Research

Phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) has demonstrated remarkable accuracy for a wide variety of transition metal-containing systems exhibiting both weak and strong correlations.  The low-polynomial scaling of the method's computational cost with respect to system size and its suitability for massive parallelization enable its application to chemical systems beyond the reach of, e.g., coupled cluster models.  We are pursuing a number of methodological advances which have the potential to position ph-AFQMC as a true "gold standard" method for ground and excited states of transition metal and f-block compounds.

Quantum chemistry can potentially benefit from the rapid advances in quantum computing/simulation hardware.  In collaboration with industry partners (including IBM), our lab develops  new quantum algorithms for strongly correlated electronic states.  For example, we have introduced a family of ansatzes based on the unitary cluster Jastrow wavefunction, which is both hardware-efficient and physically justifiable.  Our efforts in quantum algorithms tend to reveal fresh perspectives on classical ones too!

Understanding chemical systems such as the oxygen-evolving complex in photosystem II, cyctochrome C oxidase, and PFAS-capture in porous materials requires much more than solving the electronic structure problem for an isolated active site at zero-temperature.  Combining reliable reference data from first-principles methods such as AFQMC with suitable functional forms (based on physical intuition and often machine learning), the Shee lab is developing semi-empirical interatomic potentials to enable predictive simulations to reach longer length- and time-scales.