Weighted Context-Free-Language Ordered Binary Decision Diagrams
Abstract: Over the years, many variants of Binary Decision Diagrams (BDDs) have been developed to address the deficiencies of vanilla BDDs. A recent innovation is the Context-Free-Language Ordered BDD (CFLOBDD), a hierarchically structured decision diagram, akin to BDDs enhanced with a procedure-call mechanism, which allows substructures to be shared in ways not possible with BDDs. For some functions, CFLOBDDs are exponentially more succinct than BDDs. Unfortunately, the multi-terminal extension of CFLOBDDs, like multi-terminal BDDs, cannot efficiently represent functions of type B^n -> D, when the function's range has many different values. This paper addresses this limitation through a new data structure called Weighted CFLOBDDs (WCFLOBDDs). WCFLOBDDs extend CFLOBDDs using insights from the design of Weighted BDDs (WBDDs) -- BDD-like structures with weights on edges. We show that WCFLOBDDs can be exponentially more succinct than both WBDDs and CFLOBDDs. We also evaluate WCFLOBDDs for quantum-circuit simulation, and find that they perform better than WBDDs and CFLOBDDs on most benchmarks. With a 15-minute timeout, the number of qubits that can be handled by WCFLOBDDs is 1,048,576 for GHZ (1x over CFLOBDDs, 256x over WBDDs); 262,144 for BV and DJ (2x over CFLOBDDs, 64x over WBDDs); and 2,048 for QFT (128x over CFLOBDDs, 2x over WBDDs).
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