Quantum Circuit Compiler for a Shuttling-Based Trapped-Ion Quantum Computer

Abstract

The increasing capabilities of quantum computing hardware and the challenge of realizing deep quantum circuits require fully automated and efficient tools for compiling quantum circuits. To express arbitrary circuits in a sequence of native gates specific to the quantum computer architecture, it is necessary to make algorithms portable across the landscape of quantum hardware providers. In this work, we present a compiler capable of transforming and optimizing a quantum circuit targeting a shuttling-based trapped-ion quantum processor. It consists of custom algorithms set on top of the quantum circuit framework Pytket. The performance was evaluated for a wide range of quantum circuits and the results show that the gate counts can be reduced by factors up to 5.1 compared to standard Pytket and up to 2.2 compared to standard Qiskit compilation.

35 pages, 25 figures, 4 tables, accepted in Quantum

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Cited by in corpus (11)

• Optimizing quantum gates towards the scale of logical qubits
• Computational Capabilities and Compiler Development for Neutral Atom Quantum Processors: Connecting Tool Developers and Hardware Experts
• Automated Generation of Shuttling Sequences for a Linear Segmented Ion Trap Quantum Computer
• An Abstract Model and Efficient Routing for Logical Entangling Gates on Zoned Neutral Atom Architectures
• Hybrid discrete-continuous compilation of trapped-ion quantum circuits with deep reinforcement learning
• Efficient fault-tolerant code switching via one-way transversal CNOT gates
• Quantum error correction for long chains of trapped ions
• Quantum Circuit Discovery for Fault-Tolerant Logical State Preparation with Reinforcement Learning
• Lightcone Bounds for Quantum Circuit Mapping via Uncomplexity
• Routing-Aware Placement for Zoned Neutral Atom-based Quantum Computing
• Ion-Trap Chip Architecture Optimized for Implementation of Quantum Error-Correcting Code