Institute for Pure & Applied Mathematics (IPAM) Courses

High Accuracy Wavefunctions Using Deep-Learning-Based Variational Monte Carlo

Explore deep learning-based variational Monte Carlo for high-accuracy wavefunctions in computational chemistry, featuring novel architecture and improved methods for ground state energy calculations.

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

Conditional Probability Density Functional Theory - IPAM at UCLA

Explore conditional probability density functional theory for electronic structure calculations, addressing challenges in DFT and offering insights into ground-state correlations and warm dense matter simulations.

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

Neural-Network Wave Functions for Quantum Chemistry - IPAM at UCLA

Explore neural-network wave functions in quantum chemistry, covering variational quantum Monte Carlo, antisymmetric ansatzes, and applications to electronic and exciton-phonon Hamiltonians for improved accuracy in molecular modeling.

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

Auxiliary Field Quantum Monte Carlo - AFQMC with Multi Slater Wavefunctions

Explore advanced quantum Monte Carlo techniques, focusing on AFQMC with multi-Slater wavefunctions and efficient exchange matrix evaluation for large-scale quantum systems.

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

Machine Learning in Equation of State and Transport Modeling at Extreme Conditions

Explore machine learning applications in equation of state and transport modeling for extreme conditions, enhancing accuracy and efficiency in material science and astrophysics research.

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

Stochastic Density Functional Theory - IPAM at UCLA

Explore stochastic density functional theory for efficient ground-state calculations in extended materials, including noise reduction techniques and applications in warm dense matter at elevated temperatures.

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

Molecular Electron Densities via Machine Learning - IPAM at UCLA

Explore machine learning techniques for predicting molecular electron densities and energies, with applications in quantum mechanics and molecular dynamics simulations.

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

Fermionic Neural-Network Quantum States - IPAM at UCLA

Explore fermionic neural-network quantum states, their efficient representations, and applications in quantum mechanics with Giuseppe Carleo's insightful presentation at IPAM's workshop.

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

Auxiliary-Field Methods for Quantum Materials - IPAM at UCLA

Overview of auxiliary-field quantum Monte Carlo methods for simulating quantum materials, discussing recent advances in ab initio calculations, including correlated sampling and structural optimization.

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

Quantum Simulation with Noisy Intermediate-Scale Quantum Processors

Explore advanced quantum simulation techniques using noisy intermediate-scale quantum processors, focusing on cutting-edge developments and practical applications in computational quantum physics.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Video

Quantum Simulation with Noisy Intermediate-Scale Quantum Processors

Explore quantum simulation using noisy intermediate-scale quantum processors in this comprehensive tutorial by Google's Pedram Roushan, covering key concepts and challenges in the field.

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

Quantum Algorithms for Dynamics Simulation - Differential Equations - IPAM at UCLA

Explore quantum algorithms for simulating dynamics and solving differential equations, focusing on mathematical and computational challenges in quantum computing.

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

Classical ML for Quantum Problems - IPAM at UCLA

Explore classical machine learning applications in quantum computing, focusing on solving quantum problems and advancing quantum technologies.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

Learning Theory in the Quantum Universe - IPAM at UCLA

Explore quantum learning theory with Google Quantum AI expert Hsin-Yuan Huang. Discover mathematical challenges and computational advancements in quantum computing through this insightful presentation.

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

Quantum Algorithms for Dynamics Simulation - Hamiltonian Simulation & General Differential

Explore quantum algorithms for simulating dynamics, focusing on Hamiltonian simulation and differential equations in this comprehensive tutorial by Duke University's Di Fang.

• YouTube
• 1 hour 12 minutes
• On-Demand
• Free Video