Work

Isometric tensor network optimization for extensive Hamiltonians is free of barren plateaus

Year: 2024

Type: article

Abstract: Strongly correlated quantum many-body systems from condensed matter and particle physics are very hard to study classically and variational quantum algorithms (VQAs) may be hampered by barren plateaus, where energy gradients decay exponentially in the system size. The authors prove that this critical problem can be resolved by employing VQAs based on suitable isometric tensor network states, establishing a new route for the investigation of strongly correlated quantum matter on NISQ devices.

Source: Physical Review A

DOI: 10.1103/physreva.109.l050402

Authors: Qiang Miao, Thomas Barthel

Institution: Duke University

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, U.S. Department of Energy

Awards: G1938338418, QLCI-CI: NSF Quantum Leap Challenge Institute for Robust Quantum Simulation, QUANTUM COMPUTING IN CHEMICAL AND MATERIAL SCIENCES