Structured decomposition for reversible Boolean functions
Jiaqing Jiang, Xiaoming Sun, Yuan Sun, Kewen Wu, Zhiyu Xia

TL;DR
This paper introduces a structured decomposition method for even reversible Boolean functions, reducing block depth and increasing flexibility in block positioning, which advances previous work in reversible logic synthesis.
Contribution
It presents a new decomposition approach for even reversible Boolean functions with reduced block depth and more flexible block positioning, improving upon Selinger's previous results.
Findings
Decomposition of even n-bit RBFs into 7 blocks for n≥6.
Decomposition of n-bit RBFs into 10 even (n-1)-bit RBFs for n≥10.
Improved block depth constants from previous work, offering more flexible block arrangements.
Abstract
Reversible Boolean function is a one-to-one function which maps -bit input to -bit output. Reversible logic synthesis has been widely studied due to its relationship with low-energy computation as well as quantum computation. In this work, we give a structured decomposition for even reversible Boolean functions (RBF). Specifically, for , any even -bit RBF can be decomposed to blocks of -bit RBF, where is a constant independent of ; and the positions of those blocks have large degree of freedom. Moreover, if the -bit RBFs are required to be even as well, we show for , -bit RBF can be decomposed to even -bit RBFs. For simplicity, we say our decomposition has block depth and even block depth . Our result improves Selinger's work in block depth model, by reducing the constant from to ; and from to …
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum-Dot Cellular Automata · Low-power high-performance VLSI design
