Lockheed Martin Corporation

Quantum Information Science & Technology Program

Program Goals in Partnership with Lockheed Martin
The University of Southern California, home of the Center for Quantum Information Science & Technology (CQIST) and the USC-Lockheed Martin Quantum Computing Center (QCC), is preparing to offer a unique interdisciplinary Master’s program that will provide strong and broad foundations in quantum information science, along with unique opportunities to learn about and engage in cutting-edge research, through a wide range of introductory and advanced courses on the theory and experimental principles of quantum information processing. The proposed Master’s program will enable students to become active participants in advanced research in quantum information science, offer new opportunities for the workforce, and will serve as a bridge for further graduate studies and research leading towards a PhD degree. Interested students will also be able to receive specialized training in operating USC’s D-Wave quantum optimization processor.

The program is designed for engineers and scientists interested in the field of quantum information science, including quantum computation and optimization, quantum information theory, quantum communication and cryptography, etc. Program participants can come from any organization or industry – employment by Lockheed Martin is not required. A background in electrical engineering, physics, or computer science is recommended.
Courses Available
Essential:
EE441 (Applied Linear Algebra for Engineering)
EE520 (Intro to Quantum Information Processing)

Optional:
EE539 (Engineering Quantum Mechanics)
EE599 (Adiabatic Quantum Computing)
EE503 (Probability for Electrical and Computer Engineers)
EE562a (Random Processes in Engineering) – EE441 and EE503 are prerequisites

If you are interested in getting started with the Electrical Engineering – Quantum Information Science and Technology Program, there are two ways to begin:

Limited Status: Eligible students can begin taking classes as early as possible via Limited Status. To review the requirements and steps to getting started, visit the Limited Status Enrollment Option.

Spring 2018 Application: To apply for Spring 2018, applicants interested in the new graduate program in Electrical Engineering – Quantum Information Science and Technology should apply for the M.S. in Electrical Engineering and email DEN@Viterbi.usc.edu to identify a specific interest in this area.

Important Note: Curriculum for the M.S. in Electrical Engineering (Quantum Information Science & Technology) and Graduate Certificate in Quantum Information Science & Technology are pending. Please refer to the USC Catalogue for official course structure and program requirements.

Core Courses:
EE441 (3 units) | Applied Linear Algebra for Engineering [Required] EE520 (3 units) | Intro to Quantum Information Processing [Required] EE503 (4 units) | Probability for Electrical and Computer Engineers [Recommended] – or –
EE562 (3 units) | Random Processes in Engineering

Advanced (Mix/Match Possible & Recommended):
EE599 (4 units) | Adiabatic Quantum Computing [Required]

QC Track (22 units)

EE514 (3 units) | Quantum Error Correction
EE599 (3 units) | Quantom Algorithms
EE599 (3 units) | Quantum Information Theory
CS599 (3 units) | Physics and Computation

Physics Track (25-26 units)

PHYS438a (4 units) | Introduction to Quantum Mechanics and its Applications – or –
EE539 (3 units) | Engineering Quantum Mechanics
CHM550 (3 units) | Theory of Open Quantum Systems
PHY720 (3 units) | Foundations of Quantum Mechanics
PHY516 (3 units) | Methods of Computational Physics
PHY660 (3 units) | Quantum Information Science and Many-Body Physics

Q Optics/Nano Track (19 units)

EE337 (3 units) | Engineering Nano-Systems
EE531 (3 units) | Nonlinear Optics
EE612 (3 units) | Science and Practice of Nanotechnology
EE599 (3 units) | Q Enhanced Technology: Metrology, Magnetometry, etc.

Additional Courses of Interest:

EE587 (3 units) | Nonlinear and Adaptive Control
Math467 (3 units) | Theory and Computational Methods for Optimization
CHM544 (3 units) | Introduction to Quantum Chemistry
CSCI570 (3 units) | Analysis of Algorithms
EE559 (3 units) | Mathematical Pattern Recognition
EE517 (3 units) | Statistics for Engineers