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 › peer-review

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

ASJC Scopus subject areas

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

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10.1016/j.elspec.2019.05.001

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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, Article 146852. https://doi.org/10.1016/j.elspec.2019.05.001

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

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

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.",

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

note = "Publisher Copyright: {\textcopyright} 2019 Elsevier B.V.",

year = "2020",

month = jan,

doi = "10.1016/j.elspec.2019.05.001",

language = "English (US)",

volume = "238",

journal = "Journal of Electron Spectroscopy and Related Phenomena",

issn = "0368-2048",

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T1 - Second derivative analysis and alternative data filters for multi-dimensional spectroscopies

T2 - A Fourier-space perspective

AU - Li, Rongjie

AU - Zhang, Xiaoni

AU - Miao, Lin

AU - Stewart, Luca

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

PY - 2020/1

Y1 - 2020/1

N2 - 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.

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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JO - Journal of Electron Spectroscopy and Related Phenomena

JF - Journal of Electron Spectroscopy and Related Phenomena

M1 - 146852

ER -

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

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