40 citations · 101 across the 9 of their papers we have counts for
9 papers
Variational Quantum Dimension Reduction for Recurrent Quantum Models
Chufan Lyu, Ximing Wang, Mile Gu +2
Recurrent quantum models (RQMs) realize sequential quantum processes through repeated application of a unitary operation on a memory system coupled with a series of output register…
MindSpore Quantum: A User-Friendly, High-Performance, and AI-Compatible Quantum Computing Framework
Xusheng Xu, Jiangyu Cui, Zidong Cui +36
We introduce MindSpore Quantum, a pioneering hybrid quantum-classical framework with a primary focus on the design and implementation of noisy intermediate-scale quantum (NISQ) alg…
Variational simulation of higher-spin systems on qubit-based quantum simulators
Chufan Lyu, Zuoheng Zou, Xusheng Xu +2
Qubit-based quantum simulators naturally target two-level systems, whereas many quantum many-body problems are intrinsically level. Encodings from qudits to qubits then enlarge…
Multi-Level Variational Spectroscopy using a Programmable Quantum Simulator
Zhikun Han, Chufan Lyu, Yuxuan Zhou +17
Energy spectroscopy is a powerful tool with diverse applications across various disciplines. The advent of programmable digital quantum simulators opens new possibilities for condu…
Variational quantum simulation of long-range interacting systems
Chufan Lyu, Xiaoyu Tang, Junning Li +3
Current quantum simulators suffer from multiple limitations such as short coherence time, noisy operations, faulty readout and restricted qubit connectivity in some platforms. Vari…
Symmetry enhanced variational quantum spin eigensolver
Chufan Lyu, Xusheng Xu, Man-Hong Yung +1
The variational quantum-classical algorithms are the most promising approach for achieving quantum advantage on near-term quantum simulators. Among these methods, the variational q…
Accelerated variational algorithms for digital quantum simulation of many-body ground states
Chufan Lyu, Victor Montenegro, Abolfazl Bayat
One of the key applications for the emerging quantum simulators is to emulate the ground state of many-body systems, as it is of great interest in various fields from condensed mat…
Quantum transfer component analysis for domain adaptation
Xi He, Chufan Lyu, Min-Hsiu Hsieh +1
Domain adaptation, a crucial sub-field of transfer learning, aims to utilize known knowledge of one data set to accomplish tasks on another data set. In this paper, we perform one…
Quantum locally linear embedding for nonlinear dimensionality reduction
Xi He, Li Sun, Chufan Lyu +1
Reducing the dimension of nonlinear data is crucial in data processing and visualization. The locally linear embedding algorithm (LLE) is specifically a representative nonlinear di…