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Register a new userPlanets and Stellar Activity: Hide and Seek in the CoRoT-7 system
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Added by
Raphaelle D Haywood
Publication date
2014
fields
Physics
and research's language is
English
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Since the discovery of the transiting super-Earth CoRoT-7b, several investigations have yielded different results for the number and masses of planets present in the system, mainly owing to the stars high level of activity. We re-observed CoRoT-7 in January 2012 with both HARPS and CoRoT, so that we now have the benefit of simultaneous radial-velocity and photometric data. This allows us to use the off-transit variations in the stars light curve to estimate the radial-velocity variations induced by the suppression of convective blueshift and the flux blocked by starspots. To account for activity-related effects in the radial-velocities which do not have a photometric signature, we also include an additional activity term in the radial-velocity model, which we treat as a Gaussian process with the same covariance properties (and hence the same frequency structure) as the light curve. Our model was incorporated into a Monte Carlo Markov Chain in order to make a precise determination of the orbits of CoRoT-7b and CoRoT-7c. We measure the masses of planets b and c to be 4.73 +/- 0.95 Mearth and 13.56 +/- 1.08 Mearth, respectively. The density of CoRoT-7b is (6.61 +/- 1.72)(Rp/1.58 Rearth)^(-3) g.cm^(-3), which is compatible with a rocky composition. We search for evidence of an additional planet d, identified by previous authors with a period close to 9 days. We are not able to confirm the existence of a planet with this orbital period, which is close to the second harmonic of the stellar rotation at around 7.9 days. Using Bayesian model selection we find that a model with two planets plus activity-induced variations is most favoured.
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Stellar activity can induce signals in the radial velocities of stars, complicating the detection of orbiting low-mass planets. We present a method to determine the number of planetary signals present in radial-velocity datasets of active stars, using only radial-velocity observations. Instead of considering separate fits with different number of planets, we use a birth-death Markov chain Monte Carlo algorithm to infer the posterior distribution for the number of planets in a single run. In a natural way, the marginal distributions for the orbital parameters of all planets are also inferred. This method is applied to HARPS data of CoRoT-7. We confidently recover both CoRoT-7b and CoRoT-7c although the data show evidence for additional signals.
We train embodied agents to play Visual Hide and Seek where a prey must navigate in a simulated environment in order to avoid capture from a predator. We place a variety of obstacles in the environment for the prey to hide behind, and we only give the agents partial observations of their environment using an egocentric perspective. Although we train the model to play this game from scratch, experiments and visualizations suggest that the agent learns to predict its own visibility in the environment. Furthermore, we quantitatively analyze how agent weaknesses, such as slower speed, effect the learned policy. Our results suggest that, although agent weaknesses make the learning problem more challenging, they also cause more useful features to be learned. Our project website is available at: http://www.cs.columbia.edu/ ~bchen/visualhideseek/.
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