Image-noise effect on discrete power spectrum of line-edge and line-width roughness

Atsushi Hiraiwa, Akio Nishida

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

The authors investigated the effect of scanning-electron-microscope image noise on the accuracy of line-edge-roughness and line-widthroughness (LER/LWR) statistics extracted from power spectral densities (PSDs). To do this, they numerically prepared pseudo-experimental PSDs of LWR using the Monte Carlo (MC) method. The estimation error n decreased with the total number NALL of width data points in the same way as that observed in the absence of the image noise. n first increased gradually with the image-noise intensity R but markedly when R went beyond the threshold value Rth determined by the ratio of the sampling interval δy to the correlation length δy. The PSDs with these Rth's had the same maximum-to-minimum ratio γ (= 10 in this study). The authors approximated n by BNALL-3/4(1+g(R,δ;- 3/8 [1 + g(R;δy/epsi;γ where B is 49. They also empirically determined the functional form of g(R;δy/γεγ). Because these functions well fitted massive MC simulation results, they provide guidelines for setting up analysis conditions for securing arbitrarily prescribed accuracy.

Original languageEnglish
Article number016602
JournalJapanese Journal of Applied Physics
Volume50
Issue number1
DOIs
Publication statusPublished - 2011 Jan
Externally publishedYes

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Power spectral density
Power spectrum
Linewidth
power spectra
roughness
Surface roughness
noise intensity
Error analysis
Monte Carlo method
Monte Carlo methods
Electron microscopes
electron microscopes
sampling
Statistics
statistics
Sampling
intervals
Scanning
scanning
thresholds

ASJC Scopus subject areas

  • Engineering(all)
  • Physics and Astronomy(all)

Cite this

Image-noise effect on discrete power spectrum of line-edge and line-width roughness. / Hiraiwa, Atsushi; Nishida, Akio.

In: Japanese Journal of Applied Physics, Vol. 50, No. 1, 016602, 01.2011.

Research output: Contribution to journalArticle

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