Assessing and Advancing the Potential of Quantum Computing: A NASA Case Study
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866911929641992192 |
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| author | Rieffel, Eleanor G. Asanjan, Ata Akbari Alam, M. Sohaib Anand, Namit Neira, David E. Bernal Block, Sophie Brady, Lucas T. Cotton, Steve Izquierdo, Zoe Gonzalez Grabbe, Shon Gustafson, Erik Hadfield, Stuart Lott, P. Aaron Maciejewski, Filip B. Mandrà, Salvatore Marshall, Jeffrey Mossi, Gianni Bauza, Humberto Munoz Saied, Jason Suri, Nishchay Venturelli, Davide Wang, Zhihui Biswas, Rupak |
| author_facet | Rieffel, Eleanor G. Asanjan, Ata Akbari Alam, M. Sohaib Anand, Namit Neira, David E. Bernal Block, Sophie Brady, Lucas T. Cotton, Steve Izquierdo, Zoe Gonzalez Grabbe, Shon Gustafson, Erik Hadfield, Stuart Lott, P. Aaron Maciejewski, Filip B. Mandrà, Salvatore Marshall, Jeffrey Mossi, Gianni Bauza, Humberto Munoz Saied, Jason Suri, Nishchay Venturelli, Davide Wang, Zhihui Biswas, Rupak |
| contents | Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum computing hardware has advanced rapidly, from tiny laboratory experiments to quantum chips that can outperform even the largest supercomputers on specialized computational tasks, these noisy-intermediate scale quantum (NISQ) processors are still too small and non-robust to be directly useful for any real-world applications. In this paper, we describe NASA's work in assessing and advancing the potential of quantum computing. We discuss advances in algorithms, both near- and longer-term, and the results of our explorations on current hardware as well as with simulations, including illustrating the benefits of algorithm-hardware co-design in the NISQ era. This work also includes physics-inspired classical algorithms that can be used at application scale today. We discuss innovative tools supporting the assessment and advancement of quantum computing and describe improved methods for simulating quantum systems of various types on high-performance computing systems that incorporate realistic error models. We provide an overview of recent methods for benchmarking, evaluating, and characterizing quantum hardware for error mitigation, as well as insights into fundamental quantum physics that can be harnessed for computational purposes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_15601 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Assessing and Advancing the Potential of Quantum Computing: A NASA Case Study Rieffel, Eleanor G. Asanjan, Ata Akbari Alam, M. Sohaib Anand, Namit Neira, David E. Bernal Block, Sophie Brady, Lucas T. Cotton, Steve Izquierdo, Zoe Gonzalez Grabbe, Shon Gustafson, Erik Hadfield, Stuart Lott, P. Aaron Maciejewski, Filip B. Mandrà, Salvatore Marshall, Jeffrey Mossi, Gianni Bauza, Humberto Munoz Saied, Jason Suri, Nishchay Venturelli, Davide Wang, Zhihui Biswas, Rupak Quantum Physics Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum computing hardware has advanced rapidly, from tiny laboratory experiments to quantum chips that can outperform even the largest supercomputers on specialized computational tasks, these noisy-intermediate scale quantum (NISQ) processors are still too small and non-robust to be directly useful for any real-world applications. In this paper, we describe NASA's work in assessing and advancing the potential of quantum computing. We discuss advances in algorithms, both near- and longer-term, and the results of our explorations on current hardware as well as with simulations, including illustrating the benefits of algorithm-hardware co-design in the NISQ era. This work also includes physics-inspired classical algorithms that can be used at application scale today. We discuss innovative tools supporting the assessment and advancement of quantum computing and describe improved methods for simulating quantum systems of various types on high-performance computing systems that incorporate realistic error models. We provide an overview of recent methods for benchmarking, evaluating, and characterizing quantum hardware for error mitigation, as well as insights into fundamental quantum physics that can be harnessed for computational purposes. |
| title | Assessing and Advancing the Potential of Quantum Computing: A NASA Case Study |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2406.15601 |