thus ∣w(f−pˉ/qˉ)∣≤t∗ there. The quotient pˉ/qˉ and w(f−⋅) are continuous on I by [F6], so the same bound holds at the cancelled zeros by continuity. Reduce (pˉ,qˉ) using [F2]. The reduced denominator still has no zero on I because it divides qˉ; it is continuous by [F6] and has constant sign by [F9] (otherwise the intermediate value theorem would give a zero). A common sign change makes it positive, and a further positive scaling gives coefficient norm 1. The resulting pair is admissible and represents the same quotient, hence has error at most t∗. Therefore Em,n(f,w;I)≤t∗. Together with step 3.1, equality holds and the infimum is attained.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

A nonzero best polynomial error must alternate at n+2 extrema

Statement

Let I=[a,b] with a<b, let n≥0, and let f∈C(I,R). If p∈Pn(I) is a best approximant with E:=∥f−p∥∞,I>0, then there are n+2 ordered points x0<⋯<xn+1 in I and σ∈{−1,1} such that f(xi)−p(xi)=σ(−1)iE(0≤i≤n+1).

Facts & Assumptions

Given: I=[a,b] with a<b, n≥0, f∈C(I,R), and a best approximant p∈Pn(I) with E=∥f−p∥∞,I>0.

[F1]

Best uniform polynomial error on a compact interval: E is the attained uniform error on the compact interval I.

[F2]

A polynomial with the sign pattern of the active extrema: if the active extrema of a continuous residual have no n+2 alternating points, a polynomial h of degree at most n has the same strict sign as that residual on its full active-extrema set.

Proof

1.1givenF1F2F3construct

Put e=f−p. It is continuous by [F3] and has norm E by [F1]. Since I is compact, [F3] makes ∣e∣ attain E, so its active-extrema set S={x∈I:∣e(x)∣=E} is nonempty. Suppose there are not n+2 ordered alternating points in S. Applying [F2] gives a polynomial h of degree at most n with e(x)h(x)>0 for every x∈S. In particular, h is nonzero on S.

2.1F1F3step 1.1construct

The set S is compact because it is a closed subset of I. The continuous function ∣h∣ therefore has a positive minimum c on S by [F3]. The set U={x∈I:e(x)h(x)>0, ∣e(x)∣>E/2, ∣h(x)∣>c/2} is a relatively open neighborhood of S, by continuity and step 1.1.

3.1F1F3step 2.1construct

If I∖U is nonempty, it is compact and contains no point of S, so [F3] gives η:=E−max⁡x∈I∖U∣e(x)∣>0. If it is empty, set η:=E; the outside bound is then vacuous.

4.1givenF1step 1.1step 2.1step 3.1choosealgebra∎

The polynomial h is continuous and has finite norm. Choose ε>0 with ε∥h∥∞,I<min⁡(E/2,η). On U, e and h have the same sign, ∣e∣>E/2, and ε∣h∣<E/2, so ∣e−εh∣=∣e∣−ε∣h∣<E−εc/2. On I∖U, when nonempty, ∣e−εh∣≤E−η+ε∥h∥∞,I<E. Thus ∥f−(p+εh)∥∞,I<E, while p+εh∈Pn(I), contradicting that p is best. Hence the required n+2 alternating extrema exist.

CorollaryStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

The best uniform polynomial approximant is unique

Statement

For every f∈C([a,b],R) with a<b and every n≥0, there is exactly one p∗∈Pn([a,b]) with ∥f−p∗∥∞,[a,b]=En(f;[a,b]).

Facts & Assumptions

Given: I=[a,b] with a<b, n≥0, and f∈C(I,R).

[F1]

Best uniform polynomial error on a compact interval: En(f;I) is the infimum of the uniform errors over Pn(I).

[F2]

Best uniform polynomial approximants exist: at least one polynomial in Pn(I) attains En(f;I).

[F3]

A nonzero best polynomial error must alternate at n+2 extrema: if the best error is positive, a best polynomial has n+2 ordered alternating extremal points.

[F4]

Formal real polynomials, evaluation, degree, leading coefficient, and monic polynomials: every real polynomial of degree at most n has a coefficient-list representative.

[F5]

A nonzero real polynomial of degree n has no more than n distinct real roots: a nonzero real polynomial of degree at most n has at most n distinct real roots.

Proof

1.1givenF1F2algebra

Let p,q∈Pn(I) both attain E:=En(f;I). If E=0, then ∥f−p∥∞,I=∥f−q∥∞,I=0, so p=f=q at every point of I.

