Combining multiple quarters of Kepler data#

Learning Goals#

By the end of this tutorial, you will:

Understand a Kepler Quarter.
Understand how to download multiple quarters of data at once.
Learn how to normalize Kepler data.
Understand how to combine multiple quarters of data.

Introduction#

The Kepler, K2, and TESS telescopes observe stars for long periods of time. These long, time series observations are broken up into separate chunks, called quarters for the Kepler mission, campaigns for K2, and sectors for TESS.

Building light curves with as much data as is available is useful when searching for small signals, such as planetary transits or stellar pulsations. In this tutorial, we will learn how to use Lightkurve’s tools to download and stitch together multiple quarters of Kepler observations.

It is recommended to first read the tutorial discussing how to use Kepler light curve products with Lightkurve. That tutorial will introduce you to some specifics of how Kepler, K2, and TESS make observations, and how these are displayed as light curves. It also introduces some important terms and concepts that are referred to in this tutorial.

This tutorial demonstrates how to access and combine multiple quarters of data from the Kepler space telescope, using the Lightkurve package.

When accessing Kepler data through MAST, it will be stored in three-month chunks, corresponding to a quarter of observations. By combining and normalizing these separate observations, you can form a single light curve that spans all observed quarters. Utilizing all of the data available is especially important when looking at repeating signals, such as planet transits and stellar oscillations.

We will use the Kepler mission as an example, but these tools are extensible to TESS and K2 as well.

Imports#

This tutorial requires the Lightkurve package, which in turn uses matplotlib for plotting.

[1]:

import lightkurve as lk
%matplotlib inline

1. What is a Kepler Quarter?#

In order to search for planets around other stars, the Kepler space telescope performed near-continuous monitoring of a single field of view, from an Earth-trailing orbit. However, this posed a challenge. If the space telescope is trailing Earth and maintaining steady pointing, its solar panels would slowly receive less and less sunlight.

In order to make sure the solar panels remained oriented towards the Sun, Kepler performed quarterly rolls, one every 93 days. The infographic below helps visualize this, and shows the points in the orbit where the rolls took place.

After each roll, Kepler retained its fine-pointing at the same field of view. Because the camera rotated by 90 degrees, all of the target stars fell on different parts of the charge-coupled device (CCD) camera. This had an effect on the amount of flux recorded for the same star, because different CCD pixels have different sensitivities. The way in which the flux from the same stars was distributed on the CCD (called the point spread function or PSF) also changed after each roll, due to focus changes and other instrumental effects. As a result, the aperture mask set for a star had to be recomputed after each roll, and may capture slightly different amounts of flux.

The data obtained between rolls is referred to as a quarter. While there are changes to the flux systematics, not much else changes quarter to quarter, and the majority of the target list remains identical. This means that, after removing systematic trends (such as was done for the presearch data conditioning simple aperture photometry (PDCSAP) flux), multiple quarters together can form one continuous observation.

Figure: Infographic showcasing the necessity of Kepler’s quarterly rolls and its Earth-trailing orbit. Source: Kepler Science Center.

Note: Observations by K2 and TESS are also broken down into chunks of a month or more, called campaigns (for K2) and sectors (for TESS). While not discussed in this tutorial, the tools below work for these data products as well.

2. Downloading Multiple `KeplerLightCurve` Objects at Once#

To start, we can use Lightkurve’s search_lightcurve() function to see what data are available for our target star on the Mikulski Archive for Space Telescopes (MAST) archive. We will use the star Kepler-8, a star somewhat larger than the Sun, and the host of a hot Jupiter planet.

[2]:

search_result = lk.search_lightcurve("Kepler-8", author="Kepler", cadence="long")
search_result

[2]:

SearchResult containing 18 data products.

#	mission	year	author	exptime	target_name	distance
				s		arcsec
0	Kepler Quarter 00	2009	Kepler	1800	kplr006922244	0.0
1	Kepler Quarter 01	2009	Kepler	1800	kplr006922244	0.0
2	Kepler Quarter 02	2009	Kepler	1800	kplr006922244	0.0
3	Kepler Quarter 03	2009	Kepler	1800	kplr006922244	0.0
4	Kepler Quarter 04	2010	Kepler	1800	kplr006922244	0.0
5	Kepler Quarter 05	2010	Kepler	1800	kplr006922244	0.0
6	Kepler Quarter 06	2010	Kepler	1800	kplr006922244	0.0
7	Kepler Quarter 07	2010	Kepler	1800	kplr006922244	0.0
8	Kepler Quarter 10	2011	Kepler	1800	kplr006922244	0.0
9	Kepler Quarter 08	2011	Kepler	1800	kplr006922244	0.0
10	Kepler Quarter 09	2011	Kepler	1800	kplr006922244	0.0
11	Kepler Quarter 11	2012	Kepler	1800	kplr006922244	0.0
12	Kepler Quarter 12	2012	Kepler	1800	kplr006922244	0.0
13	Kepler Quarter 13	2012	Kepler	1800	kplr006922244	0.0
14	Kepler Quarter 14	2012	Kepler	1800	kplr006922244	0.0
15	Kepler Quarter 16	2013	Kepler	1800	kplr006922244	0.0
16	Kepler Quarter 15	2013	Kepler	1800	kplr006922244	0.0
17	Kepler Quarter 17	2013	Kepler	1800	kplr006922244	0.0

In this list, each row represents a different observing quarter, for a total of 18 quarters across four years. The observation column lists the Kepler Quarter. The target_name represents the Kepler Input Catalogue (KIC) ID of the target, and the productFilename column is the name of the FITS files downloaded from MAST. The distance column shows the separation on the sky between the searched coordinates and the downloaded objects — this is only relevant when searching for specific coordinates in the sky, and not when looking for individual objects.

Instead of downloading a single quarter using the download() function, we can use the download_all() function to access all 18 quarters at once (this might take a while).

[3]:

lc_collection = search_result.download_all()
lc_collection

[3]:

LightCurveCollection of 18 objects:
    0: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=0 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    1: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=1 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    2: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=2 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    3: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=3 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    4: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=4 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    5: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=5 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    6: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=6 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    7: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=7 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    8: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=10 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    9: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=8 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    10: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=9 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    11: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=11 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    12: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=12 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    13: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=13 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    14: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=14 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    15: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=16 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    16: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=15 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>
    17: <KeplerLightCurve LABEL="KIC 6922244" QUARTER=17 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux>

All of the downloaded data are stored in a LightCurveCollection. This object acts as a wrapper for 18 separate KeplerLightCurve objects, listed above.

We can access the KeplerLightCurve objects and interact with them as usual through the LightCurveCollection.

