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Title: Simulated execution of hybrid quantum computing systems

Abstract

We use modeling and simulation to study the behavior and performance of hybrid quantum computing systems. Our approach is based on a layered design with abstract machine models, which identify the key components and interfaces for quantum processing units, quantum programming models, and hybrid execution models. We use discrete-event simulating to track the dynamical state of hierarchical abstract machine models while executing test programs, and we collect statistics on time and energy consumption to forecast the resources required by quantum processors for future scientific computation.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1468202
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: Quantum Information Science, Sensing, and Computation X - Orlando, Florida, United States of America - 4/16/2018 4:00:00 AM-4/20/2018 4:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Humble, Travis S., Sadlier, Ronald J., and Britt, Keith A. Simulated execution of hybrid quantum computing systems. United States: N. p., 2018. Web. doi:10.1117/12.2303824.
Humble, Travis S., Sadlier, Ronald J., & Britt, Keith A. Simulated execution of hybrid quantum computing systems. United States. doi:10.1117/12.2303824.
Humble, Travis S., Sadlier, Ronald J., and Britt, Keith A. Tue . "Simulated execution of hybrid quantum computing systems". United States. doi:10.1117/12.2303824. https://www.osti.gov/servlets/purl/1468202.
@article{osti_1468202,
title = {Simulated execution of hybrid quantum computing systems},
author = {Humble, Travis S. and Sadlier, Ronald J. and Britt, Keith A.},
abstractNote = {We use modeling and simulation to study the behavior and performance of hybrid quantum computing systems. Our approach is based on a layered design with abstract machine models, which identify the key components and interfaces for quantum processing units, quantum programming models, and hybrid execution models. We use discrete-event simulating to track the dynamical state of hierarchical abstract machine models while executing test programs, and we collect statistics on time and energy consumption to forecast the resources required by quantum processors for future scientific computation.},
doi = {10.1117/12.2303824},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {5}
}

Conference:
Other availability
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