Kinetic Monte Carlo (KMC) L1-309

Computational ChemistryRare-event stochastic dynamicsδ=3 · standardL_DAG = 3📋 Stub — not mineable

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Unclaimed Principle — open for contribution

This Principle is declared in the catalog but has no reference solver, no pinned dataset, and is not registered on-chain. There is no reward pool. Submitting a cert against this Principle today will record the cert for reproducibility but pay zero PWM.

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Forward model E

P (i \to j ∣ s t a y ini) = k_{i} j / k \sum k_{i} k; d t = - l n (u) / k \sum k_{i} k

Kinetic Monte Carlo: discrete state space; transition rates k_ij from TST; Gillespie/residence-time algorithm samples trajectories with correct stochastic timing.

L-DAG

E.rate_catalog -> int.stochastic -> O.trajectory_distribution

E.rate_catalogint.stochasticO.trajectory_distribution

Well-posedness W

Existence:: true
Uniqueness:: true
Stability:: conditional
κ:: 100

Well-posed; Markov chain analysis gives eigenvalues of rate matrix.

Solvability C

Solver class:: KMCLib, SPPARKS; adaptive KMC with Bell saddle-search
Convergence rate q:: 2
Complexity:: principle-dependent

Specs (0)

No L2 specs registered yet for this principle.