Calibration of Differential Light Curves for Physical Analysis of Starspots

Basri, Gibor

doi:10.3847/1538-4357/aade45

Cited by 27 publications

(33 citation statements)

References 44 publications

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“…Namekata et al (2019) selected only favorable spots separated from other spots in longitude, but still have the following problems: (1) There would be large uncertainties due to several causes: stellar inclination, the extent of polar spotting, the extent of contamination from other spots at different positions, and the number of spots that local minima have (see, Basri 2018;Basri, & Nguyen 2018;Namekata et al 2019). Also, the unspotted stellar brightness level is unknown in the Kepler light curves (e.g., Basri 2018). To evaluate those effects, the development of and comparison with light curve modeling method are necessary, but even these suffer from severe degeneracies that make it unlikely to discover the true spot distribution only from a light curve.…”

Section: Introductionmentioning

confidence: 99%

Temporal Evolution of Spatially Resolved Individual Star Spots on a Planet-hosting Solar-type Star: Kepler-17

Namekata

Davenport

Morris

et al. 2020

ApJ

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Star spot evolution is visible evidence of the emergence/decay of the magnetic field on stellar surface, and it is therefore important for the understanding of the underlying stellar dynamo and consequential stellar flares. In this paper, we report the temporal evolution of individual star spot area on the hot-Jupiter-hosting active solar-type star Kepler 17 whose transits occur every 1.5 days. The spot longitude and area evolution are estimated (1) from the stellar rotational modulations of Kepler data and (2) from the brightness enhancements during the exoplanet transits caused by existence of large star spots. As a result of the comparison, number of spots, spot locations, and the temporal evolution derived from the rotational modulations is largely different from those of in-transit spots. We confirm that although only two light curve minima appear per rotation, there are clearly many spots present on the star. We find that the observed differential intensity changes are sometimes consistent with the spot pattern detected by transits, but they sometimes do not match with each other. Although the temporal evolution derived from the rotational modulation differs from those of in-transit spots to a certain degree, the emergence/decay rates of in-transit spots are within an order of magnitude of those derived for sunspots as well as our previous research based only on rotational modulations. This supports a hypothesis that the emergence/decay of sunspots and extremely-large star spots on solar-type stars occur through the same underlying processes.

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Section: Introductionmentioning

confidence: 99%

Temporal Evolution of Spatially Resolved Individual Star Spots on a Planet-hosting Solar-type Star: Kepler-17

Namekata

Davenport

Morris

et al. 2020

ApJ

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“…More spots are observationally indicated to exist than seen in the light curve (Morris et al 2017;Namekata et al 2020), whereas the light curve produced with many spots is similar to that with two spots or one spot (Eker 1994;Basri 2018). Then, we determine the number of spots based on model selection in the Bayesian framework (Kass & Raftery 1995).…”

Section: Model Selection: How Many Spots Exist?mentioning

confidence: 93%

“…In particular, Kepler data include solar-type stars on which superflares are reported (Notsu et al 2019;Okamoto et al 2020). We note that Kepler data include a long-term trend and instrumental noise, and their unspotted level is unknown (e.g., Basri 2018). It is also necessary to determine the inclination angle precisely by another method, such as spectroscopic observation, when conducting starspot modeling.…”

Section: Conclusion and Future Prospectsmentioning

confidence: 99%

“…Furthermore, the number of spots on the stellar surface can play an important role in measuring the emergence and decay rates. Several studies have investigated how the number of spots is related to light curves (e.g., Eker 1994;Notsu et al 2013b;Morris et al 2017;Basri & Nguyen 2018;Basri 2018;Namekata et al 2020). We determine the number of spots based on model selection, computing the value of each model evidence by the importance sampling algorithm (e.g., Kass & Raftery 1995;Díaz et al 2014).…”

Section: Introductionmentioning

confidence: 99%

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Starspot Mapping with Adaptive Parallel Tempering. I. Implementation of Computational Code

