The Shee lab will develop ab initio benchmark-quality methods for electronic and vibrational structure, utilizing both stochastic approaches on classical devices and algorithms for quantum computation. We will use these to tackle new science especially in the strongly correlated regime, and to develop faster, semi-empirical computational tools amenable to large-scale simulations.
Quantum Monte Carlo
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, enables its application to chemical systems beyond the reach of, e.g., coupled cluster models. We have identified a number of concrete methodological advances which will unlock the potential of ph-AFQMC to be a true "gold standard" method for ground and excited states of transition metal and f-block compounds, along with proton-tunneling systems.
Quantum chemistry can potentially benefit from the rapid advances in quantum computing hardware. In collaboration with industry partners (including IBM), our lab develops new quantum algorithms for strongly correlated electronic states. For example, we are currently exploring a new 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!
Simulations of Complex Chemical & Biological Systems
Understanding realistic catalytic systems such as the oxygen-evolving complex in photosystem II and cyctochrome C oxidase requires much more than solving the electronic structure problem for an isolated active site at zero-temperature. Combining a wealth of reliable data from first-principles methods such as AFQMC with improved physically-appropriate functional forms, the Shee group will develop semi-empirical models to reach longer length- and time-scales. These include new density functionals and semi-classical interatomic potentials for the simulation of, e.g., metal cofactors in drug design, metal organic frameworks, polynuclear transition metal compounds, and water wires. We have plans to improve implicit solvation models for beyond-main-group molecules as well.
Target Chemical Applications:
We value and welcome opportunities to collaborate with experimentalists, at Rice and beyond.