Abstract
Quantum computers are built with fragile and noise/error-prone qubits. Some prominent errors include, decoherence/dephasing, gate error, readout error, leakage, and crosstalk. Furthermore, the qubits vary in terms of their quality. Some qubits are healthy whereas others prone to errors. This presents an opportunity to exploit good quality qubits to improve the computation outcome. This chapter reviews the state-of-the-art mapping techniques for error tolerance. We take quantum benchmarks as well as approximate algorithms for applications covering MaxCut, object detection and factorization to illustrate various optimization challenges and opportunities.
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Acknowledgements
This work is supported by SRC (2847.001), NSF (CNS-1722557, CCF-1718474, DGE-1723687, DGE-1821766, OIA-2040667 and DGE-2113839) and a Seed Grant award from the Institute for Computational and Data Sciences (ICDS) at the Pennsylvania State University. The authors would like to thank the students in LOGICS lab, Penn State and Ling Qiu for contribution on VQF. This content is solely the responsibility of the authors and does not necessarily represent the views of the ICDS and NSF.
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Saki, A.A., Alam, M., Li, J., Ghosh, S. (2023). Error-Tolerant Mapping for Quantum Computing. In: Aly, M.M.S., Chattopadhyay, A. (eds) Emerging Computing: From Devices to Systems. Computer Architecture and Design Methodologies. Springer, Singapore. https://doi.org/10.1007/978-981-16-7487-7_12
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