Phys 245 - Quantum Computation
Physics
Quantum circuits, quantum Fourier transform, quantum algorithms, physical implementations and Jaynes-Cummings model.

QNT SCI 402 - Quantum Information
Physics

Density matrix evolution, decoherence, characterization of quantum states, distance measures between quantum states, fidelity, quantum error correction, entropy and information, and quantum information theory.

QNT SCI 403 - Theory of Quantum Devices
Physics

Study of advanced theories, with some elements of quantum transport and advanced many-body physics. Introduction and comparison of different types of physical building blocks available for quantum computing. Addresses practical issues, such as scalability and comparison between different physical platforms and associated devices.

QNT SCI M205 - Quantum Programming (crosslisted with COM SCI 238)
Computer Science

History of quantum computing; notion of qubit; four postulates that provide interface to quantum mechanics; concepts of quantum circuit and universal gate set; quantum teleportation; superdense coding; no-cloning theorem; suite of fundamental quantum algorithms including Shor's algorithm, Grover's algorithm, and quantum approximate optimization algorithm; several quantum programming languages and how they compare; quantum simulators; quantum compilers; quantum error correction; quantum advantage. Students implement several quantum algorithms in multiple languages and run them on both simulators and quantum computer.

COM SCI 239 - Quantum Algorithms
Computer Science

Covers quantum algorithms including quantum machine learning, Hamiltonian simulation, and quantum walk; quantum complexity classes including BQP, QMA, and QIP; quantum verification including instrumented simulation and quantum abstract interpretation; quantum languages including Silq; and big theorems in quantum computing including Gottesman-Knill.

QNT SCI 410-412 - Lab Modules
Physics

QNT SCI 410-12 are a series of Lab Modules to be completed by all MQST students. Each quarter, each student and their lab partner will select five laboratory experiments from the experiment menu, schedule dates for use of the equipment, and complete each project.

QNT SCI 597 - Capstone Project
Physics

This class will occur during Summer Sessions and consist of a nominally 9-week research experience, either in the group of a UCLA professor (for example, the faculty members of the UCLA Center for Quantum Science and Engineering) or through an approved internship at a QST-related company. During the final week of the session, students will prepare and present their research before a committee and be evaluated in a final oral exam.

BIOMATH 204 - Biomedical Data Analysis

Modern scientific research and quality and quantity of data have been greatly affected by rapid expansion of statistical computing software. Problem-oriented study of latest methods in applied statistical data analysis and its use arising in laboratory and clinical research.

CHEM C115AB - Quantum Chemistry

Designed for chemistry students with serious interest in quantum chemistry. Postulates and systematic development of nonrelativistic quantum mechanics; expansion theorems; wells; oscillators; angular momentum; hydrogen atom; matrix techniques; approximation methods; time dependent problems; atoms; spectroscopy; magnetic resonance; chemical bonding.

CHEM C215AB - Quantum Chemistry: Methods

Designed for chemistry students with serious interest in quantum chemistry. Postulates and systematic development of nonrelativistic quantum mechanics; expansion theorems; wells; oscillators; angular momentum; hydrogen atom; matrix techniques; approximation methods; time dependent problems; atoms; spectroscopy; magnetic resonance; chemical bonding.

CHEM 219S - Seminar: Research in Physical Chemistry--Nanoscience

Advanced study and analysis of current topics in physical chemistry. Discussion of current research and literature in research specialty of faculty member teaching course.

CHEM 219V - Seminar: Research in Physical Chemistry--Complex Fluids: Composition, Structure, and Rheology

Advanced study and analysis of current topics in physical chemistry. Discussion of current research and literature in research specialty of faculty member teaching course.

COM SCI 132 - Compiler Construction

Compiler structure; lexical and syntactic analysis; semantic analysis and code generation; theory of parsing.

COM SCI M146 - Introduction to Machine Learning (crosslisted with EC ENGR M146)

Introduction to breadth of data science. Foundations for modeling data sources, principles of operation of common tools for data analysis, and application of tools and models to data gathering and analysis. Topics include statistical foundations, regression, classification, kernel methods, clustering, expectation maximization, principal component analysis, decision theory, reinforcement learning and deep learning.

COM SCI 161 - Fundamentals of Artificial Intelligence

Introduction to fundamental problem solving and knowledge representation paradigms of artificial intelligence. Introduction to Lisp with regular programming assignments. State-space and problem reduction methods, brute-force and heuristic search, planning techniques, two-player games. Knowledge structures including predicate logic, production systems, semantic nets and primitives, frames, scripts. Special topics in natural language processing, expert systems, vision, and parallel architectures.