Ikuta

Maehara

Notsu

et al. 2020

ApJ

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Starspots are thought to be regions of locally strong magnetic fields, similar to sunspots, and they can generate photometric brightness modulations. To deduce stellar and spot properties, such as spot emergence and decay rates, we implement a computational code for starspot modeling. It is implemented with an adaptive parallel tempering algorithm and an importance sampling algorithm for parameter estimation and model selection in the Bayesian framework. For evaluating the performance of the code, we apply it to synthetic light curves produced with three spots. The light curves are specified in the spot parameters, such as the radii, intensities, latitudes, longitudes, and emergence/decay durations. The spots are circular with specified radii and intensities relative to the photosphere, and the stellar differential rotation coefficient is also included in the light curves. As a result, stellar and spot parameters are uniquely deduced, and the number of spots is correctly determined: the three-spot model is preferable because the model evidence is much greater than that of the two-spot model by orders of magnitude and more than that of the four-spot model by a more modest factor, whereas the light curves are produced to have two or one local minimum during one equatorial rotation period by adjusting the values of longitude. The spot emergence and decay rates can be estimated with error less than an order of magnitude, considering the difference of the number of spots.

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“…As Kepler was only able to point to the Cygnus field for 4 years, studies of rotation of Sun-like stars experienced more progress than studies of stellar cycles of Sunlike stars. From early on in the mission, surface rotation was identified in a large number of, mainly active, stars (McQuillan et al 2013;Nielsen et al 2013;McQuillan et al 2014;García et al 2014;Balona & Abedigamba 2016;Ceillier et al 2017) and there were even indications of differential rotation (Reinhold et al 2013;Bonanno et al 2014;Reinhold & Gizon 2015;Karoff et al 2018;Benomar et al 2018;Bazot et al 2018), though the possibility to accurately extract differential rotation from photometry has been called into question (Aigrain et al 2015;Basri 2018). The main result of these measurements was that the observations agreed nicely with the theory, especially for the behaviour of differential rotation (Reinhold et al 2013).…”

Section: Introductionmentioning

confidence: 92%

Sounding stellar cycles with Kepler – III. Comparative analysis of chromospheric, photometric, and asteroseismic variability

Karoff

Metcalfe

Montet

et al. 2019

Monthly Notices of the Royal Astronomical Society

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By combining ground-based spectrographic observations of variability in the chromospheric emission from Sun-like stars with the variability seen in their eigenmode frequencies, it is possible to relate the changes observed at the surfaces of these stars to the changes taking place in the interior. By further comparing this variability to changes in the relative flux from the stars, one can obtain an expression for how these activity indicators relate to the energy output from the stars. Such studies become very pertinent when the variability can be related to stellar cycles as they can then be used to improve our understanding of the solar cycle and its effect on the energy output from the Sun.Here we present observations of chromospheric emission in 20 Sun-like stars obtained over the course of the nominal 4-year Kepler mission. Even though 4 years is too short to detect stellar equivalents of the 11-year solar cycle, observations from the Kepler mission can still be used to analyse the variability of the different activity indicators thereby obtaining information of the physical mechanism generating the variability. The analysis reveals no strong correlation between the different activity indicators, except in very few cases. We suggest that this is due to the sparse sampling of our ground-based observations on the one hand and that we are likely not tracing cyclic variability on the other hand. We also discuss how to improve the situation.

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Calibration of Differential Light Curves for Physical Analysis of Starspots

Cited by 27 publications

References 44 publications

Temporal Evolution of Spatially Resolved Individual Star Spots on a Planet-hosting Solar-type Star: Kepler-17

Temporal Evolution of Spatially Resolved Individual Star Spots on a Planet-hosting Solar-type Star: Kepler-17

Starspot Mapping with Adaptive Parallel Tempering. I. Implementation of Computational Code

Sounding stellar cycles with Kepler – III. Comparative analysis of chromospheric, photometric, and asteroseismic variability

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