7 citations · 11 across the 11 of their papers we have counts for
11 papers
Learnable yet not simulable: a quantum resource theory of learning models
Xinbiao Wang, Yuxuan Du, Dacheng Tao
Quantum resource theory has sharpened our understanding of the intrinsic complexity of quantum systems, particularly their classical simulability. However, it remains unclear which…
Stochastic Pauli-path simulator for large-scale quantum optimization
Kaining Zhang, Xinbiao Wang, Kunsheng Li +4
Pauli-based simulators offer a promising route to large-scale classical simulation of quantum circuits in the low-magic regime. Yet their applicability remains largely limited to f…
AQER: a scalable and efficient data loader for digital quantum computers
Kaining Zhang, Xinbiao Wang, Yuxuan Du +2
Digital quantum computing promises to offer computational capabilities beyond the reach of classical systems, yet its capabilities are often challenged by scarce quantum resources.…
Endowing Molecular Language with Geometry Perception via Modality Compensation for High-Throughput Quantum Hamiltonian Prediction
Zhenzhong Wang, Yongjie Hou, Chenggong Huang +3
The quantum Hamiltonian is a fundamental property that governs a molecule's electronic structure and behavior, and its calculation and prediction are paramount in computational che…
Mitigating Barren Plateaus in Quantum Denoising Diffusion Probabilistic Model
Haipeng Cao, Kaining Zhang, Dacheng Tao +1
Quantum generative models exploit quantum superposition and entanglement to enhance learning efficiency for both classical and quantum data. Recently, inspired by classical diffusi…
AiDE-Q: Synthetic Labeled Datasets Can Enhance Learning Models for Quantum Property Estimation
Xinbiao Wang, Yuxuan Du, Zihan Lou +5
Quantum many-body problems are central to various scientific disciplines, yet their ground-state properties are intrinsically challenging to estimate. Recent advances in deep learn…
Artificial intelligence for representing and characterizing quantum systems
Yuxuan Du, Yan Zhu, Yuan-Hang Zhang +8
Efficient characterization of large-scale quantum systems, especially those produced by quantum analog simulators and megaquop quantum computers, poses a central challenge in quant…
Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers
Yuxuan Du, Xinbiao Wang, Naixu Guo +6
This tutorial intends to introduce readers with a background in AI to quantum machine learning (QML) -- a rapidly evolving field that seeks to leverage the power of quantum compute…
MG-Net: Learn to Customize QAOA with Circuit Depth Awareness
Yang Qian, Xinbiao Wang, Yuxuan Du +2
Quantum Approximate Optimization Algorithm (QAOA) and its variants exhibit immense potential in tackling combinatorial optimization challenges. However, their practical realization…
The curse of random quantum data
Kaining Zhang, Junyu Liu, Liu Liu +3
Quantum machine learning, which involves running machine learning algorithms on quantum devices, may be one of the most significant flagship applications for these devices. Unlike…
Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits
Yuxuan Du, Min-Hsiu Hsieh, Dacheng Tao
The vast and complicated large-qubit state space forbids us to comprehensively capture the dynamics of modern quantum computers via classical simulations or quantum tomography. Rec…