[4]:

lc_Q4 = lc_collection[4]
lc_Q4

[4]:

KeplerLightCurve length=4116 LABEL="KIC 6922244" QUARTER=4 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux

time	flux	flux_err	quality	timecorr	centroid_col	centroid_row	cadenceno	sap_flux	sap_flux_err	sap_bkg	sap_bkg_err	pdcsap_flux	pdcsap_flux_err	sap_quality	psf_centr1	psf_centr1_err	psf_centr2	psf_centr2_err	mom_centr1	mom_centr1_err	mom_centr2	mom_centr2_err	pos_corr1	pos_corr2
	electron / s	electron / s		d	pix	pix		electron / s	electron / s	electron / s	electron / s	electron / s	electron / s		pix	pix	pix	pix	pix	pix	pix	pix	pix	pix
Time	float32	float32	int32	float32	float64	float64	int32	float32	float32	float32	float32	float32	float32	int32	float64	float32	float64	float32	float64	float32	float64	float32	float32	float32
352.37632485035283	———	———	0	-1.410670e-03	682.69125	190.13296	11914	4.3689148e+04	6.6459765e+00	1.6722699e+03	4.6767941e-01	———	———	0	682.60927	7.8001787e-05	190.36814	1.1752916e-04	682.69125	1.8638317e-04	190.13296	1.8306405e-04	9.8764673e-02	-1.7217098e-01
352.3967580484896	5.2490750e+04	8.0003128e+00	10000000000000	-1.411072e-03	682.69084	190.13270	11915	4.3698070e+04	6.6462421e+00	1.6698400e+03	4.6764868e-01	5.2490750e+04	8.0003128e+00	10000000000000	682.60900	7.7997785e-05	190.36777	1.1751152e-04	682.69084	1.8633612e-04	190.13270	1.8303936e-04	9.8700106e-02	-1.7229939e-01
352.4376244455707	5.2484055e+04	7.9999790e+00	10000	-1.411874e-03	682.69038	190.13302	11917	4.3694105e+04	6.6461620e+00	1.6731306e+03	4.6705514e-01	5.2484055e+04	7.9999790e+00	10000	682.60862	7.7994831e-05	190.36848	1.1754913e-04	682.69038	1.8634219e-04	190.13302	1.8301954e-04	9.8306537e-02	-1.7180158e-01
352.45805764463876	5.2491809e+04	8.0006199e+00	0	-1.412275e-03	682.69084	190.13257	11918	4.3698316e+04	6.6463132e+00	1.6741406e+03	4.6687824e-01	5.2491809e+04	8.0006199e+00	0	682.60872	7.7998680e-05	190.36792	1.1751390e-04	682.69084	1.8635279e-04	190.13257	1.8304381e-04	9.8410256e-02	-1.7202987e-01
352.4784908439324	5.2478277e+04	7.9992733e+00	0	-1.412676e-03	682.68949	190.13304	11919	4.3687648e+04	6.6459165e+00	1.6723815e+03	4.6764576e-01	5.2478277e+04	7.9992733e+00	0	682.60829	7.7993544e-05	190.36814	1.1756293e-04	682.68949	1.8641398e-04	190.13304	1.8308057e-04	9.8039381e-02	-1.7183834e-01
352.4989240434661	5.2475855e+04	7.9986620e+00	0	-1.413077e-03	682.69036	190.13318	11920	4.3686480e+04	6.6458707e+00	1.6734375e+03	4.6817183e-01	5.2475855e+04	7.9986620e+00	0	682.60852	7.7998702e-05	190.36875	1.1761812e-04	682.69036	1.8637831e-04	190.13318	1.8304847e-04	9.8102726e-02	-1.7151666e-01
352.5193572433491	5.2487070e+04	7.9990516e+00	0	-1.413477e-03	682.69073	190.13307	11921	4.3692590e+04	6.6460714e+00	1.6731461e+03	4.6760359e-01	5.2487070e+04	7.9990516e+00	0	682.60880	7.8005593e-05	190.36825	1.1757523e-04	682.69073	1.8636670e-04	190.13307	1.8304495e-04	9.8343305e-02	-1.7184900e-01
352.53979034345684	5.2507734e+04	8.0051088e+00	10000000	-1.413877e-03	682.68909	190.13338	11922	4.3712012e+04	6.6500912e+00	1.6725844e+03	4.6755314e-01	5.2507734e+04	8.0051088e+00	10000000	682.60829	7.7979123e-05	190.36859	1.1755893e-04	682.68909	1.8644832e-04	190.13338	1.8299681e-04	9.8101854e-02	-1.7161448e-01
352.56022364380624	5.2472902e+04	8.0007839e+00	0	-1.414276e-03	682.69022	190.13343	11923	4.3683984e+04	6.6457977e+00	1.6750397e+03	4.6755785e-01	5.2472902e+04	8.0007839e+00	0	682.60824	7.7997676e-05	190.36889	1.1760603e-04	682.69022	1.8638840e-04	190.13343	1.8307337e-04	9.7997010e-02	-1.7128757e-01
352.5806568445041	5.2490586e+04	8.0011005e+00	0	-1.414675e-03	682.69067	190.13353	11924	4.3696762e+04	6.6464057e+00	1.6747676e+03	4.6741170e-01	5.2490586e+04	8.0011005e+00	0	682.60858	7.7987701e-05	190.36867	1.1758389e-04	682.69067	1.8633297e-04	190.13353	1.8302842e-04	9.8154068e-02	-1.7160916e-01
352.6010899455432	5.2484711e+04	8.0012350e+00	0	-1.415074e-03	682.69027	190.13306	11925	4.3693148e+04	6.6461196e+00	1.6724357e+03	4.6762615e-01	5.2484711e+04	8.0012350e+00	0	682.60849	7.7995923e-05	190.36871	1.1761376e-04	682.69027	1.8637281e-04	190.13306	1.8304559e-04	9.8116107e-02	-1.7139660e-01
352.6215232468239	5.2479773e+04	8.0013390e+00	10000000000000	-1.415473e-03	682.69014	190.13359	11926	4.3691348e+04	6.6462650e+00	1.6751807e+03	4.6757978e-01	5.2479773e+04	8.0013390e+00	10000000000000	682.60795	7.7985074e-05	190.36936	1.1769431e-04	682.69014	1.8639400e-04	190.13359	1.8310899e-04	9.7724356e-02	-1.7103195e-01
352.64195644845313	5.2499305e+04	8.0007114e+00	0	-1.415872e-03	682.69019	190.13330	11927	4.3703137e+04	6.6466208e+00	1.6736156e+03	4.6751177e-01	5.2499305e+04	8.0007114e+00	0	682.60841	7.7987228e-05	190.36887	1.1764505e-04	682.69019	1.8633960e-04	190.13330	1.8302450e-04	9.8125741e-02	-1.7140007e-01
352.6623896503079	5.2484117e+04	8.0014248e+00	0	-1.416270e-03	682.69002	190.13337	11928	4.3692902e+04	6.6462936e+00	1.6730603e+03	4.6794355e-01	5.2484117e+04	8.0014248e+00	0	682.60814	7.7984361e-05	190.36915	1.1766269e-04	682.69002	1.8636827e-04	190.13337	1.8306459e-04	9.7747400e-02	-1.7097178e-01
352.68282285240275	5.2487891e+04	8.0007782e+00	0	-1.416668e-03	682.68996	190.13380	11929	4.3696273e+04	6.6464286e+00	1.6735245e+03	4.6725965e-01	5.2487891e+04	8.0007782e+00	0	682.60813	7.7983277e-05	190.36919	1.1766609e-04	682.68996	1.8634208e-04	190.13380	1.8304669e-04	9.7714014e-02	-1.7095777e-01
352.70325605484686	5.2454434e+04	7.9984565e+00	0	-1.417065e-03	682.69014	190.13340	11930	4.3666207e+04	6.6449828e+00	1.6736576e+03	4.6680400e-01	5.2454434e+04	7.9984565e+00	0	682.60832	7.8020654e-05	190.36883	1.1766910e-04	682.69014	1.8649764e-04	190.13340	1.8317846e-04	9.7894058e-02	-1.7119597e-01
352.7236892575165	5.2472621e+04	8.0009689e+00	0	-1.417462e-03	682.69021	190.13375	11931	4.3683391e+04	6.6457801e+00	1.6753048e+03	4.6682772e-01	5.2472621e+04	8.0009689e+00	0	682.60797	7.7995486e-05	190.36951	1.1772667e-04	682.69021	1.8640491e-04	190.13375	1.8307207e-04	9.7682953e-02	-1.7075481e-01
352.7441224605427	5.2482875e+04	8.0009794e+00	0	-1.417859e-03	682.69041	190.13349	11932	4.3691410e+04	6.6464067e+00	1.6762039e+03	4.6761668e-01	5.2482875e+04	8.0009794e+00	0	682.60798	7.7983212e-05	190.36928	1.1769098e-04	682.69041	1.8641083e-04	190.13349	1.8309223e-04	9.7745605e-02	-1.7083719e-01
352.76455566380173	5.2493121e+04	8.0009432e+00	0	-1.418256e-03	682.68944	190.13347	11933	4.3701473e+04	6.6466613e+00	1.6743618e+03	4.6796089e-01	5.2493121e+04	8.0009432e+00	0	682.60765	7.7968449e-05	190.36908	1.1763493e-04	682.68944	1.8634081e-04	190.13347	1.8304866e-04	9.7519584e-02	-1.7081630e-01
352.7849888674027	5.2482012e+04	8.0010128e+00	0	-1.418653e-03	682.68999	190.13357	11934	4.3693109e+04	6.6463881e+00	1.6749097e+03	4.6720043e-01	5.2482012e+04	8.0010128e+00	0	682.60804	7.7987694e-05	190.36947	1.1771973e-04	682.68999	1.8636086e-04	190.13357	1.8305663e-04	9.7584486e-02	-1.7054483e-01
