A new form of image decomposition is derived that uses compound systems to target critical TCC components while at
the same time providing the usual least-squares optimal match to the TCC as a whole. Significant improvements in
accuracy under a given runtime budget are obtained by intensively correcting those portions of the TCC which are most
recalcitrant to the standard coherent decomposition used in OPC today (e.g. SOCS or OCS). In particular, the non-coherent
structure of our new decomposition systems is well-suited to extract any near-Toeplitz components present in the
spatial-domain TCC. Such components are difficult to capture with coherent decomposition, and we show that TCCs for
lithographic systems in fact contain strong Toeplitz-like components that arise from slope discontinuities associated with
the sharp aperture of the projection lens. 1D tests show that for a given kernel-count budget in the typical e.g. 10-100
range, image calculation error can routinely be reduced by at least 5X if our new systems are included in the decomposition.
Alan E. Rosenbluth, "Decomposition of the TCC using non-coherent kernels for faster calculation of lithographic images," Proc. SPIE 10147, Optical Microlithography XXX, 101470P (Presented at SPIE Advanced Lithography: March 01, 2017; Published: 30 March 2017); https://doi.org/10.1117/12.2261223.
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