Share Email Print

Proceedings Paper

Bayesian inference for OPC modeling
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The use of optical proximity correction (OPC) demands increasingly accurate models of the photolithographic process. Model building and inference techniques in the data science community have seen great strides in the past two decades which make better use of available information. This paper aims to demonstrate the predictive power of Bayesian inference as a method for parameter selection in lithographic models by quantifying the uncertainty associated with model inputs and wafer data. Specifically, the method combines the model builder's prior information about each modelling assumption with the maximization of each observation's likelihood as a Student's t-distributed random variable. Through the use of a Markov chain Monte Carlo (MCMC) algorithm, a model's parameter space is explored to find the most credible parameter values. During parameter exploration, the parameters' posterior distributions are generated by applying Bayes' rule, using a likelihood function and the a priori knowledge supplied. The MCMC algorithm used, an affine invariant ensemble sampler (AIES), is implemented by initializing many walkers which semiindependently explore the space. The convergence of these walkers to global maxima of the likelihood volume determine the parameter values' highest density intervals (HDI) to reveal champion models. We show that this method of parameter selection provides insights into the data that traditional methods do not and outline continued experiments to vet the method.

Paper Details

Date Published: 15 March 2016
PDF: 6 pages
Proc. SPIE 9780, Optical Microlithography XXIX, 97800I (15 March 2016); doi: 10.1117/12.2219707
Show Author Affiliations
Andrew Burbine, Rochester Institute of Technology (United States)
Mentor Graphics Corp. (United States)
John Sturtevant, Mentor Graphics Corp. (United States)
David Fryer, Mentor Graphics Corp. (United States)
Bruce W. Smith, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 9780:
Optical Microlithography XXIX
Andreas Erdmann; Jongwook Kye, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?