352.80542197124305	5.2485773e+04	8.0009441e+00	0	-1.419049e-03	682.68989	190.13358	11935	4.3694504e+04	6.6463594e+00	1.6748682e+03	4.6818867e-01	5.2485773e+04	8.0009441e+00	0	682.60782	7.7982280e-05	190.36952	1.1769895e-04	682.68989	1.8636433e-04	190.13358	1.8303795e-04	9.7454362e-02	-1.7061280e-01
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
441.77438253051514	5.2472027e+04	7.9701767e+00	10000000000000	-3.500895e-04	682.49137	190.34474	16289	4.3155488e+04	6.6141920e+00	1.5012952e+03	4.6742216e-01	5.2472027e+04	7.9701767e+00	10000000000000	682.42315	7.3329160e-05	190.68490	9.3236005e-05	682.49137	1.8502712e-04	190.34474	1.8690614e-04	-7.9620197e-02	1.3869031e-01
441.7948168942894	5.2483449e+04	7.9703755e+00	0	-3.493257e-04	682.49125	190.34433	16290	4.3164199e+04	6.6143861e+00	1.5015933e+03	4.6649483e-01	5.2483449e+04	7.9703755e+00	0	682.42327	7.3319563e-05	190.68475	9.3264607e-05	682.49125	1.8498245e-04	190.34433	1.8683473e-04	-7.9462834e-02	1.3846718e-01
441.8152511581502	5.2474996e+04	7.9697852e+00	0	-3.485619e-04	682.49165	190.34417	16291	4.3154418e+04	6.6140785e+00	1.5028657e+03	4.6644580e-01	5.2474996e+04	7.9697852e+00	0	682.42327	7.3324212e-05	190.68458	9.3323062e-05	682.49165	1.8503748e-04	190.34417	1.8689658e-04	-7.9532765e-02	1.3827184e-01
441.8356856221799	5.2469941e+04	7.9697943e+00	0	-3.477978e-04	682.49124	190.34488	16292	4.3153219e+04	6.6139221e+00	1.5025079e+03	4.6653268e-01	5.2469941e+04	7.9697943e+00	0	682.42314	7.3329662e-05	190.68498	9.3182280e-05	682.49124	1.8502890e-04	190.34488	1.8690157e-04	-7.9588197e-02	1.3860969e-01
441.8561199863325	5.2481059e+04	7.9711428e+00	0	-3.470337e-04	682.49182	190.34415	16293	4.3161004e+04	6.6144495e+00	1.5020490e+03	4.6753466e-01	5.2481059e+04	7.9711428e+00	0	682.42341	7.3324314e-05	190.68451	9.3318908e-05	682.49182	1.8501634e-04	190.34415	1.8688360e-04	-7.9376958e-02	1.3828298e-01
441.87655425060075	5.2466848e+04	7.9694710e+00	0	-3.462694e-04	682.49179	190.34417	16294	4.3149250e+04	6.6137443e+00	1.5030779e+03	4.6643156e-01	5.2466848e+04	7.9694710e+00	0	682.42362	7.3329109e-05	190.68459	9.3358700e-05	682.49179	1.8505476e-04	190.34417	1.8690665e-04	-7.9315238e-02	1.3822258e-01
441.89698871497967	5.2474023e+04	7.9719896e+00	10000000	-3.455050e-04	682.49150	190.34448	16295	4.3157855e+04	6.6145024e+00	1.5011398e+03	4.6713176e-01	5.2474023e+04	7.9719896e+00	10000000	682.42325	7.3322197e-05	190.68476	9.3278293e-05	682.49150	1.8496772e-04	190.34448	1.8688334e-04	-7.9429932e-02	1.3862607e-01
441.91742307953973	5.2472281e+04	7.9701529e+00	0	-3.447405e-04	682.49128	190.34399	16296	4.3154711e+04	6.6138754e+00	1.5010295e+03	4.6696991e-01	5.2472281e+04	7.9701529e+00	0	682.42318	7.3326584e-05	190.68454	9.3316215e-05	682.49128	1.8502600e-04	190.34399	1.8689150e-04	-7.9607107e-02	1.3834631e-01
441.93785734418634	5.2472938e+04	7.9703026e+00	0	-3.439758e-04	682.49165	190.34435	16297	4.3154684e+04	6.6139832e+00	1.5008883e+03	4.6656749e-01	5.2472938e+04	7.9703026e+00	0	682.42337	7.3328170e-05	190.68485	9.3249735e-05	682.49165	1.8502508e-04	190.34435	1.8690228e-04	-7.9325221e-02	1.3840406e-01
441.95829170897196	5.2471516e+04	7.9689603e+00	0	-3.432110e-04	682.49119	190.34454	16298	4.3155348e+04	6.6138535e+00	1.5008563e+03	4.6656010e-01	5.2471516e+04	7.9689603e+00	0	682.42304	7.3324562e-05	190.68514	9.3178627e-05	682.49119	1.8498173e-04	190.34454	1.8685704e-04	-7.9735115e-02	1.3892399e-01
441.9991604389361	5.2475980e+04	7.9695969e+00	0	-3.416811e-04	682.49093	190.34463	16300	4.3155496e+04	6.6140313e+00	1.5005978e+03	4.6754882e-01	5.2475980e+04	7.9695969e+00	0	682.42299	7.3329807e-05	190.68475	9.3298462e-05	682.49093	1.8499741e-04	190.34463	1.8689795e-04	-7.9793788e-02	1.3853292e-01
442.01959480413643	5.2471406e+04	7.9692073e+00	0	-3.409159e-04	682.49127	190.34491	16301	4.3153082e+04	6.6136584e+00	1.5008551e+03	4.6549889e-01	5.2471406e+04	7.9692073e+00	0	682.42285	7.3334042e-05	190.68535	9.3125935e-05	682.49127	1.8501784e-04	190.34491	1.8689032e-04	-7.9899147e-02	1.3902473e-01
442.0400292694467	5.2484672e+04	7.9713697e+00	0	-3.401506e-04	682.49096	190.34401	16302	4.3162852e+04	6.6141791e+00	1.4984926e+03	4.6637267e-01	5.2484672e+04	7.9713697e+00	0	682.42309	7.3324874e-05	190.68494	9.3243980e-05	682.49096	1.8510064e-04	190.34401	1.8683969e-04	-7.9640254e-02	1.3871230e-01
442.0604635348791	5.2490562e+04	7.9703860e+00	0	-3.393851e-04	682.49125	190.34495	16303	4.3167781e+04	6.6144958e+00	1.5003789e+03	4.6711573e-01	5.2490562e+04	7.9703860e+00	0	682.42306	7.3320742e-05	190.68526	9.3141578e-05	682.49125	1.8497938e-04	190.34495	1.8685836e-04	-7.9665780e-02	1.3868718e-01
442.0808979004214	5.2474590e+04	7.9709330e+00	10000000	-3.386196e-04	682.49142	190.34449	16304	4.3156332e+04	6.6142426e+00	1.5022838e+03	4.6630958e-01	5.2474590e+04	7.9709330e+00	10000000	682.42296	7.3331044e-05	190.68509	9.3194321e-05	682.49142	1.8501014e-04	190.34449	1.8690975e-04	-7.9900064e-02	1.3900562e-01
442.1013323661464	5.2484648e+04	7.9707704e+00	0	-3.378539e-04	682.49086	190.34446	16305	4.3164066e+04	6.6142449e+00	1.4996798e+03	4.6686992e-01	5.2484648e+04	7.9707704e+00	0	682.42295	7.3321760e-05	190.68497	9.3209848e-05	682.49086	1.8497877e-04	190.34446	1.8690305e-04	-7.9818368e-02	1.3874538e-01
442.1217667319579	5.2479809e+04	7.9702587e+00	10000000000000	-3.370880e-04	682.49145	190.34413	16306	4.3160660e+04	6.6141462e+00	1.4999071e+03	4.6648329e-01	5.2479809e+04	7.9702587e+00	10000000000000	682.42312	7.3320341e-05	190.68516	9.3171802e-05	682.49145	1.8498853e-04	190.34413	1.8685416e-04	-7.9732254e-02	1.3886212e-01
442.1422009979142	5.2475605e+04	7.9712372e+00	0	-3.363221e-04	682.49124	190.34487	16307	4.3157629e+04	6.6139336e+00	1.4981315e+03	4.6694338e-01	5.2475605e+04	7.9712372e+00	0	682.42282	7.3328265e-05	190.68556	9.3097420e-05	682.49124	1.8495553e-04	190.34487	1.8686226e-04	-7.9895072e-02	1.3914314e-01
442.16263546398113	5.2475305e+04	7.9707313e+00	0	-3.355560e-04	682.49104	190.34460	16308	4.3155801e+04	6.6138582e+00	1.4982946e+03	4.6778497e-01	5.2475305e+04	7.9707313e+00	0	682.42288	7.3337091e-05	190.68500	9.3226627e-05	682.49104	1.8501762e-04	190.34460	1.8689682e-04	-7.9854071e-02	1.3877387e-01
442.1830698302001	5.2465984e+04	7.9693055e+00	0	-3.347898e-04	682.49114	190.34490	16309	4.3148465e+04	6.6134605e+00	1.4987802e+03	4.6625513e-01	5.2465984e+04	7.9693055e+00	0	682.42267	7.3346317e-05	190.68542	9.3117917e-05	682.49114	1.8503764e-04	190.34490	1.8691395e-04	-7.9959184e-02	1.3906266e-01
442.20350409652747	5.2471043e+04	7.9698005e+00	0	-3.340235e-04	682.49069	190.34464	16310	4.3151559e+04	6.6137042e+00	1.4977747e+03	4.6697757e-01	5.2471043e+04	7.9698005e+00	0	682.42272	7.3345473e-05	190.68528	9.3169489e-05	682.49069	1.8501126e-04	190.34464	1.8690964e-04	-7.9990946e-02	1.3905971e-01

