M’s paper has been published in JPCA. This paper has been a long time coming and was one of the first things we started working on after joining Mizzou, so we are quite pleased to see its completion. In the paper, we introduce a simple modification of Wigner sampling for generating training data for machine learning-based nonadiabatic dynamics. As is hinted at in the conclusions, M is rapidly working on extending the method to electronic Hamiltonians and we hope to continue to expand and follow up on this study in the future. Link is here: https://doi.org/10.1021/acs.jpca.0c07376
Jonathan’s paper has been published in JCP! In it we show that in multicomponent OOMP2 the electron-electron correlation can be included after the orbital-optimization procedure with essentially no loss in accuracy for protonic properties relative to the original multicomponent OOMP2 method. Using the results in this paper, we hypothesize that in all multicomponent orbital-optimized methods, it is sufficient to perform the orbital-optimization procedure solely in the presence of electron-proton correlation. Link is here: https://doi.org/10.1063/5.0006743
Jonathan has been named a Barry Goldwater fellow for 2020. Way to go!
Our study on using the heat-bath flavor of selected CI to compute protonic densities of multicomponent systems has been published in JCTC. We are pretty pleased with the results from this study and learned a lot that we hope to follow up on with regards to the need for non HF-orbitals for multicomponent calculations. Go check it out here: https://pubs.acs.org/doi/10.1021/acs.jctc.9b01273
Ethan and M’s paper on using selected configuration interaction techniques to calculate vibrational excitations has been published! Check it out here: https://doi.org/10.1063/1.5126510
A new student, Ethan Lesko, has joined us for the summer. He will be working on benchmarking vibrational configuration interaction techniques that we have been developing over the past year. Welcome Ethan!
Our paper on using continuous-filter convolutional neural networks to fit global potential energy surfaces has been published in JCP. Go check it out here: doi: 10.1063/1.5093908 .
It has been a while since we have updated the group website. The most important news to report is that we have welcomed a new graduate student, Muhammad Ardiansyah, into the group! M, as he is known, will be working on improving the generation of training data for fitting quantum neural network potentials and designing new quantum neural network potentials using continuous-filter convolutional neural networks. Welcome, M!
Thanks to advice from my former postdoc colleague Yang Yang, we now have a website and hosting. As this is my first website since 8th grade (I believe we used Dreamweaver 2.0 and wrote pure HTML back then), website development has changed significantly since my last go at this. I still need to figure out how WordPress works and get the various pages up to date. More updates to come…