Transit signals detection among correlated noises
Project description
nuance
Efficient detection of planets transiting 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
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 .
Project details
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