[5]:

lc_Q4.plot();

../../_images/tutorials_2-creating-light-curves_2-1-combining-multiple-quarters_16_0.png

Note:#

The example given above also works for downloading target pixel files (TPFs). This will produce a TargetPixelFileCollection object instead.

3. Investigating the Data#

Let’s first have a look at how these observations differ from one another. We can plot the simple aperture photometry (SAP) flux of all of the observations in the `LightCurveCollection <https://docs.lightkurve.org/reference/api/lightkurve.collections.LightCurveCollection.html#lightkurve.collections.LightCurveCollection>`__ to see how they compare.

[6]:

ax = lc_collection[0].plot(column='sap_flux', label=None)
for lc in lc_collection[1:]:
    lc.plot(ax=ax, column='sap_flux', label=None)

../../_images/tutorials_2-creating-light-curves_2-1-combining-multiple-quarters_20_0.png

In the figure above, each quarter of data looks strikingly different, with global patterns repeating every four quarters as Kepler has made a full rotation.

The change in flux within each quarter is in part driven by changes in the telescope focus, which are caused by changes in the temperature of Kepler’s components as the spacecraft orbits the Sun. The changes are also caused by an effect called differential velocity aberration (DVA), which causes stars to drift over the course of a quarter, depending on their distance from the center of Kepler’s field of view.

While the figure above looks messy, all the systematic effects mentioned above are well understood, and have been detrended in the PDCSAP flux. For a more detailed overview, see the Kepler Data Characteristics Handbook, specifically: Section 5. Ongoing Phenomena.

4. Normalizing a Light Curve#

If we want to see the actual variation of the targeted object over the course of these observations, the plot above isn’t very useful to us. It is also not useful to have flux expressed in physical units, because it is affected by the observing conditions such as telescope focus and pointing (see above).

