###Seeking quantum advantage from the quantum simulation of quantum chemistry
Project ID: 2228bd1008 (You will need this ID for your application)
Research Theme: Quantum Technologies
UCL Lead department: Chemistry
Lead Supervisor: Peter V Coveney
Project Summary:
We recently established a chemically intuitive approach that permits a subdomain of a molecule’s electronic structure to be calculated accurately on a quantum device, while the rest of the molecule is described at a lower level of accuracy using density functional theory running on a classical computer. The approach is based on projection based embedding familiar within conventional quantum chemistry, but now the active part of the molecule is computed using a quantum computer with a wavefunction based method, while the remainder of the molecule is described using a less accurate method calculated on a classical computer. Our method produces improved results for molecules that cannot be simulated fully on today’s quantum computers but can be resolved classically at a cheaper level of approximation. In addition, we have developed qubit reduction methods based on a partitioning of the molecular Hamiltonian into contextual and non-contextual components; this reduces the qubit counts required in solving electronic structure problems on existing quantum hardware using the variational quantum eigensolver (VQE).
The group enjoys unique access to a wide range state of the art quantum computing devices, including the IBM Quantum Cloud. In this project, we propose to combine these methods so as to take a key further step that will enable us to study substantially larger molecules via such a hybrid quantum-classical approach. We expect to be able to apply the approaches in this project to look at large molecules, with longer-term targets such as FeMoco and the chromium dimer. The ultimate goal is to achieve chemical accuracy for systems which are intractable using conventional quantum chemistry techniques.
We are looking for a very able student with a background in mathematics, physics or chemistry, demonstrable analytical and numerical skills, and an ability to work within a highly interdisciplinary environment which welcomes creativity and innovation.