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arXiv:2605.18159 · IEEE International Symposium on Design and Diagnostics of Electronic Circuits & Systems (DDECS)

Measurement-Driven Adaptive Low-Overhead Implementation of Multi-Controlled Toffoli Gates

Abhoy Kole, Till Schnittka, Rolf Drechsler

quant-phcs.ETSubmitted May 18, 2026• Announced May 19, 2026• 0 citations
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Abstract

The Toffoli gate is a fundamental building block for quantum arithmetic and reversible logic, yet its efficient realization remains a major challenge in both near-term and fault-tolerant quantum architectures. Recent advances in dynamic quantum circuit capabilities, including mid-circuit measurement and classical feedforward, provide new opportunities for reducing the resource overhead of non-Clifford operations. In this work, we propose a set of dynamic decomposition strategies for multi-controlled Toffoli gates that exploit adaptive circuit execution and ancilla-assisted constructions. Our methods systematically reduce entangling-gate count, T-count, and T-depth compared with conventional static decompositions, while preserving fault-tolerance guarantees. Through analytical cost models and experimental evaluation, we demonstrate that relative-phase primitives and measurement-conditioned corrections enable scalable implementations with improved depth and resource efficiency.

Journal reference
2026 IEEE 29th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)
DOI
10.1109/DDECS69233.2026.11521018