Instead, it is a common practice to normalize light curves by dividing by their median value. This means that the median of the newly normalized light curve will be equal to 1, and that the relative size of signals in the observation (such as transits) will be maintained.

A normalization can be performed using the normalize() method of a KeplerLightCurve, for example:

[7]:

lc_collection[4].normalize().plot();

../../_images/tutorials_2-creating-light-curves_2-1-combining-multiple-quarters_24_0.png

In the figure above, we have plotted the normalized PDCSAP flux for Quarter 4. The median normalized flux is at 1, and the transit depths lie around 0.991, indicating a 0.9% dip in brightness due to the planet transiting the star.

The LightCurveCollection also has a plot() method. We can use it to plot the PDCSAP flux. The method automatically normalizes the flux in same way we did for a single quarter above.

[8]:

lc_collection.plot();

../../_images/tutorials_2-creating-light-curves_2-1-combining-multiple-quarters_27_0.png

As you can see above, because we have normalized the data, all of the observations form a single consistent light curve.

5. Combining Multiple Observations into a Single Light Curve#

Finally, we can combine these different light curves into a single KeplerLightCurve object. This is done using the stitch() method. This method concatenates all quarters in our LightCurveCollection together, and normalizes them at the same time, in the manner we saw above.

[9]:

lc_stitched = lc_collection.stitch()
lc_stitched

[9]:

KeplerLightCurve length=65504 LABEL="KIC 6922244" QUARTER=17 AUTHOR=Kepler FLUX_ORIGIN=pdcsap_flux

