SIGCSE 2020: Programming Quantum Computers

There is a book published in 2006 by Vazirani (with Dasgupta and Papadimitriou) that is unique among its kind. It's one of the few books on algorithms (if not the only one) that has a chapter dedicated to quantum algorithms that blends in so well with the classical material that precedes it. The book is so well thought out that it ends where it starts but on a much higher plane. It opens up new realms of exploration with generosity and explicitly asks at the end (this was 2006, after all): "Can quantum computers be built?" Over the last couple of years the many software and hardware quantum platforms now accessible in the cloud have moved the emphasis to a slightly different aspect. It now seems imperative to start teaching this new technology to undergraduates to raise a new generation of computer scientists to develop it further. As was already pointed out there's a real shortage of talent in quantum computing, which brings up an even more stringent challenge: how do we go about creating a new generation of teachers (or retraining the current one) so they can be quickly able to function at that level? This is a full day event especially designed for an audience of dedicated, innovative and motivated undergraduate CSCI teachers, with or without prior experience in quantum computation and quantum information, as part of a series of events dedicated to quantum computing and quantum programming at SIGCSE 2020.

Come to hear about the new reality of quantum hardware and the many extremely accessible online software platforms for quantum computation. And as this topic is making its way down through the curriculum slowly but steadily from the PhD level to advanced (often cross-listed) graduate courses in Physics to (ultimately) undergraduate courses in CSCI, one can even envision a curriculum with courses in (quantum) hardware and (quantum) engineering. Those courses can only be developed by the faculty that are convinced and aware of this impending reality. Come to learn from our world-class panel of experts and subsequently stay in touch with them (for the long term). In the short term we're trying to give the interested undergraduate computer science faculty a set of tools and relevant information so they can start teaching this topic properly in the classroom right away.

Updated program (as of March 4, 2020):

08:00-08:30 Setup/Breakfast

08:30-09:20 Introduction to Quantum Computing (William D Oliver) MIT xPro QCF Program [ Course 1 | Course 2 ]

09:20-09:30 Break

09:30-10:20
From Classical to Quantum Programming We start by situating quantum computing and its importance by explaining how the marriage of quantum mechanics and computer science first envisioned and popularized by Feynman and others has created an awkward, but opportune, moment. The embarrassing dilemma was concisely described by Aaronson as follows. It can be shown that only two of the following three statements can be true: (a) textbook quantum mechanics is correct; (b) there does not exist an efficient classical factoring algorithm; and (c) the extended Church-Turing thesis that probabilistic Turing machines can efficiently simulate any physically realizable model of computation is correct. So at least one of these statements must be false, in spite of existing overwhelming evidence supporting each one of them. After motivating and engaging lectures on the topic above, our technical starting point is classical reversible computation including the Controlled NOT and Toffoli gates and their completeness relative to conventional irreversible circuits using AND, OR, and NOT gates. The next technical step (superpositions and probability) is still classical and also readily accessible to our undergraduate students and it consists of introducing a probabilistic model of computation and its relation to (classical) superpositions: programs manipulate entire distributions and measurements sample the distributions. Classical analogues of entanglement is our next step. This is again a classical notion only requiring an understanding of correlations. It is however powerful enough to model 'quantum' protocols like teleportation. At this point, we would have introduced all the major concepts needed for quantum computation without overwhelming the students with new foreign notations, only expanding their classical understanding with perspectives, and relating all the new concepts to familiar ones to enhance understanding and retention. The next module is a discussion of full-fledged computation vs. special-purpose simulation. The topic is crucial for understanding the state of the art in the quantum world but is not inherently a quantum concept: it can be studied in a classical setting to again enhance understanding. The students at this point are ready to engage in the mysteries of quantum supremacy and entanglement in Nature. They are also ready to program interesting quantum algorithms on available platforms (e.g., Qiskit, Pyquil, QCEngine, Q#, etc.). After gaining experience with quantum programming at the circuit level, we will focus on high-level programming languages that are more resonate with 'quantum thinking.' Advanced students can further explore uses of Grover's algorithm in graph algorithms, machine learning applications etc.
(Amr Sabry and Gerardo Ortiz)

10:20-10:30 Break (Refreshments)

10:30-11:20 Fundamentals of Quantum Programming (Eric Johnston)

11:20-11:30 Break

11:30-12:20 Introduction to IBM Qiskit (Daniel Koch)

12:20-13:00 LUNCH (boxed, menu)

13:00-13:50 Qiskit Blocks for Educators (James Weaver)

13:50-14:00 Break

14:00-14:50 Anatomy of a Photonic QPU (Eric Johnston)

14:50-15:00 Break (Refreshments)

15:00-15:50 Quantum Programming with Python and Q# (Sarah C Kaiser)
(Replaced last minute w/ Teaching Quantum Computing ... by Mariia Mykhailova and Krysta Svore.)

15:50-16:00 Break

16:00-17:00 QBism: The Future of Quantum Physics (Hans Christian von Baeyer )

Additional information (like an abstract of sorts) for each session to be posted here soon.