Separating Gravitational Wave Signals from Instrument Artifacts

Central to the gravitational wave detection problem is the challenge of separating features in the data produced by astrophysical sources from features produced by the detector. Matched filtering provides an optimal solution for Gaussian noise, but in practice, transient noise excursions or ``glitches'' complicate the analysis. Detector diagnostics and coincidence tests can be used to veto many glitches which may otherwise be misinterpreted as gravitational wave signals. The glitches that remain can lead to long tails in the matched filter search statistics and drive up the detection threshold. Here we describe a Bayesian approach that incorporates a more realistic model for the instrument noise allowing for fluctuating noise levels that vary independently across frequency bands, and deterministic ``glitch fitting'' using wavelets as ``glitch templates'', the number of which is determined by a trans-dimensional Markov chain Monte Carlo algorithm. We demonstrate the method's effectiveness on simulated data containing low amplitude gravitational wave signals from inspiraling binary black hole systems, and simulated non-stationary and non-Gaussian noise comprised of a Gaussian component with the standard LIGO/Virgo spectrum, and injected glitches of various amplitude, prevalence, and variety. Glitch fitting allows us to detect significantly weaker signals than standard techniques.Comment: 21 pages, 18 figure

Enabling high confidence detections of gravitational-wave bursts

With the advanced LIGO and Virgo detectors taking observations the detection of gravitational waves is expected within the next few years. Extracting astrophysical information from gravitational wave detections is a well-posed problem and thoroughly studied when detailed models for the waveforms are available. However, one motivation for the field of gravitational wave astronomy is the potential for new discoveries. Recognizing and characterizing unanticipated signals requires data analysis techniques which do not depend on theoretical predictions for the gravitational waveform. Past searches for short-duration un-modeled gravitational wave signals have been hampered by transient noise artifacts, or "glitches," in the detectors. In some cases, even high signal-to-noise simulated astrophysical signals have proven difficult to distinguish from glitches, so that essentially any plausible signal could be detected with at most 2-3 $\sigma$ level confidence. We have put forth the BayesWave algorithm to differentiate between generic gravitational wave transients and glitches, and to provide robust waveform reconstruction and characterization of the astrophysical signals. Here we study BayesWave's capabilities for rejecting glitches while assigning high confidence to detection candidates through analytic approximations to the Bayesian evidence. Analytic results are tested with numerical experiments by adding simulated gravitational wave transient signals to LIGO data collected between 2009 and 2010 and found to be in good agreement.Comment: 15 pages, 6 figures, submitted to PR

Colaboratory: Design Collaboration for The Greater Good

Graphic design is a powerful tool, which has the power to shift perspective and create an impact. A recent shift in the design world has graphic designers using their skill sets to address complex social problems, to engage their audience in new ways that bring awareness to a social issue for the greater good of society. This thesis examines how graphic design collaboration ignites social change within a community and inspires transformation in human behavior. It explores how designing for the greater good impacts our society; and how these collaborative experiences improve the community and clients they serve. This thesis will also showcase how design can benefit the greater good through a multi-disciplinary design think-tank devoted to fostering experience by stimulating creativity through collaboration of students with actual clients

The Jungle Down the Street, the Town Across the Bridge, All is Very Well

The Jungle Down the Street, the Town Across the Bridge, All is Very Well is a series of short, nonfiction essays attempting to paint several portraits—regional, ecological, familial, and personal. Focused around the town of Apalachicola, Florida, it addresses themes of family, folklore, tragedy, and the “New Sublime,” or the feeling of wonder at the beauty that precedes an inevitable end. The piece attempts to blend multiple narrative and thematic arcs through the use of humor, anecdote, and historical research

Extreme distributions of ground winds /3 to 150 meters/ at Cape Kennedy, Florida

Statistical analysis of wind distribution probabilities at Cape Kenned