On the Data Structure Metrics of Quantum Multiple-Valued Decision Diagrams

This paper describes new metrics for the data structure referred to as quantum multiple-valued decision diagrams (QMDD) which are used to represent the matrices describing reversible and quantum gates and circuits. These metrics provide information about QMDD that allows for improvement of minimization techniques. We explore metrics related to the frequency of edges with non-zero weight for the entire QMDD data structure and their histograms with respect to each variable. We observe some unique regularity particular to the methodology of the QMDD. We develop new heuristics for QMDD dynamic variable ordering (DVO) that are guided by the proposed metrics. Experimental results show the effectiveness of the proposed techniques.

• Type: Conference
• Year: 2008
• Where: ISMVL
• Authors: David Y. Feinstein, Mitchell A. Thornton, D. Michael Miller
• Keywords: Artificial Intelligence, Data Structure, ISMVL 2008, Metrics Provide Information, Quantum Multiple-valued Decision