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Quantum circuit for multi-qubit Toffoli gate with optimal resource

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arxiv 2402.05053 v1 pith:53LPVZ3E submitted 2024-02-07 quant-ph

classification quant-ph
keywords quantumancillaryqubitscircuitgateresourcetoffolimulti-qubit
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

Resource consumption is an important issue in quantum information processing, particularly during the present NISQ era. In this paper, we investigate resource optimization of implementing multiple controlled operations, which are fundamental building blocks in the field of quantum computing and quantum simulation. We design new quantum circuits for the $n$-Toffoli gate and general multi-controlled unitary, which have only $O(\log n)$-depth and $O(n)$-size, and only require $1$ ancillary qubit. To achieve these results, we explore the potential of ancillary qubits and discover a method to create new conditional clean qubits from existed ancillary qubits. These techniques can also be utilized to construct an efficient quantum circuit for incrementor, leading to an implementation of multi-qubit Toffoli gate with a depth of $O(\log^2n)$ and size of $O(n)$ without any ancillary qubits. Furthermore, we explore the power of ancillary qubits from the perspective of resource theory. We demonstrate that without the assistance of ancillary qubit, any quantum circuit implementation of multi-qubit Toffoli gate must employ exponential precision gates. This finding indicates a significant disparity in computational power of quantum circuits between using and not using ancillary qubits. Additionally, we discuss the comparison of the power of ancillary qubits and extra energy levels in quantum circuit design.

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Cited by 7 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. High-level quantum structured programs as quantum registers compositions

    quant-ph 2026-08 conditional novelty 6.0 of 10

    A formal framework for structured quantum programming where operations act on entire quantum registers, demonstrated by a quantum SMT solver prototype.

  2. Optimizing sparse quantum state preparation with measurement and feedforward

    quant-ph 2025-08 conditional novelty 6.0 of 10

    Two new sparse quantum state preparation algorithms achieve O(n log d) and O(n) circuit depth with O(d) ancilla qubits and O(dn) size.

  3. Logarithmic Depth Decomposition of Approximate Multi-Controlled Single-Qubit Gates Without Ancilla Qubits

    quant-ph 2025-07 conditional novelty 6.0 of 10

    The authors construct relative-phase n-qubit Toffoli gates without ancillas and O(log n)-depth multi-controlled SU(2)/U(2) decompositions, improving on earlier methods.

  4. Preparation of cat states in many-body eigenbasis via non-local measurement

    quant-ph 2025-06 conditional novelty 6.0 of 10

    Periodically checking that a spin-1 XY chain is not in a chosen product state leaves a dark manifold of resonantly degenerate eigenstates, producing GHZ-like and time-oscillating cat states at long times.

  5. Efficient Quantum Access Model for Sparse Structured Matrices using Linear Combination of Things

    quant-ph 2025-07 conditional novelty 5.0 of 10

    The paper gives algorithms to decompose structured sparse matrices into polylogarithmically many sigma-basis operators and builds quantum circuits for both variational and fault-tolerant use, cutting term counts expon...

  6. On Exact Space-Depth Trade-Offs in Multi-Controlled Toffoli Decomposition

    quant-ph 2025-02 reject novelty 4.0 of 10

    The paper gives exact Toffoli-depth versus ancilla-count formulas for multi-controlled Toffoli decomposition and claims a ceil(log2 n) lower bound, but the main formula is inconsistent with its own example.

  7. Quantum Arithmetic Circuits in Public-Key Cryptography

    quant-ph 2026-07 accept novelty 2.5 of 10

    A structured survey of optimized quantum adders, multipliers, modular exponentiation and point-addition circuits for public-key cryptanalysis, plus fault-tolerant resource estimation techniques.

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