Advanced topics chosen by the instructor. The content of this course changes, as in the case of seminars.

Quantum computers promise to revolutionize how we think about computing in the future. At the core of quantum computation are quantum algorithms, whose structure often differs considerably from that of classical algorithms. This course introduces and surveys quantum algorithms that are particularly relevant for scientific computation. Topics covered include amplitude amplification, phase estimation, Hamiltonian simulation, solving linear systems, and "modern" quantum linear algebra algorithms based on the language of block-encoding. Some of these algorithms will be implemented on actual quantum hardware using qiskit. This course will also give a glimpse of recent topics such as hybrid variational quantum computation, quantum supremacy, quantum machine learning, and quantum algorithms for solving differential equations. The scope of the quantum algorithms covered will be mostly agnostic to physical hardware they are implemented on, and range from those that can be implemented in near-term noisy quantum computers to those for future fault-tolerant quantum computers. Upon successful completion of the course, the students can have a good understanding of main quantum algorithmic primitives and design techniques for scientific computation, and continue to follow technical talks in this subject and to design new quantum algorithms in their own research. **Prerequisite**: Linear Algebra (MATH 54 / PHYSICS 89 / EECS 16A), AND either quantum mechanics (PHYSICS 7C or PHYSICS 137A or CHEM 120A) or quantum information theory (CHEM/CS/PHYS 191) * Previous experience with CS 294-66 (Quantum computing) would be ideal, and you should still be able to get something interesting out of the course. * Basic knowledge of python programming will be useful for understanding the numerical demonstration of quantum algorithms using IBM Qiskit https://qiskit.org/. Enrollment: If you are an undergraduate student, please fill this google form first https://forms.gle/5oR5NJ4RxDGLW2rr8

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