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/M3-sims-hub.md

@@ -15,9 +15,10 @@ DESIGN-FIRST · ABSENT. Role C3; implementation C1. Mathematical foundations C4
 established); specific model parameters C1.
 
 ## 3. Language & location
-TBD · `src/economy/sims/`. Numerical computing (Julia, Octave, Fortran, R, or Solidity)
-for the simulation cores. A query facade accessible to Traders. Each sim type (M3a–M3g) may use
-a different runtime suited to its math.
+TBD · `src/economy/sims/`. Each sim type uses the runtime suited to its math: **Fortran**
+(M3d, M3e — dense numerical PDE/SDE), **Prolog** (M3b, M3f — game-theoretic equilibria),
+**R** (M3a — statistical inference), **Solidity** (M3c — on-chain precision), **Zig**
+(M3g — tick-level latency). A query facade accessible to Traders.
 
 ## 4. Does / does-not
 - **Does:** tick-advance continuously at **90:1** (1 wall-second = 90 simulated seconds)

core/docs/plans/M3a-statistical-sims.md

@@ -16,10 +16,10 @@ execution C5 (industry standard since 2001). Jump-diffusion C5 (Merton 1976). Pa
 for crypto markets C1.
 
 ## 3. Language & location
-TBD · `src/economy/sims/statistical/`. Julia, R, Fortran, or Octave for numerical computing.
-Needs efficient matrix operations, SDE solvers, and distribution sampling. Fractional Brownian
-motion generation uses spectral methods (Hosking 1984, Wood & Chan 1994) or Cholesky
-decomposition of the covariance matrix.
+TBD · `src/economy/sims/statistical/`. **R** — native statistical distribution ecosystem,
+matrix operations, and time-series libraries (GARCH, ARIMA, HMM) without wrapping external
+solvers. Fractional Brownian motion generation uses spectral methods (Hosking 1984, Wood & Chan
+1994) or Cholesky decomposition of the covariance matrix.
 
 ## 4. Does / does-not
 - **Does:** run Monte Carlo price simulations (GBM, Merton jump-diffusion, Heston stochastic

core/docs/plans/M3b-sociological-sims.md

@@ -17,9 +17,11 @@ solvers C3). Crypto pump-and-dump ABM C3 (3-agent protocol validated on historic
 Pop behavioral models C1.
 
 ## 3. Language & location
-TBD · `src/economy/sims/sociological/`. Agent-based modeling frameworks (NetLogo, or custom).
-Needs efficient population iteration, strategy mutation, PDE solvers for MFG (HJB +
-Fokker-Planck), and bandit algorithms (UCB/Thompson). Julia, R, or Fortran.
+TBD · `src/economy/sims/sociological/`. **Prolog** — game-theoretic equilibria, replicator
+dynamics, and strategy evolution are naturally expressed as logical relations over population
+states; Nash equilibrium search is constraint satisfaction. Needs efficient population iteration,
+strategy mutation, PDE solvers for MFG (HJB + Fokker-Planck), and bandit algorithms
+(UCB/Thompson).
 
 ## 4. Does / does-not
 - **Does:** simulate populations of behavioral archetypes competing in a market; apply

core/docs/plans/M3c-amm-liquidity-sims.md

@@ -12,9 +12,9 @@ impermanent loss formula C5 (closed-form: $\text{IL}(r) = \frac{2\sqrt{r}}{1+r}
 simulation parameterization C1.
 
 ## 3. Language & location
-TBD · `src/economy/sims/amm/`. Needs precise fixed-point or arbitrary-precision arithmetic for
-invariant calculations. Solidity for on-chain-equivalent precision; Julia or Octave for
-analytical models.
+TBD · `src/economy/sims/amm/`. **Solidity** — on-chain-equivalent fixed-point arithmetic
+reproduces the exact invariant calculations DEXs execute, eliminating precision-mismatch bugs
+between sim and production contracts.
 
 ## 4. Does / does-not
 - **Does:** simulate constant-product pools with fee parameter $\gamma$:

core/docs/plans/M3d-mev-adversarial-sims.md

@@ -19,9 +19,9 @@ optimization C3 (emerging — SMFRL solvers); Kolokoltsov adversarial C3 (non-li
 WENO discretization established but crypto application novel). Parameterization C1.
 
 ## 3. Language & location
-TBD · `src/economy/sims/mev/`. Needs combinatorial optimization (OR-Tools for knapsack),
-continuous-time auction modeling, PDE solvers (WENO for shock-capturing in adversarial dynamics),
-and bilevel optimization (DSMFG). Julia or Fortran.
+TBD · `src/economy/sims/mev/`. **Fortran** — dense numerical loops for PDE solvers (WENO
+shock-capturing), knapsack combinatorics, and continuous-time auction modeling at the throughput
+MEV extraction demands; no GC pauses during hot-path simulation.
 
 ## 4. Does / does-not
 - **Does:** simulate Priority Gas Auctions where multiple searcher bots compete for the same

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:

core/docs/plans/M3f-consensus-staking-sims.md

@@ -14,8 +14,10 @@ validator populations C4 (Lasry & Lions 2007; validator-specific application C3)
 simulation parameterization C1.
 
 ## 3. Language & location
-TBD · `src/economy/sims/consensus/`. Needs Markov chain solvers and game-theoretic equilibrium
-computation. Julia, R, or Fortran.
+TBD · `src/economy/sims/consensus/`. **Prolog** — Markov chain transition rules, Nash
+equilibrium search, and replicator dynamics are constraint-satisfaction problems over validator
+populations; Prolog's backtracking search finds equilibria declaratively rather than
+imperatively iterating toward them.
 
 ## 4. Does / does-not
 - **Does:** simulate validator populations where honesty evolves via **evolutionary game theory**

core/docs/plans/M3g-market-microstructure-sims.md

@@ -15,8 +15,9 @@ optimal execution C5 (industry standard since 2001; crypto adaptations validated
 Kurz CMC thesis). DEX-specific microstructure C2 (emerging). Implementation C1.
 
 ## 3. Language & location
-TBD · `src/economy/sims/microstructure/`. Needs high-frequency data handling, event-driven
-simulation, and Riccati equation solvers for optimal execution trajectories. Fortran or Julia.
+TBD · `src/economy/sims/microstructure/`. **Zig** — tick-level event-driven simulation with
+deterministic memory layout, no GC pauses, and sub-microsecond latency for Riccati solvers and
+order-book state updates; comptime generics eliminate runtime dispatch on hot paths.
 
 ## 4. Does / does-not
 - **Does:** simulate order flow across venues (DEXs and CEXs); model bid-ask spread dynamics as a