transit-least-squares

Transit Least Squares (TLS)

Transit Least Squares is a specialized algorithm optimized for detecting exoplanet transits in light curves. It's more sensitive than Lomb-Scargle for transit-shaped signals because it fits actual transit models.

Overview

TLS searches for periodic transit-like dips in brightness by fitting transit models at different periods, durations, and epochs. It's the preferred method for exoplanet transit detection.

Installation

pip install transitleastsquares

Basic Usage

CRITICAL: Always include flux_err (flux uncertainties) for best results!

import transitleastsquares as tls
import lightkurve as lk
import numpy as np

# Example 1: Using Lightkurve (recommended)
lc = lk.LightCurve(time=time, flux=flux, flux_err=error)
lc_clean = lc.remove_outliers(sigma=3)
lc_flat = lc_clean.flatten()

# Create TLS object - MUST include flux_err!
pg_tls = tls.transitleastsquares(
    lc_flat.time.value,      # Time array
    lc_flat.flux.value,      # Flux array
    lc_flat.flux_err.value   # Flux uncertainties (REQUIRED!)
)

# Search for transits (uses default period range if not specified)
out_tls = pg_tls.power(
    show_progress_bar=False,  # Set True for progress tracking
    verbose=False
)

# Extract results
best_period = out_tls.period
period_uncertainty = out_tls.period_uncertainty
t0 = out_tls.T0                    # Transit epoch
depth = out_tls.depth               # Transit depth
snr = out_tls.snr                   # Signal-to-noise ratio
sde = out_tls.SDE                   # Signal Detection Efficiency

print(f"Best period: {best_period:.5f} ± {period_uncertainty:.5f} days")
print(f"Transit epoch (T0): {t0:.5f}")
print(f"Depth: {depth:.5f}")
print(f"SNR: {snr:.2f}")
print(f"SDE: {sde:.2f}")

Example 2: With explicit period range

# Search specific period range
out_tls = pg_tls.power(
    period_min=2.0,      # Minimum period (days)
    period_max=7.0,      # Maximum period (days)
    show_progress_bar=True,
    verbose=True
)