benchmark_version: scientific-agent-generalization-v1
base_config: beam_ml_v06.yaml
training_budgets:
  - 256
  - 1024
  - 4096
runs_per_budget: 1
holdout:
  evaluation_id: beam_survival_holdout_v1
  lattice:
    kind: reference_fodo_ring_v1
  sampling:
    strategy: halton
    coordinate_ranges:
      x:
        minimum: -0.012
        maximum: 0.012
      px:
        minimum: -0.001
        maximum: 0.001
    num_points: 1024
    seed: 601
    selection: all
    fixed_coordinates:
      y: 0.0
      py: 0.0
      delta: 0.0
  num_turns: 128
baseline:
  enabled: true
  model: scaled_inverse_distance_9nn
  sampling_strategy: fixed_random
  seed: 607
  neighbors: 9
ablation:
  enabled: true
