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Record W2788691877 · doi:10.1090/jams/993

The Archimedean limit of random sorting networks

2021· preprint· lv· W2788691877 on OpenAlexaff
Duncan Dauvergne

Bibliographic record

VenueJournal of the American Mathematical Society · 2021
Typepreprint
Languagelv
FieldMathematics
TopicRandom Matrices and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCayley graphCombinatoricsMathematicsSigmaPermutation matrixCorollaryLimit (mathematics)Permutation (music)Symmetric groupSortingPath (computing)Random permutationDiscrete mathematicsGraphPhysicsComputer scienceAlgorithmMathematical analysis

Abstract

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A sorting network (also known as a reduced decomposition of the reverse permutation) is a shortest path from <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="12 midline-horizontal-ellipsis n"> <mml:semantics> <mml:mrow> <mml:mn>12</mml:mn> <mml:mo> ⋯ </mml:mo> <mml:mi>n</mml:mi> </mml:mrow> <mml:annotation encoding="application/x-tex">12 \cdots n</mml:annotation> </mml:semantics> </mml:math> </inline-formula> to <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="n midline-horizontal-ellipsis 21"> <mml:semantics> <mml:mrow> <mml:mi>n</mml:mi> <mml:mo> ⋯ </mml:mo> <mml:mn>21</mml:mn> </mml:mrow> <mml:annotation encoding="application/x-tex">n \cdots 21</mml:annotation> </mml:semantics> </mml:math> </inline-formula> in the Cayley graph of the symmetric group <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper S Subscript n"> <mml:semantics> <mml:msub> <mml:mi>S</mml:mi> <mml:mi>n</mml:mi> </mml:msub> <mml:annotation encoding="application/x-tex">S_n</mml:annotation> </mml:semantics> </mml:math> </inline-formula> generated by adjacent transpositions. We prove that in a uniform random <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="n"> <mml:semantics> <mml:mi>n</mml:mi> <mml:annotation encoding="application/x-tex">n</mml:annotation> </mml:semantics> </mml:math> </inline-formula> -element sorting network <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="sigma Superscript n"> <mml:semantics> <mml:msup> <mml:mi> σ </mml:mi> <mml:mi>n</mml:mi> </mml:msup> <mml:annotation encoding="application/x-tex">\sigma ^n</mml:annotation> </mml:semantics> </mml:math> </inline-formula> , all particle trajectories are close to sine curves with high probability. We also find the weak limit of the time- <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="t"> <mml:semantics> <mml:mi>t</mml:mi> <mml:annotation encoding="application/x-tex">t</mml:annotation> </mml:semantics> </mml:math> </inline-formula> permutation matrix measures of <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="sigma Superscript n"> <mml:semantics> <mml:msup> <mml:mi> σ </mml:mi> <mml:mi>n</mml:mi> </mml:msup> <mml:annotation encoding="application/x-tex">\sigma ^n</mml:annotation> </mml:semantics> </mml:math> </inline-formula> . As a corollary of these results, we show that if <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper S Subscript n"> <mml:semantics> <mml:msub> <mml:mi>S</mml:mi> <mml:mi>n</mml:mi> </mml:msub> <mml:annotation encoding="application/x-tex">S_n</mml:annotation> </mml:semantics> </mml:math> </inline-formula> is embedded into <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="double-struck upper R Superscript n"> <mml:semantics> <mml:msup> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="double-struck">R</mml:mi> </mml:mrow> <mml:mi>n</mml:mi> </mml:msup> <mml:annotation encoding="application/x-tex">\mathbb {R}^n</mml:annotation> </mml:semantics> </mml:math> </inline-formula> via the map <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="tau right-arrow from bar left-parenthesis tau left-parenthesis 1 right-parenthesis comma tau left-parenthesis 2 right-parenthesis comma ellipsis tau left-parenthesis n right-parenthesis right-parenthesis"> <mml:semantics> <mml:mrow> <mml:mi> τ </mml:mi> <mml:mo stretchy="false"> ↦ </mml:mo> <mml:mo stretchy="false">(</mml:mo> <mml:mi> τ </mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mn>1</mml:mn> <mml:mo stretchy="false">)</mml:mo> <mml:mo>,</mml:mo> <mml:mi> τ </mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mn>2</mml:mn> <mml:mo stretchy="false">)</mml:mo> <mml:mo>,</mml:mo> <mml:mo> … </mml:mo> <mml:mi> τ </mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mi>n</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> <mml:annotation encoding="application/x-tex">\tau \mapsto (\tau (1), \tau (2), \dots \tau (n))</mml:annotation> </mml:semantics> </mml:math> </inline-formula> , then with high probability, the path <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="sigma Superscript n"> <mml:semantics> <mml:msup> <mml:mi> σ </mml:mi> <mml:mi>n</mml:mi> </mml:msup> <mml:annotation encoding="application/x-tex">\sigma ^n</mml:annotation> </mml:semantics> </mml:math> </inline-formula> is close to a great circle on a particular <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="left-parenthesis n minus 2 right-parenthesis"> <mml:semantics> <mml:mrow> <mml:mo stretchy="false">(</mml:mo> <mml:mi>n</mml:mi> <mml:mo> − <

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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)0.002
metaresearch head score (Gemma)0.013
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0050.007
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0120.002

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 head0.023
GPT teacher head0.301
Teacher spread0.278 · 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".

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Citations20
Published2021
Admission routes1
Has abstractyes

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Same venueJournal of the American Mathematical SocietySame topicRandom Matrices and ApplicationsFrench-language works237,207