nuance 0.7.1

Transit signals detection among correlated noises

nuance

Efficient detection of planets transiting quiet or active stars

nuance uses linear models and Gaussian processes (using the JAX-based tinygp) to simultaneously search for planetary transits while modeling correlated noises (e.g. stellar variability) in a tractable way. See the paper for more details.

When to use nuance?

• To detect single or periodic transits
• When correlated noises are present in the data (e.g. stellar variability or instrumental systematics)
• For space-based or sparse ground-based observations
• To effectively find transits in light curves from multiple instruments
• To use GPUs for fast transit searches

Documentation at nuance.readthedocs.io

Example

from nuance import Nuance, utils
import numpy as np

(time, flux, error), X, gp = utils.simulated()

nu = Nuance(time, flux, gp=gp, X=X)

# linear search
epochs = time.copy()
durations = np.linspace(0.01, 0.2, 15)
nu.linear_search(epochs, durations)

# periodic search
periods = np.linspace(0.3, 5, 2000)
search = nu.periodic_search(periods)

t0, D, P = search.best

Installation

nuance is written for python 3 and can be installed using pip

pip install nuance

or from sources

git clone https://github.com/lgrcia/nuance
cd nuance
pip install -e .