Towards Early Quantum Advantage with Impurity Embedding Methods

Explore quantum computing applications in materials science through this 44-minute conference talk that examines impurity embedding methods for achieving early quantum advantage. Learn about the theoretical challenges of describing materials with strongly correlated electrons and discover how Dynamical Mean Field Theory (DMFT) addresses these complex systems. Understand the limitations of current DMFT approaches, particularly the computational bottleneck of calculating Green's functions for impurity models. Examine a proposed framework for performing DMFT calculations on quantum computers, specifically designed for near-term quantum applications. Investigate the innovative combination of low-rank Gaussian subspace representation of ground states with compressed, short-depth quantum circuits for time evolution calculations. Review demonstration results showing DMFT algorithm convergence using Gaussian subspaces in noise-free environments and hardware validation on IBM quantum processors using 8 physical qubits and 1 ancilla for a single impurity coupled to three bath orbitals. Consider the future pathways for implementing quantum computing solutions in condensed matter physics and computational chemistry research.