Daniel O'Malley
Los Alamos National Laboratory
95 Papers
341 Citations
Daniel O'Malley is an academic researcher from Los Alamos National Laboratory. The author has contributed to research in topics: Computer science & Quantum annealing. The author has an hindex of 20, co-authored 92 publications. Previous affiliations of Daniel O'Malley include University of Maryland, Baltimore County & Purdue University.
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Papers
•Posted Content
Quantum Algorithm Implementations for Beginners
Patrick J. Coles,Stephan Eidenbenz,Scott Pakin,Adetokunbo Adedoyin,John Ambrosiano,Petr M. Anisimov,William Casper,Gopinath Chennupati,Carleton Coffrin,Hristo N. Djidjev,David Gunter,Satish Karra,Nathan Lemons,Shi-Zeng Lin,Andrey Y. Lokhov,Alexander Malyzhenkov,David Dennis Lee Mascarenas,Susan M. Mniszewski,Balu Nadiga,Daniel O'Malley,Diane Oyen,Lakshman Prasad,Randy Roberts,Philip Romero,Nandakishore Santhi,Nikolai A. Sinitsyn,Pieter J. Swart,Marc Vuffray,James Wendelberger,Boram Yoon,Richard J. Zamora,Wei Zhu +31 more
TL;DR: This review aims to explain the principles of quantum programming, which are quite different from classical programming, with straightforward algebra that makes understanding of the underlying fascinating quantum mechanical principles optional.
244
Nonnegative/Binary matrix factorization with a D-Wave quantum annealer
TL;DR: It is shown that the D-Wave 2X can be effectively used as part of an unsupervised machine learning method that is able to learn facial features and accurately reproduce the set of facial images.
Understanding hydraulic fracturing: a multi-scale problem.
Jeffrey D. Hyman,Joaquin Jimenez-Martinez,Hari S. Viswanathan,James William Carey,Mark L. Porter,Esteban Rougier,Satish Karra,Qinjun Kang,Luke P. Frash,Li Chen,Zhou Lei,Daniel O'Malley,Nataliia Makedonska +12 more
TL;DR: The potential of CO2 as an alternative working fluid, both in fracturing and re-stimulating activities, beyond its environmental advantages is discussed, as part of the themed issue ‘Energy and the subsurface’.
149
Active layer hydrology in an arctic tundra ecosystem: quantifying water sources and cycling using water stable isotopes
H. Throckmorton,Brent D. Newman,Jeffrey M. Heikoop,G. Perkins,Xiahong Feng,David E. Graham,Daniel O'Malley,Velimir V. Vesselinov,Jessica M. Young,Stan D. Wullschleger,Cathy J. Wilson +10 more
TL;DR: The authors applied water stable isotope techniques (δ2H and δ18O) to infer sources and mixing of active layer waters in a polygonal tundra landscape in Barrow, Alaska, in August and September of 2012.
101
Predictive modeling of dynamic fracture growth in brittle materials with machine learning
Bryan A. Moore,Esteban Rougier,Daniel O'Malley,Gowri Srinivasan,Abigail Hunter,Hari S. Viswanathan +5 more
TL;DR: Simulation data from a high fidelity Finite-Discrete Element Model is used to build an efficient Machine Learning (ML) approach to predict fracture growth and coalescence and achieves a reduction in computational cost by multiple orders of magnitude.
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