Affiliation:
1. The University of Texas at Austin, Austin, USA
2. University of Wisconsin-Madison, Madison, USA
Abstract
This article presents a new compressed representation of Boolean functions, called
CFLOBDDs
(for Context-Free-Language Ordered Binary Decision Diagrams). They are essentially a plug-compatible alternative to BDDs (Binary Decision Diagrams), and hence are useful for representing certain classes of functions, matrices, graphs, relations, and so forth in a highly compressed fashion. CFLOBDDs share many of the good properties of BDDs, but—in the best case—the CFLOBDD for a Boolean function can be
exponentially smaller than any BDD for that function
. Compared with the size of the decision tree for a function, a CFLOBDD—again, in the best case—can give a
double-exponential reduction in size
. They have the potential to permit applications to (i) execute much faster and (ii) handle much larger problem instances than has been possible heretofore.
We applied CFLOBDDs in quantum-circuit simulation and found that for several standard problems, the improvement in scalability, compared to BDDs, is quite dramatic. With a 15-minute timeout, the number of qubits that CFLOBDDs can handle are 65,536 for Greenberger-Horne-Zellinger, 524,288 for Bernstein-Vazirani, 4,194,304 for Deutsch-Jozsa, and 4,096 for Grover’s algorithm, besting BDDs by factors of 128×, 1,024×, 8,192×, and 128×, respectively.
Funder
Office of Naval Research
National Science Foundation
Missile Defense Agency
Facebook
Publisher
Association for Computing Machinery (ACM)
Cited by
5 articles.
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