Lockheed Building 157 is one of the United States' largest experiments in contemporary daylig... more Lockheed Building 157 is one of the United States' largest experiments in contemporary daylighting. Built in 1983, the five story structure houses 3,000 employees and uses daylight for ambient illumination throughout its 56,000-m² office interior. A continuously dimmable fluorescent lighting system supplements interior daylight under the control of open-loop ceiling-mounted photosensors. In 1985 Lawrence Berkeley Laboratory (LBL) began a year-long
Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent o... more Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent of digital synoptic sky surveys. While panoramic surveys can detect variable or transient events, typically some follow-up observations are needed; for short-lived phenomena, a rapid response is essential. Ability to automatically classify and prioritize transient events for follow-up studies becomes critical as the data rates increase. We have been developing such methods using the data streams from the Palomar-Quest survey, the Catalina Sky Survey and others, using the VOEventNet framework. The goal is to automatically classify transient events, using the new measurements, combined with archival data (previous and multi-wavelength measurements), and contextual information (e.g., Galactic or ecliptic latitude, presence of a possible host galaxy nearby, etc.); and to iterate them dynamically as the follow-up data come in (e.g., light curves or colors). We have been investigating Bayesian methodologies for classification, as well as discriminated follow-up to optimize the use of available resources, including Naive Bayesian approach, and the non-parametric Gaussian process regression. We will also be deploying variants of the traditional machine learning techniques such as Neural Nets and Support Vector Machines on datasets of reliably classified transients as they build up.
Lockheed Building 157 is one of the United States' largest experiments in contemporary daylig... more Lockheed Building 157 is one of the United States' largest experiments in contemporary daylighting. Built in 1983, the five story structure houses 3,000 employees and uses daylight for ambient illumination throughout its 56,000-m² office interior. A continuously dimmable fluorescent lighting system supplements interior daylight under the control of open-loop ceiling-mounted photosensors. In 1985 Lawrence Berkeley Laboratory (LBL) began a year-long
Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent o... more Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent of digital synoptic sky surveys. While panoramic surveys can detect variable or transient events, typically some follow-up observations are needed; for short-lived phenomena, a rapid response is essential. Ability to automatically classify and prioritize transient events for follow-up studies becomes critical as the data rates increase. We have been developing such methods using the data streams from the Palomar-Quest survey, the Catalina Sky Survey and others, using the VOEventNet framework. The goal is to automatically classify transient events, using the new measurements, combined with archival data (previous and multi-wavelength measurements), and contextual information (e.g., Galactic or ecliptic latitude, presence of a possible host galaxy nearby, etc.); and to iterate them dynamically as the follow-up data come in (e.g., light curves or colors). We have been investigating Bayesian methodologies for classification, as well as discriminated follow-up to optimize the use of available resources, including Naive Bayesian approach, and the non-parametric Gaussian process regression. We will also be deploying variants of the traditional machine learning techniques such as Neural Nets and Support Vector Machines on datasets of reliably classified transients as they build up.
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