Chufan Lyu

Quantum locally linear embedding for nonlinear dimensionality reduction

2019 · arXiv (Cornell University)

Reducing the dimension of nonlinear data is crucial in data processing and visualization. The locally linear embedding algorithm (LLE) is specifically a representative nonlinear dimensionality reduction method with well maintaining the original manifold structure. In …

Symmetry enhanced variational quantum spin eigensolver

2023 · Quantum

The variational quantum-classical algorithms are the most promising approach for achieving quantum advantage on near-term quantum simulators. Among these methods, the variational quantum eigensolver has attracted a lot of attention in recent years. While it …

Variational simulation of higher-spin systems on qubit-based quantum simulators

2026 · Physical Review Research

Qubit-based quantum simulators naturally target two-level systems, whereas many quantum many-body problems are intrinsically <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"> <a:mi>d</a:mi> </a:math> level. Encodings from qudits to qubits then enlarge the Hilbert space and can introduce unphysical states that …

MindSpore Quantum: A User-Friendly, High-Performance, and AI-Compatible Quantum Computing Framework

2024 · arXiv (Cornell University)

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) algorithms. Leveraging the robust support of MindSpore, an advanced open-source deep learning …