CSCI-B 475 Quantum Computing and Applications
3 credits
- Prerequisite(s): CSCI-C 343 Data Structures (or CSCI-C 310 or CSCI 36200)
- Delivery: On-Campus
- Semesters offered: Fall (Check the schedule to confirm.)
- Equivalent(s): CSCI 49000 Quantum Computing
Description
This course introduces quantum computing, including single and multiple-qubit systems; quantum states, superposition, measurements, and entanglement; and quantum gates and circuits. Students learn principles of quantum algorithms like Simon’s, Shor’s factorization, and Grover’s search. Topics may include quantum information, programming, hardware, cryptography, and machine learning applications.
Topics
Quantum mechanics introduction
- Basic principles
Linear algebra review
- Vectors, matrices, and operations
- Eigenvalues and eigenvectors
Single-qubit systems
- Quantum states and superposition
Quantum gates
- Basic operations on qubits
- Single-qubit gates, including Pauli and Hadamard
Multiple-qubit systems
- Tensor product
- Introduction to quantum entanglement
Quantum circuits
- Building and analyzing simple quantum circuits
- Multi-qubit operations and gates
Quantum measurements
- Quantum measurements and postulates
- Reading out quantum states
Quantum algorithms
- Principles
- Simon’s algorithm
- Shor’s factorization algorithm
- Grover’s search algorithm
Complexity in quantum computing
- Quantum versus classical complexity
Quantum programming and development overview
- Quantum programming languages: Qiskit, QuTiP, Q#
- Overview of frameworks: Rigetti’s Forest, Google’s Cirq
- Quantum simulation, hardware interaction, and optimization
Current quantum hardware overview
- Major platforms: Superconducting qubits, trapped ions, spin qubits
- Challenges: Scalability, error rates, quantum volume
Learning Outcomes
- Analyze the fundamental principles behind quantum mechanics and its significance in computational sciences. CS 1
- Evaluate the role of linear algebra, such as vectors, matrices, and eigenvalues, in formulating quantum systems and algorithms. CS 1
- Dissect single-qubit systems to deduce the characteristics of quantum states and superposition principles. CS 3
- Critique the function and efficiency of basic operations on qubits using quantum gates, like the Pauli and Hadamard gates. CS 1
- Break down multiple-qubit systems, assessing the intricacies of tensor products and the mechanisms of quantum entanglement. CS 3
- Design and evaluate advanced quantum circuits, extrapolating their potential in multi-qubit operations and gates. CS 3
- Investigate the principles of quantum measurements, assessing techniques for accurate reading out of quantum states. CS 1
- Dissect key principles of quantum algorithms, critically evaluating the designs of Simon’s, Shor’s factorization, and Grover’s search algorithms. CS 1
- Compare quantum and classical computational complexities, predicting scenarios where each would be advantageous. CS 1
- Develop quantum programs, optimizing them for quantum simulation and hardware interaction. CS 2
- Evaluate the strengths and weaknesses of current quantum hardware platforms, considering challenges such as scalability and error rates. CS 3
Policies and Procedures
Please be aware of the following linked policies and procedures. Note that in individual courses instructors will have stipulations specific to their course.