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The Toffoli gate is a fundamental building block for quantum arithmetic and reversible logic, yet its efficient realization remains a major challenge in both near-term and fault-tolerant quantum architectures. Recent advances in dynamic quantum circuit capabilities, including mid-circuit measurement and classical feedforward, provide new opportunities for reducing the resource overhead of non-Clifford operations.
In this work, we propose a set of dynamic decomposition strategies for multi-controlled Toffoli gates that exploit adaptive circuit execution and ancilla-assisted constructions. Our methods systematically reduce entangling-gate count, T-count, and T-depth compared with conventional static decompositions, while preserving fault-tolerance guarantees. Through analytical cost models and experimental evaluation, we demonstrate that relative-phase primitives and measurement-conditioned corrections enable scalable implementations with improved depth and resource efficiency.
Multi-controlled Toffoli gates are fundamental building blocks in quantum computation, with applications in quantum arithmetic, simulation, and search algorithms. In fault-tolerant architectures, their realization is constrained by the high cost of non-Clifford resources, particularly in terms of T-count and T-depth. Recent advances have demonstrated that the use of ancillary qubits, relative-phase Toffoli gates, and dynamic circuit techniques can substantially reduce this overhead. In this work, we investigate the decomposition of large Toffoli gates using 3- and 4-input relative-phase Toffoli gates in the presence of a single clean ancilla and conditionally clean ancillas. We derive explicit resource bounds for Clifford+T implementations incorporating dynamic-circuit-based uncomputation and measurement-conditioned corrections. Our analysis emphasizes T-depth reduction under fixed CX and T-count overhead, ensuring relevance for near-term devices. We show that introducing 4-input relative-phase Toffoli gates enables significant T-depth reductions through enhanced parallelism while maintaining favorable ancilla requirements. We further validate our theoretical results through experimental evaluation and comparative analysis with existing approaches.
Efficient Synthesis of Multi-Controlled Toffoli Gates with Ternary Clifford+P9+P_9+P9​ Gates
Temporary occupation of qutrit levels can reduce the width and depth required for binary circuit logic in quantum computing. We introduce an efficient intermediate-qutrit decomposition of multi-controlled Toffoli gates with binary-subspace inputs and outputs. For balanced control widths n=2h−1n=2^h-1n=2h−1, the proposed decomposition is evaluated hierarchically through a tree, allowing independent subtree computations to proceed in parallel and reducing the depth from linear to logarithmic. The balanced low-depth construction requires 6n+36n+36n+3 logical P9P_9P9​ injections and n−34\frac{n-3}{4}4n−3​ clean ancillary qutrits. It matches the direct P9P_9P9​ count of a recursively extended Clifford+P9P_9P9​ baseline derived from the state-of-the-art work while using asymptotically one-quarter as many clean ancillas and replacing linear depth with logarithmic depth. For arbitrary control widths, a sequential extension preserves the 6n+36n+36n+3 P9P_9P9​ count but has depth O(log⁡m+n−m)O(\log m+n-m)O(logm+n−m) for a balanced core m=2h−1≤nm=2^h-1\leq nm=2h−1≤n, which is linear in the worst case over nnn. By reducing the resource overhead of a widely used reversible primitive, the proposed decomposition provides a practical building block for the design and compilation of more resource-efficient quantum algorithms in the fault-tolerant regime.
The multi-controlled Toffoli (MCT) gate is a fundamental primitive in quantum circuit design, with applications in quantum arithmetic, cryptanalysis, and algorithmic implementations. Being a high-level logical operation, the efficient decomposition of MCT gates into lower-level netlists has remained a major optimization challenge for decades. While emerging quantum error-correcting codes such as bivariate bicycle (BB) codes drastically reduce fault-tolerance overhead, realizing non-Clifford circuits on modular BB-code architectures introduces complex compilation bottlenecks governed by inter-module routing, factory density, and layout. Consequently, the mapping of MCT gates onto BB-code architectures remains relatively unexplored. In this paper, we overcome these challenges by mapping optimal-Toffoli-depth MCT decompositions (Dutta et al., PRA, 2025) onto BB-code-based fault-tolerant architectures via direct ∣CCZ⟩\lvert \mathrm{CCZ} \rangle∣CCZ⟩ state injection from an external magic state factory. We introduce a targeted placement strategy that exploits the binary-tree structure of MCT decompositions to co-locate interacting subtrees. This approach reduces inter-module instruction counts by up to 16.02%\mathbf{16.02}\%16.02% compared to a naive sequential first-fit placement. We also evaluate the impact of factory placement across different topologies, demonstrating that grid-based layouts yield up to a 23.7%\mathbf{23.7}\%23.7% reduction in inter-module instructions relative to linear architectures (Yoder et al., arXiv, 2025). Finally, we validate the practical viability of our compiled circuits by analyzing aggregate execution errors and logical failure probabilities using the bicycle-ISA error estimator bicycle_numerics provided by the Qiskit community, https://github.com/qiskit-community/bicycle-architecture-compiler.
The Toffoli gate (controlled-controlled-NOT) and its multi-controlled generalizations are fundamental logical building blocks of quantum algorithms and utilized extensively in pivotal algorithms such as Grover’s algorithm and Shor’s algorithm. Despite being a fundamental logical primitive of quantum algorithms, Toffoli gates must be decomposed to primitive single-qubit and two-qubit gates which are available in physical quantum hardware. These decompositions incur significant implementation costs in circuit depth and gate count, costs that propagate directly to the entire circuit. Consequently, reducing the implementation cots of Toffoli gates provides a direct method of reducing the implementation costs of many quantum algorithms. This thesis evaluates state-of-the-art methods for reducing the implementation costs of Toffoli gates by introducing approximations. While approximations introduce errors to the output of the Toffoli gate, they can reduce the depth and gate count of the implementation. This thesis finds that discrete errors in two-qubit and three-qubit controlled Toffoli gates have been utilized to reduce the gate counts in such a way that the implementation is exact cancelling the errors. Additionally, continuous errors are utilized to reduce the depth of a multi-controlled Toffoli gate decomposition in ancilla-free settings. However, this review also demonstrates other, non-approximate, construction of multi-controlled Toffoli gate, which achieves comparable implementation costs demonstrating marginal gains for the approximation techniques currently.
The multi-controlled Toffoli (MCT) gate is a key primitive in quantum arithmetic, oracle construction, and quantum cryptanalysis. Although recent work has established optimal Toffoli-depth MCT decompositions under all-to-all qubit connectivity, their realization on near-term quantum hardware with restricted qubit connectivity remains largely unexplored. While general-purpose quantum mappers can route arbitrary circuits, they do not explicitly exploit the repeated interaction patterns inherent in MCT decompositions. In our present paper, we study architecture-aware mappings of optimal Toffoli-depth MCT decompositions onto restricted two-dimensional qubit layouts. We begin with a structured geometric placements that preserve the parallelism of state-of-the-art Toffoli and MCT decompositions with no additional depth overhead. We further introduce a motif-based packing framework in which decomposition layers are represented by interaction motifs derived from basic Toffoli gates. By embedding these motifs vertex-disjointly into hardware graphs, we characterize the minimum-size topologies supporting the required qubit resources and derive explicit bounds on the resulting depth overhead under tight qubit budgets. Finally, we compare these bounds with routing-aware placement heuristics and empirically evaluate the effectiveness of embedding different motifs across a range of hardware topologies.
The need to consider fault-tolerant quantum circuits is essential due to the intrinsic fragility of quantum systems. Recent studies have focused on optimizing complexity, resource utilization, and error resilience to enhance execution efficiency on quantum hardware. This paper performs a comparative analysis of fault-tolerant implementation approaches for quantum circuit design, emphasizing resource optimization, scalability, and error resilience. This paper illustrates recent designs that include enhanced Toffoli gate decompositions with reduced T-depths and resource-effective designs, demonstrating the tradeoffs among T-depth, T-gate count, and ancilla usage. These insights facilitate developing effective, scalable, and reliable quantum computing solutions, which are essential for both near-term quantum computation and future advancements.