Published in The Astrophysical Journal Supplement Series, the study examines how temperature fluctuations across a star's surface can affect observations of exoplanets. Using data from 20 Jupiter- and Neptune-sized planets, researchers discovered that for nearly half of these planets, changes in the host star's brightness significantly altered the observational data.
This phenomenon poses a risk of misinterpreting key planetary characteristics such as size, temperature, and atmospheric composition. The study's authors highlight that the distortions caused by stellar variability can be mitigated by examining a broad range of light wavelengths, particularly in the optical spectrum, where such contamination effects are most pronounced.
"These results were unexpected-we observed greater stellar contamination in our data than we had anticipated," said lead author Dr. Arianna Saba (UCL Physics and Astronomy), who conducted this research during her PhD at UCL. "This finding is crucial for refining our models and optimizing the wealth of data expected from upcoming missions like James Webb, Ariel, and Twinkle."
Co-author Alexandra Thompson, a PhD student at UCL focusing on exoplanet host stars, elaborated on the challenges posed by stellar activity. "Distinguishing between signals from the star and the planet is complex. Some stars have 'patchy' surfaces with regions of varying temperatures, leading to misleading planetary measurements."
Brighter regions on a star, known as faculae, can cause a planet transiting across them to appear larger than it actually is, as more light is blocked. Conversely, passing over cooler starspots can make a planet seem smaller. In some cases, a reduction in starlight from starspots might even mimic a planetary transit, leading to false detections.
"These stellar variations can also impact estimates of atmospheric components, such as water vapor, by either obscuring or mimicking their spectral signatures," Thompson added.
The research team analyzed two decades of data from the Hubble Space Telescope, incorporating observations from the Space Telescope Imaging Spectrograph (STIS) and the Wide Field Camera 3 (WFC3). To ensure consistency, all data were processed uniformly, reducing biases that can arise from differing analytical techniques.
Their approach involved comparing atmospheric models that accounted for stellar variability against simpler models that did not. They found that for six of the 20 exoplanets studied, models incorporating stellar variability provided a better fit to the data, while another six planets showed minor stellar contamination effects.
By analyzing light at visible, near-infrared, and near-ultraviolet wavelengths, researchers identified stellar contamination effects most prominently in the near-UV and optical regions, rather than in the infrared spectrum.
Dr. Saba described two key methods to assess whether stellar variability is influencing planetary observations: "One is to examine the overall spectrum shape to determine whether it aligns with the planet alone or requires stellar activity adjustments. The other involves comparing multiple optical observations of the same planet taken at different times. Significant differences likely indicate stellar activity variations."
Thompson emphasized that proper wavelength coverage is essential to managing these distortions. "Shorter-wavelength optical observations, like those used in this study, are particularly valuable in detecting stellar contamination," she said.
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