Skip to content

[P2 rigorous] Feasibility study for certified finite-size bounds on square-site p_c #112

Description

@LightChainr

Motivation

The main project is numerical/operator-focused, but there is a separate route to a theorem-level result: turn finite crossing/wrapping computations into a rigorous bound or rigorous confidence interval for square-site p_c using a published finite-size criterion / renormalization reduction.

This will not compete with 1e-12 numerical threshold estimates. Its value is qualitative: a completely auditable mathematical statement derived from finite computation.

Literature anchor

Riordan & Walters, Phys. Rev. E 76, 011110 (2007), "Rigorous confidence intervals for critical probabilities", use the Balister–Bollobás–Walters finite reduction to obtain rigorous high-confidence intervals for site/bond thresholds of Archimedean lattices. Related finite-size criteria and 1-dependent renormalization methods are standard in rigorous percolation.

Phase 0: feasibility only

Before writing a production codebase, answer:

  1. Which published finite-size criterion applies directly to square-site percolation on Z^2?
  2. What finite rectangle/annulus/circuit events and numerical thresholds are required?
  3. Can our existing exact/Monte-Carlo engines estimate those events with a mathematically valid error bound (binomial tail / exact rational / interval arithmetic)?
  4. What lattice size and sample count would be needed for any nontrivial improvement over textbook bounds?
  5. Is a deterministic exact enumeration/transfer-matrix variant feasible for the required event, or is the result necessarily a rigorous confidence interval rather than a deterministic theorem?

Deliverable

A short feasibility note with a concrete theorem statement of the form that could actually be certified, including all constants from the chosen finite-size criterion and a power/cost estimate.

Only open a production implementation if the resulting bound would be scientifically meaningful relative to effort.

Possible outcome classes

  • Go: an auditable interval/bound can be obtained with modest compute; implement it.
  • Methodologically interesting but weak: document the criterion and stop before expensive production.
  • No-go: current rigorous constants make the required finite event unrealistically rare/large; close the route without spending server time.

Priority

P2. This should not delay #43/#57. It is included because a theorem-level side result would diversify the project beyond asymptotic model selection.

Activity

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Metadata

Metadata

Assignees

No one assigned

    Labels

    priority:P2Deferred research or on-demand support; no default new compute allocation.

    Projects

    No projects

      Milestone

      No milestone

      Relationships

      None yet

      Development

      No branches or pull requests

      Issue actions