IN11D:
Quantum Annealing for Earth and Space Science Applications Posters

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Session ID#: 12542

Session Description:
Quantum computing is viewed as a promising future alternative as we approach the end of Moore’s law, particularly for solving problems of exponential complexity. Access to early-stage quantum annealing computers has become more readily available to researchers at several government laboratories and university sites through proposal requests for time similar to the NSF procedures for high performance computing. Quantum annealing systems offer unique capabilities for solving hard problems requiring discrete optimization. A variety of Earth and space science problems are dependent on optimal implementations for variational analysis, neural nets, Kalman filtering, Bayesian inferences, image recognition, and satellite applications of inverse problems. Other quantum annealing applications have been applied to search and sort problems, image analysis, scheduling, wavelets, regression analysis, classification, and topic modeling. This session solicits breakthrough examples in any of the above areas as well as related tools or developments to speedup pre- and post-processing of quantum annealing algorithms.
Primary Convener:  Milton Halem, University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States
Conveners:  Tsengdar J Lee, NASA Headquarters, Washington, United States, Rupak Biswas, NASA Ames Research Center, Moffett Field, CA, United States and Alejandro Ortiz, University of California Santa Cruz, Santa Cruz, CA, United States
Chairs:  Milton Halem, University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States and Tsengdar J Lee, NASA Headquarters, Washington, United States
OSPA Liaison:  Tsengdar J Lee, NASA Headquarters, Washington, United States
Index Terms:

1908 Cyberinfrastructure [INFORMATICS]
1920 Emerging informatics technologies [INFORMATICS]
1932 High-performance computing [INFORMATICS]
1942 Machine learning [INFORMATICS]

Abstracts Submitted to this Session:

The Fair in Unfair Quantum Ground-state Sampling (122225)
Itay Hen, University of Southern California, Information Sciences Institute, Los Angeles, CA, United States, Victor Martin-Mayor, Complutense University of Madrid, Madrid, Spain and Brian Zhang, Stanford University, Stanford, CA, United States
Image Registration and Data Assimilation as a QUBO on the D-Wave Quantum Annealer (135623)
Craig Pelissier, Science Systems and Applications, Inc., Lanham, United States, Jacqueline LeMoigne, NASA, Earth Science Technology Office, Greenbelt, MD, United States, Milton Halem, University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States, David G Simpson, NASA Goddard Space Flight Ctr, Greenbelt, MD, United States and Thomas Clune, NASA Goddard Space Flight Center, Greenbelt, MD, United States
Comparison of a Classical and Quantum Based Restricted Boltzmann Machine (RBM) for Application to Non-linear Multivariate Regression. (149966)
John Edward Dorband, Neha Tilak and Asen Radov, University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States
Quantum Annealing Architectures and Restricted Boltzmann Machines (179272)
Omar Shehab, University of Maryland Baltimore County, Computer Science & Electrical Engineering, Baltimore, MD, United States

See more of: Earth and Space Science Informatics