LOCKHEED MARTIN SITE UPDATE

Transcription

1 LOCKHEED MARTIN SITE UPDATE 25 SEPTEMBER 2018 Julia Kwok Software Engineer Quantum Applications

2 THE USC-LM QUANTUM COMPUTING CENTER Dr. Edward H. Ned Allen Chief Scientist and LM Senior Fellow Lockheed Martin Corporation Greg Tallant Program Manager and LM Fellow Lockheed Martin Aeronautics Skunk Works University of Southern California Information Sciences Institute Marina de Rey, California, USA

3 QUANTUM APPLICATIONS TEAM Kristen Pudenz, Ph.D. Quantum Applications Quantum Error Correction Steve Adachi, Ph.D. Quantum Machine Learning LM Fellow, Space Systems Julia Kwok, M.E.E. Quantum Graph Coloring Classical Optimization Chris Elliott, Ph.D. Quantum Enabled V&V 15+ Years of Flight Control Development Kevin Leyden, Ph.D. Quantum Circuit Fault Diagnosis Aerospace & Mechanical Engineering Peter Stanfill 30+ Years of Flight Control Development

4 CENTER HISTORY AND TIMELINE DW-1 Rainier Early LM identified quantum information science as a high potential technology to address critical needs Nov Purchased access time and support for DW-1 Rainier quantum annealer from D-Wave Systems DW-2 Vesuvius Mar Formed partnership with USC/ISI to host DW-1 and establish collaborative QC Center Jan USC-LM QC Center Operational Mar 2013 Completed upgrade to 512-qubit DW-2 Vesuvius processor Feb 2016 Completed upgrade to qubit DW-2X Washington processor Photo credit Fatemeh Kashfia

5 FOCUS APPLICATIONS AND AREAS Machine Learning Neural network structures Quantum annealing correction for supervised and unsupervised learning Graph Coloring Hybrid quantum-classical algorithm Data from D-Wave DW2X machine Circuit Fault Diagnosis Full adder based approach Architectures and error correction integration Multiple test vector approach

6 FOCUS APPLICATIONS AND AREAS Machine Learning Neural network structures Quantum annealing correction for supervised and unsupervised learning Graph Coloring Hybrid quantum-classical algorithm Data from D-Wave DW2X machine Circuit Fault Diagnosis Full adder based approach Architectures and error correction integration Multiple test vector approach

7 GRAPH COLORING

8 BACKGROUND We proposed to develop a hybrid quantum-classical algorithm for graph coloring by using formulations of the Maximum Independent Set (MIS) and/or Vertex Cover (VC) Global graph coloring approach requires n x k variables This approach colors by embedding an n variable problem The MIS and VC QUBO penalties can be applied iteratively Find an independent set Assign set to one color Remove set the graph, and repeat until all nodes are colored Classical computing closes the loop

9 BACKGROUND Test set is a parametrized set of Erdos-Renyi Random Graphs Intrinsically hard and have explainable reasons for their hardness Controllable by parameters that provide exponential increase in problem hardness with linear size increase Located at a best estimate of the phase transition threshold in the k-colorability Improvements to full graph coloring algorithm Tree structure for exploring solution paths Incorporation of timing structures to track runtime and time-to-solution

10 GRAPH COLORING RESULTS

11 ANNEAL TIME RESULTS

12 RUNTIME RESULTS

13 MOVING FORWARD Classical graph coloring heuristic algorithms applied to QUBO formulation Largest Degree Ordering (LDO) Saturated Degree Ordering (SDO) Comparison to classical graph coloring approximation Embedding the graph to be colored takes most of the classical compute time We are investigating methods of adjusting the first embedding to make a compact yet easy to compute embedding for subsequent subgraphs as independent sets are removed Spin reversal transformations for rigor

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