Optimizing quantum algorithms for next-generation quantum chemistry - Artur Izmaylov

Quantum chemistry problem is one of the attractive targets for demonstrating the quantum advantage of quantum computing technology. Having strongly correlated systems as the main target, I would like to discuss what new classical computing techniques need to be developed to help quantum computing algorithms to solve the electronic structure problem. Encoding the electronic Hamiltonian in a second quantized form on a quantum computer is a complex task, with efficiency challenges that can significantly impact the overall performance of quantum solutions. To address these challenges, we propose partitioning the Hamiltonian into a sum of fragments that can be diagonalized through rotations derived from small Lie groups or the Clifford group. These partitions simplify algebraic manipulations critical for circuit compilation and quantum measurement processes. I will demonstrate how this Hamiltonian partitioning strategy enhances the efficiency of key quantum chemistry algorithms, including the Variational Quantum Eigensolver and Quantum Phase Estimation.