FCIQMC-Tailored Distinguishable Cluster Approach
Eugenio Vitale, Ali Alavi, Daniel Kats
Abstract
The tailored approach is applied to the distinguishable cluster method together with a stochastic FCI solver (FCIQMC). It is demonstrated that the new method is more accurate than the corresponding tailored coupled cluster and the pure distinguishable cluster methods. An F12 correction for tailored methods and FCIQMC is introduced, which drastically improves the basis set convergence. A new black-box approach to define the active space using the natural orbitals from the distinguishable cluster is evaluated and found to be a convenient alternative to the usual CASSCF approach.
Topics & Concepts
Computer scienceCluster (spacecraft)Coupled clusterSolverConvergence (economics)Set (abstract data type)Basis (linear algebra)AlgorithmAtomic orbitalData miningTheoretical computer scienceComputational sciencePhysicsMathematicsMoleculeGeometryEconomicsProgramming languageEconomic growthElectronQuantum mechanicsComplex Network Analysis TechniquesTheoretical and Computational PhysicsBayesian Methods and Mixture Models