Institute for Pure & Applied Mathematics (IPAM) Courses

Dequantization and Quantum Advantage in Learning from Experiments - IPAM at UCLA

Explore quantum advantage in data processing, learning from experiments, and dequantization. Discover how quantum technology can revolutionize experimental data acquisition and analysis in various scientific tasks.

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

The Quantum Linear Systems Problem - IPAM at UCLA

Explore quantum algorithms for solving linear systems, including improved methods and complexity analysis, with a focus on potential exponential speedups and verification challenges.

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

Fast Algorithms for Quantum Signal Processing - IPAM at UCLA

Explore fast algorithms for quantum signal processing, focusing on optimization techniques, energy landscapes, and phase factor structures in quantum singular value transformation.

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

Quantum Algorithms for Quantum Information Processing Tasks

Explore quantum linear algebra methods for efficient quantum information processing, including block-encoding, singular value transformation, and applications in estimation, testing, and tomography tasks.

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

Time-Dependent Hamiltonian Simulation of Highly Oscillatory Dynamics - IPAM at UCLA

Explore highly oscillatory dynamics in quantum systems, focusing on efficient simulation algorithms for time-dependent Hamiltonians with applications in various scientific fields.

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

Efficient Quantum Algorithm for Dissipative Nonlinear Differential Equations

Explore efficient quantum algorithms for nonlinear differential equations, overcoming limitations through Carleman linearization. Discover potential applications in biology, fluid dynamics, and plasma physics.

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

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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• Free Video