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arXiv:2204.03695 · ACM Great Lakes Symposium on VLSI (GLSVLSI)

A Shuttle-Efficient Qubit Mapper for Trapped-Ion Quantum Computers

Suryansh Upadhyay, Abdullah Ash Saki, Rasit Onur Topaloglu, Swaroop Ghosh

Published Jun 2, 2022• 14 citations
arXivHTMLPDF

Abstract

Trapped-ion (TI) quantum computer is one of the forerunner quantum technologies. Execution of a quantum gate in multiple trap TI system may frequently involve ions from two different traps, hence one of the ions needs to be shuttled (moved) between traps to be co-located, degrading fidelity, and increasing the program execution time. The choice of initial mapping influences the number of shuttles. The existing Greedy policy neglects the depth of the program at which a gate is present. Intuitively, the contribution of the late-stage gates to the initial mapping is less since the ions might have already shuttled to a different trap to satisfy other gate operations. In this paper, we target this gap and propose a new program adaptive policy especially for programs with considerable depth and high number of qubits (valid for practical-scale quantum programs). Our technique achieves an average reduction of 9% shuttles/program (with 21.3% at best) for 120 random circuits and enhances the program fidelity up to 3.3X (1.41X on average).

DOI
10.1145/3526241.3530366

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Trapped-ion (TI) quantum computer is one of the forerunner quantum technologies. Execution of a quantum gate in multiple trap TI system may frequently involve ions from two different traps, hence one of the ions needs to be shuttled (moved) between traps to be co-located, degrading fidelity, and increasing the program execution time. The choice of initial mapping influences the number of shuttles. The existing Greedy policy neglects the depth of the program at which a gate is present. Intuitively, the contribution of the late-stage gates to the initial mapping is less since the ions might have already shuttled to a different trap to satisfy other gate operations. In this paper, we target this gap and propose a new program adaptive policy especially for programs with considerable depth and high number of qubits (valid for practical-scale quantum programs). Our technique achieves an average reduction of 9% shuttles/program (with 21.3% at best) for 120 random circuits and enhances the program fidelity up to 3.3X (1.41X on average).
Trapped-ion systems can have a limited number of ions (qubits) in a single trap. Increasing the qubit count to run meaningful quantum algorithms would require multiple traps where ions need to shuttle between traps to communicate. The existing compiler has several limitations, which result in a high number of shuttle operations and degraded fidelity. In this paper, we target this gap and propose compiler optimizations to reduce the number of shuttles. Our technique achieves a maximum reduction of 51.17% in shuttles (average ~ 33%) tested over 125 circuits. Furthermore, the improved compilation enhances the program fidelity up to 22.68X with a modest increase in the compilation time.
Trapped-ion (TI) quantum bits are a front-runner technology for quantum computing. TI systems with multiple interconnected traps can overcome the hardware connectivity issue inherent in superconducting qubits and can solve practical problems at scale. With a sufficient number of qubits on the horizon, the multi-programming model for Quantum Computers (QC) has been proposed where multiple users share the same QC for their computing. Multi-programming is enticing for quantum cloud providers as it can maximize device utilization, throughput, and profit for clouds. Users can also benefit from the short wait queue. However, shared access to quantum computers can create new security issues. This paper presents one such vulnerability in shared TI systems that requireshuttleoperations for communication among traps. Repeated shuttle operations increase quantum bit energy and degrade the reliability of computations (fidelity). We show adversarial program design approaches requiring numerous shuttles. We propose a random and systematic methodology for adversary program generation. Our analysis shows shuttle-exploiting attacks can substantially degrade the fidelities of victim programs by$\approx 2 \times tototo\approx 63 \times $. Finally, we present several countermeasures such as adopting a hybrid initial mapping policy, padding victim programs with dummy qubits, and capping maximum shuttles.
