# polygloss_cfd.py — Multi-CPU Quantarion CFD
import dragon
import dragon.rpc as rpc
import numpy as np
from scipy.fft import fft2
PHI_43 = 22.93606797749979

# Multi-CPU init (32 cores)
dragon.init(backend='mpi')
world = rpc.new_world_group()
rank = world.rank

# Hyperbolic CFD grid (L26 → 512³)
if rank == 0:
    grid = np.random.randn(512,512,512).astype(np.float32)
    grid /= PHI_43  # φ⁴³ normalization
world.bcast(grid)

# CFD loop + Zeno observation
for step in range(10000):
    # Navier-Stokes step (distributed)
    grid = dragon.navier_stokes_step(grid, dt=0.02)
    
    if step % 10 == 0:  # Zeno sampling
        slice_2d = grid[rank*16:(rank+1)*16]  # Domain decomp
        fft_feats = fft2(slice_2d[:,:,0])  # Local FFT
        coherence = np.abs(fft_feats).mean() / PHI_43
        
        # Global reduce
        global_coherence = world.allreduce(coherence, 'mean')
        if rank == 0 and global_coherence > 0.95:
            print(f"φ⁴³ coherence: {global_coherence:.6f}")

dragon.finalize()