RTT Agentic Module: Chebyshev Quotients, Demazure Multiplicities, and Dyck‑Path Models
chebyshev-demazure-dyck_module.json— Agentic module schema role assignments
Module ID: chebyshev_demazure_dyck_rtt
Source paper: https://arxiv.org/pdf/2604.25246
This module wraps the paper “Chebyshev quotients, Demazure multiplicities, and Dyck‑path models” in RTT operator grammar.
It preserves the authors’ mathematics while exposing the structural regimes that govern:
- the Chebyshev‑quotient formula for numerical Demazure multiplicities,
- the eventual‑positivity dichotomy,
- the signed matching/strip‑walk model, and
- the Dyck‑path factorization families.
1. Purpose#
- Make the paper agentic and machine‑navigable.
- Clarify the regime structure behind Chebyshev quotients and positivity.
- Provide students with a clean conceptual map.
- Support AI agents in reasoning over the paper without drift.
2. Core RTT view of the paper#
The paper shows that numerical Demazure multiplicities for sl₂[t] fusion products can be computed by extracting a single coefficient from a Chebyshev quotient.
This quotient exhibits a sharp dichotomy:
- Either it becomes a polynomial (finite support),
- Or its coefficients are eventually strictly positive.
The authors then:
- give a signed combinatorial model using matchings and bounded strip walks,
- identify infinite families where the quotient factors into Dyck‑path‑compatible pieces,
- and translate these back into explicit formulas for Demazure multiplicities.
The appendix documents AxiomProver’s autonomous Lean formalization of the main theorems.
3. RTT structures in this module#
Regimes#
fusion_product_regimechebyshev_quotient_regimeeventual_positivity_regimematching_walk_regimedyck_path_factorization_regimeformalization_regime
Tensions#
representation_vs_polynomialsigned_vs_unsignedroot_behavior_vs_combinatoricsformal_vs_informal
Transitions#
demazure_to_chebyshev_transitionquotient_to_positivity_transitionpositivity_to_signed_model_transitionsigned_to_unsigned_transitioninformal_to_lean_transition
4. Operators#
chebyshev_coefficient_operator— extracts multiplicity coefficients.root_analysis_operator— determines eventual positivity.matching_operator— expands numerator via matchings.strip_walk_operator— expands denominator via strip walks.dyck_factor_operator— detects Dyck‑path factorizations.formalization_operator— maps statements to Lean.
5. How to use this module#
-
Students:
Use this README alongside the PDF to understand how Chebyshev polynomials, Dyck paths, and representation theory interact. -
Researchers:
Query the module’s regimes and operators to explore structural dependencies. -
Agents:
Treatmodule.jsonas the canonical structural map of the paper.
6. Provenance#
- Module authoring: TriadicFrameworks (RTT / agentic mapping).
- Original content: Authors of arXiv:2604.25246.
- License: Open educational use permitted.
✅ diagram.txt#
(ASCII regime–tension–transition map)
+--------------------------------------------------------------+
| chebyshev_demazure_dyck_rtt |
+--------------------------------------------------------------+
REGIMES
[R1] fusion_product_regime
[R2] chebyshev_quotient_regime
[R3] eventual_positivity_regime
[R4] matching_walk_regime
[R5] dyck_path_factorization_regime
[R6] formalization_regime
TENSIONS
[T1] representation_vs_polynomial (R1 <--> R2)
[T2] root_behavior_vs_combinatorics (R2 <--> R3 <--> R4)
[T3] signed_vs_unsigned (R4 <--> R5)
[T4] formal_vs_informal (R5 <--> R6)
TRANSITIONS
[X1] demazure_to_chebyshev_transition
[X2] quotient_to_positivity_transition
[X3] positivity_to_signed_model_transition
[X4] signed_to_unsigned_transition
[X5] informal_to_lean_transition
FLOW
fusion_product_regime (R1)
|
v
chebyshev_quotient_regime (R2)
|
v
eventual_positivity_regime (R3)
|
v
matching_walk_regime (R4)
|
v
dyck_path_factorization_regime (R5)
|
v
formalization_regime (R6)