C
Cecilia Aragon
Researcher at University of Washington
Publications - 193
Citations - 8725
Cecilia Aragon is an academic researcher from University of Washington. The author has contributed to research in topics: Supernova & Light curve. The author has an hindex of 41, co-authored 183 publications receiving 7868 citations. Previous affiliations of Cecilia Aragon include Lawrence Berkeley National Laboratory & University of California, Berkeley.
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Journal ArticleDOI
Optimization by simulated annealing: an experimental evaluation. Part I, graph partitioning
TL;DR: This paper discusses annealing and its parameterized generic implementation, describes how this generic algorithm was adapted to the graph partitioning problem, and reports how well it compared to standard algorithms like the Kernighan-Lin algorithm.
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Optimization by Simulated Annealing: An Experimental Evaluation; Part II, Graph Coloring and Number Partitioning
TL;DR: This is the second in a series of three papers that empirically examine the competitiveness of simulated annealing in certain well-studied domains of combinatorial optimization.
Journal ArticleDOI
NEARBY SUPERNOVA FACTORY OBSERVATIONS OF SN 2007if: FIRST TOTAL MASS MEASUREMENT OF A SUPER-CHANDRASEKHAR-MASS PROGENITOR
Richard Scalzo,Greg Aldering,P. Antilogus,Cecilia Aragon,S. Bailey,C. Baltay,S. Bongard,C. Buton,C. Buton,M. J. Childress,N. Chotard,N. Chotard,Y. Copin,Y. Copin,H. K. Fakhouri,Avishay Gal-Yam,E. Gangler,E. Gangler,Sergio Hoyer,Sergio Hoyer,Mansi M. Kasliwal,S. C. Loken,Peter Nugent,Reynald Pain,E. Pecontal,R. Pereira,R. Pereira,Saul Perlmutter,David Rabinowitz,A. Rau,G. Rigaudier,K. Runge,G. Smadja,Charling Tao,R. C. Thomas,Benjamin A. Weaver,C. Wu +36 more
TL;DR: In this paper, photometric and spectroscopic observations of SN 2007if, an overluminous (M_V = −20.4), red (B-V = 0.16 at B-band maximum), slow-rising (t_(rise) = 24 days) type Ia supernova (SN Ia) in a very faint (m_g = −14.10) host galaxy.
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Randomized Search Trees
TL;DR: A randomized strategy for maintaining balance in dynamically changing search trees that has optimalexpected behavior, and generalizes naturally to weighted trees, where the expected time bounds for accesses and updates again match the worst-case time bounds of the best deterministic methods.
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How people use thermostats in homes: A review
TL;DR: A review of the current state of thermostats, evaluating their effectiveness in providing thermal comfort and energy savings, and identifying areas for further improvement or research is provided in this paper, where the authors suggest research needed to design and especially test with users, that can provide more comfortable and economical indoor environments.