REBOUND N-Body Simulation Archives for Exoplanet Stability Prediction

REBOUND N-body simulation archives used to train and test the machine learning models in Tamayo et al. (2020). The data supports the SPOCK XGBoost model for predicting the long-term stability of compact multi-planet systems. The dataset is associated with research from Princeton University.

Use Cases

• Training stability classifiers for exoplanet systems based on N-body simulation outputs.
• Benchmarking machine learning models for long-term orbital predictions.
• Analyzing the dynamical features of compact multi-planet configurations.

Strengths

• Data originates from a published, peer-reviewed study (Tamayo et al., 2020).
• Associated with open-source scripts for processing and model training available on GitHub.
• Author affiliation with a reputable research institution (Princeton University).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Daniel Tamayo, Princeton University

Collection Method

Generated from REBOUND N-body simulations.

Time Range

null

Freshness

Last updated date is unknown.

Geography

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