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Record W2151383643 · doi:10.4153/cmb-2008-050-2

Expected Norms of Zero-One Polynomials

2008· article· en· W2151383643 on OpenAlexaffvenue
Peter Borwein, Kwok-Kwong Stephen Choi, Idris Mercer

Bibliographic record

VenueCanadian Mathematical Bulletin · 2008
Typearticle
Languageen
FieldMathematics
TopicLimits and Structures in Graph Theory
Canadian institutionsYork UniversitySimon Fraser University
Fundersnot available
KeywordsMathematicsCombinatoricsZero (linguistics)Degree (music)Norm (philosophy)Discrete mathematicsPhysics

Abstract

fetched live from OpenAlex

Abstract Let = {a0 + a1z + · · · + an–1zn–1 : aj ∈ ﹛0, 1﹜¯﹜, whose elements are called zero- one polynomials and correspond naturally to the 2n subsets of [n] := ﹛0, 1, … , n – 1﹜. We also let = ﹛α(z) ∈ : α(1) = m﹜, whose elements correspond to the subsets of [n] of size m, and let , whose elements are the zero-one polynomials of degree exactly n. Many researchers have studied norms of polynomials with restricted coefficients. Using ‖α‖p to denote the usual Lp norm of α on the unit circle, one easily sees that α(z) = a0+a1z+· · ·+aNzN ∈ ℝ[z] satisfies and , where . If α(z) ∈ , say α(z) = zβ1 + · · · + zβm where β1 < · · · < βm, then ck is the number of times k appears as a difference βi – βj . The condition that α ∈ satisfies ck ∈ ﹛0, 1﹜ for 1 ≤ k ≤ n – 1 is thus equivalent to the condition that ﹛β1, … , βm﹜ is a Sidon set (meaning all differences of pairs of elements are distinct). In this paper, we find the average of over α ∈ , α ∈ , and α ∈ . We further show that our expression for the average of over yields a new proof of the known result: if m = o(n1/4) and B(n,m) denotes the number of Sidon sets of size m in [n], then almost all subsets of [n] of size m are Sidon, in the sense that .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.253
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2008
Admission routes2
Has abstractyes

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Same venueCanadian Mathematical BulletinSame topicLimits and Structures in Graph TheoryFrench-language works237,207