Accession Number:

ADA624655

Title:

A Sparsity-based Framework for Resolution Enhancement in Optical Fault Analysis of Integrated Circuits

Descriptive Note:

Doctoral thesis

Corporate Author:

BOSTON UNIV MA COLL OF ENGINEERING

Personal Author(s):

Report Date:

2015-01-01

Pagination or Media Count:

223.0

Abstract:

The increasing density and smaller length scales in integrated circuits ICs create resolution challenges for optical failure analysis techniques. Due to ip-chip bonding and dense metal layers on the front side, optical analysis of ICs is restricted to backside imaging through the silicon substrate, which limits the spatial resolution due to the minimum wavelength of transmission and refraction at the planar interface. The stateof- the-art backside analysis approach is to use aplanatic solid immersion lenses in order to achieve the highest possible numerical aperture of the imaging system. Signal processing algorithms are essential to complement the optical microscopy e orts to increase resolution through hardware modi cations in order to meet the resolution requirements of new IC technologies. The focus of this thesis is the development of sparsity-based image reconstruction techniques to improve resolution of static IC images and dynamic optical measurements of device activity. A physics-based observation model is exploited in order to take advantage of polarization diversity in high numerical aperture systems. Multiplepolarization observation data are combined to produce a single enhanced image with higher resolution. In the static IC image case, two sparsity paradigms are considered. The rst approach, referred to as analysis-based sparsity, creates enhanced resolution imagery by solving a linear inverse problem while enforcing sparsity through nonquadratic regularization functionals appropriate to IC features. The second approach termed synthesis-based sparsity, is based on sparse representations with respect to overcomplete dictionaries. The domain of IC imaging is particularly suitable for the application of overcomplete dictionaries because the images are highly structured they contain predictable building blocks derivable from the corresponding computeraided design layouts.

Subject Categories:

  • Electrical and Electronic Equipment
  • Optics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE