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Record W4383878397 · doi:10.21203/rs.3.rs-3140456/v1

Nullspaces yield new explicit Runge--Kutta pairs

2023· preprint· en· W4383878397 on OpenAlexaff
J. H. Verner

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMathematics
TopicNumerical methods for differential equations
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMathematicsRunge–Kutta methodsParametric statisticsMaplePure mathematicsSet (abstract data type)Applied mathematicsYield (engineering)Isomorphism (crystallography)Mathematical analysisComputer scienceDifferential equationStatistics

Abstract

fetched live from OpenAlex

Abstract Sixty years ago Butcher [1] characterized a natural tabulation of the or- der conditions for Runge{Kutta methods as an isomorphism from the set of rooted trees having up to p nodes, and provided examples of explicit and implicit methods of several orders. Within a few years. Fehlberg [3] derived pairs of explicit methods of successive orders that could be implemented eciently by using the dierence of each pair of estimates to control the local error. Unfortunately, Fehlberg's pairs were decient for quadrature problems. Subsequently, this author [5],[6] derived para- metric families of explicit Runge{Kutta pairs of increasing orders 6 to 9 that avoided this problem altogether. These, and most known explicit methods, have been derived by exploiting certain 'simplifying conditions' suggested by Butcher [1] that imposed constraints on subsets of the co- ecients, and thereby simplied the solution of the order conditions for moderate to high order methods. 'Test 21', a MAPLE program developed recently by Butcher [2], was applied to derive known 13-stage pairs of orders 7 and 8. Unexpectedly, results of this application revealed the existence of some previously un- known methods - ie. some that satised most, but not all, of the previously known simplifying conditions. This present study develops formulas for directly computing exact coecients of these new pairs together with oth- ers lying within this new parametric family of (13,7-8) pairs. While the best of these new pairs falls short of the best of pairs already known, the properties discovered might be utilized to precisely characterize recently reported higher order methods found using other approaches by Khashin [4] and Zhang[7], and possibly lead to nding other Runge{Kutta and related yet unknown methods.

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)0.003
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.745
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.554
GPT teacher head0.540
Teacher spread0.014 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2023
Admission routes1
Has abstractyes

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