41 citations · 102 across the 27 of their papers we have counts for
27 papers
Simulation of Lindbladian dynamics via adaptive variational quantum trajectory compression
Huan-Yu Liu, Cheng Xue, Yun-Jie Wang +5
Quantum simulation of open quantum systems in the noisy intermediate-scale quantum (NISQ) era is hindered by the non-unitary nature of dissipative dynamics and the limited quantum…
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…
Quantum Simulation of Non-Hermitian Special Functions and Dynamics via Contour-based Matrix Decomposition
Chao Wang, Huan-Yu Liu, Cheng Xue +4
Simulating non-Hermitian dynamics on quantum computers is often hindered by the decay of success probability and the instability of non-diagonalizable matrices. Here, we present co…
Variational quantum simulation of many-body dissipative dynamics on a superconducting quantum processor
Huan-Yu Liu, Tai-Ping Sun, Zhao-Yun Chen +7
Open quantum systems host a wide range of intriguing phenomena, yet their simulation on well-controlled quantum devices is challenging, owing to the exponential growth of the Hilbe…
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…
Accelerating Fermionic System Simulation on Quantum Computers
Qing-Song Li, Jiaxuan Zhang, Huan-Yu Liu +3
A potential approach for demonstrating quantum advantage is using quantum computers to simulate fermionic systems. Quantum algorithms for fermionic system simulation usually involv…
Experimental robustness benchmarking of quantum neural networks on a superconducting quantum processor
Hai-Feng Zhang, Zhao-Yun Chen, Peng Wang +17
Quantum machine learning (QML) models, like their classical counterparts, are vulnerable to adversarial attacks, hindering their secure deployment. Here, we report the first system…
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…
Quantum homotopy analysis method with quantum-compatible linearization for nonlinear partial differential equations
Cheng Xue, Xiao-Fan Xu, Xi-Ning Zhuang +8
Nonlinear partial differential equations (PDEs) are crucial for modeling complex fluid dynamics and are foundational to many computational fluid dynamics (CFD) applications. Howeve…
Quantum Computational Insurance and Actuarial Science
Huan-Yu Liu, Xi-Ning Zhuang, Chao Wang +7
In recent years, quantum computation has been rapidly advancing, driving a technological revolution with significant potential across various sectors, particularly in finance. Desp…
Scalable Constant-Time Logical Gates for Large-Scale Quantum Computation Using Window-Based Correlated Decoding
Jiaxuan Zhang, Zhao-Yun Chen, Jia-Ning Li +6
Large-scale quantum computation requires to be performed in the fault-tolerant manner. One crucial challenge of fault-tolerant quantum computing (FTQC) is reducing the overhead of…
Statistics-Informed Parameterized Quantum Circuit via Maximum Entropy Principle for Data Science and Finance
Xi-Ning Zhuang, Zhao-Yun Chen, Cheng Xue +7
Quantum machine learning has demonstrated significant potential in solving practical problems, particularly in statistics-focused areas such as data science and finance. However, c…
Simulation of open quantum systems on universal quantum computers
Huan-Yu Liu, Xiaoshui Lin, Zhao-Yun Chen +8
The rapid development of quantum computers has enabled demonstrations of quantum advantages on various tasks. However, real quantum systems are always dissipative due to their inev…
Towards Fault-Tolerant Quantum Deep Learning: Designing and Analyzing Quantum ResNet and Transformer with Quantum Arithmetic and Linear Algebra Primitives
Xiao-Fan Xu, Cheng Xue, Xi-Ning Zhuang +8
Achieving a practical quantum speedup for deep neural networks (DNNs) remains a central yet elusive goal, hindered by the dual challenges of constructing deep architectures and the…
CAMEL: Physically Inspired Crosstalk-Aware Mapping and gatE scheduLing for Frequency-Tunable Quantum Chips
Bin-han Lu, Peng Wang, Zhao-yun Chen +5
Crosstalk represents a formidable obstacle in quantum computing. When quantum gates are executed parallelly, the resonance of qubit frequencies can lead to residual coupling, compr…
Can Variational Quantum Algorithms Demonstrate Quantum Advantages? Time Really Matters
Huan-Yu Liu, Zhao-Yun Chen, Tai-Ping Sun +3
Applying low-depth quantum neural networks (QNNs), variational quantum algorithms (VQAs) are both promising and challenging in the noisy intermediate-scale quantum (NISQ) era: Desp…
Hardware-Efficient Quantum Random Access Memory Design with a Native Gate Set on Superconducting Platforms
Yun-Jie Wang, Sheng Zhang, Tai-Ping Sun +9
Quantum Random Access Memory (QRAM) is a critical component for enabling data queries in superposition, which is the cornerstone of quantum algorithms. Among various QRAM architect…
Data-driven Quantum Dynamical Embedding Method for Long-term Prediction on Near-term Quantum Computers
Tai-Ping Sun, Zhao-Yun Chen, Cheng Xue +7
The increasing focus on long-term time series prediction across various fields has been significantly strengthened by advancements in quantum computation. In this paper, we introdu…
Scalable Program Implementation and Simulation of the Large-Scale Quantum Algorithm: Quantum Linear Solver and Beyond
Zhao-Yun Chen, Cheng Xue, Xi-Ning Zhuang +5
Program implementation and simulation are essential for research in the field of quantum algorithms. However, complex and large-scale quantum algorithms can pose challenges for exi…
Efficient and Error-Resilient Data Access Protocols for a Limited-Sized Quantum Random Access Memory
Zhao-Yun Chen, Cheng Xue, Yun-Jie Wang +8
Quantum Random Access Memory (QRAM) is a critical component for loading classical data into quantum computers. While constructing a practical QRAM presents several challenges, incl…
Mitigating Barren Plateaus with Transfer-learning-inspired Parameter Initializations
Huan-Yu Liu, Tai-Ping Sun, Yu-Chun Wu +2
Variational quantum algorithms (VQAs) are widely applied in the noisy intermediate-scale quantum era and are expected to demonstrate quantum advantage. However, training VQAs faces…