1.2F1F3givenchoosealgebra

Suppose E>0 and set r=(p+q)/2∈Pn(I). The triangle inequality gives ∥f−r∥∞,I≤E, while [F1] gives ∥f−r∥∞,I≥E; hence r is also best. By [F3], choose ordered alternating extrema x0<⋯<xn+1 for f−r.

2.1givenF2F3step 1.2algebra

At each xi, f(xi)−r(xi) equals either E or −E. It is the average of f(xi)−p(xi) and f(xi)−q(xi), each lying in [−E,E]. An average of two numbers in this interval equals E only if both are E, and equals −E only if both are −E. Thus p(xi)=q(xi) for all n+2 nodes.

3.1F2F4F5step 2.1algebra∎

Choose coefficient-list representatives P,Q of p,q using [F4]. The polynomial P−Q has degree at most n and vanishes at the n+2 distinct points from step 2.1. If it were nonzero, [F5] would bound its distinct real roots by n, a contradiction. Thus P−Q=0, so their restrictions satisfy p=q. Existence is [F2], hence the best approximant is unique.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passOpen item page →

A budgeted polynomial Remez exchange terminates within its finite cap

Statement

For any finite integer budget B∈N0, the procedure Finite-budget polynomial Remez exchange with an exact extrema oracle makes at most B+1 linear solves and at most B+1 oracle calls (at most 2(B+1) calls total) and returns a status, provided each exact linear solve and each oracle call terminates. This is a finite-budget termination statement, not an iterative convergence theorem.

Facts & Assumptions

Given: The algorithm inputs and exact-solver/oracle behavior of Finite-budget polynomial Remez exchange with an exact extrema oracle, with a finite integer budget B∈N0 and terminating exact solves and oracle calls.

[F1]

Finite-budget polynomial Remez exchange with an exact extrema oracle: each loop iteration makes one exact alternation solve and one extrema-oracle call, then either returns a status or updates one reference node.

[F2]

The Remez alternation linear system has a unique solution: each alternation solve has a unique solution for the supplied distinct ordered reference set.

Proof

1.1givenF1F2construct

At the start of each iteration the reference is ordered and distinct: it is so initially, and each permitted replacement preserves strict order. For an interior index the new node lies strictly between its neighboring reference nodes; at index 0 it satisfies a≤y<x1, and at index n+1 it satisfies xn<y≤b, so endpoint equality still leaves all reference nodes distinct and ordered. Therefore [F2] supplies a unique solve on every entered iteration, and the termination hypothesis together with [F1] gives a terminating oracle call or one reference update.

2.1givenF1step 1.1algebra∎

The loop indices are exactly 0,…,B, a finite set of B+1 iterations. Each entered iteration makes one linear solve and at most one oracle call, so there are at most B+1 solves and B+1 oracle calls in total. Each iteration returns or advances once, so after at most B+1 iterations the procedure either has returned earlier or returns budget-exhausted.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passOpen item page →

Weighted rational minimizers satisfy the defect-sensitive alternation criterion

Statement

Let I=[a,b] with a<b, let m,n≥0, and let f,w∈C(I,R) with w>0 on I. A best rational approximant in Rm,n+(I) exists and is unique. For a candidate r=p/q with positive weighted error Er:=∥w(f−r)∥∞,I>0, let N=Nm,n(r)=m+n−dm,n(r). Then r is best if and only if there are N+2 ordered nodes x0<⋯<xN+1 in I and σ∈{−1,1} such that w(xi)(f(xi)−r(xi))=σ(−1)iEr(0≤i≤N+1). If the best error is 0, positivity of w forces the unique best function to be f itself. In the normal case d=0 the count is m+n+2; for defective candidates the count is m+n+2−d.

Facts & Assumptions

Given: A nondegenerate compact interval I=[a,b], integers m,n≥0, continuous real functions f,w on I with w>0, and a candidate r=p/q∈Rm,n+(I).

[F1]

Weighted rational minimax families and defect: the rational family has positive reduced denominators, weighted error ∥w(f−r)∥∞,I, defect d, effective perturbation degree N=m+n−d, and the zero-function convention d=n.

[F2]

Best weighted rational approximants exist: a candidate attaining Em,n(f,w;I) exists.

[F3]

The rational first-variation space has dimension set by defect: for a candidate of defect d, the polynomials uq−pv with deg⁡u≤m and deg⁡v≤n form exactly PN.