time	flux	flux_err	quality	timecorr	centroid_col	centroid_row	cadenceno	sap_flux	sap_flux_err	sap_bkg	sap_bkg_err	pdcsap_flux	pdcsap_flux_err	sap_quality	psf_centr1	psf_centr1_err	psf_centr2	psf_centr2_err	mom_centr1	mom_centr1_err	mom_centr2	mom_centr2_err	pos_corr1	pos_corr2
				d	pix	pix		electron / s	electron / s	electron / s	electron / s	electron / s	electron / s		pix	pix	pix	pix	pix	pix	pix	pix	pix	pix
Time	float32	float32	int32	float32	float64	float64	int32	float32	float32	float32	float32	float32	float32	int32	float64	float32	float64	float32	float64	float32	float64	float32	float32	float32
120.53979406206781	1.0002389e+00	1.7835133e-04	0	1.641642e-03	676.76061	192.21102	568	4.0029211e+04	7.1942086e+00	1.3501000e+03	6.9019127e-01	4.9790078e+04	8.8780060e+00	0	———	———	———	———	676.76061	2.4257520e-04	192.21102	2.8915040e-04	-6.1361594e-03	1.2139007e-02
120.56022845695406	1.0000123e+00	1.7952095e-04	0	1.642437e-03	676.76010	192.21002	569	4.0014566e+04	7.1924801e+00	1.3488469e+03	6.8939346e-01	4.9778801e+04	8.9362278e+00	0	———	———	———	———	676.76010	2.4263318e-04	192.21002	2.8926603e-04	-6.3053877e-03	1.1505429e-02
120.58066275172314	9.9970073e-01	1.7981241e-04	0	1.643232e-03	676.76146	192.20988	570	4.0000406e+04	7.1918778e+00	1.3513733e+03	6.8988037e-01	4.9763289e+04	8.9507360e+00	0	———	———	———	———	676.76146	2.4270279e-04	192.20988	2.8932444e-04	-5.5118860e-03	1.1369802e-02
120.60109724637005	1.0002698e+00	1.7900635e-04	0	1.644026e-03	676.76139	192.20938	571	4.0018668e+04	7.1936789e+00	1.3461132e+03	6.8999070e-01	4.9791617e+04	8.9106121e+00	0	———	———	———	———	676.76139	2.4260787e-04	192.20938	2.8922342e-04	-5.5788676e-03	1.0246177e-02
120.62153164102347	1.0001223e+00	1.7974019e-04	0	1.644821e-03	676.76213	192.20898	572	4.0008617e+04	7.1923513e+00	1.3499850e+03	6.9054097e-01	4.9784277e+04	8.9471407e+00	0	———	———	———	———	676.76213	2.4259168e-04	192.20898	2.8918759e-04	-4.6821944e-03	1.0072310e-02
120.6419659354433	9.9984479e-01	1.7990815e-04	0	1.645615e-03	676.76170	192.20871	573	3.9994742e+04	7.1914024e+00	1.3490905e+03	6.8729931e-01	4.9770461e+04	8.9555016e+00	0	———	———	———	———	676.76170	2.4268354e-04	192.20871	2.8930244e-04	-4.2848983e-03	9.4073853e-03
120.66240032985661	9.9989384e-01	1.7951278e-04	0	1.646410e-03	676.76318	192.20914	574	3.9994105e+04	7.1914792e+00	1.3482495e+03	6.8812454e-01	4.9772902e+04	8.9358206e+00	0	———	———	———	———	676.76318	2.4266902e-04	192.20914	2.8928166e-04	-4.3740734e-03	9.1674784e-03
120.68283482416155	1.0001035e+00	1.7969948e-04	0	1.647204e-03	676.76312	192.20849	575	3.9999207e+04	7.1918936e+00	1.3490680e+03	6.8974006e-01	4.9783336e+04	8.9451141e+00	0	———	———	———	———	676.76312	2.4268078e-04	192.20849	2.8929702e-04	-4.1775936e-03	9.0572909e-03
120.70326911834854	1.0001053e+00	1.7944223e-04	0	1.647998e-03	676.76273	192.20788	576	3.9999398e+04	7.1918974e+00	1.3484713e+03	6.9063425e-01	4.9783430e+04	8.9323092e+00	0	———	———	———	———	676.76273	2.4269335e-04	192.20788	2.8931847e-04	-4.2246603e-03	8.9526922e-03
120.72370351241261	9.9972838e-01	1.7980891e-04	0	1.648792e-03	676.76356	192.20844	577	3.9980332e+04	7.1909018e+00	1.3500632e+03	6.8898243e-01	4.9764668e+04	8.9505615e+00	0	———	———	———	———	676.76356	2.4274348e-04	192.20844	2.8934795e-04	-3.6518988e-03	8.6694220e-03
120.7441380063683	9.9991816e-01	1.7982410e-04	0	1.649586e-03	676.76290	192.20823	578	3.9986969e+04	7.1911378e+00	1.3483744e+03	6.8921554e-01	4.9774113e+04	8.9513178e+00	0	———	———	———	———	676.76290	2.4267519e-04	192.20823	2.8925485e-04	-4.2593810e-03	8.6670099e-03
120.76457230020605	1.0000777e+00	1.7961828e-04	0	1.650380e-03	676.76368	192.20832	579	3.9993461e+04	7.1915126e+00	1.3493782e+03	6.9010836e-01	4.9782059e+04	8.9410725e+00	0	———	———	———	———	676.76368	2.4261384e-04	192.20832	2.8921201e-04	-4.0798583e-03	8.5424539e-03
120.78500669403729	1.0001794e+00	1.7991407e-04	0	1.651174e-03	676.76312	192.20837	580	3.9994191e+04	7.1915045e+00	1.3484170e+03	6.9068658e-01	4.9787117e+04	8.9557962e+00	0	———	———	———	———	676.76312	2.4261570e-04	192.20837	2.8919929e-04	-3.9779227e-03	8.7358346e-03
120.80544108764298	1.0000017e+00	1.7959387e-04	0	1.651968e-03	676.76315	192.20820	581	3.9988062e+04	7.1911521e+00	1.3466672e+03	6.8924570e-01	4.9778270e+04	8.9398575e+00	0	———	———	———	———	676.76315	2.4270946e-04	192.20820	2.8934758e-04	-4.1689188e-03	8.5440101e-03
120.82587548124866	1.0000064e+00	1.7977894e-04	10000000000000	1.652761e-03	676.76347	192.20857	582	3.9987578e+04	7.1914353e+00	1.3481720e+03	6.8972218e-01	4.9778508e+04	8.9490700e+00	10000000000000	———	———	———	———	676.76347	2.4273068e-04	192.20857	2.8933285e-04	-3.8271099e-03	8.4978435e-03
120.84630987473065	9.9976701e-01	1.7967194e-04	0	1.653555e-03	676.76349	192.20819	583	3.9975953e+04	7.1906495e+00	1.3464335e+03	6.8944293e-01	4.9766590e+04	8.9437437e+00	0	———	———	———	———	676.76349	2.4274443e-04	192.20819	2.8933870e-04	-4.0272451e-03	8.7294048e-03
120.8667442681035	9.9991292e-01	1.7955873e-04	0	1.654348e-03	676.76277	192.20799	584	3.9982359e+04	7.1910934e+00	1.3462968e+03	6.8985498e-01	4.9773852e+04	8.9381084e+00	0	———	———	———	———	676.76277	2.4271930e-04	192.20799	2.8933887e-04	-4.4883061e-03	8.4281666e-03
120.8871787613607	1.0003110e+00	1.7942073e-04	0	1.655141e-03	676.76269	192.20812	585	3.9996445e+04	7.1915159e+00	1.3462880e+03	6.8817896e-01	4.9793668e+04	8.9312391e+00	0	———	———	———	———	676.76269	2.4267842e-04	192.20812	2.8925715e-04	-3.7898819e-03	8.3442759e-03
120.90761305449269	1.0002247e+00	1.7923271e-04	0	1.655934e-03	676.76323	192.20749	586	3.9994336e+04	7.1921434e+00	1.3603102e+03	6.9024485e-01	4.9789371e+04	8.9218798e+00	0	———	———	———	———	676.76323	2.4267327e-04	192.20749	2.8929141e-04	-4.1035144e-03	8.1515834e-03
120.92804744751629	1.0001659e+00	1.7970537e-04	0	1.656728e-03	676.76282	192.20776	587	3.9991961e+04	7.1913185e+00	1.3493534e+03	6.8825614e-01	4.9786445e+04	8.9454079e+00	0	———	———	———	———	676.76282	2.4264003e-04	192.20776	2.8921882e-04	-3.8633295e-03	7.8232531e-03
120.94848194041697	1.0000652e+00	1.7924111e-04	0	1.657520e-03	676.76404	192.20744	588	3.9985609e+04	7.1911731e+00	1.3472162e+03	6.8970609e-01	4.9781434e+04	8.9222975e+00	0	———	———	———	———	676.76404	2.4266091e-04	192.20744	2.8927453e-04	-3.9033771e-03	7.8699794e-03
