4 papers · 1 filter
QuGStep: Refining Step Size Selection in Gradient Estimation for Variational Quantum Algorithms
Senwei Liang, Linghua Zhu, Xiaosong Li +1
Variational quantum algorithms (VQAs) offer a promising approach to solving computationally demanding problems by combining parameterized quantum circuits with classical optimizati…
Exploring the Nexus of Many-Body Theories through Neural Network Techniques: the Tangent Model
Senwei Liang, Karol Kowalski, Chao Yang +1
In this paper, we present a physically informed neural network representation of the effective interactions associated with coupled-cluster downfolding models to describe chemical…
Effective Many-body Interactions in Reduced-Dimensionality Spaces Through Neural Network Models
Senwei Liang, Karol Kowalski, Chao Yang +1
Accurately describing properties of challenging problems in physical sciences often requires complex mathematical models that are unmanageable to tackle head-on. Therefore, develop…
Artificial-Intelligence-Driven Shot Reduction in Quantum Measurement
Senwei Liang, Linghua Zhu, Xiaolin Liu +2
Variational Quantum Eigensolver (VQE) provides a powerful solution for approximating molecular ground state energies by combining quantum circuits and classical computers. However,…