[F4]

A polynomial with the sign pattern of the active extrema: if a continuous residual has no N+2 alternating active extrema, a polynomial of degree at most N can be chosen with the same strict sign on every active extremum.

[F5]

Alternating interpolation weights annihilate lower-degree polynomials: for N+2 ordered nodes, set wi=∏j≠i(xi−xj). Every polynomial g of degree at most N has ∑ig(xi)/wi=0, and if ε(−1)ig(xi)≥0 for one fixed ε∈{−1,1} then all node values are zero.

[F6]

Alternating polynomial signs force the Haar zero-count contradiction: a nonzero polynomial of degree at most N cannot have nonzero alternating signs at N+2 ordered nodes.

[F7]

Reduced real rational representations are unique up to scale: a rational function has a unique coprime reduced pair up to scale, and a positive coefficient-norm normalization fixes that scalar.

Proof

1.1F1F3F6givenalgebra

First suppose Er>0 and that r has N+2 alternating weighted extrema. If another admissible s=p′/q′ had strictly smaller weighted error, write ei=w(xi)(f(xi)−r(xi))=σ(−1)iEr and ei′=w(xi)(f(xi)−s(xi)), so ∣ei′∣<Er. Then σ(−1)iw(xi)(s(xi)−r(xi))=Er−σ(−1)iei′>0. Since w(xi)q(xi)q′(xi)>0, the numerator p′q−pq′ has nonzero alternating signs at those nodes. It lies in PN by [F3], contradicting [F6]. Thus no rational candidate has smaller weighted error and r is best.

1.2F1F3F4F8F10givenconstruct

Now suppose r is best with E:=Er>0, and put e=w(f−r). It is continuous by [F8], and [F10] makes ∣e∣ attain E on compact I, so its active-extrema set is nonempty and compact. If it had no N+2 alternating points, [F4] would give a polynomial g∈PN with e(x)g(x)>0 on that set. By [F3], choose u,v with deg⁡u≤m, deg⁡v≤n, and g=uq−pv.

1.3F1F2algebra

If the best error is zero, then w(f−r)=0 everywhere; since w>0, r=f pointwise, so the best rational function is unique.

2.1F1F3F4F7F8F9F10givenstep 1.2choosealgebra

Since q>0 on compact I, [F10] gives q0=min⁡Iq>0. For all sufficiently small ε>0, q+εv>0 on I. Reduce (p+εu,q+εv) by [F7]. Its reduced denominator has no zero on I, since it divides q+εv; it is continuous by [F8] and has constant sign by [F9], so a common sign change makes it positive and a further positive scaling gives coefficient norm 1. Thus rε=(p+εu)/(q+εv), as a rational function, is represented by an admissible member of Rm,n+(I). Its weighted residual is eε=e−εhε, where hε:=wg/[q(q+εv)]. On the active-extrema set, h0=wg/q2 has the same sign as e and is bounded away from zero. By [F8] and [F10], h0 and e are continuous and bounded; the denominator bound implies hε→h0 uniformly as ε↓0. Hence there are a neighborhood U of that set and a constant c>0 such that ∣e∣>E/2, e and hε have the same sign, and ∣hε∣≥c on U for all sufficiently small ε. Shrink ε further so ε∥hε∥∞,I<E/2; then ε∣hε∣<∣e∣ on U and ∣eε∣=∣e∣−ε∣hε∣≤E−εc<E. The compact complement I∖U, if nonempty, contains no active extremum, so [F10] gives ∣e∣≤E−η there for some η>0; a further small choice of ε makes ε∥hε∥∞,I<η/2. Hence ∥eε∥∞,I<E, contradicting best approximation. This proves necessity.

3.1F1F3F5F7step 2.1algebra

Suppose the best error E is positive and r,s=p′/q′ are both best. By step 2.1, r has N+2 alternating nodes. At each such node, w(s−r)=er−es has weak sign σ(−1)i, because ∣es∣≤E. The numerator g=p′q−pq′ lies in PN by [F3], and its values have the same weak alternating signs since wqq′>0. Thus ε(−1)ig(xi)≥0 with ε=σ, so [F5] gives g=0 and hence r=s.

4.1F2step 1.1step 2.1step 1.3step 3.1∎

Steps 1.1 and 2.1 prove the two directions of the criterion for positive error; steps 1.3 and 3.1 prove uniqueness in the zero- and positive-error cases. Existence is [F2].

