8 papers
Numerical Construction of Quasi-Periodic Solutions for Nonlinear PDEs: I. Bounded Perturbation
Mingwei Fu, Bin Shi
In this paper, we propose an alternating numerical scheme for constructing quasi-periodic solutions to a class of nonlinear partial differential equations (PDEs) with bounded pertu…
Passive Synchronization of Nonlocal Franson Interferometry for Fiber-Based Quantum Networks Using Co-propagating Classical Clock Signals
Xiao Xiang, Runai Quan, Yuting Liu +7
We demonstrate a robust, high-visibility nonlocal Franson interferometry for fiber-based quantum networks by co-propagating a classical Radio-over-Fiber clock signal with energy-ti…
Co-Propagation of Quantum Time Synchronization and Optical Frequency Transfer over a 122 km Hollow-Core Fiber
Huibo Hong, Xiao Xiang, Runai Quan +15
The co-propagation of quantum and classical signals through shared optical fibers is crucial for scalable quantum networks. However, this coexistence is fundamentally limited by sp…
Numerical Construction of Quasi-Periodic Solutions Beyond Symplectic Integrators
Mingwei Fu, Bin Shi
Symplectic integrators are the established standard for long-term simulations of nearly-integrable Hamiltonian systems due to their preservation of geometric structures. However, t…
Quantum Optimization via Gradient-Based Hamiltonian Descent
Jiaqi Leng, Bin Shi
With rapid advancements in machine learning, first-order algorithms have emerged as the backbone of modern optimization techniques, owing to their computational efficiency and low…
On Pseudospectral Concentration for Rank-1 Sampling
Kuo Gai, Bin Shi
Pseudospectral analysis serves as a powerful tool in matrix computation and the study of both linear and nonlinear dynamical systems. Among various numerical strategies, random sam…
A Family of Controllable Momentum Coefficients for Forward-Backward Accelerated Algorithms
Mingwei Fu, Bin Shi
Nesterov's accelerated gradient method (NAG) marks a pivotal advancement in gradient-based optimization, achieving faster convergence compared to the vanilla gradient descent metho…
Lyapunov Analysis For Monotonically Forward-Backward Accelerated Algorithms
Mingwei Fu, Bin Shi
Nesterov's accelerated gradient method (NAG) achieves faster convergence than gradient descent for convex optimization but lacks monotonicity in function values. To address this, B…