Recorded 24 May 2022. Claudia Filippi of Universiteit Twente presents "Targeting excited states with quantum Monte Carlo" at IPAM's Monte Carlo and Machine Learning Approaches in Quantum Mechanics Workshop. Abstract: While real-space quantum Monte Carlo methods are routinely employed to predict accurate ground-state energies of relatively large systems, their use is relatively uncommon when coming to excited states, especially for properties other than total energies. Here, I will illustrate their performance in combination with different choices of Jastrow-Slater wave functions, when variational and structural parameters are consistently optimized within the method. For several challenging, increasingly large molecules, I will show that the use of a selected-configuration-interaction scheme to generate compact determinantal components leads to the fast and accurate computation of ground- and excited-state structures as well as excitation energies of different nature already at the variational Monte Carlo level. Finally, we will discuss the use of different variational principles in quantum Monte Carlo to target the states involved in the excitation. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/workshop-iv-monte-carlo-and-machine-learning-approaches-in-quantum-mechanics/?tab=schedule