7 papers
Optimal Strategies for Multi-parameter Quantum Metrology
Linxuan Li, Zihao Hu, Longyun Chen +2
Estimating multiple unknown parameters simultaneously is essential for practical quantum sensing. However, it faces a fundamental challenge: the optimal strategy for estimating one…
HNAG: An Accelerated Gradient Method with a Refined Asymptotic Rate for Strongly Convex Optimization
Long Chen, Zeyi Xu
The paper introduces two accelerated first‑order algorithms, HNAG⁺ and HNAG⁺⁺, for smooth strongly convex problems, achieving optimal global convergence and a refined asymptotic ra…
Adaptive Accelerated Gradient Descent Methods for Convex Optimization
Zeyi Xu, Long Chen
This work proposes AGD, a novel adaptive accelerated gradient descent method for convex and composite optimization. Smoothness and convexity constants are updated via Lyapunov…
Accelerated Mirror Descent Method through Variable and Operator Splitting
Long Chen, Hao Luo, Jingrong Wei +2
Mirror descent uses the mirror function to encode geometry and constraints, improving convergence while preserving feasibility. Accelerated Mirror Descent Methods (Acc-MD) are deri…
Optimal quantum metrology under energy constraints
Longyun Chen, Yuxiang Yang
The traditional framework of quantum metrology commonly assumes unlimited access to resources, overlooking resource constraints in realistic scenarios. As such, the optimal strateg…
Optimal quantum sampling on distributed databases
Longyun Chen, Jingcheng Liu, Penghui Yao
Quantum sampling, a fundamental subroutine in numerous quantum algorithms, involves encoding a given probability distribution in the amplitudes of a pure state. Given the hefty cos…