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Learn domain-specific quantum algorithms and how to run them on present-day quantum hardware.
After a course session ends, it will be archived.
This course is part III of the series of Quantum computing courses, which covers aspects from fundamentals to present-day hardware platforms to quantum software and programming.
The goal of part III is to discuss some of the key domain-specific algorithms that are developed by exploiting the fundamental quantum phenomena (e.g. entanglement)and computing models discussed in part I. We will begin by discussing classic examples of quantum Fourier transform and search algorithms, along with its application for factorization (the famous Shor’s algorithm). Next, we will focus on the more recently developed algorithms focusing on applications to optimization, quantum simulation, quantum chemistry, machine learning, and data science.
A particularly exciting recent development has been the emergence of near-intermediate scale quantum (NISQ) computers. We will also discuss how these machines are driving new algorithmic development. A key aspect of the course is to provide hands-on training for running (few qubit instances of) the quantum algorithms on present-day quantum hardware. For this purpose, we will take advantage of the availability of cloud-based access to quantum computers and quantum software.
The material will appeal to engineering students, natural sciences students, and professionals whose interests are in using as well as developing quantum technologies.
Attention:
Quantum Computing 1: Fundamentals is an essential prerequisite to Quantum Computing 2: Hardware and Quantum Computing 3: Algorithm and Software. Learners should plan to complete Fundamentals (1) before enrolling in the Hardware (2) or the Algorithm and Software (3) courses.
Alternatively, learners can enroll in courses 2 or 3 if they have solid experience with or knowledge of quantum computing fundamentals, including the following: 1) postulates of quantum mechanics; 2) gate-based quantum computing; 3) quantum errors and error correction; 3) adiabatic quantum computing; and 5) quantum applications and NISQ-era.
Applied Quantum Computing I: Fundamentals
Undergraduate linear algebra, differential equations, physics, and chemistry.
Quantum Fourier transform and search algorithms
Hybrid quantum-classical algorithms
Quantum annealing, simulation, and optimization algorithms
Quantum machine-learning algorithms
Cloud-based quantum programming
Who can take this course?
Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.
Who can take this course?
Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.
