{
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"source": [
"# Removing noise from *K2* and *TESS* light curves using Pixel Level Decorrelation (`PLDCorrector`)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "A9eLo3kLAn9E"
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"source": [
"## Learning Goals\n",
"\n",
"By the end of this tutorial, you will:\n",
"\n",
"* Understand how to apply the [Lightkurve](https://docs.lightkurve.org) [PLDCorrector](https://docs.lightkurve.org/reference/api/lightkurve.correctors.PLDCorrector.html?highlight=pldcorrector) tool to remove instrumental noise from *K2* and *TESS* light curves.\n",
"* Be able to create an exoplanet transit mask and use it to improve PLD.\n",
"* Be aware of common issues, caveats, and potential biases associated with the use of PLD."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "wMnkYd8EA40B"
},
"source": [
"## Introduction\n",
"\n",
"The [*K2*](https://archive.stsci.edu/k2) and [*TESS*](https://archive.stsci.edu/tess) missions both provide high-precision photometry for thousands of exoplanet candidates. However, observations by both telescopes can be muddled by instrumental systematic trends, making exoplanet detection or stellar characterization difficult.\n",
"\n",
"Pixel Level Decorrelation (PLD) is a method that has primarily been used to remove systematic trends introduced by small spacecraft motions during observations, and has been shown to be successful at improving the precision of data taken by the *Spitzer* space telescope ([Deming et al. 2015](https://ui.adsabs.harvard.edu/abs/2015ApJ...805..132D/abstract)) and the *K2* mission ([Luger et al. 2016](https://ui.adsabs.harvard.edu/abs/2016AJ....152..100L/abstract); [2018](https://ui.adsabs.harvard.edu/abs/2018AJ....156...99L/abstract)). PLD works by identifying a set of trends in the pixels surrounding the target star, and performing linear regression to create a combination of these trends that effectively models the systematic noise introduced by spacecraft motion. This noise model is then subtracted from the uncorrected light curve.\n",
"\n",
"This method has been shown to be very effective at removing the periodic systematic trends in *K2*, and can also help remove the scattered light background signal in *TESS* observations. This tutorial will demonstrate how to use the [Lightkurve](https://docs.lightkurve.org) [PLDCorrector](https://docs.lightkurve.org/reference/api/lightkurve.correctors.PLDCorrector.html?highlight=pldcorrector) for each mission, and will give advice on how to best implement PLD. The [PLDCorrector](https://docs.lightkurve.org/reference/api/lightkurve.correctors.PLDCorrector.html?highlight=pldcorrector) is a special case of the [Lightkurve](https://docs.lightkurve.org) [RegressionCorrector](https://docs.lightkurve.org/reference/api/lightkurve.correctors.RegressionCorrector.html?highlight=regressioncorrector). For more information on how to use [RegressionCorrector](https://docs.lightkurve.org/reference/api/lightkurve.correctors.RegressionCorrector.html?highlight=regressioncorrector) to choose custom regressors and remove scattered light from *TESS*, please see the tutorial specifically on removing scattered light from *TESS* data using the Lightkurve [RegressionCorrector](https://docs.lightkurve.org/reference/api/lightkurve.correctors.RegressionCorrector.html?highlight=regressioncorrector).\n",
"\n",
"Before reading this tutorial, it is recommended to first familiarize yourself with using target pixel file (TPF) products and light curve products with Lightkurve."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "5wOFCyG74-fA"
},
"source": [
"## Imports\n",
"\n",
"We only need to import the **[Lightkurve](https://docs.lightkurve.org)** package for this tutorial, which in turn uses **[Matplotlib](https://matplotlib.org/)** for plotting."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"execution": {
"iopub.execute_input": "2023-11-03T14:22:12.536833Z",
"iopub.status.busy": "2023-11-03T14:22:12.536717Z",
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"outputs": [],
"source": [
"import lightkurve as lk\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "O9KCiDg2sCmc"
},
"source": [
"---"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "VqvB7m3c1wbF"
},
"source": [
"## 1. Applying PLD to a *K2* Light Curve\n",
"\n",
"The dominant source of noise in *K2* data is created by the motion of the *Kepler* spacecraft due to periodic thruster firings. This causes stars to drift across different pixels on the detector, which have varied sensitivity. There are two classes of sensitivity variation on a charge-couped device (CCD) detector — variation between pixels (inter-pixel) and variation within each pixel (intra-pixel). Both inter- and intra-pixel sensitivity variations are present on the *Kepler* detector, which ultimately causes different flux levels to be detected as the target's Point Spread Function (PSF) drifts across the variations, introducing the systematic trends.\n",
"\n",
"The [PLDCorrector](https://docs.lightkurve.org/reference/api/lightkurve.correctors.PLDCorrector.html?highlight=pldcorrector) uses information from nearby pixels to create a noise model, so we need to use the [TargetPixelFile](https://docs.lightkurve.org/reference/targetpixelfile.html?highlight=targetpixelfile) data product (for more information, see the tutorial on using *Kepler* target pixel file products). We can use the [search_targetpixelfile](https://docs.lightkurve.org/reference/api/lightkurve.search_targetpixelfile.html?highlight=search_targetpixelfile) method to identify available observations for the desired target, and the [download](https://docs.lightkurve.org/reference/search.html?highlight=download) method to access the data.\n",
"\n",
"In what follows below, we will demonstrate PLD on the exoplanet system K2-199, which was observed during *K2* Campaign 6. We can download the pixel data as follows:"
]
},
{
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"user": {
"displayName": "Geert Barentsen",
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"outputs": [
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",
"text/plain": [
"\n",
"
"
],
"text/plain": [
"SearchResult containing 1 data products.\n",
"\n",
" # mission year author exptime target_name distance\n",
" s arcsec \n",
"--- -------------- ---- ------- ------- ----------- --------\n",
" 0 TESS Sector 10 2019 TESScut 1426 WR40 0.0"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"search_result = lk.search_tesscut('WR40', sector=10)\n",
"search_result"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "5YrXnxhnXRrH"
},
"source": [
"We can download the pixel data with the [download](https://docs.lightkurve.org/reference/search.html?highlight=download) method. When using TESScut, this method takes the additional parameter `cutout_size`, which determines how many pixels each side length of the cutout target pixel file should have.\n",
"\n",
"Here, we use seven pixels on each side, which strikes a good balance between downloading enough pixels to create a good background model, and not downloading too many pixels, which can result in the corrector running slowly or including neighboring stars in the noise model."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 420
},
"execution": {
"iopub.execute_input": "2023-11-03T14:23:01.049143Z",
"iopub.status.busy": "2023-11-03T14:23:01.048916Z",
"iopub.status.idle": "2023-11-03T14:23:02.655795Z",
"shell.execute_reply": "2023-11-03T14:23:02.655350Z"
},
"executionInfo": {
"elapsed": 14922,
"status": "ok",
"timestamp": 1601325388777,
"user": {
"displayName": "Geert Barentsen",
"photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj8sjdnDeqdejfe7OoouYPIclAQV0KSTpsU469Jyeo=s64",
"userId": "05704237875861987058"
},
"user_tz": 420
},
"id": "HzVkJdboxNbx",
"outputId": "3f214311-9196-4202-b9ba-73ef72eee8e3"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
" \n",
"# mission year author exptime target_name distance \n",
"s arcsec \n",
"0 TESS Sector 10 2019 TESScut 1426 WR40 0.0