{
  "model_name": "Surya",
  "model_type": "surya",
  "architectures": [
    "Surya"
  ],
  "framework": "PyTorch",
  "domain": "heliophysics",
  "task": "solar-dynamics-forecasting",
  "implementation": {
    "entry_point": "model/surya.py",
    "scope": "spectral-gated and long-short-attention autoregressive forecasting of aligned SDO AIA/HMI observations",
    "train_script": "scripts/train.py",
    "inference_script": "scripts/inference.py",
    "evaluation_script": "scripts/result.py",
    "synthetic_data_script": "scripts/fake_data.py"
  },
  "architecture": {
    "family": "spectral-gated spatiotemporal transformer",
    "image_size": 32,
    "patch_size": 4,
    "input_channels": 13,
    "input_steps": 2,
    "forecast_steps": 4,
    "embed_dim": 64,
    "depth": 4,
    "spectral_blocks": 1,
    "num_heads": 4,
    "window_size": 3,
    "global_tokens": 4,
    "prediction_mode": "autoregressive"
  },
  "data": {
    "datasets": [
      "SDO/AIA",
      "SDO/HMI"
    ],
    "protocol": "synthetic_SDO_AIA_HMI",
    "format": "NPZ",
    "input_key": "inputs",
    "input_shape": [
      "N",
      2,
      13,
      "H",
      "W"
    ],
    "target_key": "targets",
    "target_shape": [
      "N",
      "S",
      13,
      "H",
      "W"
    ],
    "activity_key": "activity",
    "activity_shape": [
      "N",
      "S"
    ],
    "channel_names": [
      "AIA_94",
      "AIA_131",
      "AIA_171",
      "AIA_193",
      "AIA_211",
      "AIA_304",
      "AIA_335",
      "AIA_1600",
      "HMI_magnetogram",
      "HMI_continuum",
      "HMI_doppler",
      "HMI_vector_x",
      "HMI_vector_y"
    ],
    "normalization": "signum-log followed by configured per-channel affine normalization",
    "default_train_file": "data/train.npz",
    "default_test_file": "data/test.npz"
  },
  "configuration_sources": [
    "conf/config.yaml",
    "model/surya.py",
    "scripts/fake_data.py",
    "scripts/train.py",
    "scripts/inference.py",
    "scripts/result.py"
  ]
}