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Analyzers API

Overview​

The analyzers module provides tools for analyzing spacetime properties, energy conditions, and kinematic scalars.

Kinematic Scalars​

get_kinematic_scalars​

Computes expansion, shear, and vorticity scalars.

Parameters:

  • metric (Metric): Input metric object

Returns:

  • KinematicScalars: Object with expansion, shear, vorticity tensors

Example:

from core.analyzer.scalars import get_kinematic_scalars

scalars = get_kinematic_scalars(metric)
print(f"Expansion: {scalars.expansion.shape}")

get_expansion​

Computes only the expansion scalar.

Parameters:

  • metric (Metric): Input metric object

Returns:

  • torch.Tensor: Expansion tensor θ

get_shear​

Computes only the shear scalar.

Parameters:

  • metric (Metric): Input metric object

Returns:

  • torch.Tensor: Shear tensor σ_μν

get_vorticity​

Computes only the vorticity scalar.

Parameters:

  • metric (Metric): Input metric object

Returns:

  • torch.Tensor: Vorticity tensor ω_μν

Energy Condition Analyzers​

check_nec​

Checks violation of the Null Energy Condition.

Parameters:

  • energy_tensor (EnergyTensor): Input energy tensor

Returns:

  • torch.Tensor: Boolean tensor indicating NEC violations

Example:

from core.analyzer.energy_conditions import check_nec

nec_violated = check_nec(energy_tensor)
print(f"NEC violations: {nec_violated.sum().item()}")

check_wec​

Checks violation of the Weak Energy Condition.

Parameters:

  • energy_tensor (EnergyTensor): Input energy tensor

Returns:

  • torch.Tensor: Boolean tensor indicating WEC violations

check_sec​

Checks violation of the Strong Energy Condition.

Parameters:

  • energy_tensor (EnergyTensor): Input energy tensor

Returns:

  • torch.Tensor: Boolean tensor indicating SEC violations

get_energy_condition_violation_map​

Creates comprehensive energy condition violation maps.

Parameters:

  • energy_tensor (EnergyTensor): Input energy tensor

Returns:

  • dict: Dictionary with violation maps for NEC, WEC, SEC

Data Export​

export_metric_to_json​

Exports metric data for WebGL visualization.

Parameters:

  • metric (Metric): Input metric object
  • filename (str): Output JSON filename
  • slices (list): Which spacetime slices to export

Returns:

  • str: Path to exported JSON file

Example:

from core.analyzer.export import export_metric_to_json

export_metric_to_json(
    metric,
    "output/alcubierre_data.json",
    slices=[0]  # Export first time slice
)