E: minnichlab@gmail.com

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Minnich Lab

1200 E. California Blvd, M.C. 104-44

Pasadena, CA 91125

 

APh 250/ME 201:Physics on near-term quantum computers

 Quantum computers with tens of physical qubits and high gate fidelities will become available in the next few years. This class will explore how this new type of computing device could be used to address research questions in physics. Specific topics to be covered include:

  • Fundamentals of quantum computing and key algorithms

  • Translating states and Hamiltonians to qubits and Pauli gates

  • Algorithms to find ground states, including phase estimation, variational methods, imaginary time evolution, and quantum annealing

  • Algorithms for quantum dynamics

  • Noise and error mitigation strategies on near-term devices

Prerequisites: PH 125, CH 125 or equivalent graduate quantum mechanics course. ACM 104 or equivalent linear algebra course. Some familiarity with fundamental concepts of quantum computing is beneficial. 
 

Class notes

Lecture 1:   Quantum Simulation04/01/2019

Lecture 2:   Efficient Quantum Simulations 04/03/2019

Lecture 3:   Overview of Computational Complexity 04/05/2019

Lecture 4:   Review of Linear Algebra and Quantum Mechanics 04/08/2019

Lecture 5:   Review of Quantum Computing 04/12/2019

Lecture 6:   Second quantization 04/22/2019

Lecture 7:   Jordan-Wigner transform 04/26/2019

Lecture 8:   Brayvi-Kitaev transform 05/01/2019

Lecture 9:   Iterative Phase Estimation 05/03/2019

Lecture 10: Variational Quantum Eigensolver 05/06/2019

Lecture 11: Variational imaginary time evolution 05/08/2019

Lecture 12: QITE, QLancozs, QMETTs 05/13/2019

Lecture 13: Inelastic neutron scattering on quantum hardware 05/20/2019

Lecture 14: Density matrix dynamics 05/22/2019

Lecture 15: Electron-phonon coupling on quantum computer 5/29/2019

Lecture 16: Resources estimate 5/31/2019

Lecture 17: Error mitigation 5/31/2019

Lecture 18: Quantum annealing and adiabatic quantum computation BONUS

In class tutorial files: 04/24/2019

Homework 1: 04/05/2019

                        Solution 1

Homework 2: 04/12/2019

                        Solution 2

Homework 3: 04/19/2019

                        Solution 3

Homework 4: 05/01/2019

                        Files required

                        Solution 4

                        Github link to solution for qns 2

Homework 5: 05/20/2019

                        Files required

                        Github link to solution