Institute for Pure & Applied Mathematics (IPAM) Courses

Global Cyberinfrastructure for LIGO, Virgo, Kagra, IceCube, and Others

Explore global cyberinfrastructure supporting multi-messenger astrophysics experiments, including data management, compute clusters, and modular software stacks for collaborative research.

• YouTube
• 41 minutes
• Self-Paced
• Free Video

Rapid and Robust Parameter Estimation for Gravitational Wave Observations

Explore rapid parameter estimation techniques for gravitational wave observations, focusing on machine learning approaches like DINGO that use normalizing flows to efficiently analyze data from future detectors.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Low-Latency Noise Mitigation Techniques in Gravitational-Wave Detector Data Using Auxiliary Sensor Information

Explore low-latency noise mitigation techniques in gravitational-wave detectors, focusing on automated methods to enhance sensitivity and enable rapid multi-messenger follow-up of astrophysical events.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

Machine Learning and Gravitational Wave Detectors

Explore machine learning applications in gravitational wave detector science, focusing on noise subtraction and advanced control systems to enhance sensitivity and robustness in astrophysical research.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

Computational Challenges in Gravitational Wave Parameter Estimation - IPAM at UCLA

Explore computational challenges in gravitational wave parameter estimation, including novel techniques and future requirements for analyzing compact binary signals in astrophysics.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Variational Models and Algorithms for GW Denoising and Reconstruction

Explore variational models and algorithms for gravitational wave denoising and reconstruction, including applications to simulated and real detector data, signal classification, and glitch detection.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

Rapidly Searching for Continuous Gravitational Waves

Explore challenges and solutions in detecting continuous gravitational waves from neutron stars, focusing on SOAP's rapid search method using neural networks for signal identification and parameter estimation.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

Machine Learning in Low-Latency Electromagnetic Counterpart Inference

Explore machine learning applications in electromagnetic counterpart inference from gravitational waves, focusing on low-latency data products for efficient follow-up of gravitational wave candidates.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Nobody Likes a Glitch - IPAM at UCLA

Explore transient noise artifacts in gravitational wave astronomy, their impact on signal detection, and innovative approaches for understanding and mitigating these glitches in data analysis.

• YouTube
• 32 minutes
• Self-Paced
• Free Video

Power Spectral Density Uncertainty and Gravitational-Wave Parameter Estimation

Explore power spectral density uncertainty in gravitational-wave parameter estimation, its impact on Bayesian analysis, and methods to incorporate this uncertainty for more accurate results in compact binary coalescence detection.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

Waveform Systematics in the Gravitational-Wave Inference of Tidal Parameters

Exploración de sistemáticas en formas de onda para inferir parámetros de marea y ecuación de estado en señales de ondas gravitacionales de sistemas binarios de estrellas de neutrones.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

Gravitational-Wave Observations of Neutron-Star Mergers - IPAM at UCLA

Explore gravitational-wave observations of neutron-star mergers, their impact on understanding dense matter and stellar evolution, and future prospects in gravitational-wave astronomy.

• YouTube
• 41 minutes
• Self-Paced
• Free Video

Simulation-Based Inference for Gravitational Wave Astronomy - IPAM at UCLA

Explore simulation-based inference techniques for gravitational wave astronomy, covering frequentist vs. Bayesian approaches, summary statistics, and the role of neural networks and inductive bias.

• YouTube
• 49 minutes
• Self-Paced
• Free Video

A Brief Introduction to Nested Sampling - IPAM at UCLA

Explore Nested Sampling for Bayesian model uncertainty and selection. Learn its principles, advantages, and recent extensions like Dynamic Nested Sampling for estimating marginal likelihoods and posterior distributions.

• YouTube
• 38 minutes
• Self-Paced
• Free Video

Gravitational Wave Parameter Estimation with Compressed Likelihood Evaluations

Explore advanced techniques for efficient gravitational wave parameter estimation, focusing on Reduced Order Quadratures (ROQs) to accelerate likelihood evaluations and improve Bayesian inference in GW astronomy.

• YouTube
• 42 minutes
• Self-Paced
• Free Video