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Record W1999726326 · doi:10.1002/qua.1803

Evaluation of quantum mechanical perturbative sums in terms of quadratic surds and their use in the approximation of ζ(3)/π<sup>3</sup>

2002· article· en· W1999726326 on OpenAlexafffund
Paul Bracken, Jiřı́ Čı́žek

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of WaterlooUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaAlexander von Humboldt-Stiftung
KeywordsGround statePerturbation theory (quantum mechanics)Algebraic numberMathematicsQuadratic equationEuler's formulaQuantumEuclidean geometryQuantum mechanicsPerturbation (astronomy)Non-perturbativePhysicsMathematical physicsMathematical analysisGeometry

Abstract

fetched live from OpenAlex

Abstract The first correction to the energy using Rayleigh–Schrödinger perturbation theory is calculated for the ground state of the one‐dimensional Hubbard model. An algebraic technique is developed which can be used to evaluate these perturbative sums such that the final result is expressed as a finite linear combination of the elements which occur in the individual terms of the sum. The first nontrivial correction to the energy for the ground state of the one‐dimensional Hubbard model in closed form is evaluated. A number theoretic application of this calculation will be given, which is related to the Euclidean construction of regular polygons inside the circle. It is shown that ζ(3) can be approximated by a product of nested radicals and rational constants, multiplied by π 3 , much in the same way that ζ(2) was expressed by Euler as a product of rational numbers and π 2 . It is discussed how this analysis can be continued to higher orders in perturbation theory such that ζ(2 m +1) is obtained as a multiple of π 2 m +1 and nested radicals. © 2002 Wiley Periodicals, Inc. Int J Quantum Chem, 2002

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.292
Teacher spread0.248 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2002
Admission routes2
Has abstractyes

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