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Full-Text Articles in Physical Sciences and Mathematics
Mapping The Gravitational-Wave Sky With Lisa: A Bayesian Spherical Harmonic Approach, Sharan Banagiri, Alexander Criswell, Tommy Kuan, Vuk Mandic, Joseph D. Romano, Stephen R. Taylor
Mapping The Gravitational-Wave Sky With Lisa: A Bayesian Spherical Harmonic Approach, Sharan Banagiri, Alexander Criswell, Tommy Kuan, Vuk Mandic, Joseph D. Romano, Stephen R. Taylor
Physics and Astronomy Faculty Publications and Presentations
The millihertz gravitational-wave frequency band is expected to contain a rich symphony of signals with sources ranging from Galactic white dwarf binaries to extreme mass ratio inspirals. Many of these gravitational-wave signals will not be individually resolvable. Instead, they will incoherently add to produce stochastic gravitational-wave confusion noise whose frequency content will be governed by the dynamics of the sources. The angular structure of the power of the confusion noise will be modulated by the distribution of the sources across the sky. Measurement of this structure can yield important information about the distribution of sources on Galactic and extragalactic scales, …
Detecting Optical Transients Using Artificial Neural Networks And Reference Images From Different Surveys, Katarzyna Wardęga, Adam Zadrozny, Martin Beroiz, Richard S. Camuccio, Mario C. Diaz
Detecting Optical Transients Using Artificial Neural Networks And Reference Images From Different Surveys, Katarzyna Wardęga, Adam Zadrozny, Martin Beroiz, Richard S. Camuccio, Mario C. Diaz
Physics and Astronomy Faculty Publications and Presentations
We present a technique to detect optical transients based on an artificial neural networks method. We describe the architecture of two networks capable of comparing images of the same part of the sky taken by different telescopes. One image corresponds to the epoch in which a potential transient could exist; the other is a reference image of an earlier epoch. We use data obtained by the Dr. Cristina V. Torres Memorial Astronomical Observatory and archival reference images from the Sloan Digital Sky Survey. We trained a convolutional neural network and a dense layer network on simulated source samples and then …