AlgorithmAlgorithm: AI-adaptedProof: Not applicableOpen item page →

Finite-budget weighted rational Remez exchange with defect status

Definition

Inputs. A nondegenerate interval I=[a,b], degrees m,n≥0, continuous real target f, strictly positive continuous weight w, a finite exchange integer budget B∈N0, an initial reference X=(x0,…,xm+n+1) satisfying a≤x0<⋯<xm+n+1≤b, an exact rational alternation-solver procedure, and an exact weighted-extrema oracle.

The alternation solver is an explicit input procedure. On a reference X=(x0,…,xm+n+1), it solves the nonlinear equations w(xi)(f(xi)−p(xi)/q(xi))=(−1)iλ with p,q coprime, deg⁡p≤m, deg⁡q≤n, q>0 on I, and ∥q∥coef,2=1. It reports one of: a unique candidate with defect d=0 and its solved level λ; an exact defective candidate with its computed d>0 and solved level λ; singular or nonunique system; no normal solution; or inconclusive. The procedure does not assume that this nonlinear solve always succeeds.

The weighted-extrema oracle for a returned candidate r=p/q reports one of:

  • alternation(E,Y) only when E=∥w(f−r)∥∞,I and Y consists of Nm,n(r)+2 ordered distinct points in I with weighted residuals σ(−1)iE;
  • maximum(E,x) only when x∈I, E=∥w(f−r)∥∞,I and ∣w(x)(f(x)−r(x))∣=E; or
  • inconclusive.

Procedure. For k=0,…,B, call the alternation solver on the current reference. Return its singular, no-normal-solution, or inconclusive status unchanged. If it returns a defective candidate, return defective(d,Nm,n(r)) immediately; do not apply the normal m+n+2-point count. For a normal candidate (r,λ), query the weighted-extrema oracle. If it returns inconclusive, return oracle-inconclusive. A response alternation(0,Y) or maximum(0,x) returns exact(r), since either certifies zero weighted error. An alternation response with E>0 returns certified(r,E,Y), with optimality supplied by Weighted rational minimizers satisfy the defect-sensitive alternation criterion. For maximum(E,x) with E=∣λ∣, the current reference itself is an exact global alternation certificate, so return certified(r,E,X). If λ=0<E, return zero-level-no-exchange. If k=B, return budget-exhausted before attempting an exchange. Otherwise E>∣λ∣; exchange the returned maximum point x for the smallest reference node xi whose expected sign sgn⁡(λ)(−1)i matches the sign of w(x)(f(x)−r(x)) and for which replacing xi by x preserves strict ordering. If no such index exists, return no-valid-exchange. After an exchange, continue to the next iteration.

Outputs. The procedure returns an exact minimax certificate, an exact zero-error candidate, or an explicit defect, singularity, no-solution, oracle, exchange, or budget status. It claims no existence of a successful nonlinear solve and no iterative convergence.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passOpen item page →

A budgeted weighted rational Remez exchange terminates within its finite cap

Statement

For a finite integer budget B∈N0, the procedure Finite-budget weighted rational Remez exchange with defect status makes at most B+1 alternation solver calls and at most B+1 extrema-oracle calls (at most 2(B+1) calls total) and returns an explicit status, provided each input procedure terminates. This does not assert that the nonlinear solver succeeds or that the exchange iterates converge.

Facts & Assumptions

Given: The input and status contract of Finite-budget weighted rational Remez exchange with defect status, with a finite integer budget B∈N0 and terminating solver/oracle calls.

[F1]

Finite-budget weighted rational Remez exchange with defect status: each iteration makes one solver call and, only after a normal candidate, at most one extrema-oracle call; it either returns a status or exchanges one reference node.

Proof

1.1givenF1

Every entered iteration has exactly one solver call; if the solver returns a status, the procedure terminates. If it returns a defective candidate, the explicit defect branch terminates. Otherwise a normal candidate receives one oracle call. An inconclusive response returns oracle-inconclusive; every other response either returns a certificate or zero-level status, or searches the finite reference set for an exchange and then returns no-valid-exchange or updates one node. Thus each iteration terminates under the given termination hypothesis.

2.1givenF1step 1.1algebra∎

The loop has only the indices 0,…,B, so it has at most B+1 iterations. Each iteration makes one solver call and at most one oracle call, giving at most B+1 calls to each procedure. If no earlier branch returns, the final iteration is followed by budget-exhausted. Therefore the procedure terminates within the stated total call bound.

5 · Examples, counterexamples and false statements

None yet.

Sources