92 citations · 344 across the 13 of their papers we have counts for
13 papers
Evaluating Multiconfigurational Trials for Accurate Phaseless Auxiliary-Field Quantum Monte Carlo on 3d Transition Metal Complexes
Hung T. Vuong, Ankit Mahajan, John L. Weber +3
In this study, we evaluate multi-configurational trial wave function protocols for phaseless auxiliary field quantum Monte Carlo (ph-AFQMC) on transition metal containing systems.…
Efficient Long-Range Machine Learning Force Fields for Liquid and Materials Properties
John L. Weber, Rishabh D. Guha, Garvit Agarwal +10
Machine learning force fields (MLFFs) have emerged as a sophisticated tool for cost-efficient atomistic simulations approaching DFT accuracy, with recent message passing MLFFs able…
Scalable Training of Neural Network Potentials for Complex Interfaces Through Data Augmentation
In Won Yeu, Annika Stuke, Jon L. pez-Zorrilla +5
Artificial neural network (ANN) potentials enable highly accurate atomistic simulations of complex materials at unprecedented scales. Despite their promise, training ANN potentials…
Scalable Ab Initio Electronic Structure Methods with Near Chemical Accuracy for Main Group Chemistry
Yujing Wei, Sibali Debnath, John L. Weber +3
This study evaluates the precision of widely recognized quantum chemical methodologies, CCSD(T), DLPNO-CCSD(T) and localized ph-AFQMC, for determining the thermochemistry of main g…
The Design of New Practical Constraints in Auxiliary-Field Quantum Monte Carlo
John L. Weber, Hung Vuong, Richard A. Friesner +1
We formulate and characterize a new constraint for Auxiliary Field Quantum Monte Carlo (AFQMC) applicable for general fermionic systems, which allows for the accumulation of phase…
A Localized-Orbital Energy Evaluation for Auxiliary-Field Quantum Monte Carlo
John L. Weber, Hung Vuong, Pierre A. Devlaminck +4
Phaseless Auxiliary-Field Quantum Monte Carlo (ph-AFQMC) has recently emerged as a promising method for the production of benchmark-level simulations of medium to large-sized molec…
Predicting Ligand-Dissociation Energies of 3d Coordination Complexes with Auxiliary-Field Quantum Monte Carlo
Benjamin Rudshteyn, Dilek Coskun, John L. Weber +5
Transition metal complexes are ubiquitous in biology and chemical catalysis, yet they remain difficult to accurately describe with ab initio methods due to the presence of a large…
Singlet-Triplet Energy Gaps of Organic Biradicals and Polyacenes with Auxiliary-Field Quantum Monte Carlo
James Shee, Evan J. Arthur, Shiwei Zhang +2
The energy gap between the lowest-lying singlet and triplet states is an important quantity in chemical photocatalysis, with relevant applications ranging from triplet fusion in op…
Transitions in ZnS and CdSe quantum dots and wave-function symmetry
B. Zorman, R. A. Friesner
Excitation energies for wurtzite spherical ZnS and CdSe quantum dots in the range of 40-4000 atoms were calculated using empirical pseudopotentials and a real-space basis. The ener…
On Achieving High Accuracy in Quantum Chemical Calculations of 3d Transition Metal Systems: A Comparison of Auxiliary-Field Quantum Monte Carlo with Coupled Cluster, Density Functional Theory, and Experiment for Diatomic Molecules
James Shee, Benjamin Rudshteyn, Evan J. Arthur +3
The bond dissociation energies of a set of 44 3d transition metal-containing diatomics are computed with phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) utilizing a correl…
Prediction of Cytochrome P450-Mediated Metabolism Using a Combination of QSAR Derived Reactivity and Induced Fit Docking
Shulu Feng, Richard A. Friesner
Prediction of metabolism in cytochrome P450s remains to be a crucial yet challenging topic in discovering and designing drugs, agrochemicals and nutritional supplements. The proble…
Phaseless Auxiliary-Field Quantum Monte Carlo on Graphical Processing Units
James Shee, Evan J. Arthur, Shiwei Zhang +2
We present an implementation of phaseless Auxiliary-Field Quantum Monte Carlo (ph-AFQMC) utilizing graphical processing units (GPUs). The AFQMC method is recast in terms of matrix…
Chemical Transformations Approaching Chemical Accuracy via Correlated Sampling in Auxiliary-Field Quantum Monte Carlo
James Shee, Shiwei Zhang, David R. Reichman +1
The exact and phaseless variants of Auxiliary-Field Quantum Monte Carlo (AFQMC) have been shown to be capable of producing accurate ground-state energies for a wide variety of syst…