The cost of exact computations of molecules and materials diverges exponentially in the number of orbitals on classical computers.  Using quantum computation, the cost becomes polynomial, allowing much larger systems to be simulated in principle.  The Noisy Intermediate-Scale Quantum (NISQ) technology available today is limited to short-depth circuits on tens of quantum bits (qubits), but the industry is improving rapidly.

The objective of this research is to squeeze the most computational power from current NISQ computers for simulations of molecules and materials.  We will improve current Variational Quantum Eigensolvers (VQE) [1] in two directions: 

• Using symmetries of the Hamiltonians, we will reduce the size of the Hilbert space, allowing larger systems to be simulated on smaller quantum computers.
• We will improve the implementation of the VQE to allow a more accurate solutions in shorter-depth quantum circuits.

[1]  Kandala, A., et al. Nature 567, 491–495 (2019).

key words

Quantum computers; Quantum simulations; Quantum algorithms; Quantum information processing; Materials science; Defects; Many-body physics; Model Hamiltonians; Hubbard model; Density functional theory; Theoretical physics; Computational physics; Condensed matter

Citizenship:  Open to U.S. citizens and permanent residents

Level:  Open to Postdoctoral applicants