Drop Julia, assign one primary language per M3 sim spec

Ranked languages per spec by fit; took only the top pick:
- M3a (statistical): R — native stats ecosystem
- M3b (sociological): Prolog — equilibria as constraint satisfaction
- M3c (AMM): Solidity — on-chain-equivalent precision
- M3d (MEV): Fortran — dense PDE/knapsack numerics, no GC
- M3e (tokenomics): Fortran — SDE/VAR matrix loops, same toolchain as M3d
- M3f (consensus): Prolog — Markov/Nash as declarative search
- M3g (microstructure): Zig — tick-level latency, deterministic memory
- Hub: updated to reflect per-spec assignments

Julia removed project-wide: JIT startup cost and large toolchain
not justified when the project isn't going all-in on a single runtime.

core/docs/plans/M3e-tokenomics-macro-sims.md

@@ -19,9 +19,10 @@ DeXposure inter-protocol credit propagation C3 (emerging, 2025 — high DeFi spe
 composable yield optimization C4 (Yearn v3, Beefy, production-validated). Specific parameters C1.
 
 ## 3. Language & location
-TBD · `src/economy/sims/tokenomics/`. Needs SDE solvers (Euler-Maruyama, Milstein),
-state-space estimation, and VAR (vector autoregression) for credit exposure impulse responses.
-Julia (DifferentialEquations.jl) or Octave.
+TBD · `src/economy/sims/tokenomics/`. **Fortran** — SDE solvers (Euler-Maruyama, Milstein),
+state-space estimation, and VAR impulse responses are dense matrix-heavy loops where Fortran's
+array intrinsics and zero-overhead numerics dominate; same language as M3d avoids a toolchain
+split across the heaviest numerical sims.
 
 ## 4. Does / does-not
 - **Does:** simulate token state dynamics via the SDE framework: