A227
Course Coordinator: 
Jason Twamley
Quantum Engineering – Simulation and Design
Description: 


Target Students
This course is targeted to students with a background in physics or any relevant discipline who have good knowledge of quantum mechanics and who wish to develop skills in the computational modelling of quantum machines. Advanced experience with Python is not required but some familiarity and competence with Python (such as taking the Python boot-camp) is required.


Description
This course explores the topic of integrated quantum devices. Such devices bring together different types of quantum systems which provide new functionality not possible within an individual quantum system. Such devices are used for fundamental quantum mechanic studies, quantum sensing, quantum communication and quantum computing. During the course students will develop “engineering” type skills towards learning how to design and model – theoretically and computationally, various types of composite quantum devices. Systems to be studied include integrated photonic with atomic, condensed matter and motional atomic systems including cavity quantum electrodynamics, cavity optomechanics, Nitrogen vacancy defects in diamond and levitated quantum systems.

The course consists of an initial section consisting of weekly lectures and computer labs. These labs are the central component of the course and during these labs students will learn computational techniques to study the properties of integrated quantum devices using python. The second section of the course consists of journal clubs and a final computational project with a poster presentation.
 

Aim: 
Students who complete this course will be able to: a) Analyse and computationally model interacting quantum machines to uncover their unique quantum behaviours Assessment: One take home computational assignment and a final computational project b) Discuss and critically analyse recent scientific articles which focus on quantum machines Assessment: Presentation of a recent published paper of their choice to the class within a weekly journal club c) Communicate their research achievements in quantum engineering to formal and informal audiences. Assessment: Communication of their final computational project via the creation of a poster and an in-person poster explanation at a final course poster session
Course Content: 

Each week consists of both lecture and computational lab work.


• Week 1: Introduction to quantum optics and the QuTip computational Python package, pure quantum states, two level states visualized on the Bloch sphere, harmonic oscillator states visualized using Wigner functions
• Week 2: Dynamics of quantum systems: Time evolution of nonlinear quantum oscillators, dynamics of spins and simulation of the Stern Gerlach experiment
• Week 3: More advanced quantum optical systems: Introduction to cavity QED, derivation and simulation of the Jaynes Cummings/Rabi system, Photon Blockade, Collapse and revivals.
• Week 4: Study of open quantum systems including decoherence:
Study of the Lindblad master equation for a Qubit system
• Week 5: Application study: Two-level atomic Landau-Zener transitions and cavity-QED Photon-number Quantum Non-Demolition experiment
• Week 6: Introduction to optomechanical quantum systems: intro to optical cavities, derivation of Langevin equations and linearized Hamiltonian for optomechanical systems.
• Week 6: Cooling to the quantum ground state: review of optomechanical cooling, experimental results and theory/simulations.
• Week 7: More advanced analysis of optomechanics: coupled moment dynamics, study of the generation of entanglement between two spins in a mechanical system.
• Week 8: Review of magneto-mechanical systems. Final Project selections/ Journal Club Starts
• Week 9: Introduction to quantum sensing/parameter estimation. Journal Club and Project work.
• Week 10: Invited short seminar : Journal Club and Project Work.
• Week 11: Invited short seminar : Journal Club and Project Work.
• Week 12: Preparation of Posters reporting on Project Work.
• Week 13: Poster session on Project Work, involving all students and Zoom invited guests and other OIST faculty

Course Type: 
Elective
Credits: 
2
Assessment: 
[30%] One mid-course take home computational assignment (individual work) [30%] Final project assignment (group work) [20%] Presentation at a journal club [20%] Attendance at each weekly computational lab.
Text Book: 
Introduction to Quantum Optics https://www.amazon.co.jp/-/en/Christopher-Gerry/dp/052152735X
Quantum Optics: An Introduction https://www.amazon.co.jp/dp/0198566735/ref=cm_sw_em_r_mt_dp_AW0YM4GHBF3WXK6N77CY
Qutip: A quantum physics toolbox for Python. http://qutip.org
Prior Knowledge: 

Undergraduate quantum mechanics (full year), experience is pre-required. This includes good knowledge of the quantum matrix mechanics for spin, Schrodinger equation (stationary and time dependent), and the operator treatment of the quantum harmonic oscillator including creation and annihilation operators. Desirable pre-knowledge includes cavity quantum electrodynamics and atoms interacting with electromagnetic radiation. Python boot-camp is required but no other Python skills are required.