Quantum Computing: Programs and Systems will be structured around reading and discussing several foundational research papers in realizing quantum computers. Students will also complete programming assignments to implement algorithms in open-source quantum frameworks. The goal of the course is to bring students up-to-speed on recent developments in realizing quantum computers, which will be a strong foundation for pursuing research or to be a subject expert in industry.
Basic course information
- Canvas: https://rutgers.instructure.com/courses/140409
- In-person attendance: We meet Mondays and Wednesdays 7pm – 8:20pm in CoRE 101
- Virtual attendance: Class will also be streamed via Zoom; recording will be posted after class
Instructor information
- Yipeng Huang
- Email: yipeng.huang@rutgers.edu
- Students can expect a 2-day turnaround from me on emails.
- Office hours: Wednesdays at 3pm via Zoom
- Please see Canvas site for office hour Zoom info.
- Office: CoRE 317
Prerequisites
- Courses in or experience in Python programming, computer architecture, algorithms, linear algebra, probability.
- Taking first an introductory class in quantum computing such as Rutgers ECE’s Quantum Computing Algorithms (Prof. Emina Soljanin) or Rutgers Physics’s An Introduction to Quantum Computing (Prof. Steve Schnetzer) is ideal but not required.
- Senior undergraduates interested in quantum computing have successfully taken this class in the past.
Course components
- We will discuss a mix of introductory, foundational, and recent research articles on realizing quantum computing systems.
- For a handful of the most contentious topics in quantum computing, we will have debates via student presentations representing various viewpoints in the latest research.
- Participation in reading discussions on the forum, oral presentations, and completion of the short programming assignments will be important.
Grading rubric
- 50% programming assignments; including: QAOA implementation in Google Cirq and VQE implementation in Qiskit.
- 50% student presentation of reading assignments.
- For both programming assignments and presentations, full marks will be given for student work that demonstrate evaluation and synthesis of concepts in programming and using quantum systems. Detailed rubrics for assignments will be released before each assignment.
- This class has no final exam.
Rutgers CS diversity and inclusion statement
Rutgers Computer Science Department is committed to creating a consciously anti-racist, inclusive community that welcomes diversity in various dimensions (e.g., race, national origin, gender, sexuality, disability status, class, or religious beliefs). We will not tolerate micro-aggressions and discrimination that creates a hostile atmosphere in the class and/or threatens the well-being of our students. We will continuously strive to create a safe learning environment that allows for the open exchange of ideas and cherished freedom of speech, while also ensuring equitable opportunities and respect for all of us. Our goal is to maintain an environment where students, staff, and faculty can contribute without the fear of ridicule or intolerant or offensive language. If you witness or experience racism, discrimination micro-aggressions, or other offensive behavior, you are encouraged to bring it to the attention to the undergraduate program director and/or the department chair. You can also report it to the Bias Incident Reporting System http://inclusion.rutgers.edu/report-bias-incident/
Syllabus
| Date | Theme | Topic | Reading assignment |
|---|---|---|---|
| Wed. 9/1 | Fall Semester Begins | ||
| Wed. 9/1 | Introduction [slides] | Preview of the syllabus, course objectives & activities. | “Quantum Computing in the NISQ era and beyond” by Preskill |
| Wed. 9/8 (Monday classes) | QC fundamentals: one qubit [slides] | 1. Universal classical computing 2. A single qubit: the Hadamard gate, superposition, interference, measurement 3. Multiple qubits: the tensor product | |
| Mon. 9/13 | QC fundamentals: multiple qubits [slides] | • Measurement • Tensor products of state vectors and unitary matrices • Deutsch-Jozsa algorithm | |
| Wed. 9/15 | QC fundamentals: Deutsch-Jozsa programs and systems [slides] | • Problem description • Circuit diagram and what is in the oracle • Demonstration of Deutsch-Jozsa for the n = 1 case • Deutsch-Jozsa programs and systems | “Quantum computing 40 years later” by John Preskill “The Limits of Quantum Computers” by Scott Aaronson “Recent progress in quantum algorithms” by Bacon and van Dam |
