Light source mask optimization method adopting compression sensing technology

Abstract

The invention discloses a light source mask optimization method adopting a compression sensing technology. The light source optimization SO problem is configured into an image recovery problem for solving 2 norm in a non-constraint condition, namely a formula which is as shown in the specification, wherein by virtue of a constraint condition linear equation a formula which is as shown in the specification, the space image corresponding to the optimized light source is close to a target image value as far as possible. In addition, the mask optimization MO problem is configured into image optimization problem comprising a sparse regular term and a low-rank regular item, namely a formula which is as shown in the specification, wherein by virtue of a constraint condition linear equation a formula which is as shown in the specification, the space image observed data corresponding to the optimized mask and light source can be close to graphical observation data as far as possible, a formulawhich is as shown in the specification; by virtue of the constraint condition, the number of equations in the optimization process can be further lowered; a formula which is as shown in the specification; and by virtue of the constraint condition, mask complexity in the optimization process can be lowered as far as possible.

Description

technical field [0001] The invention relates to the technical field of lithographic resolution enhancement, in particular to a light source mask optimization method using compressed sensing technology. Background technique [0002] Optical lithography is the current mainstream lithography technology. It uses the principle of optical projection imaging to transfer the integrated circuit pattern on the mask to the wafer coated with photoresist through step-and-scan exposure. With the rapid development of the semiconductor industry, the feature size of VLSI is also shrinking. The lithography system is the main core equipment in the IC manufacturing industry. The current mainstream lithography technology mainly adopts the deep ultraviolet immersion lithography technology with a light source wavelength of 193nm. [0003] As the lithography technology node enters 45-14nm, the critical dimensions of integrated circuits have entered the deep sub-wavelength range. At this time, the ...

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Problems solved by technology

[0007] However, there are two shortcomings in the above method: first, the linear Bregman algorithm used in the above method needs to force the optimization variable of the light source to zero in each optimization process, and this operation will inevitably affect the optimal solution of the SO problem, thus affect the imaging performance of the lithography system; secondly, the above method only considers the application of the linear compressive sensing technology in the light source optimization problem, and does not apply the nonlinear compressive sensing technology to the mask optimization problem, so the final lithography Imaging performance is not yet optimal results

[0008] In summary, the computational efficiency of the traditional SMO method and the SO optimal solution problem based on linear compressed sensing technology need to be further improved and improved.

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