Understanding the mixing of open quantum systems is a fundamental problem in physics
and quantum information science. Existing approaches for estimating the mixing time often …

Simulating the dynamics of open quantum systems is a crucial task in quantum computing,
offering wide-ranging applications but remaining computationally challenging. In this paper …

Finite-sum optimization has wide applications in machine learning, covering important
problems such as support vector machines, regression, etc. In this paper, we initiate the …

We study computational problems related to the Schr\" odinger operator $ H=-\Delta+ V $ in
the real space under the condition that (i) the potential function $ V $ is smooth and has its …

In recent years, there has been a surge of interest in studying different ways to reformulate
nonconvex optimization problems, especially those that involve binary variables. This …

We investigate the mixing properties of primitive hypocoercive Lindblad dynamics. By
extending the variational framework originally developed for underdamped Langevin …

A Quantum Natural Gradient (QNG) algorithm for optimization of variational quantum circuits
has been proposed recently. In this study, we employ the Langevin equation with a QNG …