Discovery and Atmospheric Characterization of Giant Planet Kepler-12b: An Inflated Radius Outlier

We report the discovery of planet Kepler-12b (KOI-20), which at 1.695 ± 0.030 R_J is among the handful of planets with super-inflated radii above 1.65 R_J. Orbiting its slightly evolved G0 host with a 4.438 day period, this 0.431 ± 0.041 M_J planet is the least irradiated within this largest-planet-radius group, which has important implications for planetary physics. The planet's inflated radius and low mass lead to a very low density of 0.111 ± 0.010 g cm^(–3). We detect the occultation of the planet at a significance of 3.7σ in the Kepler bandpass. This yields a geometric albedo of 0.14 ± 0.04; the planetary flux is due to a combination of scattered light and emitted thermal flux. We use multiple observations with Warm Spitzer to detect the occultation at 7σ and 4σ in the 3.6 and 4.5 μm bandpasses, respectively. The occultation photometry timing is consistent with a circular orbit at e < 0.01 (1σ) and e < 0.09 (3σ). The occultation detections across the three bands favor an atmospheric model with no dayside temperature inversion. The Kepler occultation detection provides significant leverage, but conclusions regarding temperature structure are preliminary, given our ignorance of opacity sources at optical wavelengths in hot Jupiter atmospheres. If Kepler-12b and HD 209458b, which intercept similar incident stellar fluxes, have the same heavy-element masses, the interior energy source needed to explain the large radius of Kepler-12b is three times larger than that of HD 209458b. This may suggest that more than one radius-inflation mechanism is at work for Kepler-12b or that it is less heavy-element rich than other transiting planets

Outliagnostics: Visualizing Temporal Discrepancy in Outlying Signatures of Data Entries

This paper presents an approach to analyzing two-dimensional temporal datasets focusing on identifying observations that are significant in calculating the outliers of a scatterplot. We also propose a prototype, called Outliagnostics, to guide users when interactively exploring abnormalities in large time series. Instead of focusing on detecting outliers at each time point, we monitor and display the discrepant temporal signatures of each data entry concerning the overall distributions. Our prototype is designed to handle these tasks in parallel to improve performance. To highlight the benefits and performance of our approach, we illustrate and validate the use of Outliagnostics on real-world datasets of various sizes in different parallelism configurations. This work also discusses how to extend these ideas to handle time series with a higher number of dimensions and provides a prototype for this type of datasets.Comment: in IEEE Visualization in Data Science (IEEE VDS) (2019

Data Stream Clustering: A Review

Number of connected devices is steadily increasing and these devices continuously generate data streams. Real-time processing of data streams is arousing interest despite many challenges. Clustering is one of the most suitable methods for real-time data stream processing, because it can be applied with less prior information about the data and it does not need labeled instances. However, data stream clustering differs from traditional clustering in many aspects and it has several challenging issues. Here, we provide information regarding the concepts and common characteristics of data streams, such as concept drift, data structures for data streams, time window models and outlier detection. We comprehensively review recent data stream clustering algorithms and analyze them in terms of the base clustering technique, computational complexity and clustering accuracy. A comparison of these algorithms is given along with still open problems. We indicate popular data stream repositories and datasets, stream processing tools and platforms. Open problems about data stream clustering are also discussed.Comment: Has been accepted for publication in Artificial Intelligence Revie

Swift and Suzaku Observations of the X-Ray Afterglow from the GRB 060105

Results are presented of early X-ray afterglow observations of GRB 060105 by Swift and Suzaku. The bright, long gamma-ray burst GRB 060105 triggered the Swift Burst Alert Telescope (BAT) at 06:49:28 on 5 January 2006. The Suzaku team commenced a pre-planned target of opportunity observation at 19 ks (5.3 hr) after the Swift trigger. Following the prompt emission and successive very steep decay, a shallow decay was observed from T_0+187 s to T_0+1287 s. After an observation gap during T_0 +(1.5-3) ks, an extremely early steep decay was observed in T_0+(4-30) ks. The lightcurve flattened again at T_0+30 ks, and another steep decay followed from T_0+50 ks to the end of observations. Both steep decays exhibited decay indices of 2.3 - 2.4. This very early break, if it is a jet break, is the earliest case among X-ray afterglow observations, suggesting a very narrow jet whose opening angle is well below 1 degree. The unique Suzaku/XIS data allow us to set very tight upper limits on line emission or absorption in this GRB. For the reported pseudo-redshift of z=4.0+/-1.3 the upper limit on the iron line equivalent width is 50 eV.Comment: 8 pages, 5 figures, Accepted for publication in PASJ Suzaku Special Issue (vol. 58