Institute for Pure & Applied Mathematics (IPAM) Courses

Computational Challenges with Modeling Core Collapse Supernovae - IPAM at UCLA

Explore computational challenges in modeling core collapse supernovae and gravitational wave emission, covering recent progress, physics requirements, and future directions in multi-dimensional simulations.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Binary Neutron Star Mergers - IPAM at UCLA

Explore neutron star mergers, their multimessenger emissions, and implications for astrophysics. Gain insights into recent simulations, future challenges, and prospects in this cutting-edge field.

• YouTube
• 48 minutes
• On-Demand
• Free Video

Introduction to Modelling Gravitational Waves from Compact Binaries

Explore gravitational wave modeling techniques for compact binary systems, covering inspiral, merger, and ringdown phases. Learn about semi-analytic models crucial for detection and analysis.

• YouTube
• 1 hour 24 minutes
• On-Demand
• Free Video

Seeing Through Space-Time - IPAM at UCLA

Explore inverse problems in spacetime structure, light observation sets, and cosmic microwave background, delving into mathematical challenges in gravitational wave astronomy.

• YouTube
• 1 hour 16 minutes
• On-Demand
• Free Video

Helvi Witek - Introduction to Numerical Relativity, Part 2 - IPAM at UCLA

Explore advanced concepts in numerical relativity, including 3+1 spacetime decomposition, Einstein's equations, and stable simulation techniques for gravitational wave research.

• YouTube
• 59 minutes
• On-Demand
• Free Video

Helvi Witek - Introduction to Numerical Relativity, Part 1 of 2 - IPAM at UCLA

Explore the foundations of numerical relativity, including spacetime decomposition, Einstein's equations, and coordinate choices for stable simulations in gravitational wave astronomy.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Characterization of Ground-Based Gravitational-Wave Detector Data - IPAM at UCLA

Explore techniques for distinguishing gravitational wave signals from noise in detector data, including traditional methods and innovative approaches to improve data quality and reduce search backgrounds.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

Quantum Field Theory of Exotic Systems - IPAM at UCLA

Explore quantum field theory of exotic systems, focusing on fracton phases and their challenges to conventional understanding. Delve into subsystem symmetries, tensor gauge theories, and peculiar UV/IR mixing phenomena.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

Topological Defect Networks for Fracton Models - IPAM at UCLA

Explore topological defect networks in fracton models, covering fundamental concepts, excitations, and their implications in topological phases of matter.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Building Manifolds from Error Correcting Codes - IPAM at UCLA

Explore the intersection of error correcting codes and manifold construction, delving into quantum error correction, topology, and complex mathematical concepts.

• YouTube
• 1 hour 14 minutes
• On-Demand
• Free Video

Lattice Topological Phases - IPAM at UCLA

Explore lattice topological phases with Fiona Burnell, covering lattice Hamiltonians, vector spaces, local rules, and gauge choices in this comprehensive lecture on advanced quantum physics concepts.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Opinion Models and Social Influence on Networks - IPAM at UCLA

Explore opinion dynamics on networks, including threshold models, voter models, and bounded-confidence models. Discover how network structure influences social contagions and opinion polarization.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis

Explore efficient and interpretable spatial analysis using multiresolution tensor learning, with applications in geology, sports, and climate science. Discover improved methods for handling complex spatial data.

• YouTube
• 28 minutes
• On-Demand
• Free Video

The Effectiveness of Nonconvex Tensor Completion - Fast Convergence and Uncertainty Quantification

Explores nonconvex optimization for tensor completion, proposing a two-stage algorithm with guaranteed success, linear convergence, and statistical accuracy. Discusses distribution characterization and confidence interval construction.

• YouTube
• 33 minutes
• On-Demand
• Free Video

Implicit and Explicit Regularization in Deep Neural Networks

Explores implicit and explicit regularization in deep neural networks, connecting learning algorithms to H-infinity control and explaining convergence behavior in over-parametrized models, offering insights into generalization abilities.

• YouTube
• 37 minutes
• On-Demand
• Free Video