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Proceedings Paper

Quantum information theory for model abstraction techniques
Author(s): Marjorie V. Quant; Ryan Colburn
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Paper Abstract

The intent of this paper to bring forward and explore a possible use of the emerging field of quantum information sciences to the modeling and simulation community. It is desired that this research will open new pathways and partnerships where quantum information theory may be applied to modeling techniques. The issue for a mixed resolution model/simulation is how one may provide for the correct data exchange between the differing levels of detail that exist among individual models. The concept behind model abstraction is to extract the essence of a high-resolution model to a level proper for the simulation. There is always a challenge to find a balance between speed of the simulation (lower resolution in the models) and the required level of detail to extract the intended information from the simulation. While computing speed is a quantity, which may be measured somewhat easily, the fitness of the detail extracted from a model is often questionable and subjectively measured. This paper will discuss the use of quantum information theory as a means to quantify differing levels of detail in mixed resolution simulations. An overview of information theory is provided in section 2. This is followed by a brief look at methods used to determine the fidelity of information passed as an abstracted model.

Paper Details

Date Published: 19 September 2001
PDF: 10 pages
Proc. SPIE 4367, Enabling Technology for Simulation Science V, (19 September 2001); doi: 10.1117/12.440050
Show Author Affiliations
Marjorie V. Quant, Air Force Research Lab. (United States)
Ryan Colburn, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 4367:
Enabling Technology for Simulation Science V
Alex F. Sisti; Dawn A. Trevisani, Editor(s)

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