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Record W4247653758 · doi:10.1145/1113439.1113445

Space-efficient evaluation of hypergeometric series

2005· article· en· W4247653758 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACM SIGSAM Bulletin · 2005
Typearticle
Languageen
FieldMathematics
TopicMathematical functions and polynomials
Canadian institutionsWilfrid Laurier UniversityUniversity of Lethbridge
Fundersnot available
KeywordsMathematicsCombinatorics

Abstract

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We consider the evaluation of the truncated hypergeometric series [EQUATION] to high precision, where <i>a, b, p</i>, and <i>q</i> are polynomials with integer coefficients, and <i>a</i>(<i>n</i>), <i>b</i>(<i>n</i>), <i>p</i>(<i>n</i>), <i>q</i>(<i>n</i>) have bit length <i>O</i>(log <i>n</i>). We also assume that the series is linearly convergent, so that the <i>n</i>th term of (1) is <i>O</i>(<i>c<sup>-n</sup></i>) with <i>c</i> > 1. These series are commonly used in the high precision evaluation of elementary functions and other constants, including the exponential function, logarithms, trigonometric functions, and constants such as the Apéry's constant ζ(3) [9, 10]. "Binary splitting" is an approach that has been independently discovered and used by many authors in the computation of (1) [2, 3, 4, 5, 8, 10, 12]. Binary splitting computes the numerator and denominator of the rational number <i>S</i>(<i>N</i>). The decimal representation of <i>S</i>(<i>N</i>) is then computed by fixed-point division of the numerator by the denominator. The binary splitting approach takes advantage of the special form of the series (1) to obtain a denominator that is relatively small (of size <i>O</i>(<i>N</i> log <i>N</i>)). It also takes advantage of fast integer multiplication to obtain a time complexity of <i>O</i>((log <i>N</i>)<sup>2</sup>M(<i>N</i>)), where M(<i>N</i>) = <i>O</i>(<i>N</i> log <i>N</i> log log <i>N</i>) is the complexity of integer multiplication of two <i>N</i>-bit integers [16]. The space complexity of the algorithm is <i>O</i>(<i>N</i> log <i>N</i>), the size of the computed numerator and denominator. Typically, the numerator and denominator computed by binary splitting have large common factors. For example, in the computation of 640000 digits of ζ(3), as much as 86% of the size of the computed numerator and denominator can be attributed to their common factor [7]. Empirically, we have observed that the size of the reduced numerator and denominator is <i>O</i>(<i>N</i>) instead of <i>O</i>(<i>N</i> log <i>N</i>) as computed by binary splitting. The additional digits computed not only slow down the final division but also require more memory to be used during the computation. For computing a large number of decimal digits, either the computation cannot be done at all or some data would have to be swapped out of memory, increasing the computation time dramatically. In this poster, we study the application of well-known techniques in computer algebra to the evaluation of (1). If a bound on the size of the <i>reduced</i> numerator and denominator is known, we can compute the image of <i>S</i>(<i>N</i>) in (1) under an appropriately chosen modulus. Fast rational number reconstruction can then be applied to recover the reduced numerator and denominator [13, 14, 15, 17]. We show how to apply our techniques to the computation of ζ(3), including the prediction of the size of the reduced numerator and denominator. In particular, we obtain the desired <i>O</i>(<i>N</i>) bound on the size of reduced numerator and denominator, which is an interesting result by itself. The techniques used in the analysis can be applied to similar hypergeometric series.

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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)0.002
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
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)0.0160.001

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 head0.087
GPT teacher head0.332
Teacher spread0.246 · 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