Quantum Computing Algorithms for Cybersecurity, Chemistry, and Optimization is a four-week online course that builds on the foundation of Introduction to Quantum Computing and uses it to probe more deeply applications of quantum computing in several important areas.
The course reviews the quantum fundamentals introduced in the first course and then applies the knowledge and skills to explore real-world examples of quantum computing—and its future potential—in cybersecurity, chemistry, and process optimization through investigations of quantum cryptography, quantum simulation, and quantum optimization.
This course is well suited for professionals and leaders in business, government, and technology that need to get an understanding of the business and technical implications of quantum computing. Given that quantum computing is in its earliest stages as an industry, any interested participant who would like to lead the quantum revolution within their field is encouraged to join this course to get a leading edge on this technology. (It is highly recommended that participants have a basic knowledge of vector and matrix multiplication as linear algebra is at the core of quantum computing algorithms. For more information about prerequisite knowledge, please visit this FAQ article.)
Due to the technical nature of the course, it is strongly recommended that learners possess basic knowledge of linear algebra fundamentals, especially vector and matrix multiplication methods. Linear algebra is at the core of quantum computing algorithms. For more information about prerequisite knowledge, please visit this FAQ article.
The coursework features video lectures, real-world case studies, interactive projects, practice activities with immediate feedback, as well as a self-reflection with peer-review. You will also will utilize the IBM Quantum Experience—a real quantum computer—to implement and run Grover’s Algorithm for quantum search.
A faculty-led webinar will allow learners the opportunity to ask course-related questions and allow instructors to expand on the course content, referencing examples from their own experience advancing the field of quantum computing.
In this course, learners will investigate some of the quantum algorithms used in cybersecurity, chemistry, and optimization, at a high level—without taking into consideration practical issues such as noise—in order to develop an understanding of how the algorithms function and how their applications can be realized. You explore the potential of quantum computing in the fields of search optimization and chemistry simulation. In particular, quantum computing is emerging as a uniquely suited tool for chemistry simulations, given the complexities of interactions between molecules and environments.
In the first week of this course, learners will review quantum computing fundamentals and discuss the fundamentals of modern cryptography and its reliance on the classically hard, one-way function of prime factorization. You will then study the workings of Shor’s Algorithm at both an intuitive and technical level—with a deep dive from Peter Shor himself—to discover how it can perform those operations in a much more efficient manner in order to effectively break the foundations of modern cryptography.
In the second week, learners will investigate how quantum mechanics not only provides tools for compromising existing secure communication protocols, but provides possibilities to enhance the security of existing and future communication channels, learning about quantum key distribution and the possibility and applications of generating true randomness.
In the third week of the course, learners will further explore quantum simulation, studying various algorithms and approaches to resolving the problems of quantum simulation—like phase estimation. This week will include with a specific example of the applications of quantum simulation in quantum chemistry, and a case study on the variational quantum eigensolver protocol—utilizing both classical and quantum computers in order to balance the unique capabilities and weaknesses of existing, noisy quantum computers to optimize performance and capability.
The fourth week of the course will narrow the focus to quantum optimization. Learners will learn about adiabatic quantum computing and quantum annealing as an alternative paradigm to gate-model quantum computing, and explore efforts to identify optimization approximation methods suited for the unique challenges of quantum computing. Finally, you will take a deep dive into quantum search capabilities, learn to code a version of Grover's Algorithm for quantum search, and implement it on the IBM Quantum Experience computer. Please review the Course Schedule for more details.
You will expand your understanding of the current approaches to realizing quantum computing, as well as some of the specific fields and types of problems where quantum computers are best poised to deliver disruption and supremacy in the near future. You will understand the technology requirements for quantum computers to be able to run realistically large quantum algorithms and gain firsthand experience implementing and using quantum algorithms for unstructured search.