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1590.593485989477	9.9980414e-01	1.8180821e-04	0	1.005969e-03	676.80108	192.10167	72511	3.7832156e+04	6.9086194e+00	1.2795405e+03	5.9311622e-01	4.8590555e+04	8.8358927e+00	0	676.75919	1.4914248e-04	192.31926	1.9162059e-04	676.80108	2.5236819e-04	192.10167	2.5268109e-04	-4.0421635e-03	1.5071657e-02
1590.6139205341824	9.9987459e-01	1.8174193e-04	0	1.006814e-03	676.80150	192.10118	72512	3.7836773e+04	6.9088635e+00	1.2761102e+03	5.9432328e-01	4.8593980e+04	8.8326712e+00	0	676.75924	1.4911359e-04	192.31938	1.9166723e-04	676.80150	2.5231350e-04	192.10118	2.5263822e-04	-4.0005427e-03	1.5168709e-02
1590.6343548788936	1.0001699e+00	1.8185568e-04	0	1.007659e-03	676.80087	192.10175	72513	3.7846160e+04	6.9093790e+00	1.2783875e+03	5.9488696e-01	4.8608328e+04	8.8381996e+00	0	676.75903	1.4909731e-04	192.31937	1.9157933e-04	676.80087	2.5224124e-04	192.10175	2.5255818e-04	-4.0560486e-03	1.5126259e-02
1590.6547893236057	9.9989152e-01	1.8180616e-04	0	1.008504e-03	676.80145	192.10152	72514	3.7833961e+04	6.9087481e+00	1.2788304e+03	5.9421456e-01	4.8594801e+04	8.8357925e+00	0	676.75913	1.4912970e-04	192.31944	1.9164132e-04	676.80145	2.5234083e-04	192.10152	2.5264587e-04	-4.0063737e-03	1.4987757e-02
1590.6752238681947	9.9965316e-01	1.8175396e-04	0	1.009348e-03	676.80135	192.10134	72515	3.7828738e+04	6.9084511e+00	1.2780225e+03	5.9484589e-01	4.8583219e+04	8.8332558e+00	0	676.75914	1.4913827e-04	192.31913	1.9162054e-04	676.80135	2.5233746e-04	192.10134	2.5268053e-04	-4.1187471e-03	1.4959974e-02
1590.6956583127903	9.9944270e-01	1.8181655e-04	0	1.010193e-03	676.80077	192.10169	72516	3.7816570e+04	6.9078817e+00	1.2804856e+03	5.9302461e-01	4.8572988e+04	8.8362980e+00	0	676.75913	1.4919603e-04	192.31928	1.9171166e-04	676.80077	2.5247029e-04	192.10169	2.5280181e-04	-4.0578465e-03	1.5171147e-02
1590.716092757386	9.9996263e-01	1.8163536e-04	0	1.011037e-03	676.80175	192.10160	72517	3.7834430e+04	6.9086723e+00	1.2790287e+03	5.9365737e-01	4.8598258e+04	8.8274918e+00	0	676.75950	1.4910228e-04	192.31909	1.9151477e-04	676.80175	2.5231022e-04	192.10160	2.5262687e-04	-3.9766431e-03	1.5037012e-02
1590.7365272019742	1.0000714e+00	1.8180149e-04	0	1.011882e-03	676.80106	192.10141	72518	3.7839820e+04	6.9090056e+00	1.2800005e+03	5.9376341e-01	4.8603547e+04	8.8355656e+00	0	676.75910	1.4913200e-04	192.31898	1.9152767e-04	676.80106	2.5234206e-04	192.10141	2.5265501e-04	-4.0287725e-03	1.4835904e-02
1590.7569616465698	1.0001386e+00	1.8167667e-04	0	1.012727e-03	676.80150	192.10170	72519	3.7840723e+04	6.9090314e+00	1.2798903e+03	5.9264499e-01	4.8606812e+04	8.8295002e+00	0	676.75936	1.4909540e-04	192.31915	1.9152566e-04	676.80150	2.5233233e-04	192.10170	2.5265972e-04	-4.0084850e-03	1.4944902e-02
1590.777396091049	1.0002724e+00	1.8169760e-04	0	1.013571e-03	676.80118	192.10118	72520	3.7845848e+04	6.9092903e+00	1.2783662e+03	5.9346884e-01	4.8613312e+04	8.8305168e+00	0	676.75932	1.4911308e-04	192.31909	1.9152572e-04	676.80118	2.5229072e-04	192.10118	2.5260213e-04	-4.0129293e-03	1.5089383e-02
1590.797830535521	9.9970955e-01	1.8178376e-04	0	1.014416e-03	676.80111	192.10123	72521	3.7825008e+04	6.9083376e+00	1.2804839e+03	5.9345853e-01	4.8585957e+04	8.8347044e+00	0	676.75931	1.4916483e-04	192.31883	1.9153745e-04	676.80111	2.5238545e-04	192.10123	2.5271109e-04	-4.1054105e-03	1.4747544e-02
1590.81826498	9.9976480e-01	1.8179227e-04	0	1.015260e-03	676.80111	192.10133	72522	3.7826906e+04	6.9083934e+00	1.2777081e+03	5.9248704e-01	4.8588645e+04	8.8351183e+00	0	676.75927	1.4917154e-04	192.31890	1.9156512e-04	676.80111	2.5241618e-04	192.10133	2.5272943e-04	-3.9865761e-03	1.4864406e-02
1590.8386995243636	9.9977714e-01	1.8188541e-04	0	1.016104e-03	676.80109	192.10132	72523	3.7828023e+04	6.9085383e+00	1.2810897e+03	5.9335488e-01	4.8589242e+04	8.8396444e+00	0	676.75917	1.4919229e-04	192.31896	1.9155757e-04	676.80109	2.5239991e-04	192.10132	2.5271578e-04	-4.0576421e-03	1.4865786e-02
1590.8591338688348	9.9998957e-01	1.8168797e-04	0	1.016949e-03	676.80133	192.10114	72524	3.7832582e+04	6.9087262e+00	1.2798925e+03	5.9355038e-01	4.8599566e+04	8.8300486e+00	0	676.75919	1.4914903e-04	192.31896	1.9151389e-04	676.80133	2.5240114e-04	192.10114	2.5271127e-04	-4.0520453e-03	1.4725811e-02
1590.8795683131975	9.9989623e-01	1.8185582e-04	10000010000000	1.017793e-03	676.80167	192.10122	72525	3.7832602e+04	6.9091139e+00	1.2815891e+03	5.9373122e-01	4.8595031e+04	8.8382063e+00	10000010000000	676.75954	1.4915224e-04	192.31898	1.9158589e-04	676.80167	2.5239732e-04	192.10122	2.5277122e-04	-3.9305747e-03	1.5043449e-02
1590.900002857561	9.9988633e-01	1.8179342e-04	0	1.018638e-03	676.80148	192.10108	72526	3.7831559e+04	6.9085450e+00	1.2787664e+03	5.9414190e-01	4.8594551e+04	8.8351736e+00	0	676.75930	1.4916631e-04	192.31896	1.9152595e-04	676.80148	2.5232948e-04	192.10108	2.5263420e-04	-4.0509203e-03	1.4821382e-02
1590.9204372017994	9.9999821e-01	1.8173133e-04	0	1.019482e-03	676.80166	192.10131	72527	3.7836602e+04	6.9087906e+00	1.2786053e+03	5.9385866e-01	4.8599988e+04	8.8321562e+00	0	676.75946	1.4911903e-04	192.31899	1.9154462e-04	676.80166	2.5230341e-04	192.10131	2.5262410e-04	-4.0993756e-03	1.4611045e-02
1590.9408717461629	9.9969560e-01	1.8179418e-04	0	1.020326e-03	676.80144	192.10146	72528	3.7825430e+04	6.9083652e+00	1.2797456e+03	5.9316140e-01	4.8585281e+04	8.8352108e+00	0	676.75953	1.4916577e-04	192.31908	1.9160371e-04	676.80144	2.5239564e-04	192.10146	2.5271456e-04	-3.9369571e-03	1.4928485e-02
1590.9613061904092	9.9994302e-01	1.8176372e-04	0	1.021170e-03	676.80124	192.10091	72529	3.7834938e+04	6.9087672e+00	1.2764705e+03	5.9434044e-01	4.8597305e+04	8.8337307e+00	0	676.75914	1.4914536e-04	192.31884	1.9145805e-04	676.80124	2.5227590e-04	192.10091	2.5260207e-04	-4.1014180e-03	1.4680510e-02
1590.9817405346475	1.0001228e+00	1.8151020e-04	0	1.022015e-03	676.80224	192.10165	72530	3.7828816e+04	6.9086733e+00	1.2774485e+03	5.9289569e-01	4.8606039e+04	8.8214092e+00	0	676.75981	1.4909096e-04	192.31980	1.9197758e-04	676.80224	2.5231845e-04	192.10165	2.5264811e-04	-3.6829417e-03	1.6025381e-02
1591.0021750787782	9.9999636e-01	1.8174112e-04	0	1.022859e-03	676.80192	192.10123	72531	3.7825363e+04	6.9084020e+00	1.2774999e+03	5.9428430e-01	4.8599898e+04	8.8326321e+00	0	676.75964	1.4915710e-04	192.31887	1.9161010e-04	676.80192	2.5232456e-04	192.10123	2.5267553e-04	-3.9303382e-03	1.5094034e-02

