Search Results for author: Ruth Angus

Found 4 papers, 4 papers with code

Data-driven derivation of stellar properties from photometric time series data using convolutional neural networks

1 code implementation19 May 2020 Kirsten Blancato, Melissa Ness, Daniel Huber, Yuxi Lu, Ruth Angus

Stellar variability is driven by a multitude of internal physical processes that depend on fundamental stellar properties.

Solar and Stellar Astrophysics

Inference of stellar parameters from brightness variations

1 code implementation11 May 2018 Melissa K. Ness, Victor Silva Aguirre, Mikkel N. Lund, Matteo Cantiello, Daniel Foreman-Mackey, David W. Hogg, Ruth Angus

We find that this model, trained using 1000 stars, can be used to recover the temperature $T_{\rm eff}$ to $<$100 K, the surface gravity to $<$ 0. 1 dex, and the asteroseismic power-spectrum parameters $\rm \nu_{max}$ and $\rm \Delta{\nu}$ to $<11$ $\mu$Hz and $<0. 9$ $\mu$Hz ($\lesssim$ 15\%).

Solar and Stellar Astrophysics

Science-Driven Optimization of the LSST Observing Strategy

1 code implementation14 Aug 2017 LSST Science Collaboration, Phil Marshall, Timo Anguita, Federica B. Bianco, Eric C. Bellm, Niel Brandt, Will Clarkson, Andy Connolly, Eric Gawiser, Zeljko Ivezic, Lynne Jones, Michelle Lochner, Michael B. Lund, Ashish Mahabal, David Nidever, Knut Olsen, Stephen Ridgway, Jason Rhodes, Ohad Shemmer, David Trilling, Kathy Vivas, Lucianne Walkowicz, Beth Willman, Peter Yoachim, Scott Anderson, Pierre Antilogus, Ruth Angus, Iair Arcavi, Humna Awan, Rahul Biswas, Keaton J. Bell, David Bennett, Chris Britt, Derek Buzasi, Dana I. Casetti-Dinescu, Laura Chomiuk, Chuck Claver, Kem Cook, James Davenport, Victor Debattista, Seth Digel, Zoheyr Doctor, R. E. Firth, Ryan Foley, Wen-fai Fong, Lluis Galbany, Mark Giampapa, John E. Gizis, Melissa L. Graham, Carl Grillmair, Phillipe Gris, Zoltan Haiman, Patrick Hartigan, Suzanne Hawley, Renee Hlozek, Saurabh W. Jha, C. Johns-Krull, Shashi Kanbur, Vassiliki Kalogera, Vinay Kashyap, Vishal Kasliwal, Richard Kessler, Alex Kim, Peter Kurczynski, Ofer Lahav, Michael C. Liu, Alex Malz, Raffaella Margutti, Tom Matheson, Jason D. McEwen, Peregrine McGehee, Soren Meibom, Josh Meyers, Dave Monet, Eric Neilsen, Jeffrey Newman, Matt O'Dowd, Hiranya V. Peiris, Matthew T. Penny, Christina Peters, Radoslaw Poleski, Kara Ponder, Gordon Richards, Jeonghee Rho, David Rubin, Samuel Schmidt, Robert L. Schuhmann, Avi Shporer, Colin Slater, Nathan Smith, Marcelles Soares-Santos, Keivan Stassun, Jay Strader, Michael Strauss, Rachel Street, Christopher Stubbs, Mark Sullivan, Paula Szkody, Virginia Trimble, Tony Tyson, Miguel de Val-Borro, Stefano Valenti, Robert Wagoner, W. Michael Wood-Vasey, Bevin Ashley Zauderer

The Large Synoptic Survey Telescope is designed to provide an unprecedented optical imaging dataset that will support investigations of our Solar System, Galaxy and Universe, across half the sky and over ten years of repeated observation.

Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics Earth and Planetary Astrophysics Astrophysics of Galaxies Solar and Stellar Astrophysics

Fast and scalable Gaussian process modeling with applications to astronomical time series

3 code implementations28 Mar 2017 Daniel Foreman-Mackey, Eric Agol, Sivaram Ambikasaran, Ruth Angus

We present a mathematical description of the method and compare it to existing scalable Gaussian Process methods.

Instrumentation and Methods for Astrophysics Earth and Planetary Astrophysics Solar and Stellar Astrophysics Data Analysis, Statistics and Probability Applications

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