valley-k-small
ring_lazy_jump_ext

Lazy Ring Shortcut Beta Scan

This extension quantifies how shortcut strength beta reshapes first-passage bimodality on lazy rings at fixed N=100, then checks transfer by N sweeps and Monte Carlo class decomposition. Across beta in [0,0.2], both peaks move earlier and tail decay accelerates, while K=4 preserves a wider and deeper bimodal window than K=2.

Updated: 9 Jun 2026, 21:57:42 UTC

Model

The model keeps the lazy ring baseline with one directed shortcut under the selfloop probability rule, and compares K=2 versus K=4 under matched parameter settings.

Method

The workflow runs exact AW beta sweeps, selects a stable beta anchor, executes N sweeps, and cross-checks class composition through Monte Carlo trajectory statistics and tail diagnostics.

Result

Increasing beta advances both peaks and steepens tail decay; under the same beta, K=4 remains more robustly bimodal, and exact-versus-MC diagnostics agree on phase-level trends.

Book Position

This report is part of the chapterized mainline. Use chapter links to keep continuity instead of reading reports in isolation.

Primary chapter Chapter 4: Shortcut Variants

Also appears in chapter-4-shortcut-variants

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Reading Path

  1. Scan key findings first to decide whether this report is relevant.
  2. Use the interactive panel to test parameter and shape sensitivity.
  3. Then read the mathematical chain and formula library for derivation details.

Key Findings

Connected Reports

This report sits inside a shared chain. Use links below to move upstream/downstream and across model families.

Narrative Arc Position

This report appears in one or more global arcs. Use these checkpoints to keep reading continuity across pages.

Verifiable Claims

Claims below are tied to explicit evidence paths so each statement can be audited.

Report Objective

Increasing beta advances both peaks and steepens tail decay; under the same beta, K=4 remains more robustly bimodal, and exact-versus-MC diagnostics agree on phase-level trends.

Verification Steps
  1. Read the key claims and their evidence references first.
  2. Verify at least one equation card and one dataset panel against source paths.
  3. Cross-check this report with upstream/downstream linked reports.

MODEL

model ring_lazy_jump_ext-c1

The model keeps the lazy ring baseline with one directed shortcut under the selfloop probability rule, and compares K=2 versus K=4 under matched parameter settings.

Evidence trail
  • source_document research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    The model keeps the lazy ring baseline with one directed shortcut under the selfloop probability rule, and compares K=2 versus K=4 under matched parameter settings.

  • section_summary research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Research report ring_lazy_jump_ext.

  • math_block research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Model formula context in Lazy Ring Shortcut Beta Scan: The model keeps the lazy ring baseline with one directed shortcut under the

Linked reports Lazy Ring Flux BaselineLazy Ring Jump-Over Mechanism (K2 vs K4)Lazy Ring Shortcut Figure-1 RevisionTwo-Target Lazy Ring Mechanics

METHOD

method ring_lazy_jump_ext-c2

The workflow runs exact AW beta sweeps, selects a stable beta anchor, executes N sweeps, and cross-checks class composition through Monte Carlo trajectory statistics and tail diagnostics.

Evidence trail
  • source_document research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    The workflow runs exact AW beta sweeps, selects a stable beta anchor, executes N sweeps, and cross-checks class composition through Monte Carlo trajectory statistics and tail

  • section_summary research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Research report ring_lazy_jump_ext.

  • math_block research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Method formula context in Lazy Ring Shortcut Beta Scan: The workflow runs exact AW beta sweeps, selects a stable beta anchor, executes N

  • dataset /data/v1/reports/ring_lazy_jump_ext/series/scan_n_k4_beta002-probability.json

    scan_N_K4_beta002 [probability]: N -> q [probability]

Linked reports Destination-Scan Valley ControlTwo-Target Lazy Ring MechanicsGrid2D Rectangle BimodalityLazy Ring Jump-Over Mechanism (K2 vs K4)

RESULT

result ring_lazy_jump_ext-c3

Increasing beta advances both peaks and steepens tail decay; under the same beta, K=4 remains more robustly bimodal, and exact-versus-MC diagnostics agree on phase-level trends.

