699 citations
- Nvidia (United Kingdom)GB27 papers
- University of WashingtonUS10 papers
- California Institute of TechnologyUS9 papers
- Stanford UniversityUS9 papers
- Argonne National LaboratoryUS8 papers
- Georgia Institute of TechnologyUS8 papers
- Lawrence Berkeley National LaboratoryUS8 papers
- Seattle UniversityUS8 papers
- University of TorontoCA8 papers
- Oak Ridge National LaboratoryUS7 papers
- University of California, BerkeleyUS7 papers
- University of Illinois Urbana-ChampaignUS7 papers
14 papers · 1 filter
A Model Context Protocol Server for Quantum Execution in Hybrid Quantum-HPC Environments
Masaki Shiraishi, Ikko Hamamura, Tatsuya Ishigaki +1
The integration of large language models (LLMs) into scientific research is accelerating the realization of autonomous ``AI Scientists.'' While recent advancements have empowered A…
TensorHyper-VQC: A Tensor-Train-Guided Hypernetwork for Robust and Scalable Variational Quantum Computing
Jun Qi, Chao-Han Huck Yang, Pin-Yu Chen +1
Variational Quantum Computing (VQC) faces fundamental scalability barriers, primarily due to barren plateaus and sensitivity to quantum noise. To address these challenges, we intro…
Quantum-Classical Auxiliary Field Quantum Monte Carlo with Matchgate Shadows on Trapped Ion Quantum Computers
Luning Zhao, Joshua J. Goings, Willie Aboumrad +38
We demonstrate an end-to-end workflow to model chemical reaction barriers with the quantum-classical auxiliary field quantum Monte Carlo (QC-AFQMC) algorithm with quantum tomograph…
A Perspective on Quantum Computing Applications in Quantum Chemistry using 25--100 Logical Qubits
Yuri Alexeev, Victor S. Batista, Nicholas Bauman +27
The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owin…
Synthesis of discrete-continuous quantum circuits with multimodal diffusion models
Florian Fürrutter, Zohim Chandani, Ikko Hamamura +2
Efficiently compiling quantum operations remains a major bottleneck in scaling quantum computing. Today's state-of-the-art methods achieve low compilation error by combining search…
Quantum Walks-Based Adaptive Distribution Generation with Efficient CUDA-Q Acceleration
Yen-Jui Chang, Wei-Ting Wang, Chen-Yu Liu +2
We present a novel Adaptive Distribution Generator that leverages a quantum walks-based approach to generate high precision and efficiency of target probability distributions. Our…