This returns a single KeplerLightCurve! It is in all ways identical to KeplerLightCurve of a single quarter, just longer. We can plot it the usual way.

[10]:

lc_stitched.plot();

../../_images/tutorials_2-creating-light-curves_2-1-combining-multiple-quarters_33_0.png

In this final normalized light curve, the interesting observational features of the star are more clear. Specifically: repeating transits that can be used to characterize planets and a noisy stellar flux that can be used to study brightness variability through asteroseismology.

Normalizing individual Kepler Quarters before combining them to form a single light curve isn’t the only way to make sure different quarters are consistent with one another. For a breakdown of other available methods and their benefits, see Section 6. Stitching Kepler Quarters Together in Kinemuchi et al. 2012.

About this Notebook#

Authors: Oliver Hall (oliver.hall@esa.int), Geert Barentsen

Updated On: 2020-09-15

Citing Lightkurve and Astropy#

If you use lightkurve or astropy for published research, please cite the authors. Click the buttons below to copy BibTeX entries to your clipboard.

[11]:

lk.show_citation_instructions()

[11]:

@ARTICLE{astropy:2022,
       author = {{Astropy Collaboration} and {Price-Whelan}, Adrian M. and {Lim}, Pey
       Lian and {Earl}, Nicholas and {Starkman}, Nathaniel and {Bradley}, Larry and
       {Shupe}, David L. and {Patil}, Aarya A. and {Corrales}, Lia and {Brasseur}, C.~E.
       and {N{\"o}the}, Maximilian and {Donath}, Axel and {Tollerud}, Erik and {Morris},
       Brett M. and {Ginsburg}, Adam and {Vaher}, Eero and {Weaver}, Benjamin A. and
       {Tocknell}, James and {Jamieson}, William and {van Kerkwijk}, Marten H. and
       {Robitaille}, Thomas P. and {Merry}, Bruce and {Bachetti}, Matteo and
       {G{\"u}nther}, H. Moritz and {Aldcroft}, Thomas L. and {Alvarado-Montes}, Jaime
       A. and {Archibald}, Anne M. and {B{\'o}di}, Attila and {Bapat}, Shreyas and
       {Barentsen}, Geert and {Baz{\'a}n}, Juanjo and {Biswas}, Manish and {Boquien},
       M{\'e}d{\'e}ric and {Burke}, D.~J. and {Cara}, Daria and {Cara}, Mihai and
       {Conroy}, Kyle E. and {Conseil}, Simon and {Craig}, Matthew W. and {Cross},
       Robert M. and {Cruz}, Kelle L. and {D'Eugenio}, Francesco and {Dencheva}, Nadia
       and {Devillepoix}, Hadrien A.~R. and {Dietrich}, J{\"o}rg P. and {Eigenbrot},
       Arthur Davis and {Erben}, Thomas and {Ferreira}, Leonardo and {Foreman-Mackey},
       Daniel and {Fox}, Ryan and {Freij}, Nabil and {Garg}, Suyog and {Geda}, Robel and
       {Glattly}, Lauren and {Gondhalekar}, Yash and {Gordon}, Karl D. and {Grant},
       David and {Greenfield}, Perry and {Groener}, Austen M. and {Guest}, Steve and
       {Gurovich}, Sebastian and {Handberg}, Rasmus and {Hart}, Akeem and
       {Hatfield-Dodds}, Zac and {Homeier}, Derek and {Hosseinzadeh}, Griffin and
       {Jenness}, Tim and {Jones}, Craig K. and {Joseph}, Prajwel and {Kalmbach}, J.
       Bryce and {Karamehmetoglu}, Emir and {Ka{\l}uszy{\'n}ski}, Miko{\l}aj and
       {Kelley}, Michael S.~P. and {Kern}, Nicholas and {Kerzendorf}, Wolfgang E. and
       {Koch}, Eric W. and {Kulumani}, Shankar and {Lee}, Antony and {Ly}, Chun and
       {Ma}, Zhiyuan and {MacBride}, Conor and {Maljaars}, Jakob M. and {Muna}, Demitri
       and {Murphy}, N.~A. and {Norman}, Henrik and {O'Steen}, Richard and {Oman}, Kyle
       A. and {Pacifici}, Camilla and {Pascual}, Sergio and {Pascual-Granado}, J. and
       {Patil}, Rohit R. and {Perren}, Gabriel I. and {Pickering}, Timothy E. and
       {Rastogi}, Tanuj and {Roulston}, Benjamin R. and {Ryan}, Daniel F. and {Rykoff},
       Eli S. and {Sabater}, Jose and {Sakurikar}, Parikshit and {Salgado}, Jes{\'u}s
       and {Sanghi}, Aniket and {Saunders}, Nicholas and {Savchenko}, Volodymyr and
       {Schwardt}, Ludwig and {Seifert-Eckert}, Michael and {Shih}, Albert Y. and
       {Jain}, Anany Shrey and {Shukla}, Gyanendra and {Sick}, Jonathan and {Simpson},
       Chris and {Singanamalla}, Sudheesh and {Singer}, Leo P. and {Singhal}, Jaladh and
       {Sinha}, Manodeep and {Sip{\H{o}}cz}, Brigitta M. and {Spitler}, Lee R. and
       {Stansby}, David and {Streicher}, Ole and {{\v{S}}umak}, Jani and {Swinbank},
       John D. and {Taranu}, Dan S. and {Tewary}, Nikita and {Tremblay}, Grant R. and
       {Val-Borro}, Miguel de and {Van Kooten}, Samuel J. and {Vasovi{\'c}}, Zlatan and
       {Verma}, Shresth and {de Miranda Cardoso}, Jos{\'e} Vin{\'\i}cius and {Williams},
       Peter K.~G. and {Wilson}, Tom J. and {Winkel}, Benjamin and {Wood-Vasey}, W.~M.
       and {Xue}, Rui and {Yoachim}, Peter and {Zhang}, Chen and {Zonca}, Andrea and
       {Astropy Project Contributors}}, title = "{The Astropy Project: Sustaining and
       Growing a Community-oriented Open-source Project and the Latest Major Release
       (v5.0) of the Core Package}",
      journal = {\apj},
     keywords = {Astronomy software, Open source software, Astronomy data analysis, 1855, 1866, 1858, Astrophysics - Instrumentation and Methods for Astrophysics},
         year = 2022,
        month = aug,
       volume = {935},
       number = {2},
          eid = {167},
        pages = {167},
          doi = {10.3847/1538-4357/ac7c74},
archivePrefix = {arXiv},
       eprint = {2206.14220},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2022ApJ...935..167A},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@ARTICLE{2019AJ....157...98G,
   author = {{Ginsburg}, A. and {Sip{\H o}cz}, B.~M. and {Brasseur}, C.~E. and
    {Cowperthwaite}, P.~S. and {Craig}, M.~W. and {Deil}, C. and
    {Guillochon}, J. and {Guzman}, G. and {Liedtke}, S. and {Lian Lim}, P. and
    {Lockhart}, K.~E. and {Mommert}, M. and {Morris}, B.~M. and
    {Norman}, H. and {Parikh}, M. and {Persson}, M.~V. and {Robitaille}, T.~P. and
    {Segovia}, J.-C. and {Singer}, L.~P. and {Tollerud}, E.~J. and
    {de Val-Borro}, M. and {Valtchanov}, I. and {Woillez}, J. and
    {The Astroquery collaboration} and {a subset of the astropy collaboration}
    },
    title = "{astroquery: An Astronomical Web-querying Package in Python}",
  journal = {\aj},
archivePrefix = "arXiv",
   eprint = {1901.04520},
 primaryClass = "astro-ph.IM",
 keywords = {astronomical databases: miscellaneous, virtual observatory tools},
     year = 2019,
    month = mar,
   volume = 157,
      eid = {98},
    pages = {98},
      doi = {10.3847/1538-3881/aafc33},
   adsurl = {http://adsabs.harvard.edu/abs/2019AJ....157...98G},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

When using Lightkurve, we kindly request that you cite the following packages:

lightkurve
astropy
astroquery — if you are using search_lightcurve() or search_targetpixelfile().
tesscut — if you are using search_tesscut().

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