Quantum Brain
← Back to papers

Ever more optimized simulations of fermionic systems on a quantum computer

Qingfeng Wang, Ze-Pei Cian, Ming Li, I. Markov, Y. Nam·March 6, 2023·DOI: 10.1109/DAC56929.2023.10247693
Computer SciencePhysics

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

Despite using a novel model of computation, quantum computers break down programs into elementary gates. Among such gates, entangling gates are the most expensive. In the context of fermionic simulations, we develop a suite of compilation and optimization techniques that massively reduce the entangling-gate counts. We exploit the well-studied non-quantum optimization algorithms to achieve up to 24% savings over the state of the art for several small-molecule simulations, with no loss of accuracy or hidden costs. Our methodologies straightforwardly generalize to wider classes of near-term simulations of the ground state of a fermionic system or real-time simulations probing dynamical properties of a fermionic system.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.