2 citations · 3 across the 8 of their papers we have counts for
8 papers
When AI meets quantum information: A comprehensive review
Min Chen, Yu Gan, Xin Jin +15
Artificial intelligence (AI) and quantum information (QI) are rapidly co-evolving. AI is becoming a practical tool for learning, designing, controlling, and verifying quantum syste…
Infeasibility Aware Large Language Models for Combinatorial Optimization
Yakun Wang, Min Chen, Zeguan Wu +3
Large language models (LLMs) are increasingly explored for NP-hard combinatorial optimization problems, but most existing methods emphasize feasible-instance solution generation an…
Artificial Entanglement in the Fine-Tuning of Large Language Models
Min Chen, Zihan Wang, Canyu Chen +3
Large language models (LLMs) can be adapted to new tasks using parameter-efficient fine-tuning (PEFT) methods that modify only a small number of trainable parameters, often through…
An Analytic Theory of Quantum Imaginary Time Evolution
Min Chen, Bingzhi Zhang, Quntao Zhuang +1
Quantum imaginary time evolution (QITE) algorithm is one of the most promising variational quantum algorithms (VQAs), bridging the current era of Noisy Intermediate-Scale Quantum d…
Symbolic Analysis of Grover Search Algorithm via Chain-of-Thought Reasoning and Quantum-Native Tokenization
Min Chen, Jinglei Cheng, Pingzhi Li +3
Understanding the high-level conceptual structure of quantum algorithms from their low-level circuit representations is a critical task for verification, debugging, and education.…
GroverGPT: A Large Language Model with 8 Billion Parameters for Quantum Searching
Haoran Wang, Pingzhi Li, Min Chen +3
Quantum computing is an exciting non-Von Neumann paradigm, offering provable speedups over classical computing for specific problems. However, the practical limits of classical sim…
Towards Symmetry-Aware Efficient Simulation of Quantum Systems and Beyond
Min Chen, Minzhao Liu, Changhun Oh +3
The efficient simulation of complex quantum systems remains a central challenge due to the exponential growth of Hilbert space with system size. Tensor network methods have long be…
Catapult Dynamics and Phase Transitions in Quadratic Nets
David Meltzer, Min Chen, Junyu Liu
Neural networks trained with gradient descent can undergo non-trivial phase transitions as a function of the learning rate. In \cite{lewkowycz2020large} it was discovered that wide…