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Lecture notes in networks and systems

Quantum-Inspired Evolutionary Auto-synthesis of Reversible Circuits with Adaptive Rotation

Siyasha Singh

Published Aug 14, 2026• 0 citations
Publisher
DOI
10.1007/978-3-032-34772-5_11

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Reversible logic plays an important role in quantum computation, which is a promising research field. The reversible logic synthesis problem focuses on generating a reversible circuit automatically and finding the lowest cost when an output function is given. The synthesis of reversible logic circuits can be formulated as a combinatorial optimization problem. This paper proposes a new evolutionary algorithm for synthesizing reversible circuits based on Quantum-Inspired Tabu Search Algorithm (QTS). The proposed algorithm uses the QTS-based approach to find fewer gates and reduce the cost of reversible circuits. This method is simpler, has better performance in computational cost, and reduce the gate counts of reversible circuits. This paper also compares experimental results with other heuristic and evolutionary algorithms. The final outcome shows that the QTS-based approach performs much better than other algorithms.
In the recent years reversible logic circuits have gained a remarkable interest in the light of advancements made in quantum computation. The promise of theoretically zero power consumption is a major driving force for researchers to develop circuits using this logic. Synthesis of reversible logic and generating reversible logic circuit automatically with lower cost always has been a challenging task as reducing the search space is one of the major issues in the synthesis process using permutation. In this work, we proposed an Adaptive Genetic Algorithm (AGA) for synthesizing reversible logic circuits. NCT (NOT, CNOT, Toffoli) gate based library has been considered for synthesis of reversible logic circuits (RLC). The proposed algorithm produces a cascade of Toffoli gates for a given reversible specification of a circuit. Comparison of experimental results for several benchmark circuits shows that proposed evolutionary algorithm enables optimal or near-optimal solutions with lesser Gate Counts.
The quantum circuit is the prime factor to realize quantum computation. This paper proposes a novel quantum-inspired evolutionary computation method to synthesize quantum circuits effectively and efficiently. Recently, the Clifford+T gate library has become popular, as the T gate has a better fault-tolerant and error correction efficacy, which is essential to near-term quantum computation. The proposed quantum-inspired evolutionary computation is more flexible in constructing diverse solutions than the classical synthesis method. The entangled local search mechanism further enhances the ability to discover the optimal solutions on an efficient frontier. The encoding can be slightly changed to achieve various gate libraries circuit synthesis in the quantum or reversible Boolean circuits. The experiments demonstrate that our proposed method can be more effective in composing a compact quantum circuit than the state-of-the-art method. Meanwhile, the T-depth can attain an optimal value without ancilla bits. Furthermore, we provide an illustration to construct the function equivalent quantum circuit with the NOT, CNOT, Controlled-Square-Root-of-NOT quantum gate library (NCV). We also conduct exhaustion to prove that our synthesized circuit is an optimal solution, requiring far fewer resources in time and evaluation than exhaustion.