20 citations · 38 across the 13 of their papers we have counts for
13 papers
QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning
Songxin Qu, Tai-Ping Sun, Yun-Jie Wang +8
Large language models (LLMs) show strong capabilities in general reasoning but typically lack reliability in scientific domains like quantum mechanics, which demand strict adherenc…
A Pathway to Practical Quantum Advantage in Solving Navier-Stokes Equations
Xi-Ning Zhuang, Zhao-Yun Chen, Ming-Yang Tan +12
The advent of fault-tolerant quantum computing (FTQC) promises to tackle classically intractable problems. A key milestone is solving the Navier-Stokes equations (NSE), which has r…
PolyQROM: Orthogonal-Polynomial-Based Quantum Reduced-Order Model for Flow Field Analysis
Yu Fang, Cheng Xue, Tai-Ping Sun +10
Quantum computing promises exponential acceleration for fluid flow simulations, yet the measurement overhead required to extract flow features from quantum-encoded flow field data…
Quantum-Enhanced LLM Efficient Fine Tuning
Xiaofei Kong, Lei Li, Zhaoyun Chen +10
Low-Rank Adaptation (LoRA) enables efficient fine-tuning of pre-trained language models through low-rank matrix approximation, achieving effectiveness in many scenarios. However, i…
SparQSim: Simulating Scalable Quantum Algorithms via Sparse Quantum State Representations
Tai-Ping Sun, Zhao-Yun Chen, Yun-Jie Wang +6
Efficient simulation of large-scale quantum algorithms is pivotal yet challenging due to the exponential growth of the state space inherent in both Schödinger-based and Feynman-bas…
Refined Criteria for QRAM Error Suppression via Efficient Large-Scale QRAM Simulator
Yun-Jie Wang, Tai-Ping Sun, Xi-Ning Zhuang +6
Quantum random access memory (QRAM) is a critical primitive for quantum algorithms that require data lookup in superposition, but its lack of fault tolerance poses a major obstacle…