Quantitative analysis and optimization of magnetization precession initiated by ultrafast optical pulses

Dustin M. Lattery, Jie Zhu, Delin Zhang, Jian Ping Wang, Paul A. Crowell, Xiaojia Wang

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12 Scopus citations


Magnetic storage and magnetic memory have recently shifted towards the use of magnetic thin films with large perpendicular magnetic anisotropy (PMA) to simultaneously satisfy the requirements in storage density and thermal stability. Understanding the magnetic switching process and its dependence on the Gilbert damping (α) of materials with large PMA is crucial for developing low-power consumption, fast-switching, and high-thermal stability devices. The need to quantify α of materials with large PMA has resulted in the development of the all-optical ultrafast Time-Resolved Magneto-optical Kerr Effect (TR-MOKE) technique. While TR-MOKE has demonstrated its capability of capturing magnetization dynamics of materials with large PMA, a quantitative analysis regarding the operational optimization of this emerging technique is still lacking. In this paper, we discuss the dependence of the TR-MOKE signal on the magnitude and angle of the applied field, by utilizing a numerical algorithm based on the Landau-Lifshitz-Gilbert equation. The optimized operational conditions that produce the largest TR-MOKE signals are predicted. As an experimental verification, we conduct TR-MOKE measurements on a representative sample of a tungsten-seeded CoFeB PMA thin film to show the excellent agreement of the model prediction with measurements. Our analysis results in a better understanding of the external field influence on the magnetization precession processes. The results of this work can also provide guidance on selecting operational conditions of the TR-MOKE technique to achieve optimal signal-to-noise ratios and thus more accurate measurements of magnetization dynamics.

Original languageEnglish (US)
Article number162405
JournalApplied Physics Letters
Issue number16
StatePublished - Oct 15 2018

Bibliographical note

Funding Information:
This work was supported by C-SPIN (Award No. 2013-MA-2381), one of the six centers of STARnet, a Semiconductor Research Corporation Program, sponsored by MARCO and DARPA.

Publisher Copyright:
© 2018 Author(s).


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