Trapped-ion quantum computers offer high-fidelity operations, long coherence times, and all-to-all connectivity within a single trap. However, scaling to large circuits is limited by the trap's ion capacity. The QCCD architecture addresses this by enabling ion shuttling across multiple traps, but excessive shuttling increases execution time and degrades fidelity. This paper presents an improved ion-shuttling approach targeting linear QCCD architectures. Building on a state-of-the-art approach [27] for linear trapped-ion devices, our approach introduces a front-layer-based scheduling method that dynamically prioritizes executable gates, along with a novel destination trap selection method for ion-shuttling, effectively reducing unnecessary ion movements. We also present a look-ahead gate selection strategy based on the gate dependency graph, avoiding the high runtime of the gate proximity approach used in the state-of-the-art approach, especially in circuits with all-to-all communication. Our approach achieves up to a 37.67% reduction in shuttle count and up to a 74.91% reduction in compilation time compared to the state-of-the-art approach for linear trapped-ion devices on actual NISQ benchmarks and synthetic circuits. On average, our approach achieves a 16.44% reduction in shuttle count and a 30.77% reduction in compilation time across all test cases. These improvements highlight the effectiveness of our approach, particularly for actual circuits.
Effective qubit mapping facilitates quantum algorithm implementations in physical quantum computing architectures. Recent work reported promising qubit mapping on one-dimensional trapped-ion systems. Due to manufacturing complexity, however, it is insufficient to map all logical qubits into one single qubit array in a large-scale quantum circuit; instead, we shall divide a quantum circuit into subcircuits for extending to two-dimensional trapped-ion systems. Nevertheless, operating a two-qubit gate between different subcircuits reduces the circuit fidelity. As a result, it is desirable to develop an effective partitioning algorithm that can maintain fidelity and minimize the execution time. This paper develops an effective divide-and-conquer algorithm for each array. Unlike traditional min-cut partitioning to balance the qubit number on each array, we propose a depth-aware partitioning algorithm to expand the solution space for all mapping solutions and optimize the execution time on each array. Besides, we develop a satisfiability modulo theories-based algorithm to optimize the mapping solution for each array. Experimental results show that our algorithm can averagely achieve a 14% total time step reduction and a 30% total fidelity improvement for commonly used benchmarks.
Trapped ions (TI) are at the forefront of quantum computing implementation, offering unparalleled coherence, fidelity, and connectivity. However, the scalability of TI systems is hampered by the limited capacity of individual ion traps, necessitating intricate ion shuttling for advanced computational tasks. The Quantum Charge-Coupled Device (QCCD) framework has emerged as a promising solution, facilitating ion mobility for universal quantum computation. Current QCCD architectures predominantly feature a linear topology, which is increasingly recognized as inefficient for complex quantum operations. Anticipating the shift towards more efficacious designs, this paper introduces an innovative quantum scheduling strategy optimized for parallel QCCD topologies. Our strategy proposes a probabilistic formula for ion movement, alongside ingenious methods for local layer generation and layer compression, yielding a significant reduction in ion shuttle times. Through simulations, we demonstrate that our strategy not only substantially outstrips the linear model but also exhibits better performance over other parallel strategies that employ greedy algorithms. This is achieved through our nuanced resolution of complexities such as traffic blocks and trap capacity limitations. The consequent reduction in shuttle operations leads to lower energy consumption and an enhancement in the quantum computer's fidelity, ultimately accelerating program execution times.
Trapped-ion quantum computers are a promising platform, offering high-quality qubits with long coherence times and high-fidelity gate operations. The Quantum Charge Coupled Device (QCCD) architecture provides a scalable blueprint by leveraging the ability to shuttle ions between distinct zones. However, realizing such architectures in practice requires software support to manage ion movement across multi-zone layouts. In this work, we propose a compilation strategy for QCCD architectures with multiple processing zones located outside a grid-type memory zone. Unlike previous approaches that treat processing zones as black-boxes, our method explicitly models their structural constraints, enabling optimized ion movement to and through them. It combines qubit partitioning with dependency-aware gate selection to reduce inter-zone shuttling while enabling simultaneous gate execution. We implemented the method in an open-source tool and empirically demonstrated its effectiveness across several QCCD layouts, laying a foundation for the compilation of multi-zone trapped-ion systems.