Symbol sigma_dose
sigmose is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.
Read this term in its guide →Published equation contexts
Why this formula appears here
Frederick Chen’s analysis of a real 3-nanometer via layer measured this directly: at typical exposure conditions (roughly 60–89 mJ/cm² depending on resist chemistry), the observed missing-via rate came in at the parts-per-million level — “many orders of magnitude higher than expected from basic estimates” that treat each pixel’s exposure as statistically independent [ 3 ] . The gap between the naive estimate and the measured rate is explained by correlation between neighboring exposed pixels: a defect does not need every pixel in a feature to fail independently, it needs a contiguous cluster of neighboring pixels to under- or over-expose together, which happens far more often than…
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Symbol N_photons
hotons occurs below the fraction bar. The quantity above the bar is divided by this expression; zero is excluded as a denominator.
Read this term in its guide →Denominator: sqrtN_photons
The complete quantity below the fraction bar; it must be nonzero for this division.
Read this term in its guide →How to interpret it
With a fixed numerator, increasing a nonzero denominator reduces the fraction.
Research cited beside this formula
Published contexts (1)
A symbol can carry a different meaning in another article. Each occurrence keeps its own guide and term definitions.
Equation 1 · Semiconductors
Advanced Semiconductor Fabrication in Practice: An Advanced Technical Guide
This mathematical expression combines the displayed quantities; its precise role follows from the surrounding article text.
Frederick Chen’s analysis of a real 3-nanometer via layer measured this directly: at typical exposure conditions (roughly 60–89 mJ/cm² depending on resist chemistry), the observed missing-via rate came in at the parts-per-million level — “many orders of magnitude higher than expected from basic estimates” that treat each pixel’s exposure as statistically independent [ 3 ] . The gap between the naive estimate and the measured rate is explained by correlation between neighboring exposed pixels: a defect does not need every pixel in a feature to fail independently, it needs a contiguous cluster of neighboring pixels to under- or over-expose together, which happens far more often than…
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