The Clifford+T quantum gate library has attracted much interest in the design of quantum circuits, particularly since the contained operations can be implemented in a fault-tolerant manner. Since fault tolerant implementations of the T gate have very high latency, synthesis and optimization are aiming at minimizing the number of T stages, referred to as the T-depth. In this paper, we present an approach to map mixed polarity multiple controlled Toffoli gates into Clifford+T quantum circuits. Our approach is based on the multiple control Toffoli mapping algorithms proposed by Barenco et al., which are given T-depth optimized Clifford+T translations. Experiments show that our approach leads to a significant T-depth reduction of 54% on average.
The Clifford+T quantum gate library has attracted much interest in the design of quantum circuits, particularly since the contained operations can be implemented in a fault-tolerant manner. Since fault tolerant implementations of the T gate have very high latency, synthesis and optimization are aiming at minimizing the number of T stages, referred to as the T-depth. In this paper, we present an approach to map mixed polarity multiple controlled Toffoli gates into Clifford+T quantum circuits. Our approach is based on the multiple control Toffoli mapping algorithms proposed by Barenco et al., which are given T-depth optimized Clifford+T translations. Experiments show that our approach leads to a significant T-depth reduction of 54% on average.
The Clifford+T gate library consisting of Hadamard, T, and CNOT gates has attracted much interest in quantum circuit synthesis, particularly due to its applicability to fault tolerant realizations. Since fault tolerant implementations of the T gate have very high latency, recent work in this area is aiming at minimizing the number of T stages, referred to as the T-depth. In this paper, we present an approach to exploit additional ancilla qubits in the mapping of reversible circuits consistina of multiple controlled Toffoli gates (MCT gates) into califford+T quantum circuits, with the primary optimization objective to minimize the T-depth. Our proposed approach takes advantage of and generalizes earlier work on corresponding mapping algorithms. An experimental evaluation shows that our approach leads to a significant T-depth reduction compared to earlier approaches.
Optimal synthesis of reversible circuits is a very hard task. In 2010, a method and a tool of practical usage for finding optimal circuits built from multi-control Toffoli gates for any 4-bit reversible specification were finally developed. In 2011 we published an extension to the algorithm, which allows to reduce the quantum cost of the resulting circuits. In this paper we present another extension to this approach. Namely, we have extended the reversible gate library to mixed-polarity multi-control Toffoli gates (i.e. with both positive and negative controls). Our experimental results for the known reversible benchmarks show that using mixed-polarity Toffoli gates gives significant savings in gate count. The paper presents standard computational experiments for circuit synthesis. These results have implications in testing synthesis algorithms for reversible mixed-polarity circuits and quantum circuits.
Optimal synthesis of reversible circuits is a very hard task. In 2010, a method and a tool of practical usage for finding optimal circuits built from multi-control Toffoli gates for any 4-bit reversible specification were finally developed. In 2011 we published an extension to the algorithm, which allows to reduce the quantum cost of the resulting circuits. In this paper we present another extension to this approach. Namely, we have extended the reversible gate library to mixed-polarity multi-control Toffoli gates (Le. with both positive and negative controls). Our experimental results for the known reversible benchmarks show that using mixed-polarity Toffoli gates gives significant savings in gate count. The paper presents standard computational experiments for circuit synthesis. These results have implications in testing synthesis algorithms for reversible mixed-polarity circuits and quantum circuits.
The well-known 3-bit Hermitian gate (a Toffoli gate) has been implemented using Clifford + T circuits. Compared with the Peres gate, its implementation circuit requires more controlled-NOT (CNOT) gates. However, the Peres gate is not Hermitian. This paper reports four 3-bit Hermitian gates named LI gates. Whose realized circuits have the same T-count, T-depth, and CNOT-count as the Peres gate. Furthermore, two decomposition methods of a multiple control Toffoli (MCT) gate are proposed for different primary optimization goals. Then, we design the equality, less-than, and full comparators with the minimum circuit width using proposed Hermitian gates and optimized MCT gates. A fault-tolerant circuit is required for robust quantum computing. Clifford+T circuits are accepted solutions for fault-tolerant implementation. Considering T-count, T-depth, CNOT-count, and circuit width as the primary optimization goals, we design the optimized Clifford + T circuits of three comparators using LI gates and optimized MCT gates. Comparison and analysis show that the proposed comparators have better overall performances for T-count, T-depth, CNOT-count, and circuit width than the best-known comparators without quantum measurements.
Currently, the most used universal quantum gate set is the augmented Clifford+T set of gates. Most commonly, we use the cost reduction in terms of the T-depth or T-count to implement logic primitives such as the Toffoli gate. While a lot of research has been done in this area, the Clifford+T set of gates is difficult to use for the synthesis of larger multi-controlled NOT gates (CnNOT) or simply larger circuits. To address this issue, in this work, we examine the composition of the Toffoli gate in relation to the T-gates. We adopt an approach based on the logic formalization of the T-gate placement and deduce three main results. First, if the trailing phase is not a concern, we can efficiently reduce the number of T gates. The second result is that to construct CnNOT gates for n>2 the T gates require smaller angles of rotation (analogous to the original scaling problem in the Barenco et al. Toffoli implementation). Lastly, we demonstrate that it is feasible to substitute all T gates with RZrotations, ensuring the correct logic operation and a constant phase across all outputs.
The synthesis of efficient reversible logic circuits is critical for fault-tolerant quantum computing (FTQC). The primary motivation of this work is to overcome the inherent disadvantages of existing synthesis techniques: approximate heuristic methods often miss optimal solutions, while pure exact computational methods suffer from combinatorial explosion on deep circuits. While the strict NCT library (NOT, CNOT, Toffoli) is often preferred due to the high cost of distilling non-Clifford states required for arbitrary gates, standard physical implementations frequently utilize the broader NCV library (NOT, CNOT, V, V-dagger), requiring the decomposition of Toffoli gates into five elementary operations. To bridge this gap, this paper presents a unified, highly scalable methodology for the optimal design of reversible circuits across both libraries. First, a Mixed-Integer Non-Linear Programming (MINLP) formulation, linearized for the high-performance IBM ILOG CPLEX solver, is introduced to automate the exact generation of globally optimal strict NCT topologies. Second, a systematic four-phase optimization framework is proposed to reduce NCV costs. By replacing Toffoli gates with specific NCV decompositions, permuting control lines to match subsequent linear gates, and applying exact local searches via an extended MINLP solver on bounded sliding windows, significant gate cancellations are achieved. Applying this methodology to prominent primitives (MIG, SAYEM, URG, TSG, and MKG), we match global NCT optimality constraints and achieve highly optimized NCV Quantum Costs of 7, 14, and 12 for the MIG, TSG, and MKG gates, respectively, establishing best-known upper bounds that significantly outperform heuristic literature benchmarks.