ForecastStudy.Config(
        experiment_name='exp005',
        seed=None,
        data=ForecastData.Config(
        │   seq_len=24,
        │   pred_len=12,
        │   cheap=Oscillator.Config(
        │       step_size=0.1,
        │       substeps=4,
        │       stiffness=1.0,
        │       damping=0.15,
        │       cubic=0.0
        │   ),
        │   reference=CorrectedOscillator.Config(
        │       step_size=0.1,
        │       substeps=4,
        │       stiffness=1.0,
        │       damping=0.15,
        │       cubic=0.4,
        │       corrections=[
        │           WeightedForce.Config(
        │               term=PowerForce.Config(axis=1, power=2),
        │               coefficient=0.35
        │           )
        │       ]
        │   ),
        │   train=InitialStates.Config(
        │       seed=101,
        │       count=32,
        │       amplitude=(0.2, 1.5),
        │       velocity=0.5
        │   ),
        │   validation=InitialStates.Config(
        │       seed=202,
        │       count=16,
        │       amplitude=(0.2, 1.5),
        │       velocity=0.5
        │   ),
        │   synthetic=InitialStates.Config(
        │       seed=303,
        │       count=256,
        │       amplitude=(0.2, 1.5),
        │       velocity=0.5
        │   ),
        │   test=InitialStates.Config(
        │       seed=404,
        │       count=64,
        │       amplitude=(0.2, 1.5),
        │       velocity=0.5
        │   ),
        │   shifted=InitialStates.Config(
        │       seed=505,
        │       count=64,
        │       amplitude=(1.5, 2.5),
        │       velocity=0.5
        │   )
        ),
        method=SparseSimulator.Config(
            terms=[
                PowerForce.Config(axis=0, power=1),
                PowerForce.Config(axis=0, power=3),
                PowerForce.Config(axis=0, power=5),
                PowerForce.Config(axis=1, power=1),
                PowerForce.Config(axis=1, power=2),
                PowerForce.Config(axis=1, power=3)
            ],
            max_terms=2,
            complexity_penalty=1e-06,
            initial_coefficient=0.1,
            search=BoundedLeastSquares.Config(
                bounds=(0.0, 2.0),
                max_evaluations=40,
                ftol=1e-09,
                xtol=1e-09,
                gtol=1e-09
            ),
            dtype=torch.float64
        )
    )
