most citedOutput Prediction of Quantum Circuits based on Graph Neural Networks

4 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

quant-ph2026

Hardware-Aware Quantum Kernel Design Based on Graph Neural Networks

Fanxu Meng, Yuxiang Liu, Lu Wang +3

Quantum kernels hold significant promise for achieving computational advantages in quantum machine learning (QML), yet their effectiveness critically depends on the design of expre…

quant-ph20264 cited

Output Prediction of Quantum Circuits based on Graph Neural Networks

Yuxiang Liu, Fanxu Meng, Lu Wang +3

The output prediction of quantum circuits is a formidably challenging task imperative in developing quantum devices. Motivated by the natural graph representation of quantum circui…

quant-ph2025

Shot and Architecture Adaptive Subspace Variational Quantum Eigensolver for Microwave Simulation

Zhixiu Han, Fanxu Meng, Weidong Li +2

Quantum computing offers a promising paradigm for electromagnetic eigenmode analysis, enabling compact representations of complex field interactions and potential exponential speed…

quant-ph2025

Quantum-Based Self-Attention Mechanism for Hardware-Aware Differentiable Quantum Architecture Search

Yuxiang Liu, Sixuan Li, Fanxu Meng +2

The automated design of parameterized quantum circuits for variational algorithms in the NISQ era faces a fundamental limitation, as conventional differentiable architecture search…

quant-ph2025

Quantum Approximate Optimization Algorithm for Maximum Likelihood Detection in Massive MIMO

Yuxiang Liu, Fanxu Meng, Zetong Li +2

In the massive multiple-input and multiple-output (Massive MIMO) systems, the maximum likelihood (ML) detection problem is NP-hard and becoming classically intricate with the numbe…