| Mon. 9/20 | QC fundamentals: Deutsch-Jozsa programs and systems [slides] Programming frameworks 1: Cirq [slides] | 1. The Deutch-Jozsa algorithm circuit 2. The state after the first set of Hadamards 3. The state after applying oracle U 4. Lemma: the Hadamard transform 5. The state after the final set of Hadamards 6. Probability of measuring upper register to get 0 7. A demonstration in Google Cirq | |
| Wed. 9/22 | QC fundamentals: entanglement [slides] | 1. Orthogonal measurement bases 2. Entangled states: Bell states 3. Superdense coding 4. Quantum teleportation | |
| Mon. 9/27 | QC fundamentals: teleportation and dense coding [slides] | 1. Entangled states: Bell states 2. Quantum teleportation 3. Superdense coding 4. Channel capacity of dense coding 5. Dense coding with multipartite qubit entanglement | |
| Wed. 9/29 | QC fundamentals: dense coding, Bell’s inequality [slides] | 1. The lens we take when studying quantum computing 2. Dense coding with multipartite qubit entanglement 3. Dense coding with high-dimensional qudit entanglement | |
| Mon. 10/4 | QC fundamentals: Hardy’s paradox / CHSH / Bell’s inequality [slides] | 1. Quantum computing fundamentals: Hardy’s paradox / CHSH / Bell’s inequality 2. Dense coding with high-dimensional qudit entanglement 3. The lens we take when studying quantum computing Bell inequality testing protocol / game | |
| Wed. 10/6 | Shor’s factoring algorithm: the classical part [slides] | 1. The factoring problem 2. The classical part: converting factoring to order finding / period finding | |
| Mon. 10/11 | Shor’s factoring algorithm: the quantum part [slides] | The quantum part: period finding using quantum Fourier transform 1. Calculate modular exponentiation 2. Measurement of target (bottom, ancillary) qubit register 3. Quantum Fourier transform to obtain period | |
| Wed. 10/13 | Shor’s factoring algorithm: quantum Fourier transform [slides] | The quantum part: period finding using quantum Fourier transform 1. Measurement of target (bottom, ancillary) qubit register 2. Quantum Fourier transform to obtain period | |
| Mon. 10/18 | Wrapping up Shor’s and QFT; quantum approximate optimization algorithm [slides] | QAOA for MAX-CUT: general strategy 1. Each node in n nodes of the MAX-CUT graph corresponds to one of n qubits in the quantum circuit. 2. The state vector across the qubits |ψ⟩ encodes a node partitioning σ ∈ {−1, +1}^n. 3. Put the initial state vector |ψs⟩ in a superposition of all possible node partitionings. | |
| Wed. 10/20 | NISQ algorithms: QAOA [slides] | NISQ (Noisy Intermediate Scale Quantum) vs FTQC (Fault Tolerant Quantum Computation) • NISQ algorithms: attributes, examples Quantum Approximate Optimization Algorithm for MAX-CUT 1. The MAX-CUT problem 2. Encoding the vertices 3. Encoding the edges 4. A simulated annealing schedule | “A Quantum Approximate Optimization Algorithm” by Farhi, Goldstone, and Gutmann “Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor” by Google AI Quantum and Collaborators |
| Mon. 10/25 | NISQ algorithms: QAOA [slides] | Evaluation of QAOA: depth, width, problem instance, optimization method, generalizations | |
| Wed. 10/27 | A systems view of quantum computer engineering [slides] | 1. Fault-tolerant, error-corrected quantum computers for algorithms 2. Programming: High level languages to aid algorithm discovery 3. Programming: Facilities for program correctness (debuggers, assertions) 4. Programming: Intermediate representations that aid analysis 5. Simulation: Support to validate and design next-gen quantum computers 6. Architecture: Standard instruction set architectures 7. Architecture: Memory hierarchy to store quantum data Microarchitecture: Abundant and reliable quantum devices | “Programming languages and compiler design for realistic quantum hardware” by Chong, Franklin, and Martonosi “Quantum Computer Systems for Scientific Discovery” report from 2019 NSF workshop on Quantum Computing “Challenges and Opportunities of Near-Term Quantum Computing Systems” by Corcoles et al. “Quantum Computer Architecture: Towards Full-Stack Quantum Accelerators” by Bertels et al. |
| Mon. 11/1 | QC languages: stabilizers [slides] | General strategy for using stabilizers to simulate quantum circuits consisting of only Clifford gates 1. Start with N qubits with initial state |0…0⟩. 2. Represent the state as its group of stabilizers. 3. When simulating the quantum circuit, decompose the Clifford gates to stabilizer gates {CNOT, H, P}. 4. Apply each of the stabilizer gates to the stabilizer representation. | “The Heisenberg Representation of Quantum Computers” by Gottesman |
