TransitKit Documentation

Professional Exoplanet Transit Light Curve Analysis Toolkit

TransitKit is a comprehensive Python package for analyzing exoplanet transit light curves. It provides publication-quality tools for transit detection, parameter estimation, validation, and visualization.

Getting Started

User Guide

API Reference

Development

Features

Core Analysis

  • Transit Signal Generation: Mandel & Agol (2002) limb-darkened transit models

  • Period Detection: Multiple methods (BLS, GLS, PDM) with consensus weighting

  • Parameter Estimation: MCMC-based fitting with full uncertainty quantification

  • Transit Timing Variations: Automatic TTV detection and analysis

Data Handling

  • TESS/Kepler Support: Native lightkurve integration

  • Ground-based Data: Flexible I/O for various formats

  • NASA Exoplanet Archive: Direct TAP queries

Validation & Quality

  • Detection Significance: Bootstrap FAP estimation

  • Odd-Even Tests: Eclipse depth consistency checks

  • Injection-Recovery: Detection efficiency assessment

Quick Example

import numpy as np
from transitkit.core import (
    generate_transit_signal_mandel_agol,
    find_transits_bls_advanced,
    add_noise
)

# Generate synthetic data
time = np.linspace(0, 30, 2000)
flux = generate_transit_signal_mandel_agol(
    time, period=5.0, depth=0.01
)
flux_noisy = add_noise(flux, noise_level=0.001)

# Detect transit
result = find_transits_bls_advanced(time, flux_noisy)
print(f"Detected period: {result['period']:.4f} days")
print(f"SNR: {result['snr']:.1f}")

Installation

# Basic installation
pip install transitkit

# With all optional features
pip install transitkit[all]

Citation

If you use TransitKit in your research, please cite:

@software{transitkit,
  author = {Solmaz, Arif},
  title = {TransitKit: Professional Exoplanet Transit Analysis Toolkit},
  year = {2024},
  url = {https://github.com/arifsolmaz/transitkit},
  version = {2.0.0}
}

Indices and tables