Work

Predicting Open Quantum Dynamics with Data-Informed Quantum-Classical Dynamics

Year: 2025

Type: article

Abstract: We introduce a data-informed quantum-classical dynamics (DIQCD) approach for predicting the evolution of an open quantum system. The equation of motion in DIQCD is a Lindblad equation with a flexible, time-dependent Hamiltonian that can be optimized to fit sparse and noisy data from local observations of an extensive open quantum system. We demonstrate the accuracy and efficiency of DIQCD for both experimental and simulated quantum devices. We show that DIQCD can predict entanglement dynamics of ultracold molecules (calcium fluoride) in optical tweezer arrays. DIQCD also successfully predicts carrier mobility in organic semiconductors (rubrene) with accuracy comparable to nearly exact numerical methods.

Source: Physical Review Letters

DOI: 10.1103/7lsx-ssjl

Authors: Pinchen Xie, Ke Wang, Anupam Mitra, Yuanran Zhu, Xiantao Li, Wibe Albert de Jong, Chao Yang

Institutions: Lawrence Berkeley National Laboratory, Pennsylvania State University

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,750