COM SCI 260B - Algorithmic Machine Learning

In-depth examination of handful of ubiquitous algorithms in machine learning. Covers several classical tools in machine learning but more emphasis on recent advances and developing efficient and provable algorithms for learning tasks. Topics include low-rank approximations, online learning, multiplicative weights framework, mathematical optimization, outlier-robust algorithms, streaming algorithms.

COM SCI 260C - Deep Learning

Study of basics of deep neural networks and their applications, including but not limited to computer vision, natural language processing, and graph mining. Covers topics including foundation of deep learning, how to train neural network (optimization), architecture designs for various tasks, and other advanced topics. By course end, students are expected to be familiar with deep learning and be able to apply deep learning algorithms to variety of tasks.

COM SCI 263 - Natural Language Processing

Natural language processing (NLP) enables computers to understand and process human languages. NLP techniques have been widely used in many applications, including machine translation, question answering, machine summarization, and information extraction. Study of fundamental elements and recent trends in NLP. Students gain ability to apply NLP techniques in text-orientated applications, understand machine learning and algorithms used in NLP, and propose new approaches to solve NLP problems.

COM SCI 267A - Probabilistic Programming and Relational Learning

Introduction to computational models of probability and statistical models of relational data. Study of relational representations such as probabilistic databases, relational graphical models, and Markov logic networks, as well as various probabilistic programming languages. Covers their syntax and semantics, probabilistic inference problems, parameter, and structure learning algorithms, and theoretical properties of representation and inference. Expressive statistical modeling, how to formalize and reason about complex statistical assumptions and encode knowledge in machine learning models. Survey of key applications in natural language processing, graph mining, computer vision, and computational biology.

EC ENGR 100 - Electrical and Electronic Circuits

Electrical quantities, linear circuit elements, circuit principles, signal waveforms, transient and steady state circuit behavior, semiconductor diodes and transistors, small signal models, and operational amplifiers.

EC ENGR 101B - Electromagnetic Waves

Time-varying fields and Maxwell equations, plane wave propagation and interaction with media, energy flow and Poynting vector, guided waves in waveguides, phase and group velocity, radiation and antennas.

EC ENGR 110/110H - Circuit Theory II/Circuit Theory II (Honors)

Sinusoidal excitation and phasors, AC steady state analysis, AC steady state power, network functions, poles and zeros, frequency response, mutual inductance, ideal transformer, application of Laplace transforms to circuit analysis.

EC ENGR 110L - Circuit Measurements Lab

Experiments with basic circuits containing resistors, capacitors, inductors, and op-amps. Ohm’s law voltage and current division, Thevenin and Norton equivalent circuits, superposition, transient and steady state analysis, and frequency response principles.

EC ENGR 113 - Digital Signal Processing

Relationship between continuous-time and discrete-time signals. Z-transform. Discrete Fourier transform. Fast Fourier transform. Structures for digital filtering. Introduction to digital filter design techniques.

EC ENGR 115A - Analog Electronic Circuits I

Review of physics and operation of diodes and bipolar and MOS transistors. Equivalent circuits and models of semiconductor devices. Analysis and design of single-stage amplifiers. DC biasing circuits. Small-signal analysis. Operational amplifier systems.

EC ENGR 115AL - Analog Electronics Lab I

Experimental determination of device characteristics, resistive diode circuits, single-stage amplifiers, compound transistor stages, effect of feedback on single-stage amplifiers, operational amplifiers, and operational amplifier circuits. Introduction to hands-on design experience based on individual student hardware design and implementation platforms.

EC ENGR 115B - Analog Electronic Circuits II

Analysis and design of differential amplifiers in bipolar and CMOS technologies. Current mirrors and active loads. Frequency response of amplifiers. Feedback and its properties. Stability issues and frequency compensation.

EC ENGR 115C - Digital Electronic Circuits

Transistor-level digital circuit analysis and design. Modern logic families (static CMOS, pass-transistor, dynamic logic), integrated circuit (IC) layout, digital circuits (logic gates, flipflops/latches, counters, etc.), computer-aided simulation of digital circuits.

EC ENGR 121B - Principles of Semiconductor Device Design

Introduction to principles of operation of bipolar and MOS transistors, equivalent circuits, high-frequency behavior, voltage limitations.

EC ENGR M153 - Introduction to Microscale and Nanoscale Manufacturing

Introduction to general manufacturing methods, mechanisms, constrains, and microfabrication and nanofabrication. Focus on concepts, physics, and instruments of various microfabrication and nanofabrication techniques that have been broadly applied in industry and academia, including various photolithography technologies, physical and chemical deposition methods, and physical and chemical etching methods. Hands-on experience for fabricating microstructures and nanostructures in modern clean-room environment.

