2 citations · 4 across the 2 of their papers we have counts for
6 papers
Quantum Gradient Algorithm for General Polynomials
Keren Li, Pan Gao, Shijie Wei +2
Gradient-based algorithms, popular strategies to optimization problems, are essential for many modern machine-learning techniques. Theoretically, extreme points of certain cost fun…
Dynamical-Invariant-based Holonomic Quantum Gates: Theory and Experiment
Yingcheng Li, Tao Xin, Chudan Qiu +5
Among existing approaches to holonomic quantum computing, the adiabatic holonomic quantum gates (HQGs) suffer errors due to decoherence, while the non-adiabatic HQGs either require…
Optimizing a Polynomial Function on a Quantum Simulator
Keren Li, Shijie Wei, Feihao Zhang +5
Gradient descent method, as one of the major methods in numerical optimization, is the key ingredient in many machine learning algorithms. As one of the most fundamental way to sol…
Implementation of Multiparty quantum clock synchronization
Xiangyu Kong, Tao Xin, ShiJie Wei +4
The quantum clock synchronization (QCS) is to measure the time difference among the spatially separated clocks with the principle of quantum mechanics. The first QCS algorithm prop…
Optimal experiment design for quantum state tomography
Jun Li, Shilin Huang, Zhihuang Luo +3
Quantum state tomography is an indispensable but costly part of many quantum experiments. Typically, it requires measurements to be carried in a number of different settings on a f…
Quantum State and Process Tomography via Adaptive Measurements
Hengyan Wang, Wenqiang Zheng, Nengkun Yu +9
We investigate quantum state tomography (QST) for pure states and quantum process tomography (QPT) for unitary channels via measurements. For a quantum system with a …