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CALCOLO

Synthesis of reversible circuits with minimal costs

Guowu Yang, Xiaoyu Song B, William N. N. Hung, Marek A. Perkowski, Chang-Jun Seo

Published Sep 1, 2008• 16 citations
Publisher
DOI
10.1007/s10092-008-0150-7

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In this article, we propose a flexible and efficient reversible logic synthesizer. It exploits the complementary advantages of two methods: Reed-Muller Reversible Logic Synthesis (RMRLS) and Decision Diagram Synthesis (DDS), and is thus called Reed-Muller Decision Diagram Synthesis (RMDDS). RMRLS does not scale to a large number of qubits (i.e., quantum bits). DDS tools, even though efficient, add a large number of ancillary qubits and typically incur much higher quantum cost than necessary. RMDDS overcomes these obstacles. It is flexible in the sense that users can either optimize the number of qubits or the quantum cost in the circuit implementation. It is also efficient because the circuits can be synthesized within user-defined CPU times. This combination of flexibility and efficiency has been missing from synthesizers presented earlier. When used to synthesize reversible functions, RMDDS reduces the number of qubits by up to 79.2% (average of 54.6%) when the synthesis objective is to minimize the number of qubits and the quantum cost by up to 71.5% (average of 35.7%) when the synthesis objective is to minimize quantum cost, relative to DDS methods. For irreversible functions (which are automatically embedded in reversible functions), the corresponding best (average) reductions in the number of qubits is 42.1% (22.5%) when minimizing the number of qubits, and in quantum cost, it is 63.0% (25.9%) when minimizing quantum cost.

ACM Journal on Emerging Technologies in Computing Systems•Feb 1, 2014•24 citations
This paper presents a heuristic cost minimization approach to synthesizing linear reversible circuits. Two bidirectional linear reversible circuit synthesis methods are introduced, the Alternating Elimination with Cost Minimization method (AECM) and the Multiple CNOT Gate method (MCG). Algorithms, example syntheses, and extensions to these methods are presented. An MCG variant which incorporates line reordering is introduced. Tests comparing the new cost minimization methods with the best known method for large circuits are presented. Results show that of the three methods MCG had the lowest average CNOT gate counts for linear reversible circuits up to 24 lines, and that AECM had the lowest counts between 28 and 60 lines.
We present fast algorithms to synthesize exact minimal reversible circuits for various types of gates and costs. By reducing reversible logic synthesis problems to group theory problems, we use the powerful algebraic software GAP to solve such problems. Our algorithms are not only able to minimize for arbitrary cost functions of gates, but also orders of magnitude faster than the existing approaches to reversible logic synthesis. In addition, we show that the Peres gate is a better choice than the standard Toffoli gate in libraries of universal reversible gates.
In this article, we propose a flexible and efficient reversible logic synthesizer. It exploits the complementary advantages of two methods: Reed-Muller Reversible Logic Synthesis (RMRLS) and Decision Diagram Synthesis (DDS), and is thus called Reed-Muller Decision Diagram Synthesis (RMDDS). RMRLS does not scale to a large number of qubits (i.e., quantum bits). DDS tools, even though efficient, add a large number of ancillary qubits and typically incur much higher quantum cost than necessary. RMDDS overcomes these obstacles. It is flexible in the sense that users can either optimize the number of qubits or the quantum cost in the circuit implementation. It is also efficient because the circuits can be synthesized within user-defined CPU times. This combination of flexibility and efficiency has been missing from synthesizers presented earlier. When used to synthesize reversible functions, RMDDS reduces the number of qubits by up to 79.2% (average of 54.6%) when the synthesis objective is to minimize the number of qubits and the quantum cost by up to 71.5% (average of 35.7%) when the synthesis objective is to minimize quantum cost, relative to DDS methods. For irreversible functions (which are automatically embedded in reversible functions), the corresponding best (average) reductions in the number of qubits is 42.1% (22.5%) when minimizing the number of qubits, and in quantum cost, it is 63.0% (25.9%) when minimizing quantum cost.