A binary neural k-nearest neighbour technique

K-Nearest Neighbour (k-NN) is a widely used technique for classifying and clustering data. K-NN is effective but is often criticised for its polynomial run-time growth as k-NN calculates the distance to every other record in the data set for each record in turn. This paper evaluates a novel k-NN classifier with linear growth and faster run-time built from binary neural networks. The binary neural approach uses robust encoding to map standard ordinal, categorical and real-valued data sets onto a binary neural network. The binary neural network uses high speed pattern matching to recall the k-best matches. We compare various configurations of the binary approach to a conventional approach for memory overheads, training speed, retrieval speed and retrieval accuracy. We demonstrate the superior performance with respect to speed and memory requirements of the binary approach compared to the standard approach and we pinpoint the optimal configurations

The Exoplanet Population Observation Simulator. I - The Inner Edges of Planetary Systems

The Kepler survey provides a statistical census of planetary systems out to the habitable zone. Because most planets are non-transiting, orbital architectures are best estimated using simulated observations of ensemble populations. Here, we introduce EPOS, the Exoplanet Population Observation Simulator, to estimate the prevalence and orbital architectures of multi-planet systems based on the latest Kepler data release, DR25. We estimate that at least 42% of sun-like stars have nearly coplanar planetary systems with 7 or more exoplanets. The fraction of stars with at least one planet within 1 au could be as high as 100% depending on assumptions about the distribution of single transiting planets. We estimate an occurrence rate of planets in the habitable zone around sun-like stars of eta_earth=36+-14%. The innermost planets in multi-planet systems are clustered around an orbital period of 10 days (0.1 au), reminiscent of the protoplanetary disk inner edge or could be explained by a planet trap at that location. Only a small fraction of planetary systems have the innermost planet at long orbital periods, with fewer than ~8% and ~3% having no planet interior to the orbit of Mercury and Venus, respectively. These results reinforce the view that the solar system is not a typical planetary system, but an outlier among the distribution of known exoplanetary systems. We predict that at least half of the habitable zone exoplanets are accompanied by (non-transiting) planets at shorter orbital periods, hence knowledge of a close-in exoplanet could be used as a way to optimize the search for Earth-size planets in the Habitable Zone with future direct imaging missions.Comment: Accepted in AAS journals, code available on githu

The PHASES Differential Astrometry Data Archive. V. Candidate Substellar Companions to Binary Systems

The Palomar High-precision Astrometric Search for Exoplanet Systems monitored 51 subarcsecond binary systems to evaluate whether tertiary companions as small as Jovian planets orbited either the primary or secondary stars, perturbing their otherwise smooth Keplerian motions. Six binaries are presented that show evidence of substellar companions orbiting either the primary or secondary star. Of these six systems, the likelihoods of two of the detected perturbations to represent real objects are considered to be "high confidence", while the remaining four systems are less certain and will require continued observations for confirmation.Comment: 16 Pages, Accepted to A

The M33 Synoptic Stellar Survey. II. Mira Variables

We present the discovery of 1847 Mira candidates in the Local Group galaxy M33 using a novel semi-parametric periodogram technique coupled with a Random Forest classifier. The algorithms were applied to ~2.4x10^5 I-band light curves previously obtained by the M33 Synoptic Stellar Survey. We derive preliminary Period-Luminosity relations at optical, near- & mid-infrared wavelengths and compare them to the corresponding relations in the Large Magellanic Cloud.Comment: Includes small corrections to match the published versio