Litcius/Paper detail

A hybrid approach to excited-state-specific variational Monte Carlo and doubly excited states

Leon Otis, Isaac M. Craig, Eric Neuscamman

2020The Journal of Chemical Physics27 citationsDOIOpen Access PDF

Abstract

We extend our hybrid linear-method/accelerated-descent variational Monte Carlo optimization approach to excited states and investigate its efficacy in double excitations. In addition to showing a superior statistical efficiency when compared to the linear method, our tests on small molecules show good energetic agreement with benchmark methods. We also demonstrate the ability to treat double excitations in systems that are too large for a full treatment by using selected configuration interaction methods via an application to 4-aminobenzonitrile. Finally, we investigate the stability of state-specific variance optimization against collapse to other states' variance minima and find that symmetry, Ansatz quality, and sample size all have roles to play in achieving stability.

Topics & Concepts

AnsatzExcited stateMaxima and minimaMonte Carlo methodBenchmark (surveying)Stability (learning theory)Variational Monte CarloPhysicsStatistical physicsSymmetry (geometry)Quantum Monte CarloMathematicsQuantum mechanicsComputer scienceMathematical analysisStatisticsGeometryMachine learningGeodesyGeographyAdvanced Chemical Physics StudiesMachine Learning in Materials ScienceSpectroscopy and Quantum Chemical Studies