Machine-learning approach for constructing control landscape maps of three-dimensional alignment of asymmetric-top molecules-Reference-Cited by-同舟云学术

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Machine-learning approach for constructing control landscape maps of three-dimensional alignment of asymmetric-top molecules

Published:2020-07-14 Issue:2 Volume:153 Page:024120
ISSN:0021-9606
Container-title:The Journal of Chemical Physics
language:en
Short-container-title:J. Chem. Phys.

Author:

Namba Tomotaro¹,Yoshida Masataka¹,Ohtsuki Yukiyoshi¹^ORCID

Affiliation:

1. Department of Chemistry, Graduate School of Science, Tohoku University, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8578, Japan

Funder

Joint Usage/Research Program on Zero-Emission Energy Research

Research Center for Computational Science, Okazaki

Grant-in-Aid for Scientific Research

Grant-in-Aid for JSPS Fellows

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0012303

Reference17 articles.

1. Nonadiabatic Alignment by Intense Pulses. Concepts, Theory, and Directions

2. Quantum control of molecular rotation

3. Field-Free Three Dimensional Molecular Axis Alignment

4. Field-Free Three-Dimensional Alignment of Polyatomic Molecules

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