Related papers: Event Discovery in Time Series
We analyze three years (1998-2000) of OGLE observations of microlensing events to place limits on the abundance of planets with a planet-to-star mass ratio $q=10^{-3}$ at distances $\sim 1-4$AU from their host stars, i.e. `cool Jupiters'.…
Time-series classification is an important problem for the data mining community due to the wide range of application domains involving time-series data. A recent paradigm, called shapelets, represents patterns that are highly predictive…
An automated, rapid classification of transient events detected in the modern synoptic sky surveys is essential for their scientific utility and effective follow-up using scarce resources. This presents some unusual challenges: the data are…
We explore the usefulness of future gravitational microlensing surveys in the study of binary properties such as the binary fraction and the distributions of binary separation and mass ratio by using the binary sample detectable through a…
We report the detection of 45 candidate microlensing events in fields toward the Galactic bulge. These come from the analysis of 24 fields containing 12.6 million stars observed for 190 days in 1993. Many of these events are of extremely…
Due to the rapid growth of social media platforms, these tools have become essential for monitoring information during ongoing disaster events. However, extracting valuable insights requires real-time processing of vast amounts of data. A…
The Vera C. Rubin Legacy Survey of Space and Time will discover thousands of microlensing events across the Milky Way Galaxy, allowing for the study of populations of exoplanets, stars, and compact objects. We evaluate numerous survey…
We summarize the status of a computer simulator for microlens planet surveys. The simulator generates synthetic light curves of microlensing events observed with specified networks of telescopes over specified periods of time. Particular…
Continuous-time event sequences, i.e., sequences consisting of continuous time stamps and associated event types ("marks"), are an important type of sequential data with many applications, e.g., in clinical medicine or user behavior…
Microlensing searches aim to detect compact halo dark matter via its gravitational lensing effect on stars within the Large Magellanic Cloud. The most recent results have led to the claim that roughly one fifth of the galactic halo dark…
Automated event detection has emerged as one of the fundamental practices to monitor the behavior of technical systems by means of sensor data. In the automotive industry, these methods are in high demand for tracing events in time series…
Microlensing light curves are now being monitored with the precision required to detect small perturbations due to planetary companions of the primary lens. Microlensing is complementary to other planetary search techniques in its potential…
Microlensing surveys, which have discovered about a dozen extrasolar planets to date, have focused on the small minority of high-magnification lensing events, which have a high sensitivity to planet detection. In contrast, second-generation…
The MACHO project is searching for dark matter in the form of massive compact halo objects (Machos), by monitoring the brightness of millions of stars in the Magellanic Clouds to search for gravitational microlensing events. Analysis of our…
Indexing of static and dynamic sets is fundamental to a large set of applications such as information retrieval and caching. Denoting the characteristic vector of the set by B, we consider the problem of encoding sets and multisets to…
We show that the statistical error, $\sigma_{\tau}$, in estimating the optical depth, $\tau$, due to microlensing is substantially higher than the naive Poisson estimate: $\sigma_{\tau} = \sqrt{\eta / N} \tau$, where $N$ is the number of…
We analyze the data of the gravitational microlensing survey carried out by by the MOA group during 2000 towards the Galactic Bulge (GB). Our observations are designed to detect efficiently high magnification events with faint source stars…
We investigate hide-and-seek games on complex networks using a random walk framework. Specifically, we investigate the efficiency of various degree-biased random walk search strategies to locate items that are randomly hidden on a subset of…
Change point detection in time series aims to identify moments when the probability distribution of time series changes. It is widely applied in many areas, such as human activity sensing and medical science. In the context of multivariate…
Sliding window approaches have been widely used for object recognition tasks in recent years. They guarantee an investigation of the entire input image for the object to be detected and allow a localization of that object. Despite the…