Add FAMM Semantic Mass math-forest plow documentation

6-Documentation/famm/FAMM_SEMANTIC_MASS_MATH_FOREST_PLOW.md

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+# FAMM Semantic Mass Math-Forest Plow
+
+## Purpose
+
+This note records the point where the project moved beyond the initial Semantic Mass Number concept.
+
+The original concept treated Semantic Mass as an accounting scalar: a way to score load, inertia, cost, density, unresolved residue, or route weight.
+
+The current architecture welds Semantic Mass directly into FAMM and turns it into a live routing field:
+
+```text
+Semantic Mass stream
+→ FAMM route/scar/gate state
+→ Z-domain recurrence
+→ delta-memory carry
+→ Hessian curvature receipt
+→ residual seal / closure test
+```
+
+The goal is to stop rediscovering solved structure and instead use existing mathematical operators, proofs, algorithms, and physics solvers as route priors.
+
+## Evidence from existing project work
+
+The existing MOIM document already states that Mass-Numbers are the finite accounting profile that scores a routed object's weight, cost, inertia, density, or unresolved load. It also places Mass-Number under MOIM operationally and beside MOIM architecturally as a sibling profile inside GCL objects.
+
+The existing superfluid semantic adapter already exports semantic state summaries such as mass_number, semantic_density, torsion, kinetic_pressure, basin_strength, receipt_coverage, and gate status. This gives the accelerator real input lanes rather than only theory.
+
+The current Hessian-basis recompute makes HESSIAN_EIGEN the routing basis for FAMM layers: every layer becomes a curvature object with stiff invariant directions, flat compression gauges, saddle scars, and residual-seal receipts.
+
+## New welded object
+
+```math
+\mathfrak M_{\mathrm{FMS}}(u,k)
+=
+A_{16}(u)
+\otimes
+\left[
+\mu[k]
++
+\Gamma_{\mathrm{FAMM}}(u)
++
+H_\mu(z)
++
+\mathcal C_H(u)
++
+\epsilon_k
+\right]
+```
+
+Where:
+
+- `A16(u)` is the RFS-16384 address.
+- `mu[k]` is the semantic mass sample.
+- `Gamma_FAMM` is the route/scar/gate field.
+- `H_mu(z)` is the Z-domain recurrence / transfer law.
+- `C_H(u)` is the Hessian curvature receipt.
+- `epsilon_k` is the residual seal.
+
+## Search acceleration doctrine
+
+```text
+Never search from scratch if a solved route, pole, scar, closure, or eigendirection already exists.
+```
+
+The pipeline becomes:
+
+```text
+input object / route history
+→ compute semantic mass stream μ[k]
+→ fit Z-domain recurrence Hμ(z)
+→ rank routes by mass × invariant overlap × scar penalty
+→ classify local geometry with Hessian receipt
+→ test closure if poles or residuals misbehave
+→ seal bounded residuals
+→ emit route receipt
+```
+
+## CFD Python / Navier-Stokes bridge
+
+Lorena Barba's CFD Python ladder is useful because it gives a staged PDE forest:
+
+```text
+linear convection
+→ nonlinear convection
+→ diffusion
+→ Burgers equation
+→ Laplace / Poisson
+→ cavity flow
+→ channel flow
+→ Navier-Stokes
+```
+
+FAMM should treat each stage as a semantic-mass stream rather than only as a numerical field.
+
+For a 2D incompressible flow state, define lanes:
+
+```math
+\mu_{\mathrm{CFD}}[k]
+=
+w_u\|u_k\|
++
+w_v\|v_k\|
++
+w_p\|p_k\|
++
+w_\omega\|\omega_k\|
++
+w_d\|\nabla\cdot\mathbf u_k\|
++
+w_r\|R_k\|
++
+w_b\|B_k\|
+```
+
+Where:
+
+- `u, v` are velocity components.
+- `p` is pressure.
+- `omega` is vorticity.
+- `div u` is incompressibility violation.
+- `R_k` is PDE residual.
+- `B_k` is boundary-condition residual.
+
+Then fit:
+
+```math
+M_{\mathrm{CFD}}(z)=\sum_{k\ge 0}\mu_{\mathrm{CFD}}[k]z^{-k}
+```
+
+and route by poles:
+
+| Pole / residual behavior | Meaning | Route action |
+|---|---|---|
+| stable poles | solver state is contractive | carry recurrence |
+| near-unit poles | long-memory/inertia | delta-memory carry |
+| outside-ROC poles | instability or missing boundary | closure test / CFL check |
+| high residual but bounded | lawful unresolved tail | seal residual |
+| stiff Hessian direction | invariant/boundary constraint | protect / do not overpress |
+| flat Hessian direction | gauge/compressible subspace | press / compress |
+
+## BraiNCA bridge
+
+BraiNCA's useful lesson is that local Moore-neighborhood updates are not enough when distributed coordination requires long-range connections and dynamic routing.
+
+FAMM's ugly/profound version:
+
+```text
+do not update every neighbor equally;
+route through semantic mass, invariant overlap, scar pressure, and curvature receipts.
+```
+
+A graph-cell update becomes:
+
+```math
+s_i[k+1]
+=
+f\left(
+  s_i[k],
+  \operatorname{TopK}_j[\mu_j[k]P(i\to j)],
+  R_i[k]
+\right)
+```
+
+Where:
+
+```math
+P(i\to j)
+\propto
+\exp[-\alpha d_{ij}-\beta\Omega_{ij}+\gamma I_{ij}-\eta C_{ij}]
+```
+
+## Implementation target
+
+Add a runner that accepts:
+
+```text
+semantic mass lanes
+route candidates
+scar penalties
+optional CFD residual streams
+optional Hessian receipt
+```
+
+and emits:
+
+```text
+ranked routes
+Z-domain recurrence
+pole/ROC diagnosis
+residual seal
+closure recommendation
+```
+
+## Project sentence
+
+FAMM Semantic Mass is now a math-forest plow: it uses solved operators, recurrence laws, curvature receipts, scars, and residual seals as routing priors so the system can move through dense mathematical terrain without rediscovering every branch from scratch.