On the Design and Implementation of a Quantum Architectures Knowledge Unit for a CS Curriculum

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Abstract

Sixteen years ago, Scott Aaronson remarked (in the presence of Ray Laflamme) that quantum mechanics (QM) resembles an operating system on which the rest of Physics is running its application software (except for general relativity "which has not yet been successfully ported to this particular OS''). Prior to that, it took the insight of an educator and eminent computer scientist (Umesh Vazirani) to realize that a complete and consistent introduction to QM can be given via the language of qubits and quantum gates. Closer to the present, it took the profound intuition of another polymath (Terry Rudolph) to realize that the linear algebra normally at the foundation of such an approach can be replaced with a simple rewriting system accessible to middle school students. Rewriting systems are at the foundation of Computer Science, they are, in fact, the very fabric of it (e.g., Turing machines and lambda calculus), so these are very fortunate developments. Furthermore, a linear algebra prerequisite is now shared firmly in the CS undergraduate curriculum with Machine Learning, a topic that has known a very deep and sudden revival. Quantum Information Science and Technology (QIST) is inherently interdisciplinary and spans physics, computer science, mathematics, engineering, chemistry and materials science. We present three curricular plans for incorporating QIST topics (via Quantum Computing) into the CS undergraduate curriculum. Such plans have been constructed with a preliminary consultation with QED-C members (industry, academia, national labs, and government agencies) asking for comments, suggestions and general input on these three curricular plans.

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APA

German, A., Pias, M., & Xiang, Q. (2023). On the Design and Implementation of a Quantum Architectures Knowledge Unit for a CS Curriculum. In SIGCSE 2023 - Proceedings of the 54th ACM Technical Symposium on Computer Science Education (Vol. 1, pp. 1150–1156). Association for Computing Machinery, Inc. https://doi.org/10.1145/3545945.3569845

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