Class Requirements

 Topological quantum computation algorithms, Eugene Dimitrescu, ORNL

In this elective we will parse the many distinct facets of Topological Quantum Computing Algorithms. After this elective the student will be able to distinguish between i) topological materials for qubits, ii) algorithms for topological invariants, iii) topological qubits for quantum computers, iv) topological error correction, and iv) the topology of quantum algorithms.

Requirements

• Ability to tape paper together and cut with scissors safely.
• Knowing the derivative and integral of the sine, cosine, and exponential functions.
• Software 1: Python 4
• Software 2: Qiskit Open Plan (10 minutes free runtime)

Files and Materials

Day 1

Topological Quantum Compuation Algorithms Day 1 (PDF)
Day1-iPython_Files (Archive)

Day 2

Topological Quantum Compuation Algorithms Day 2 (PDF)

 Theory of Topological superconductivity Chetan Nayak, Microsoft

This course will cover the basis of topological superconductivity and the theory of its use for quantum computing. This could include Kitaev chains, superconducting nanowires, and the Fu-Kane approach to topological superconductivity in heterostructures. The state of the art of methods for characterizing topological superconducting materials and identifying Majorana fermions and ideas towards eventual topological quantum computation via braided non-abelion anyons could be reviewed.

Requirements

A background in condensed matter physics.

Software

TBD

 Topological Spin Liquids: From Simple Models to Quantum Computing, Gabor Halasz, ORNL

This theoretical course will contain two independent modules. In the first module, the students will explore quantum spin liquids in the setting of an exactly solvable model and learn how spins can fractionalize into nonlocal quasiparticles like Majorana zero modes that are fundamental building blocks of topological quantum computing. The second module will introduce students to density matrix renormalization group (DMRG) – a state-of-the-art numerical technique for studying realistic spin models, including those relevant for quantum spin liquids.

Requirements

Students should have taken at least a basic course in condensed matter physics. They should be familiar with the formalism of second quantization (i.e., creation and annihilation operators for bosonic and fermionic particles) and the quantum mechanical description of angular momentum (i.e., spin operators). Furthermore, students should have a solid understanding of fundamental linear algebra concepts, such as eigenvalues and eigenvectors, transpose and conjugate transpose operations, orthogonality, QR decomposition, and singular value decomposition.

Software

For the first module, Mathematica is required and a free 15-day trial version of Mathematica can be downloaded just before the summer school. The second module utilizes iTensors, an open-source library designed for efficient tensor network algorithms. To achieve optimal performance and support, we strongly recommend using the Julia version of ITensors. Julia is a high-level, general purpose, and open-source programming language, which necessitates its installation for this module.

Files and Course Material

Elective theory of spin liquids (Archive)

Topological spin liquids I – lecture slides & associated homework (Archive)
QIS Summer School Lecture Slides 2024 (PDF)

 Surface Science, An-Ping Li, ORNL

Surface analytical techniques are established as a powerful and mostly non-destructive method to characterize the composition, structure, dynamics, chemistry, and low-dimensional physical phenomena that occur at surfaces. In particular, scanning tunneling microscopy (STM) is indispensable for understanding electronic properties and their relationship with atomic structures. This elective class offers an overview on the capability and application of STM, and the first-hand experience in operating an STM to map surface topography, tunneling spectroscopy, and manipulating atoms or molecules.

Participants are encouraged to install an STM simulator to explore the STM control system as if it were connected to a real STM operating on a Si(111) surface. The simulator is available for free download.

Files and Course Material

Surface Science Class for NQI Summer School_2024 (PDF)

 Quantum Generative Models: From Born to Boltzmann and Back Again, Kathleen Hamilton, ORNL

The goal of this elective is to provide students the opportunity to build and train quantum generative models using data-driven training of Quantum Circuit Born Machines, or energy-based training of other quantum generative models such as Boltzmann machines). Quantum models will be used to generate samples from classical data or quantum data distributions.

Requirements

General familiarity with Python scripting, including setting up a virtual environment and installing packages. Required packages: Pennylane version>0.37.0 and required dependencies.

Prior familiarity with variational algorithms is helpful as is knowledge of machine learning methods (e.g. gradient descent).

Bring a laptop for running simulations, software TBD.

 QICK board – Qubit Control and Readout with the Quantum Instrumentation Control Kit, Sara Sussman, FNAL and team

In this elective, students will learn how to control and read out superconducting qubits with RF/microwave pulses. We will do this using the open source Quantum Instrumentation Control Kit (QICK), which was developed by researchers at QSC and collaborators, and is now widely used. Students will gain understanding of the QICK hardware/firmware/software stack before participating in hands-on demonstrations of qubit control and readout with QICK boards.

Requirements

The only background necessary is the “QICK & superconducting qubits” lecture given earlier in the QSC summer school. Other engineering, math, computer science or physics background is helpful but is not necessary.

Files and Course Material

Pre-Reading for QICK Lecture:
A practical guide for building superconducting quantum devices:  (APS)  (arXiv)
QICK Labs (Github)
Multiple Choice Questions (Google Sheets)

 Neutron scattering for Quantum Materials, Alan Tennant, ORNL

The course will cover the basics of neutron scattering for quantum materials to understand their quantum phases and dynamics. This includes the principals of neutron scattering and instrumentation, how measurements are planned and performed, as well as the analysis and interpretation of data.

Requirements

The course is self-contained but requires a background in materials and/or physical sciences. The exercises will be run on the analysis cluster at the Spallation Neutron Source. The students need a computer with a web browser. They do not need to download software.

 Nano-fabrication for Quantum Information Science Applications, Stephen Jesse, ORNL

In this course we will discuss some of the important principles, approaches, and problems with using and adapting nanofabrication approaches, which were originally developed for large scale microelectronics device manufacturing, to quantum information sciences. This class will include both lecture and hands-on demonstrations (in a classroom, not in a clean room). The content is primarily intended for those with little to no experience in a clean room, but would like to have a better understanding of the steps that are part of turning great ideas and/or materials into devices.