We present a new lower bound on the number of gates in reversible logic circuits that represent a given reversible logic function, in which the circuits are assumed to consist of general Toffoli gates and have no redundant input/output lines. We make a theoretical comparison of lower bounds, and prove that the proposed bound is better than the previous one. Moreover, experimental results for lower bounds on randomly-generated reversible logic functions and reversible benchmarks are given. The results also demonstrate that the proposed lower bound is better than the former one.
We present a new lower bound on the number of gates in reversible logic circuits that represent a given reversible logic function, in which the circuits are assumed to consist of general Toffoli gates and have no redundant input/output lines. We make a theoretical comparison of lower bounds, and prove that the proposed bound is better than the previous one. Moreover, experimental results for lower bounds on randomly-generated reversible logic functions and reversible benchmarks are given. The results also demonstrate that the proposed lower bound is better than the former one.
This paper presents an improved lower bound, denoted asv, on the number of gates in Toffoli-based reversible circuits that realize a given reversible logic function. The previous lower boundσ−lbused the characteristic vectors of reversible functions to formulate the theory of lower bounds. We carefully investigate cofactors of reversible functions to refine the characteristic vectors, and obtain a new theoretical basis for improving lower bounds. We show that the proposed lower boundvis better than the previous lower boundσ−lbby making both mathematical and experimental comparisons. Although the gain of refinement is not so significant in the experiments, an improvement of lower bounds is valuable as a theoretical achievement.
We present a time-efficient lower bound $\tilde \sigma $ on the number of gates in Toffoli-based reversible circuits that represent a given reversible logic function. For the characteristic vector s of a reversible logic function, the value of σ~(s) is almost the same as σ-lb (s), which is known as a relatively-efficient lower bound in terms of the evaluation time and the tightness. By slightly sacrificing the tightness of the lower bound, $\tilde \sigma $ achieves fast computation. We prove that $\tilde \sigma $ is a lower bound on σ-lb. Next, we show $\tilde \sigma $ can be calculated faster than σ-lb. The time complexity of σ~(s) is О(n2), where n is the dimension of s. Experimental results to compare $\tilde \sigma $ and σ-lb are also given. The results demonstrate that the values of σ~(s) are equal to those of σ-lb (s) for most reversible functions and that the computation time of σ~(s) is much shorter than that of σ-lb(s).
We present a time-efficient lower bound κ on the number of gates in Toffoli-based reversible circuits that represent a given reversible logic function. For the characteristic vector s of a reversible logic function, κ(s) closely approximates σ-lb(s), which is known as a relatively efficient lower bound in respect of evaluation time and tightness. The primary contribution of this paper is that κ enables fast computation while maintaining a tightness of the lower bound, approximately equal to σ-lb. We prove that the discrepancy between κ(s) and σ-lb(s) is at most one only, by providing upper and lower bounds on σ-lb in terms of κ. Subsequently, we show that κ can be calculated more efficiently than σ-lb. An algorithm for κ(s) with a complexity of O(n) is presented, where n is the dimension of s. Experimental results comparing κ and σ-lb are also given. The results demonstrate that the two lower bounds are equal for most reversible functions, and that the calculation of κ is significantly faster than σ-lb by several orders of magnitude.
Reversible logic finds many applications, especially in the area of quantum computing. A completely specified n-input, n-output Boolean function is called reversible if it maps each input assignment to a unique output assignment and vice versa. Logic synthesis for reversible functions differs substantially from traditional logic synthesis and is currently an active area of research. The authors present an algorithm and tool for the synthesis of reversible functions. The algorithm uses the positive-polarity Reed-Muller expansion of a reversible function to synthesize the function as a network of Toffoli gates. At each stage, candidate factors, which represent subexpressions common between the Reed-Muller expansions of multiple outputs, are explored in the order of their attractiveness. The algorithm utilizes a priority-based search tree, and heuristics are used to rapidly prune the search space. The synthesis algorithm currently targets the generalized n-bit Toffoli gate library. However, other algorithms exist that can convert an n-bit Toffoli gate into a cascade of smaller Toffoli gates. Experimental results indicate that the authors' algorithm quickly synthesizes circuits when tested on the set of all reversible functions of three variables. Furthermore, it is able to quickly synthesize all four-variable and most five-variable reversible functions that were in the test suite. The authors also present results for some benchmark functions widely discussed in literature and some new benchmarks that the authors have developed. The algorithm is shown to synthesize many, but not all, randomly generated reversible functions of as many as 16 variables with a maximum gate count of 25
Reversible logic studies have promising potential on energy lossless circuit design, quantum computation, nanotechnology, etc. Reversible logic features a one-to-one input output correspondence which makes the logic synthesis for reversible functions differs greatly from traditional Boolean functions. Exact synthesis methods can provide optimal solutions in terms of the total number of reversible gates in the synthesis results. Unfortunately, they may suffer from long computation time, due to the fact that the search space is likely to grow exponentially as the circuit size increases. Therefore, in this paper, we propose an efficient synthesis heuristic which provides high quality synthesis results of Toffoli network in more reasonable computation time. We use a weighted, directed graph for reversible function representation and complexity measurement. The proposed algorithm maximally decreases function complexity during synthesis steps. It has the ability to climb out of local minimums and guarantees algorithm convergence. The experimental results show that our algorithm can achieve optimal or very close to optimal solutions with computation time several orders of magnitude less than the exact methods. Compared with other heuristics, our method demonstrates superior performance in terms of reversible gate count as well as computation time.
Reversible logic studies have promising potential on energy lossless circuit design, quantum computation, nanotechnology, etc. Reversible logic features a one-to-one input output correspondence which makes the logic synthesis for reversible functions differs greatly from traditional Boolean functions. Exact synthesis methods can provide optimal solutions in terms of the total number of reversible gates in the synthesis results. Unfortunately, they may suffer from long computation time, due to the fact that the search space is likely to grow exponentially as the circuit size increases. Therefore, in this paper, we propose an efficient synthesis heuristic which provides high quality synthesis results of Toffoli network in more reasonable computation time. We use a weighted, directed graph for reversible function representation and complexity measurement. The proposed algorithm maximally decreases function complexity during synthesis steps. It has the ability to climb out of local minimums and guarantees algorithm convergence. The experimental results show that our algorithm can achieve optimal or very close to optimal solutions with computation time several orders of magnitude less than the exact methods. Compared with other heuristics, our method demonstrates superior performance in terms of reversible gate count as well as computation time.