Introduction to Quantum Monte Carlo and QMCPACK - Session 1

Learn the fundamentals of Quantum Monte Carlo methods and get introduced to the QMCPACK software package in this comprehensive 49-minute lecture by Paul Kent. Explore the electronic structure problem and discover why Quantum Monte Carlo is a powerful computational approach for solving complex many-body physics problems. Understand the key features that make QMC methods attractive, including their systematic improvability and ability to handle strong correlation effects. Examine recent applications of QMC in various research areas and analyze computational costs associated with these methods. Discover how machine learning is being integrated into modern QMC approaches to enhance efficiency and accuracy. Get hands-on guidance for setting up the computational environment, including detailed instructions for installing and configuring the summer school virtual machine on both x86 systems using VirtualBox and Apple Silicon devices using UTM. Follow along with a practical example calculation on a water molecule to see QMC methods in action. Access comprehensive presentation materials and example files through the accompanying GitHub repository to reinforce your learning and prepare for subsequent sessions in this seven-part summer school series.