EC ENGR 163A - Introductory Microwave Circuits

Transmission lines description of waveguides, impedance matching techniques, power dividers, directional couplers, active devices, transistor amplifier design.

EC ENGR 163C - Fundamental Principles of Radiofrequency and Microwave Systems

Theory and design of modern radiofrequency (RF) and microwave systems such as cellular communications, satellite systems, radar systems, wireless sensors, and biological applications of microwaves such as magnetic resonance imaging (MRI).

EC ENGR 163DA - Microwave and Wireless Design I

Capstone design course, with emphasis on transmission line-based circuits and components to address need in industry and research community for students with microwave and wireless circuit design experiences. Standard design procedure for waveguide and transmission line-based microwave circuits and systems to gain experience in using Microwave CAD software such as Agilent ADS or HFSS. How to fabricate and test these designs.

EC ENGR 170A - Principles of Photonics

Development of solid foundation on essential principles of photonics from ground up with minimum prior knowledge on this subject. Topics include optical properties of materials, optical wave propagation and modes, optical interferometers and resonators, optical coupling and modulation, optical absorption and emission, principles of lasers and light-emitting diodes, and optical detection.

EC ENGR 170B - Lasers and Photonic Devices

Coverage of laser physics, related photonic devices, and applications of lasers. Topics include resonators, thermal radiation, Einstein coefficients, optical amplification, semiconductor lasers, optical modulation and detection.

EC ENGR 170C - Photonic Sensors and Solar Cells

Fundamentals of detection of light for communication and sensing, as well as conversion of light to electrical energy in solar cells. Introduction to radiometry, semiconductor photodetectors, noise processes and figures of merit, thermal detectors, and photovoltaic solar cells of various types and materials.

EC ENGR 231E - Channel Coding Theory

Fundamentals of error control codes and decoding algorithms. Topics include block codes, convolutional codes, trellis codes, and turbo codes.

EC ENGR 232E - Large Scale Social and Complex Networks: Design and Algorithms

Modeling and design of large-scale complex networks, including social networks, peer-to-peer file-sharing networks, World Wide Web, and gene networks. Modeling of characteristic topological features of complex networks, such as power laws and percolation threshold. Mining topology to design algorithms for various applications, such as e-mail spam detection, friendship recommendations, viral popularity, and epidemics. Introduction to network algorithms, computational complexity, and nondeterministic, polynomial-time completeness.

EC ENGR C243A - Neural Signal Processing

Topics include fundamental properties of electrical activity in neurons; technology for measuring neural activity; spiking statistics and Poisson processes; generative models and classification; regression and Kalman filtering; principal components analysis, factor analysis, and expectation maximization.

EC ENGR M252 - Microelectromechanical Systems (MEMS) Device Physics and Design

Introduction to MEMS design. Design methods, design rules, sensing and actuation mechanisms, microsensors, and microactuators. Designing MEMS to be produced with both foundry and nonfoundry processes. Computer-aided design for MEMS. Design project required.

MATH 120AB - Differential Geometry

Curves in 3-space, Frenet formulas, surfaces in 3-space, normal curvature, Gaussian curvature, congruence of curves and surfaces, intrinsic geometry of surfaces, isometries, geodesics, Gauss/Bonnet theorem.

MATH 156 - Machine Learning

Introductory course on mathematical models for pattern recognition and machine learning. Topics include parametric and nonparametric probability distributions, curse of dimensionality, correlation analysis and dimensionality reduction, and concepts of decision theory. Advanced machine learning and pattern recognition problems, including data classification and clustering, regression, kernel methods, artificial neural networks, hidden Markov models, and Markov random fields. Projects in MATLAB to be part of final project presented in class.

MATH 167 - Mathematical Game Theory

Quantitative modeling of strategic interaction. Topics include extensive and normal form games, background probability, lotteries, mixed strategies, pure and mixed Nash equilibria and refinements, bargaining; emphasis on economic examples. Optional topics include repeated games and evolutionary game theory.

MATH 210C - Algebra

Group theory, including theorems of Sylow and Jordan/Holder/Schreier; rings and ideals, factorization theory in integral domains, modules over principal ideal rings, Galois theory of fields, multilinear algebra, structure of algebras.

MATH 226A - Differential Geometry

Manifold theory; connections, curvature, torsion, and parallelism. Riemannian manifolds; completeness, submanifolds, constant curvature. Geodesics; conjugate points, variational methods, Myers theorem, nonpositive curvature. Further topics such as pinched manifolds, integral geometry, Kahler manifolds, symmetric spaces.

PHYSICS 115C - Quantum Mechanics

Time-independent perturbation theory, application to atomic spectra. Time-dependent perturbation theory. Fermi’s golden rule. Scattering. Wentzel-Kramers-Brillouin (WKB) approximation.

