Paper detail

Modelling systematics of ground-based transit photometry I. Implications on transit timing variations

The transit timing variation technique (TTV) has been widely used to detect and characterize multiple planetary systems. Due to the observational biases imposed mainly by the photometric conditions and instrumentation and the high signal-to-noise required to produce primary transit observations, ground-based data acquired using small telescopes limit the technique to the follow-up of hot Jupiters. However, space-based missions such as Kepler and CoRoT have already revealed that hot Jupiters are mainly found in single systems. Thus, it is natural to question ourselves if we are properly using the observing time at hand carrying out such follow-ups, or if the use of medium-to-low quality transit light curves, combined with current standard techniques of data analysis, could be playing a main role against exoplanetary search via TTVs. The purpose of this work is to investigate to what extent ground-based observations treated with current modelling techniques are reliable to detect and characterize additional planets in already known planetary systems. To meet this goal, we simulated typical primary transit observations of a hot Jupiter mimicing an existing system, Qatar-1. To resemble ground-based observations we attempt to reproduce, by means of physically and empirically motivated relationships, the effects caused by the Earth's atmosphere and the instrumental setup on the synthetic light curves. Therefore, the synthetic data present different photometric quality and transit coverage. In addition, we introduced a perturbation in the mid-transit times of the hot Jupiter, caused by an Earth-sized planet in a 3:2 mean motion resonance. Analyzing the synthetic light curves produced after certain epochs, we attempt to recover the synthetically added TTV signal by means of usual primary transit fitting techniques, and show how these can recover (or not) the TTV signal.

preprint2016arXivOpen access

Signal facts

What is known right now

Open access5 authors1 topic

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.