HPC Tier Module

Geometric Graph Sampler - detailed-balance MCMC over molecular graphs (no AI)

Property-targeted molecular-graph generation by EXPLICIT-ENERGY, detailed-balance MCMC - the geometric, VERIFIABLE alternative to a learned energy-based or discrete-diffusion generator.

See it run - a worked example, 100% in this browser tab

What it is

Property-targeted molecular-graph generation by EXPLICIT-ENERGY, detailed-balance MCMC - the geometric, VERIFIABLE alternative to a learned energy-based or discrete-diffusion generator. There is NO neural net, no training, no tuning to the target. A molecule is a benzene-ring graph with a fixed set of editable substituent-group and bond-order slots; proposals are a symmetric single-slot re-draw so Metropolis-Hastings needs no proposal-ratio correction and provably targets the Gibbs measure exp(-beta V). The energy V is CITED, not fit: a Hansch-Leo 1979 logP pi-additivity term toward your target logP plus a defined valence-validity penalty (and an optional defined geometric term). Two modes: a gem-analog two-phase transport-plus-mixing sampler, and a diffusion-analog corrupt-to-noise then reverse-transport-down-the-energy sampler. Because the working state space is small enough to ENUMERATE, the plugin computes the EXACT Gibbs measure and the EXACT detailed-balance residual of the transition kernel, and measures the sampler mixing histogram against ground truth (total-variation distance, reported). HONEST + LOAD-BEARING: the GTI verdict is on the SAMPLER (detailed-balance residual), NOT on whether a molecule is good, novel, or synthesizable; EXACT/PRECISE describes the computation, never chemical truth. The geometric embedding is a defined embedding - the genuine mesh57/HVP embedding was benchmarked as information-equivalent to standard methods (no chemical advantage) - and geometric distance is NOT claimed to equal chemical similarity (now tested: does not track composition; 3D shape resolves stereochemistry; substrate matches standard methods). No competitor benchmark is claimed; a "beats discrete diffusion" statement would need a matched-frame benchmark that has NOT been run here.

Honest scope

Deterministic and citation-backed: every figure is exact arithmetic or a cited rule. Any year- or jurisdiction-indexed value is a confirmable input, never an eternal hardcode. This is a computation tool, not professional (legal, tax, medical, or financial) advice - confirm against the controlling authority for your context.

Authorities cited

Run it on your own data

Open it inside GDBS to save runs to Sandbox, attach results to a Worklog case, or share through a Gate client portal - all in the browser, nothing uploaded to anyone’s cloud.

GDBS by VaultSync Solutions Inc. - Verifiable Computation. gdbs.getvaultsync.com