In the McCoy Group, most of us work primarily with our own home-built code. But we recently had two group members (Dr. Ryan Dirisio and Dr. Mark Boyer), who wrote up big python packages for Diffusion Monte Carlo (PyVibDMC) and nth-order Vibrational Perturbation Theory (PyVibPTn). Now, we still believe the best way to learn a new method is to code it yourself, these two packages are filled with tricky tricks and lots of handlers to make the code run faster, reliably, and hopefully bug-free. Although there is always room for user error…
Read about it:
Read about what we’ve done with it:
- Fast Near Ab Initio Potential Energy Surfaces Using Machine Learning
- Using Diffusion Monte Carlo Wave Functions to Analyze the Vibrational Spectra of H7O3+ and H9O4+
- GPU-Accelerated Neural Network Potential Energy Surfaces for Diffusion Monte Carlo
Read about how you can use it!
Read about it:
Read about what we’ve done with it:
- Electronic and Mechanical Anharmonicities in the Vibrational Spectra of the H-bonded, Cryogenically Cooled X−HOCl (X=Cl, Br, I) Complexes: Characterization of the Strong Anionic H-bond to an Acidic OH Group
- Preparation and Characterization of the Halogen-Bonding Motif in the Isolated Cl–·IOH Complex with Cryogenic Ion Vibrational Spectroscopy
- with more coming soon!
Read about how you can use it!