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Optimizing Quantum Fourier Transformation (QFT) Kernels for Modern NISQ and FT Architectures
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Optimizing Quantum Fourier Transformation (QFT) Kernels for Modern NISQ and FT Architectures
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Rapid development in quantum computing leads to the appearance of several quantum applications. Quantum Fourier Transformation (QFT) sits at the heart of many of these applications. Existing work leverages SAT solver or heuristics to generate a hardware-compliant circuit for QFT by inserting SWAP gates to remap logical qubits to physical qubits. However, they might face problems such as long compilation time due to the huge search space for SAT solver or suboptimal outcome in terms of the number of cycles to finish all gate operations. In this paper, we propose a domain-specific hardware mapping approach for QFT. We unify our insight of relaxed ordering and unit exploration in QFT to search for a qubit mapping solution with the help of program synthesis tools. Our method is the first one that guarantees linear-depth QFT circuits for Google Sycamore, IBM heavy-hex, and the lattice surgery, with respect to the number of qubits. Compared with state-of-the-art approaches, our method can save up to 53% in SWAP gate and 92% in depth.
Forward citations
Cited by 1 Pith paper
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Towards an Optimally Distributed Quantum Fourier Transform Circuit
Presents an optimal gate-packing partitioning scheme for the QFT that aims to minimize e-bit count in distributed quantum systems and validates it on hardware.
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