Abstract:
A method of calibrating a substrate positioning system of a lithographic apparatus, the method including: exposing a pattern with the lithographic apparatus on an exposed layer on the surface of a substrate having a reference layer, wherein the pattern corresponds to a movement of the substrate by the substrate positioning system; measuring overlay data between the exposed layer and the reference layer on a plurality of positions on the substrate; transforming the overlay data from a spatial domain to a frequency domain by a discrete cosine transformation; modifying the overlay data in the frequency domain by selecting a subset of the overlay data; transforming the modified overlay data from the frequency domain back to the spatial domain by an inverse discrete cosine transformation; calibrating the substrate positioning system by using the modified overlay data in the spatial domain.
Abstract:
A lithographic apparatus is described having a liquid supply system configured to at least partly fill a space between a projection system of the lithographic apparatus and a substrate with liquid, a barrier member arranged to substantially contain the liquid within the space, and a heater.
Abstract:
A lithographic apparatus is described having a liquid supply system configured to at least partly fill a space between a projection system of the lithographic apparatus and a substrate with liquid, a substrate temperature control system configured to provide a control signal to control a substrate temperature conditioning system based on a determined temperature; and a parameter control system configured to adjust a lithographic apparatus parameter, that is other than, or in addition to, the control signal, based on temperature information of the substrate and/or substrate table or on a measure derived from the temperature information.
Abstract:
A method for analyzing a process, the method including obtaining a multi-dimensional probability density function representing an expected distribution of values for a plurality of process parameters; obtaining a performance function relating values of the process parameters to a performance metric of the process; and using the performance function to map the probability density function to a performance probability function having the process parameters as arguments.