Evidence trail
  • source_document research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Increasing beta advances both peaks and steepens tail decay; under the same beta, K=4 remains more robustly bimodal, and exact-versus-MC diagnostics agree on phase-level trends.

  • section_summary research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Research report ring_lazy_jump_ext.

  • math_block research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Result formula context in Lazy Ring Shortcut Beta Scan: Increasing beta advances both peaks and steepens tail decay

  • dataset /data/v1/reports/ring_lazy_jump_ext/series/scan_n_k4_beta002-probability.json

    scan_N_K4_beta002 [probability]: N -> q [probability]

Linked reports Ring Valley Regime MapLazy Ring Shortcut Figure-1 RevisionCross-Model Luca Regime MapGrid2D Blackboard Endpoint Case

FINDING

finding ring_lazy_jump_ext-c4

At fixed N=100, beta sweeps show systematic left-shifts of peak times and a larger tail-decay rate as shortcut strength increases.

Evidence trail
  • source_document research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    At fixed N=100, beta sweeps show systematic left-shifts of peak times and a larger tail-decay rate as shortcut strength increases.

  • section_summary research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Research report ring_lazy_jump_ext.

  • math_block research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Finding formula context in Lazy Ring Shortcut Beta Scan: At fixed N=100, beta sweeps show systematic left-shifts of peak times and a

  • dataset /data/v1/reports/ring_lazy_jump_ext/series/scan_n_k4_beta002-probability.json

    scan_N_K4_beta002 [probability]: N -> q [probability]

Linked reports Grid2D One Target — BaseLazy Ring Flux BaselineLazy Ring Jump-Over Mechanism (K2 vs K4)Destination-Scan Valley Control

finding ring_lazy_jump_ext-c5

K=4 keeps a broader bimodal interval and deeper valley than K=2 under matched beta schedules.

Evidence trail
  • source_document research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    K=4 keeps a broader bimodal interval and deeper valley than K=2 under matched beta schedules.

  • section_summary research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Research report ring_lazy_jump_ext.

  • math_block research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

    Finding formula context in Lazy Ring Shortcut Beta Scan: K=4 keeps a broader bimodal interval and deeper valley than K=2 under matched

  • dataset /data/v1/reports/ring_lazy_jump_ext/series/scan_n_k4_beta002-probability.json

    scan_N_K4_beta002 [probability]: N -> q [probability]

Linked reports Lazy Ring Shortcut Figure-1 RevisionGrid2D Blackboard Endpoint CaseGrid2D Reflecting-Boundary BimodalityLazy Ring Jump-Over Mechanism (K2 vs K4)

Interactive Dataset

Plot controls
window=1

N q [probability]

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Provenance: research/reports/ring_lazy_jump_ext/artifacts/data/scan_N_K4_beta002.csv

Mathematical Logic Chain

From model assumptions to interpretation in a short, ordered chain.

Distribution Setup

Defines first-passage probability objects used by later diagnostics.

f(t)=Pr⁡[T=t],S(t)=Pr⁡[T>t],h(t)=f(t)S(t−1)f(t)=\Pr[T=t],\quad S(t)=\Pr[T>t],\quad h(t)=\frac{f(t)}{S(t-1)}

Fallback

Mathematical Principles

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Fallback EN

f(t)=Pr⁡[T=t],S(t)=Pr⁡[T>t],h(t)=f(t)S(t−1)f(t)=\Pr[T=t],\quad S(t)=\Pr[T>t],\quad h(t)=\frac{f(t)}{S(t-1)}
Formula source

research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

Narrative Sections

Cleaned chapter summaries are shown first; low-value placeholders are hidden.

Overview

Research report ring_lazy_jump_ext.

Source

research/reports/ring_lazy_jump_ext/artifacts/tables/beta_scan_N100_K2.tex

Reproducibility Commands

Open command list
  • python3 scripts/reportctl.py build --report ring_lazy_jump_ext --lang en
  • python3 scripts/reportctl.py translation-qc
  • python3 scripts/reportctl.py web-build --mode changed --skip-npm-ci

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N100 K4 beta002 jumpover control.compare f t

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N100 K2 beta002.classes (outputs/_smoketest)

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N100 K2 beta002.cond by t (outputs/_smoketest)

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