| Wed. 11/3 | QC languages: tensor networks [slides] | 1. Feynman path sum 2. Treewidth controls difficulty of simulation with a classical computer | “Quantum Tensor Networks in a Nutshell” by Biamonte and Bergholm “Lectures on Quantum Tensor Networks: a pathway to modern diagrammatic reasoning” by Biamonte |
| Mon. 11/8 | QC languages: density matrices, noise [slides] | ||
| Wed. 11/10 | QC languages: tensor network simplification [slides] | A. Tensor networks Tensors Tensor networks Tensor network contraction Tensor network contraction order B. Unification of stabilizers and tensors Example: inverting a CNOT Splitting a CNOT into network of two rank-3 tensors Tensor simplification rules Automatic simplification of circuits | |
| Mon. 11/15 | QC languages: logical abstractions [slides] | Our toolchain: Bayesian network knowledge compilation for noisy quantum circuit simulation and sampling 1. Noisy quantum circuits to Bayesian network 2. Bayesian networks to conjunctive normal form (CNF) 3. CNF to arithmetic circuit (AC) 4. Exact inference on AC for quantum circuit simulation 5. Gibbs sampling on AC to sample from final wavefunction | “Closing In on Quantum Error Correction” by Monroe |
| Wed. 11/17 | NISQ algorithms: quantum chemistry [slides] | 1. Motivation for quantum chemistry 2. Ground state estimation 3. Simplification of problem representation 4. Quantum computing for quantum chemistry 5. Qubit representation of orbitals | “Quantum Chemistry in the Age of Quantum Computing” by Cao et al. “Towards quantum chemistry on a quantum computer” by Lanyon et al. “A variational eigenvalue solver on a photonic quantum processor” by Peruzzo at al. “Hartree-Fock on a superconducting qubit quantum computer” by Arute et al. |
| Mon. 11/22 | NISQ algorithms: VQE on Qiskit | In-class lab on IBM Qiskit quantum framework | https://qiskit.org/textbook/ch-applications/vqe-molecules.html |
| Wed. 11/24 – Sun. 11/28 | Thanksgiving Recess | ||
| Mon. 11/29 (Wednesday classes) | NISQ algorithms: VQE on Qiskit [slides] | 1. LiH ground state energy estimation at known bond length 2. Hydrogen molecule bond length 1. determination by finding ground state energy minimum 3. Plotting the LiH energy curve | “Full-Stack, Real-System Quantum Computer Studies: Architectural Comparisons and Design Insights” by Murali et al. “Not All Qubits Are Created Equal: A Case for Variability-Aware Policies for NISQ-Era Quantum Computers” by Tannu and Qureshi “A Quantum Computational Compiler and Design Tool for Technology-Specific Targets” by Smith and Thornton “Extracting Success from IBM’s 20-Qubit Machines Using Error-Aware Compilation” by Nishio et al. |
| Wed. 12/1 | NISQ algorithms: VQE on Qiskit [slides] | 1. Motivation for quantum chemistry 2, Ground state estimation 3, Simplification of problem representation 4. Qubit representation of orbitals 5. Variational quantum eigensolver 6. VQE ansatz | “Open Quantum Assembly Language” by Cross et al. “Qiskit Pulse: Programming Quantum Computers Through the Cloud with Pulses” by Alexander et al. “eQASM: An Executable Quantum Instruction Set Architecture” by Fu et al. “The electronic interface for quantum processors” by van Dijk, Charbon, and Sebastiano |
| Mon. 12/6 | QC systems: architecture [slides] | Challenges of quantum computer architecture 1. Scheduling 2. Qubit mapping 3. Topological constraints resolving (The SWAP gate decomposes to three CNOT gates) 4. Physical-gate decomposition | “The Physical Implementation of Quantum Computation” by DiVincenzo Ladd et al., Quantum Computing “Experimental comparison of two quantum computing architectures” by Linke et al. “A Quantum Engineer’s Guide to Superconducting Qubits” by Krantz et al. “Towards Efficient Superconducting Quantum Processor Architecture Design” by Li, Ding, and Xie |
| Wed. 12/8 | QC systems: ion traps [slides] | A. Anatomy of a quantum computer 1. Essential hardware components of a quantum computer 2. DiVincenzo’s criteria B. Device technologies 1. Trapped ion quantum computers 2. Superconducting quantum computers 3. Other technologies | “The trapped-ion qubit tool box” by Ozeri “Architecting Noisy Intermediate-Scale Trapped Ion Quantum Computers” by Murali et al. |
| Mon. 12/13 | QC systems: ion traps, superconductors [slides] | A. Anatomy of a quantum computer 1. Essential hardware components of a quantum computer 2. DiVincenzo’s criteria B. Device technologies 1. Trapped ion quantum computers 2. Superconducting quantum computers 3. Other technologies | |
| Mon. 12/13 | Regular Classes End | ||
| Tue. 12/14 | Reading Day | ||
| Wed. 12/15 | Reading Day | ||
| Thu. 12/16 | Fall Exams Begin | ||
| Thu. 12/23 | Fall Exams End |
Resources
Health and safety requirements for Fall 2021
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