{
  "model_type": "physics-informed-neural-network",
  "version": "1.0.0",
  "author": "Ramprasad Atluri (@At1uri)",
  "framework": "scipy / numpy / pytorch-compatible",
  "architecture": {
    "network_type": "Deep Collocation Multi-Layer Perceptron (MLP)",
    "input_dimension": 2,
    "input_features": ["spot_price_S", "time_to_maturity_tau"],
    "hidden_layers": [64, 64, 64],
    "output_dimension": 1,
    "output_feature": "solution_u",
    "activation_function": "tanh"
  },
  "loss_formulation": {
    "interior_pde_loss": "Mean Squared Residual of Parabolic Black-Scholes Operator",
    "terminal_condition_loss": "Mean Squared Error against max(S - K, 0) at tau = 0",
    "boundary_condition_loss": "Asymptotic Dirichlet Boundary Loss as S -> 0 and S -> S_max",
    "loss_weights": {
      "lambda_pde": 1.0,
      "lambda_initial": 15.0,
      "lambda_boundary": 10.0
    }
  },
  "diagnostics": {
    "training_collocation_points": 5000,
    "final_pde_residual_l2_norm": 0.000421,
    "relative_sobolev_h1_error": 0.00185
  }
}