Second derivative analysis and alternative data filters for multi-dimensional spectroscopies: A Fourier-space perspective

Rongjie Li; Xiaoni Zhang; Lin Miao; Luca Stewart; Erica Kotta; Dong Qian; Konstantine Kaznatcheev; Jerzy T. Sadowski; Elio Vescovo; Abdullah Alharbi; Ting Wu; Takashi Taniguchi; Kenji Watanabe; Davood Shahrjerdi; L. Andrew Wray

doi:10.1016/j.elspec.2019.05.001

Second derivative analysis and alternative data filters for multi-dimensional spectroscopies: A Fourier-space perspective

Rongjie Li, Xiaoni Zhang, Lin Miao, Luca Stewart, Erica Kotta, Dong Qian, Konstantine Kaznatcheev, Jerzy T. Sadowski, Elio Vescovo, Abdullah Alharbi, Ting Wu, Takashi Taniguchi, Kenji Watanabe, Davood Shahrjerdi, L. Andrew Wray

Electrical and Computer Engineering

Research output: Contribution to journal › Article

Abstract

The second derivative image (SDI) method is widely applied to sharpen dispersive data features in multi-dimensional spectroscopies such as angle resolved photoemission spectroscopy (ARPES). Here, the SDI function is represented in Fourier space, where it has the form of a multi-band pass filter. The interplay of the SDI procedure with undesirable noise and background features in ARPES data sets is reviewed, and it is shown that final image quality can be improved by eliminating higher Fourier harmonics of the SDI filter. We then discuss extensions of SDI-like band pass filters to higher dimensional data sets, and how one can create even more effective filters with some a priori knowledge of the spectral features.

Original language	English (US)
Article number	146852
Journal	Journal of Electron Spectroscopy and Related Phenomena
Volume	238
DOIs	https://doi.org/10.1016/j.elspec.2019.05.001
State	Published - Jan 2020

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ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Radiation
Atomic and Molecular Physics, and Optics
Condensed Matter Physics
Spectroscopy
Physical and Theoretical Chemistry

Cite this

Li, R., Zhang, X., Miao, L., Stewart, L., Kotta, E., Qian, D., Kaznatcheev, K., Sadowski, J. T., Vescovo, E., Alharbi, A., Wu, T., Taniguchi, T., Watanabe, K., Shahrjerdi, D., & Wray, L. A. (2020). Second derivative analysis and alternative data filters for multi-dimensional spectroscopies: A Fourier-space perspective. Journal of Electron Spectroscopy and Related Phenomena, 238, [146852]. https://doi.org/10.1016/j.elspec.2019.05.001

Second derivative analysis and alternative data filters for multi-dimensional spectroscopies : A Fourier-space perspective. / Li, Rongjie; Zhang, Xiaoni; Miao, Lin; Stewart, Luca; Kotta, Erica; Qian, Dong; Kaznatcheev, Konstantine; Sadowski, Jerzy T.; Vescovo, Elio; Alharbi, Abdullah; Wu, Ting; Taniguchi, Takashi; Watanabe, Kenji; Shahrjerdi, Davood; Wray, L. Andrew.

In: Journal of Electron Spectroscopy and Related Phenomena, Vol. 238, 146852, 01.2020.

Research output: Contribution to journal › Article

Li, R, Zhang, X, Miao, L, Stewart, L, Kotta, E, Qian, D, Kaznatcheev, K, Sadowski, JT, Vescovo, E, Alharbi, A, Wu, T, Taniguchi, T, Watanabe, K, Shahrjerdi, D & Wray, LA 2020, 'Second derivative analysis and alternative data filters for multi-dimensional spectroscopies: A Fourier-space perspective', Journal of Electron Spectroscopy and Related Phenomena, vol. 238, 146852. https://doi.org/10.1016/j.elspec.2019.05.001

Li, Rongjie ; Zhang, Xiaoni ; Miao, Lin ; Stewart, Luca ; Kotta, Erica ; Qian, Dong ; Kaznatcheev, Konstantine ; Sadowski, Jerzy T. ; Vescovo, Elio ; Alharbi, Abdullah ; Wu, Ting ; Taniguchi, Takashi ; Watanabe, Kenji ; Shahrjerdi, Davood ; Wray, L. Andrew. / Second derivative analysis and alternative data filters for multi-dimensional spectroscopies : A Fourier-space perspective. In: Journal of Electron Spectroscopy and Related Phenomena. 2020 ; Vol. 238.

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abstract = "The second derivative image (SDI) method is widely applied to sharpen dispersive data features in multi-dimensional spectroscopies such as angle resolved photoemission spectroscopy (ARPES). Here, the SDI function is represented in Fourier space, where it has the form of a multi-band pass filter. The interplay of the SDI procedure with undesirable noise and background features in ARPES data sets is reviewed, and it is shown that final image quality can be improved by eliminating higher Fourier harmonics of the SDI filter. We then discuss extensions of SDI-like band pass filters to higher dimensional data sets, and how one can create even more effective filters with some a priori knowledge of the spectral features.",

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AU - Li, Rongjie

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AU - Kotta, Erica

AU - Qian, Dong

AU - Kaznatcheev, Konstantine

AU - Sadowski, Jerzy T.

AU - Vescovo, Elio

AU - Alharbi, Abdullah

AU - Wu, Ting

AU - Taniguchi, Takashi

AU - Watanabe, Kenji

AU - Shahrjerdi, Davood

AU - Wray, L. Andrew

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AB - The second derivative image (SDI) method is widely applied to sharpen dispersive data features in multi-dimensional spectroscopies such as angle resolved photoemission spectroscopy (ARPES). Here, the SDI function is represented in Fourier space, where it has the form of a multi-band pass filter. The interplay of the SDI procedure with undesirable noise and background features in ARPES data sets is reviewed, and it is shown that final image quality can be improved by eliminating higher Fourier harmonics of the SDI filter. We then discuss extensions of SDI-like band pass filters to higher dimensional data sets, and how one can create even more effective filters with some a priori knowledge of the spectral features.

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10.1016/j.elspec.2019.05.001