IN41B:
Advances in Quantum Computing for the Geophysical Sciences I eLightning


Submit an Abstract to this Session


Session ID#: 48910

Session Description:
Quantum computing is perhaps the most promising breakthrough to come along in computer technology as we approach the end of Moore’s Law. The advent of cloud-based, freely accessible, quantum computers has prompted a surge in research using this technology. Several architectural approaches are now available and others are evolving rapidly and offering simulators and maturing software stacks that simplify usage and execution of quantum algorithms. Can the application of any of these quantum approaches be expected to gain dominance over classical systems for relevant science algorithms? We invite abstracts employing any quantum computing approach that addresses Earth or space science disciplines including modeling, data assimilation, remote sensing, and image analysis that can be employed to solve geoscience problems with either current or future quantum architectures. We also solicit the presentation of related software tools and algorithms that could accelerate the utilization of quantum computing algorithms more broadly.
Primary Convener:  Milton Halem, University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States
Conveners:  Craig Pelissier, NASA Goddard Space Flight Center, Computational and Information Science & Technology Office, Greenbelt, MD, United States, Michael M Little, NASA Langley Research Center, Hampton, VA, United States and Tsengdar J Lee, NASA, Washington, United States
Primary Liaison:  Milton Halem, University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States
Chairs:  Milton Halem, University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States and Craig Pelissier, NASA Goddard Space Flight Center, Computational and Information Science & Technology Office, Greenbelt, MD, United States
OSPA Liaison:  Tsengdar J Lee, NASA, Washington, United States

Cross-Listed:
  • A - Atmospheric Sciences
  • EP - Earth and Planetary Surface Processes
  • GC - Global Environmental Change
  • NG - Nonlinear Geophysics
Index Terms:

0428 Carbon cycling [BIOGEOSCIENCES]
1920 Emerging informatics technologies [INFORMATICS]
1932 High-performance computing [INFORMATICS]
3315 Data assimilation [ATMOSPHERIC PROCESSES]

Abstracts Submitted to this Session:

Quantum Linear System Solvers on the IBMQ (378303)
Christopher Culver, George Washington University, Washington, DC, United States, Craig Pelissier, NASA Goddard Space Flight Center, Computational and Information Science & Technology Office, Greenbelt, MD, United States, Andrei Alexandru, George Washington University, Washington D.C., United States and Daniel Duffy, NASA Center for Climate Simulation, Greenbelt, United States
An approach to quantum-computational hydrologic inverse analysis (Invited) (380805)
Daniel O'Malley, Los Alamos National Laboratory, Computational Earth Sciences, Los Alamos, NM, United States
Learning Image Registration and Quantum Annealing Statistics (402353)
Craig Pelissier, Science Systems and Applications, Inc., Lanham, United States, Jacqueline Le Moigne, NASA Goddard Institute for Space Studies, Greenbelt, MD, United States, Milton Halem, University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States and Troy Ames, NASA Goddard Space Flight Center, Greenbelt, United States
Analyzing the Quantum Annealing Approach for Solving Linear Least Squares Problems (416598)
Ajinkya Borle, University of Maryland Baltimore County, Baltimore, MD, United States and Sam Lomonaco, University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States
Solving Hard SAT Instances with Adiabatic Quantum Computers (438647)
Ramin Ayanzadeh1, Milton Halem2 and Tim Finin1, (1)University of Maryland Baltimore County, Baltimore, MD, United States, (2)University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States
Towards Quantum PCA for Deep Feature Learning (455117)
David Chapman1, Milton Halem2 and John Edward Dorband2, (1)University of Maryland Baltimore County, Baltimore, MD, United States, (2)University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States
Variational Autoencoders using D-Wave Quantum Annealing (464627)
Jennifer A. Sleeman, University of Maryland Baltimore County, Baltimore, MD, United States

See more of: Earth and Space Science Informatics