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arXiv:2504.02632

A Scalable Synthesis Algorithm for Reversible Functions

Moein Sarvaghad-Moghaddam, Morteza Saheb Zamani, Mehdi Sedighi

Published Apr 3, 2025• 0 citations
arXivHTMLPDF

Abstract

Reversible computation is an emerging technology that has gained significant attention due to its critical role in quantum circuit synthesis and low-power design. This paper introduces a transformation-based method for exact synthesis of reversible circuits. The proposed approach utilizes a novel adaptation of the Quine-McCluskey algorithm to eliminate input-output discrepancies in the truth table, transforming the permutation matrix into an identity matrix. Furthermore, a novel search space reduction technique is presented which, combined with the primary method, enables the synthesis algorithm to handle high-input reversible functions. This approach combines the influence of multiple control qubits on a target qubit, evaluating their collective impact. This aggregation can decrease the control qubit count within quantum gates. Consequently, it proves beneficial for applications like surface code error correction architectures as well as current Noisy Intermediate-Scale Quantum (NISQ) hardwares. Experimental results demonstrate significant improvements over the state-of-the-art exact synthesis methods, achieving up to 99% improvements in terms of the number of levels of T-gates.

DOI
10.48550/arxiv.2504.02632

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Reversible computation is an emerging technology that has gained significant attention due to its critical role in quantum circuit synthesis and low-power design. This paper introduces a transformation-based method for exact synthesis of reversible circuits. The proposed approach utilizes a novel adaptation of the Quine-McCluskey algorithm to eliminate input-output discrepancies in the truth table, transforming the permutation matrix into an identity matrix. Furthermore, a novel search space reduction technique is presented which, combined with the primary method, enables the synthesis algorithm to handle high-input reversible functions. This approach combines the influence of multiple control qubits on a target qubit, evaluating their collective impact. This aggregation can decrease the control qubit count within quantum gates. Consequently, it proves beneficial for applications like surface code error correction architectures as well as current Noisy Intermediate-Scale Quantum (NISQ) hardwares. Experimental results demonstrate significant improvements over the state-of-the-art exact synthesis methods, achieving up to 99% improvements in terms of the number of levels of T-gates.
Reversible circuits are an emerging technology where all computations are performed in an invertible manner. Motivated by their promising applications, e.g. in the domain of quantum computation or in the low-power design, the synthesis of such circuits has been intensely studied. However, how to automatically realize reversible circuits with the minimal number of lines for large functions is an open research problem. In this paper, we propose a new synthesis approach which relies on concepts that are complementary to existing ones. While “conventional” function representations have been applied for synthesis so far (such as truth tables, ESOPs, BDDs), we exploit Quantum Multiple-valued Decision Diagrams (QMDDs) for this purpose. An algorithm is presented that performs transformations on this data-structure eventually leading to the desired circuit. Experimental results show the novelty of the proposed approach through enabling automatic synthesis of large reversible functions with the minimal number of circuit lines. Furthermore, the quantum cost of the resulting circuits is reduced by 50% on average compared to an existing state-of-the-art synthesis method.
Algorithms specifically designed for quantum computers have been developed. In quantum circuits, the Feynman, Toffoli, and Fredkin gates are employed instead of traditional inputs such as AND, OR, NAND, NOR, XOR, and XNOR in combinational logic gates. The ability to convert quantum circuits into combinational logic circuits, or vice versa, is of utmost importance. This essay study (or paper) aims to demonstrates the process of deriving combinational logic circuits from reversible quantum circuits. To achieve this, the Quine-McCluskey technique was utilized along with state tables generated from the quantum circuits to obtain an optimal logic expression that serves as the basis for constructing the combinational logic circuit. The resultant obtained combinational logic circuit was implemented within the MATLAB Simulink environment, and state tables were obtained. A comparison was made between the state tables derived from the quantum circuit and the combinational circuit, yielding successful results.
Reversible hardware finds application in emerging areas such as low power circuit design, quantum computing, optical computing, and DNA computing. Intensive research has recently focused on the synthesis of reversible architectures. Most of these approaches derive efficient or even optimal circuits having as major drawback the scalability: they can only handle small circuits (up to a few hundred inputs for the most promising ones). In this paper, we propose a graph-based hierarchical synthesis method for large reversible and quantum architectures which can be combined with any of the existing synthesis methods to deliver unlimited scalability for arbitrary large and/or irregular architectures. The specification of any complex function is provided in the form of a sequential algorithm consisting of primitive pre-synthesized operations available in a library. The components of the library may have been designed by ad-hoc methods or synthesized by the known methods in the literature or even by the proposed synthesis procedure. The synthesized architecture is represented as a dependence graph whose nodes correspond to the available components of the library and their respective inverses so as to reset possible intermediate ancillae bits used during the synthesis procedure back to their initial state. The method can be recursively applied at multiple levels to build any complex reversible or quantum architecture.
We present a synthesis framework to map logic networks into quantum circuits for quantum computing. The synthesis framework is based on lookup-table (LUT) networks, which play a key role in conventional logic synthesis. Establishing a connection between LUTs in an LUT network and reversible single-target gates in a reversible network allows us to bridge conventional logic synthesis with logic synthesis for quantum computing, despite several fundamental differences. We call our synthesis framework LUT-based hierarchical reversible logic synthesis (LHRS). Input to LHRS is a classical logic network representing an arbitrary Boolean combinational operation; output is a quantum network (realized in terms of Clifford+T gates). The framework allows one to account for qubit count requirements imposed by the overlying quantum algorithm or target quantum computing hardware. In a fast first step, an initial network is derived that only consists of single-target gates and already completely determines the number of qubits in the final quantum network. Different methods are then used to map each single-target gate into Clifford+T gates, while aiming at optimally using available resources. We demonstrate the versatility of our method by conducting a design space exploration using different parameters on a set of large combinational benchmarks. On the same benchmarks, we show that our approach can advance over the state-of-the-art hierarchical reversible logic synthesis algorithms.
Improving circuit realization of known quantum algorithms by CAD techniques has benefits for quantum experimentalists. In this paper, we address the problem of synthesizing a given k-input, m-output lookup table (LUT) by a reversible circuit. This problem has interesting applications in the famous Shor's number-factoring algorithm and in quantum walk on sparse graphs. For LUT synthesis, our approach targets the number of control lines in multiple-control Toffoli gates to reduce synthesis cost. To achieve this, we propose a multi-level optimization technique for reversible circuits to benefit from shared cofactors. To reuse output qubits and/or zero-initialized ancillae, we un-compute intermediate cofactors. Our experiments reveal that the proposed LUT synthesis has a significant impact on reducing the size of modular exponentiation circuits for Shor's quantum factoring algorithm, oracle circuits in quantum walk on sparse graphs, and the well-known MCNC benchmarks.
In order to efficiently automatically construct quantum reversible logic circuits with low cost,a novel method for quantum circuit's synthesis is proposed.Through the line topology transformation and truth table permutation,it converts an n-qubit circuit synthesis problem into single quantum circuit synthesis using traditional recursive thought.Then directly generate relevant circuit.After optimization,the quantum reversible logic circuit is synthesized finally.All 3-qubit reversible logic circuits have been synthesized by this method.The average number of EGT gates is only 6.41,and the number is down to 5.22 after optimization.Experimental results show that the number of gates to construct reversible logic circuits is less than other methods.For any n-qubit binary logic function,the number of EGT gates is less than n2n-1.Meanwhile,it voids the exponential nature of the memory or run-time complexity,and is very simple to implement in classical computer.