## Contact information

**Instructor:**Professor Lin Lin

**Lecture hours:**TTh 3:30 pm - 4:59 pm, Evans 9 (Floor G)

**Office Hours:**By appointment. Evans 817 Evans

**Email:**linlin@math.berkeley.edu

**Course catalog:**https://classes.berkeley.edu/content/2024-spring-math-275-001-lec-001

## Course description

Quantum computers have the potential to revolutionize how we think about computing. Central to quantum computation are quantum algorithms, which often differ considerably from classical algorithms. This is an advanced graduate course course that introduces quantum algorithms essential for scientific computation. Topics include phase estimation, Hamiltonian simulation, block encoding, quantum singular value transformation, and their applications in tasks like solving linear systems, eigenvalue problems, and differential equations. The focus is on algorithmic components, design, and analysis. The quantum algorithms discussed are largely independent of the specific physical hardware on which they're implemented. Upon completing the course, students will have a solid understanding of the primary quantum algorithmic techniques for scientific computation and will be prepared to engage with technical discussions and design novel quantum algorithms in their research.

Linear Algebra (MATH 54 / PHYSICS 89 / EECS 16A, or MATH 110)

Quantum mechanics (PHYSICS 7C or PHYSICS 137A or CHEM 120A) or quantum information theory (CHEM/CS/PHYS 191, or CS 294-66)

Before the first class: please read Chapter 1 (Preliminaries of quantum computation) 1.1-1.6 of the Notes. Ensure that you either have prior knowledge of the material or can comprehend it upon reading.

https://math.berkeley.edu/~linlin/qasc/

**Prerequisites**Linear Algebra (MATH 54 / PHYSICS 89 / EECS 16A, or MATH 110)

Quantum mechanics (PHYSICS 7C or PHYSICS 137A or CHEM 120A) or quantum information theory (CHEM/CS/PHYS 191, or CS 294-66)

Before the first class: please read Chapter 1 (Preliminaries of quantum computation) 1.1-1.6 of the Notes. Ensure that you either have prior knowledge of the material or can comprehend it upon reading.

**Enrollment**Instructor consent is not needed. However, undergraduate students need to submit Sp24 Graduate Enrollment Request Form to be granted a permission. Additionally, please also fill this Google form https://forms.gle/7R8dUNwfMAU5bNtq9**Lecture notes:**https://math.berkeley.edu/~linlin/qasc/

**Resources:**- A significant portion of the course materials are related to the IPAM Tutorial (Tuesday and Wednesday) in Fall 2023 (see presentations and slides)
- Andrew Childs, Lecture Notes on Quantum Algorithms
- John Preskill's Lecture notes
- Eleanor Rieffel and Wolfgang Polak, Quantum Computing: A Gentle Introduction, 2014 ISBN-13 : 978-0262526678
- Michael Nielsen, Issac Chuang, Quantum computation and quantum information, 10th anniversary edition, ISBN-13: 978-1107002173
- Quantum Algorithm Zoo. This should be viewed as a dictionary.

## Schedule

Weekly schedule is given below, subject to
possible changes.

**NOTE: due to QIP 2024, after departmental approval, the first class will start on 1/23 instead 1/16!**

The make-up class will be held during the RRR week.The make-up class will be held during the RRR week.

## Evaluation

Throughout the semester, two written homework assignments will
be given. If a GSI is assigned to the course, these
assignments will be graded and will contribute to the final
grade, but they will not exceed 30% of the total. There is no final exam.

The primary assessment for this course will be a project, constituting at least 70% of the final grade. Please refer to this document for detailed requirements and evaluation policies.

The primary assessment for this course will be a project, constituting at least 70% of the final grade. Please refer to this document for detailed requirements and evaluation policies.