Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userPractical suggestions on detecting exomoons in exoplanet transit light curves
163
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
The number of known transiting exoplanets is rapidly increasing, which has recently inspired significant interest as to whether they can host a detectable moon. Although there has been no such example where the presence of a satellite was proven, several methods have already been investigated for such a detection in the future. All these methods utilize post-processing of the measured light curves, and the presence of the moon is decided by the distribution of a timing parameter. Here we propose a method for the detection of the moon directly in the raw transit light curves. When the moon is in transit, it puts its own fingerprint on the intensity variation. In realistic cases, this distortion is too little to be detected in the individual light curves, and must be amplified. Averaging the folded light curve of several transits helps decrease the scatter, but it is not the best approach because it also reduces the signal. The relative position of the moon varies from transit to transit, the moons wing will appear in different positions on different sides of the planets transit. Here we show that a careful analysis of the scatter curve of the folded light curves enhances the chance of detecting the exomoons directly.
rate research
Read More
We present photometry of six transits of the exoplanet XO-2b. By combining the light-curve analysis with theoretical isochrones to determine the stellar properties, we find the planetary radius to be 0.996 +0.031/-0.018 rjup and the planetary mass to be 0.565 +/- 0.054 mjup. These results are consistent with those reported previously, and are also consistent with theoretical models for gas giant planets. The mid-transit times are accurate to within 1 min and are consistent with a constant period. However, the period we derive differs by 2.5 sigma from the previously published period. More data are needed to tell whether the period is actually variable (as it would be in the presence of an additional body) or if the timing errors have been underestimated.
The increasing number of transiting exoplanets sparked a significant interest in discovering their moons. Most of the methods in the literature utilize timing analysis of the raw light curves. Here we propose a new approach for the direct detection of a moon in the transit light curves via the so called Scatter Peak. The essence of the method is the valuation of the local scatter in the folded light curves of many transits. We test the ability of this method with different simulations: Kepler short cadence, Kepler long cadence, ground-based millimagnitude photometry with 3-min cadence, and the expected data quality of the planned ESA mission of PLATO. The method requires ~100 transit observations, therefore applicable for moons of 10-20 day period planets, assuming 3-4-5 year long observing campaigns with space observatories. The success rate for finding a 1 R_Earth moon around a 1 R_Jupiter exoplanet turned out to be quite promising even for the simulated ground-based observations, while the detection limit of the expected PLATO data is around 0.4 R_Earth. We give practical suggestions for observations and data reduction to improve the chance of such a detection: (i) transit observations must include out-of-transit phases before and after a transit, spanning at least the same duration as the transit itself; (ii) any trend filtering must be done in such a way that the preceding and following out-of-transit phases remain unaffected.
Reliable estimations of ephemeris errors are fundamental for the follow-up of CoRoT candidates. An equation for the precision of minimum times, originally developed for eclipsing binaries, has been optimized for CoRoT photometry and been used to calculate such errors. It may indicate expected timing precisions for transit events from CoRoT, as well as from Kepler. Prediction errors for transit events may also be used to calculate probabilities about observing entire or partial transits in any given span of observational coverage, leading to an improved reliability in deductions made from follow-up observations.
Many moons have been detected around planets in our Solar System, but none has been detected unambiguously around any of the confirmed extrasolar planets. We test the feasibility of a supervised convolutional neural network to classify photometric transit light curves of planet-host stars and identify exomoon transits, while avoiding false positives caused by stellar variability or instrumental noise. Convolutional neural networks are known to have contributed to improving the accuracy of classification tasks. The network optimization is typically performed without studying the effect of noise on the training process. Here we design and optimize a 1D convolutional neural network to classify photometric transit light curves. We regularize the network by the total variation loss in order to remove unwanted variations in the data features. Using numerical experiments, we demonstrate the benefits of our network, which produces results comparable to or better than the standard network solutions. Most importantly, our network clearly outperforms a classical method used in exoplanet science to identify moon-like signals. Thus the proposed network is a promising approach for analyzing real transit light curves in the future.
We present nine newly observed transits of TrES-3, taken as part of a transit timing program using the RISE instrument on the Liverpool Telescope. A Markov-Chain Monte-Carlo analysis was used to determine the planet-star radius ratio and inclination of the system, which were found to be Rp/Rstar=0.1664^{+0.0011}_{-0.0018} and i = 81.73^{+0.13}_{-0.04} respectively, consistent with previous results. The central transit times and uncertainties were also calculated, using a residual-permutation algorithm as an independent check on the errors. A re-analysis of eight previously published TrES-3 light curves was conducted to determine the transit times and uncertainties using consistent techniques. Whilst the transit times were not found to be in agreement with a linear ephemeris, giving chi^2 = 35.07 for 15 degrees of freedom, we interpret this to be the result of systematics in the light curves rather than a real transit timing variation. This is because the light curves that show the largest deviation from a constant period either have relatively little out-of-transit coverage, or have clear systematics. A new ephemeris was calculated using the transit times, and was found to be T_c(0) = 2454632.62610 +- 0.00006 HJD and P = 1.3061864 +- 0.0000005 days. The transit times were then used to place upper mass limits as a function of the period ratio of a potential perturbing planet, showing that our data are sufficiently sensitive to have probed for sub-Earth mass planets in both interior and exterior 2:1 resonances, assuming the additional planet is in an initially circular orbit.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
