Quantum Computer Systems for Scientific Discovery
Yuri Alexeev, Dave Bacon, Kenneth R. Brown, Robert Calderbank, Lincoln, D. Carr, Frederic T. Chong, Brian DeMarco, Dirk Englund, Edward Farhi, Bill, Fefferman, Alexey V. Gorshkov, Andrew Houck, Jungsang Kim, Shelby Kimmel,, Michael Lange, Seth Lloyd, Mikhail D. Lukin

TL;DR
This paper advocates for a co-design approach to quantum computer systems and their scientific applications, emphasizing integrated development to accelerate progress and discovery in quantum science.
Contribution
It highlights the importance of simultaneous development of quantum hardware and applications, and discusses community needs, opportunities, and challenges for scientific quantum computing.
Findings
Identification of key scientific needs and opportunities.
Case studies illustrating potential quantum applications.
Discussion of major challenges for quantum computer development.
Abstract
The great promise of quantum computers comes with the dual challenges of building them and finding their useful applications. We argue that these two challenges should be considered together, by co-designing full-stack quantum computer systems along with their applications in order to hasten their development and potential for scientific discovery. In this context, we identify scientific and community needs, opportunities, a sampling of a few use case studies, and significant challenges for the development of quantum computers for science over the next 2--10 years. This document is written by a community of university, national laboratory, and industrial researchers in the field of Quantum Information Science and Technology, and is based on a summary from a U.S. National Science Foundation workshop on Quantum Computing held on October 21--22, 2019 in Alexandria, VA.
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