{
  "case_id": "zeng_2025_dd_pinn_smalln_cmm_stage2",
  "status": "constrained_smalln_baseline_not_paper_scale_reproduction",
  "paper": {
    "title": "Data-Driven Versus Physics-Informed Neural Networks for Nonadiabatic Semiclassical Mapping Dynamics",
    "doi": "10.4208/cicc.2025.152.01",
    "pdf_sha256": "64b49daf6918cf3e8c114a98ebaf83195e0d728aa844279f6901e6dceeaf8b97",
    "equation_scope": [2, 3, 6, 7, 8, 10, 11, 16, 17, 18, 20, 22, 23, 24]
  },
  "model": {
    "n_modes": 4,
    "n_electronic_states": 2,
    "epsilon": 1.0,
    "gamma_electronic_coupling": 1.0,
    "kondo_xi": 0.1,
    "omega_c": 2.5,
    "beta": 5.0,
    "hbar": 1.0,
    "mass": 1.0,
    "mapping_zpe_gamma": 0.5,
    "initial_electronic_state": 0,
    "mapping_sampling": "uniform_on_2F_minus_1_sphere",
    "nuclear_sampling": "thermal_wigner",
    "project_mapping_after_rk4": true
  },
  "data": {
    "dt": 0.01,
    "fine_dt": 0.005,
    "trajectory_steps": 500,
    "train_trajectories": 256,
    "validation_trajectories": 64,
    "test_batches": 2,
    "test_trajectories_per_batch": 256,
    "seed": 20260825
  },
  "network": {
    "hidden_sizes": [256, 256],
    "activation": "sigmoid",
    "dd_form": "residual_fcn_predicting_normalized_one_step_increment",
    "pinn_form": "two_fcn_potential_and_gradient_maps_inside_constrained_primitive_mmst_rk4",
    "pinn_learned_scalars": ["mass", "mapping_zpe_gamma"],
    "pinn_project_mapping_after_step": true
  },
  "training": {
    "epochs": 300,
    "batch_size": 8192,
    "learning_rate": 0.001,
    "weight_decay": 0.0,
    "gradient_clip_norm": 10.0,
    "mapping_constraint_weight": 1.0,
    "device": "cuda",
    "torch_seed": 20260826
  },
  "predeclared_thresholds": {
    "finite_all_outputs": true,
    "initial_mapping_sphere_max_abs_error": 1e-12,
    "reference_mapping_sphere_max_abs_drift": 1e-8,
    "reference_relative_energy_max_abs_drift": 0.0001,
    "reference_dt_halving_population_max_abs_difference": 0.01,
    "pinn_validation_increment_nrmse": 0.20,
    "pinn_rollout_state_nrmse": 0.35,
    "pinn_population_rmse": 0.08,
    "pinn_mapping_sphere_max_abs_drift": 0.05,
    "pinn_population_rmse_not_worse_than_dd_factor": 1.0,
    "independent_test_batch_population_max_abs_difference": 0.15,
    "curve_roughness_rms_fraction": 0.02,
    "curve_roughness_max_fraction": 0.08,
    "curve_isolated_spike_fraction": 0.08,
    "curve_endpoint_roughness_max_fraction": 0.08
  },
  "scope_limits": [
    "N=4 rather than the paper's N=100 bath discretization",
    "256 rather than 1024 units in each hidden layer",
    "256 rather than 500 CMM training trajectories",
    "500 rather than 1000 training steps per trajectory",
    "FCN comparison only",
    "increment-normalized optimization is used",
    "Eq. 16 mapping-constraint loss and mapping-sphere projection are numerical stabilizers not explicitly reported in the paper",
    "no claim of reproducing the paper's published figures"
  ]
}