S-SYNC: Shuttle and Swap Co-Optimization in Quantum Charge-Coupled Devices
- URL: http://arxiv.org/abs/2505.01316v1
- Date: Fri, 02 May 2025 14:45:25 GMT
- Title: S-SYNC: Shuttle and Swap Co-Optimization in Quantum Charge-Coupled Devices
- Authors: Chenghong Zhu, Xian Wu, Jingbo Wang, Xin Wang,
- Abstract summary: We introduce S-SYNC, a compiler designed to co-optimize the number of shuttling and swapping operations.<n>S-SYNC exploits the unique properties of QCCD and incorporates generic SWAP operations to efficiently manage shuttle and SWAP counts simultaneously.<n>Our evaluations demonstrate that our approach reduces the shuttling number by 3.69x on average and improves the success rate of quantum applications by 1.73x on average.
- Score: 33.720436732911644
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The Quantum Charge-Coupled Device (QCCD) architecture is a modular design to expand trapped-ion quantum computer that relies on the coherent shuttling of qubits across an array of segmented electrodes. Leveraging trapped ions for their long coherence times and high-fidelity quantum operations, QCCD technology represents a significant advancement toward practical, large-scale quantum processors. However, shuttling increases thermal motion and consistently necessitates qubit swaps, significantly extend execution time and negatively affect application success rates. In this paper, we introduce S-SYNC -- a compiler designed to co-optimize the number of shuttling and swapping operations. S-SYNC exploits the unique properties of QCCD and incorporates generic SWAP operations to efficiently manage shuttle and SWAP counts simultaneously. Building on the static topology formulation of QCCD, we develop scheduling heuristics to enhance overall performance. Our evaluations demonstrate that our approach reduces the shuttling number by 3.69x on average and improves the success rate of quantum applications by 1.73x on average. Moreover, we apply S-SYNC to gain insights into executing applications across various QCCD topologies and to compare the trade-offs between different initial mapping methods.
Related papers
- Adaptive Job Scheduling in Quantum Clouds Using Reinforcement Learning [1.0542466736167886]
Current quantum systems face critical bottlenecks, including limited qubit counts, brief coherence intervals, and high susceptibility to errors.<n>We introduce a simulation-based tool that supports distributed scheduling and concurrent execution of quantum jobs on networked QPUs connected via real-time classical channels.
arXiv Detail & Related papers (2025-06-12T16:54:19Z) - Spatial and temporal circuit cutting with hypergraphic partitioning [0.0]
This paper presents a hypergraph-based circuit cutting methodology suitable for both spatial and temporal scenarios.<n>By modeling quantum circuits as high-level hypergraphs, we apply partitionings such as Stoer-Wagner, Fiduccia-Mattheyses, and Kernighan-Lin.
arXiv Detail & Related papers (2025-04-12T20:31:07Z) - Runtime Reduction in Linear Quantum Charge-Coupled Devices using the Parity Flow Formalism [0.32985979395737786]
We show that physical SWAP gates can be eliminated in linear hardware architectures without increasing the total number of two-qubit operations.
This has a significant impact on the execution time of quantum circuits in linear Quantum Charge-Coupled Devices.
arXiv Detail & Related papers (2024-10-21T18:00:29Z) - Scaling and assigning resources on ion trap QCCD architectures [0.0]
Ion trap technologies have earned significant attention as potential candidates for quantum information processing.
We propose a novel approach for initial qubit placement, demonstrating enhancements of up to 50% compared to prior methods.
arXiv Detail & Related papers (2024-08-01T01:35:55Z) - Shuttling for Scalable Trapped-Ion Quantum Computers [2.8956730787977083]
We propose an efficient shuttling schedule for Trapped-ion quantum computers.
The proposed approach produces shuttling schedules with a close-to-minimal amount of time steps.
An implementation of the proposed approach is publicly available as part of the open-source Munich Quantum Toolkit.
arXiv Detail & Related papers (2024-02-21T19:00:04Z) - Near-Term Distributed Quantum Computation using Mean-Field Corrections
and Auxiliary Qubits [77.04894470683776]
We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production.
We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
arXiv Detail & Related papers (2023-09-11T18:00:00Z) - Scaling Limits of Quantum Repeater Networks [62.75241407271626]
Quantum networks (QNs) are a promising platform for secure communications, enhanced sensing, and efficient distributed quantum computing.
Due to the fragile nature of quantum states, these networks face significant challenges in terms of scalability.
In this paper, the scaling limits of quantum repeater networks (QRNs) are analyzed.
arXiv Detail & Related papers (2023-05-15T14:57:01Z) - A self-consistent field approach for the variational quantum
eigensolver: orbital optimization goes adaptive [52.77024349608834]
We present a self consistent field approach (SCF) within the Adaptive Derivative-Assembled Problem-Assembled Ansatz Variational Eigensolver (ADAPTVQE)
This framework is used for efficient quantum simulations of chemical systems on nearterm quantum computers.
arXiv Detail & Related papers (2022-12-21T23:15:17Z) - Decomposition of Matrix Product States into Shallow Quantum Circuits [62.5210028594015]
tensor network (TN) algorithms can be mapped to parametrized quantum circuits (PQCs)
We propose a new protocol for approximating TN states using realistic quantum circuits.
Our results reveal one particular protocol, involving sequential growth and optimization of the quantum circuit, to outperform all other methods.
arXiv Detail & Related papers (2022-09-01T17:08:41Z) - Synergy Between Quantum Circuits and Tensor Networks: Short-cutting the
Race to Practical Quantum Advantage [43.3054117987806]
We introduce a scalable procedure for harnessing classical computing resources to provide pre-optimized initializations for quantum circuits.
We show this method significantly improves the trainability and performance of PQCs on a variety of problems.
By demonstrating a means of boosting limited quantum resources using classical computers, our approach illustrates the promise of this synergy between quantum and quantum-inspired models in quantum computing.
arXiv Detail & Related papers (2022-08-29T15:24:03Z) - QSAN: A Near-term Achievable Quantum Self-Attention Network [73.15524926159702]
Self-Attention Mechanism (SAM) is good at capturing the internal connections of features.
A novel Quantum Self-Attention Network (QSAN) is proposed for image classification tasks on near-term quantum devices.
arXiv Detail & Related papers (2022-07-14T12:22:51Z) - Realization of arbitrary doubly-controlled quantum phase gates [62.997667081978825]
We introduce a high-fidelity gate set inspired by a proposal for near-term quantum advantage in optimization problems.
By orchestrating coherent, multi-level control over three transmon qutrits, we synthesize a family of deterministic, continuous-angle quantum phase gates acting in the natural three-qubit computational basis.
arXiv Detail & Related papers (2021-08-03T17:49:09Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.