.png){kind=icon}
返回
Evaluating a quantum-classical quantum Monte Carlo algorithm with Matchgate shadows
.png){kind=icon}
OA
AI
DOI：10.1103/PhysRevResearch.6.043063.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Solving the electronic structure problem of molecules and solids to high accuracy is a major challenge in quantum chemistry and condensed matter physics. The rapid emergence and development of quantum computers offer a promising route to systematically tackle this problem. Recent work by [Huggins et al., Nature (London) 603, 416 (2022)] proposed a hybrid quantum-classical quantum Monte Carlo (QC-QMC) algorithm using Clifford shadows to determine the ground state of a Fermionic Hamiltonian. This approach displayed inherent noise resilience and the potential for improved accuracy compared to its purely classical counterpart. Nevertheless, the use of Clifford shadows introduces an exponentially scaling postprocessing cost. In this work, we investigate an improved QC-QMC scheme utilizing the recently developed Matchgate shadows technique [Commun. Math. Phys. 404, 629 (2023)], which removes the aforementioned exponential bottleneck. We observe from experiments on quantum hardware that the use of Matchgate shadows in QC-QMC is inherently noise robust. We show that this noise resilience has a more subtle origin than in the case of Clifford shadows. Nevertheless, we find that classical postprocessing, while asymptotically efficient, requires hours of runtime on thousands of classical CPUs for even the smallest chemical systems, presenting a major challenge to the scalability of the algorithm.
Keyword:
EQUIVALENCE
STATES
期刊
IF:
4.2
论文数:
7.6K
被引数:
2.7W
机构
引用论文
Evolution of Generative Adversarial Networks Using PSO for Synthesis of COVID-19 Chest X-ray Images
PREAI
分享收藏Determining eigenstates and thermal states on a quantum computer using quantum imaginary time evolution.png)
NATURE PHYSICS
NATURE PHYSICSIF18.4
PREAI
分享收藏A variational eigenvalue solver on a photonic quantum processor光子量子处理器上的变分特征值求解器NATURE COMMUNICATIONS
OAAI
NATURE COMMUNICATIONSIF15.7
OAAI分享收藏
查看更多内容