Skip to main content
×
×
Home

Reliable inference of light curve parameters in the presence of systematics

  • Neale P. Gibson (a1) (a2)
Abstract

Time-series photometry and spectroscopy of transiting exoplanets allow us to study their atmospheres. Unfortunately, the required precision to extract atmospheric information surpasses the design specifications of most general purpose instrumentation. This results in instrumental systematics in the light curves that are typically larger than the target precision. Systematics must therefore be modelled, leaving the inference of light-curve parameters conditioned on the subjective choice of systematics models and model-selection criteria. Here, I briefly review the use of systematics models commonly used for transmission and emission spectroscopy, including model selection, marginalisation over models, and stochastic processes. These form a hierarchy of models with increasing degree of objectivity. I argue that marginalisation over many systematics models is a minimal requirement for robust inference. Stochastic models provide even more flexibility and objectivity, and therefore produce the most reliable results. However, no systematics models are perfect, and the best strategy is to compare multiple methods and repeat observations where possible.

    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Reliable inference of light curve parameters in the presence of systematics
      Available formats
      ×
      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Reliable inference of light curve parameters in the presence of systematics
      Available formats
      ×
      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Reliable inference of light curve parameters in the presence of systematics
      Available formats
      ×
Copyright
References
Hide All
Brown, T. M. 2001, ApJ, 553, 1006
Charbonneau, D., Brown, T. M., Noyes, R. W., & Gilliland, R. L. 2002, ApJ, 568, 377
Gibson, N. P., Pont, F., & Aigrain, S. 2011, MNRAS, 411, 2199
Gibson, N. P., Aigrain, S., Roberts, S. et al. 2012, MNRAS, 419, 2683
Gibson, N. P. 2014, MNRAS, 445, 3401
Nikolov, N. et al. 2014, MNRAS, 437, 46
Seager, S. & Sasselov, D. D. 2000, ApJ, 537, 916
Sing, D. K. et al. 2011, MNRAS, 416, 1443
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Proceedings of the International Astronomical Union
  • ISSN: 1743-9213
  • EISSN: 1743-9221
  • URL: /core/journals/proceedings-of-the-international-astronomical-union
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords:

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 13 *
Loading metrics...

Abstract views

Total abstract views: 69 *
Loading metrics...

* Views captured on Cambridge Core between 27th October 2016 - 12th June 2018. This data will be updated every 24 hours.