Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Berthusen, Noah F."'
Publikováno v:
Communications Physics 6, 4 (2023)
Hybrid quantum-classical embedding methods for correlated materials simulations provide a path towards potential quantum advantage. However, the required quantum resources arising from the multi-band nature of $d$ and $f$ electron materials remain la
Externí odkaz:
http://arxiv.org/abs/2203.06745
Publikováno v:
Phys. Rev. Research 4, 023097 (2022)
We demonstrate a post-quench dynamics simulation of a Heisenberg model on present-day IBM quantum hardware that extends beyond the coherence time of the device. This is achieved using a hybrid quantum-classical algorithm that propagates a state using
Externí odkaz:
http://arxiv.org/abs/2112.12654
Publikováno v:
SciPost Phys. 11, 011 (2021)
We present a deep machine learning algorithm to extract crystal field (CF) Stevens parameters from thermodynamic data of rare-earth magnetic materials. The algorithm employs a two-dimensional convolutional neural network (CNN) that is trained on magn
Externí odkaz:
http://arxiv.org/abs/2011.12911
Autor:
Gomes, Niladri, Zhang, Feng, Berthusen, Noah F., Wang, Cai-Zhuang, Ho, Kai-Ming, Orth, Peter P., Yao, Yongxin
Publikováno v:
J. Chem. Theory Comput. 2020
We develop a resource efficient step-merged quantum imaginary time evolution approach (smQITE) to solve for the ground state of a Hamiltonian on quantum computers. This heuristic method features a fixed shallow quantum circuit depth along the state e
Externí odkaz:
http://arxiv.org/abs/2006.15371
Autor:
Zhang, Feng, Gomes, Niladri, Berthusen, Noah F., Orth, Peter P., Wang, Cai-Zhuang, Ho, Kai-Ming, Yao, Yong-Xin
Publikováno v:
Phys. Rev. Research 3, 013039 (2021)
Development of resource-friendly quantum algorithms remains highly desirable for noisy intermediate-scale quantum computing. Based on the variational quantum eigensolver (VQE) with unitary coupled cluster ansatz, we demonstrate that partitioning of t
Externí odkaz:
http://arxiv.org/abs/2006.11213
Publikováno v:
npj Quantum Inf 9, 108 (2023)
Reinforcement learning has witnessed recent applications to a variety of tasks in quantum programming. The underlying assumption is that those tasks could be modeled as Markov Decision Processes (MDPs). Here, we investigate the feasibility of this as
Externí odkaz:
http://arxiv.org/abs/1912.12002
Autor:
Mukherjee, Anirban1 (AUTHOR), Berthusen, Noah F.1,2,3 (AUTHOR), Getelina, João C.1 (AUTHOR), Orth, Peter P.1,4 (AUTHOR) porth@iastate.edu, Yao, Yong-Xin1,4 (AUTHOR) ykent@iastate.edu
Publikováno v:
Communications Physics. 1/4/2023, Vol. 6 Issue 1, p1-15. 15p.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.