PHYSICS 118 - Electronics for Physical Measurements

Provides students with opportunity to apply basic knowledge of circuit design for purpose of building stand-alone circuits with function related to control or measurement. Examples of physics-oriented projects include radio-frequency detection and measurement of mechanical resonances of bar, FM transmitter, speed of sound using radio-frequency pulsed ultrasound, sun-following pointers, cosmic ray detector.

PHYSICS 123 - Atomic Structure

Theory of atomic structure. Interaction of radiation with matter.

PHYSICS 140A - Introduction to Solid-State Physics

Introduction to basic theoretical concepts of solid-state physics with applications. Crystal symmetry; cohesive energy; diffraction of electron, neutron, and electromagnetic waves in a lattice; reciprocal lattice; phonons and their interactions; free electron theory of metals; energy bands.

PHYSICS 140B - Properties of Solids

Elementary discussion of properties of solids. Use of theory of electrons and the lattice to examine properties of semiconductors, metals, and superconductors, together with magnetic and dielectric properties of materials. Properties of noncrystalline solids.

PHYSICS 170A - Electronics for Physics Measurement

Hands-on experimental course to develop understanding of design principles in modern electronics for physics measurements. Broad introduction to analog and digital electronics from practical viewpoint, followed by examination of typical circuits for scientific instrumentation and study of methods of computer data acquisition and signal processing.

PHYSICS 170N - Computational Physics and Astronomy Laboratory

Designed to give first-hand experience in solving physics and astronomy problems on computers. Project-based course, with projects selected from core areas of classical mechanics, electrodynamics, quantum physics, statistical physics, and astronomy. Introduction to problems and to required numerical methods in lectures, so students can write programs in one modern programming language of their choice (Python recommended) and carry out numerical experiments with it, with results documented in reports.

PHYSICS 192 - Undergraduate Practicum in Physics

Training and supervised practicum for advanced undergraduate students. Students assist in preparation of materials and development of innovative programs with guidance of faculty members in small course settings. May be repeated for credit.

PHYSICS 213A - Advanced Atomic, Molecular, and Optical Physics

Atomic and molecular structure, light-matter interactions, density matrix representation, Jayne-Cummings Hamiltonian, and sample of current techniques.

PHYSICS 213B - Advanced Atomic, Molecular, and Optical Physics

Quantum optics, quantum entanglement, quantum information processing, quantum sensing, quantum communication.

PHYSICS 213C - Molecular Structure

Application of group theory to vibrational and electronic states of molecules. Molecular orbital theory. Raman effect. Angular momentum and coupling in molecules.

PHYSICS 215A - Statistical Physics

Microstates and macrostates, statistical ensembles, entropy and other thermodynamic functions, equilibrium, variational principles, functional integration methods. Applications: ideal gas, oscillators, rotors, elasticity, paramagnetism. Indistinguishable particles, Fermi/Dirac and Bose/Einstein distributions. Applications: electron gas, neutron stars, white dwarfs, Bose/Einstein condensation. Kinetics.

PHYSICS 221A - Quantum Mechanics

Fundamentals of quantum mechanics, Hilbert spaces, correspondence principle, quantum dynamics, and rotations and angular momentum. Special topics such as Bell inequalities, and aspects of quantum information.

PHYSICS 221B - Quantum Mechanics

Symmetries and conservation laws, perturbation theory, scattering theory. Special topics such as Berry's phase and related geometric and topological aspects.

PHYSICS 221C - Quantum Mechanics

Quantum theory of radiation, introduction to relativistic quantum mechanics, second quantization, elements of many-body theory, and special topics.

PHYSICS 231B - Methods of Mathematical Physics

Widely used methods of group theory with applications to physics, including matrix Lie groups and Lie algebras, crystallographic groups, representations of groups and Lie algebras, tensors, spinors, roots, weights, structure of simple Lie algebras, and homogeneous spaces.

PHYSICS 241A - Solid State Physics

Symmetry, free electrons, electrons in periodic potential, experimental measurement of band structure and Fermi surface parameters, cohesive energy, lattice vibrations, thermal properties.

PHYSICS 241B - Solid State Physics

Transport theory with applications, electron/electron interactions.

PHYSICS 241C - Solid State Physics

Semiconductors, magnetism, phase transitions, superconductivity.

STATS 202C - Monte Carlo Methods for Optimization

Monte Carlo methods and numerical integration. Importance and rejection sampling. Sequential importance sampling. Markov chain Monte Carlo (MCMC) sampling techniques, with emphasis on Gibbs samplers and Metropolis/Hastings. Simulated annealing. Exact sampling with coupling from past. Permutation testing and bootstrap confidence intervals.