As part of the Illinois Wesleyan University physics department’s Quantum Science and Technology (QST) initiative, we have been developing a series of computational labs with twin foci; one on near-term applications of quantum computing in Quantum Chemistry, the other on preparing incoming students to use quantum algorithms on cloud platforms for Quantum Computing. These computational labs will deepen the students’ understanding of fundamental concepts in quantum mechanics, linear algebra, and quantum chemistry while building, in parallel, their technical competence with quantum computers. These computational labs will further enhance the current curriculum of the QST concentration, and might also serve as a blueprint for other educational institutions seeking to train the next-generation quantum workforce.
As part of the Illinois Wesleyan University physics department’s Quantum Science and Technology (QST) initiative, we have been developing a series of computational labs with twin foci; one on near-term applications of quantum computing in Quantum Chemistry, the other on preparing incoming students to use quantum algorithms on cloud platforms for Quantum Computing. These computational labs will deepen the students’ understanding of fundamental concepts in quantum mechanics, linear algebra, and quantum chemistry while building, in parallel, their technical competence with quantum computers. These computational labs will further enhance the current curriculum of the QST concentration, and might also serve as a blueprint for other educational institutions seeking to train the next-generation quantum workforce.
Abstract The rise of quantum information as a viable technology requires appropriate instructional curricula for preparing a future workforce. Key concepts that are the basis of quantum information involve fundamentals of quantum mechanics, such as superposition, entanglement and measurement. To complement modern initiatives to teach quantum physics to the emerging workforce, lab experiences are needed. We have developed a curriculum of quantum optics experiments to teach quantum mechanics fundamentals and quantum algebra. These laboratories provide hands-on experimentation of optical components on a table-top. We have also created curricular materials, manuals, tutorials, parts and price lists for instructors. Automation of the apparatus offers the flexibility of using the apparatus remotely and for giving access to a greater number of students with a single setup.
As we enter the post-Moore era, we experience the rise of various non-von-Neumann-architectures to address the increasing computational demand for modern applications, with quantum computing being among the most prominent and promising technologies. However, this development creates a gap in current computer science curricula since most quantum computing lectures are strongly physics-oriented and have little intersection with the remaining curriculum of computer science. This fact makes designing an appealing course very difficult, in particular for non-physicists. Furthermore, in the academic community, there is consensus that quantum computers are going to be used only for specific computational tasks (e.g., in computational science), where hybrid systems - combined classical and quantum computers - facilitate the execution of an application on both quantum and classical computing resources. A hybrid system thus executes only certain suitable parts of an application on the quantum machine, while other parts are executed on the classical components of the system. To fully exploit the capabilities of hybrid systems and to meet future requirements in this emerging field, we need to prepare a new generation of computer scientists with skills in both distributed computing and quantum computing. To bridge this existing gap in standard computer science curricula, we designed a new lecture and exercise series on Hybrid Quantum-Classical Systems, where students learn how to decompose applications and implement computational tasks on a hybrid quantum-classical computational continuum. While learning the inherent concepts underlying quantum systems, students are obligated to apply techniques and methods they are already familiar with, making the entrance to the field of quantum computing comprehensive yet appealing and accessible to students of computer science.
The quantum computing curriculum developed in the Freshman Research Initiative at The University of Texas at Austin caters to students who have not yet studied advanced math and science. We lower the barrier to entry by simplifying notation and teaching through application of the concepts, only covering math methods as they become necessary. Physical motivation and simulation connect with students, and embedded examples and practice problems help cement their understanding. Through learning to program in Python and completing creative technical projects, students gain valuable, transferable skills while exploring quantum information and computing.
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.
Abstract The emerging field of Quantum Computing (QC) is novel for most K12 educators. Fundamental understandings of QC rely on advanced mathematics and physics. Therefore, why is a middle or high school introduction to QC relevant or needed? In our local area, the Pennsylvania (PA) Department of Education specifies that PA science teachers implement learning experiences that allow students to understand the nexus of how societal needs create a demand for new technologies that in turn advance scientific knowledge and impact society [1], that science teachers create opportunities for students to engage in computational thinking and mathematics within authentic science and engineering contexts [2], and that mathematics pedagogy supports students to model with mathematics and make sense of complex problems [3]. To fulfill these existing learning aims, we present a collaborative curriculum development project based on our interdisciplinary research in which we develop quantum computing methods and tools for therapeutic drug discovery. The team includes faculty from medicine, quantum computing, machine learning, and science education. The curriculum development work aims to develop resources for middle and high school (U.S. grades 6 – 12) teachers to facilitate an introduction to Quantum Information Science (QIS) and QC, embedded in existing learning aims including mathematical, scientific, and engineering practices and concepts in statistics and probability, the natural sciences, and computing. We therefore demonstrate a proof-of-concept paper for how an introduction to QC designed for teachers and students in middle and high school can be responsive to disciplinary science and math learning goals (e.g., interpreting a distribution of quantum states and decoding it into viable molecular structures) and situated in contexts of emerging quantum technologies. The educational resources provide a developmentally-appropriate approximation [4] of the drug discovery goals of the project and utilize existing cloud-based quantum infrastructure from IBM (IBM Quantum Experience), making the QIS concepts accessible and useful in the middle and high school contexts in relation to these existing discipline-based learning goals. The associated professional development (PD) will foster a pathway for teachers to engage with scientists and engineers around unfinished problems, supporting an epistemological stance toward science that aligns with interdisciplinary negotiations and model-based reasoning characteristic of ongoing scientific research. This, at its most basic level, supports teachers and students to engage with technological innovation as a form of scientific literacy. The teacher toolkit will support practitioners to visualize qubit states and facilitate learning activities that address how QC is an ongoing engineering endeavor, driven by societal needs for new technologies, and enabling QIS applications that young learners can authentically engage in. [1] Pennsylvania Technology and Engineering Standards (2020). https://www.education.pa.gov/Documents/Teachers-Administrators/Curriculum/Science%20Education/PA-Technology%20and%20Engineering%20Standards%20Grade%206-12.pdf [2] National Research Council. (2015). Guide to implementing the next generation science standards. National Academies Press. [3] National Governors Association. (2010). Common core state standards. Washington, DC. [4] Grossman, P., Compton, C., Igra, D., Ronfeldt, M., Shahan, E., & Williamson, P. (2009). Teaching practice: A cross-professional perspective. Teachers College Record, 111(9), 2055-2100.
The nascent but rapidly growing field of Quantum Information Science and Technology has led to an increased demand for skilled quantum workers and an opportunity to build a diverse workforce at the outset. In order to meet this demand and encourage women and underrepresented minorities in STEM to consider a career in QIST, we have developed a curriculum for introducing quantum computing to teachers and students at the high school level with no prerequisites. In 2022, this curriculum was delivered over the course of two one-week summer camps, one targeting teachers and another targeting students. Here, we present an overview of the objectives, curriculum, and activities, as well as results from the formal evaluation of both camps and the outlook for expanding QCaMP in future years.