A method of enhancing a layout pattern includes determining a vector transmission cross coefficient (vector-TCC) operator of an optical system of a lithographic system based on an illumination source of the optical system and an exit pupil of the optical system of the lithographic system. The method also includes performing an optical proximity correction (OPC) operation of a layout pattern of a photo mask to generate an OPC corrected layout pattern. The OPC operation uses the vector-TCC operator to determine a projected pattern of the layout pattern of the photo mask on a wafer. The method includes producing the OPC corrected layout pattern on a mask blank to create a photo mask.

A method of enhancing a layout pattern includes determining a vector transmission cross coefficient (vector-TCC) operator of an optical system of a lithographic system based on an illumination source of the optical system and an exit pupil of the optical system of the lithographic system. The method also includes performing an optical proximity correction (OPC) operation of a layout pattern of a photo mask to generate an OPC corrected layout pattern. The OPC operation uses the vector-TCC operator to determine a projected pattern of the layout pattern of the photo mask on a wafer. The method includes producing the OPC corrected layout pattern on a mask blank to create a photo mask.

An operating method of an extreme ultraviolet (EUV) lithography device includes defining a target image to render an illumination system, assigning priorities to respective positions of facets of a pupil facet mirror corresponding to the target image, assigning a mirror according to the assigned priorities using linear programming, generating the illumination system by selecting one of the facets of the pupil facet mirror based on a symmetry criterion, and converting mirror assignment information and source map information corresponding to the selected facet into a form recognizable by an EUV scanner.

A projection system model is configured to predict optical aberrations of a projection system based upon a set of projection system characteristics and to determine and output a set of optical element adjustments based upon a merit function. The merit function comprises a set of parameters and corresponding weights. The method comprises receiving an initial merit function and executing an optimization algorithm to determine a second merit function. The optimization algorithm scores different merit functions based upon projection system characteristics of a projection system adjusted according to the output of the projection system model using a merit function having that set of parameters and weights.

An operating method of an extreme ultraviolet (EUV) lithography device includes defining a target image to render an illumination system, assigning priorities to respective positions of facets of a pupil facet mirror corresponding to the target image, assigning a mirror according to the assigned priorities using linear programming, generating the illumination system by selecting one of the facets of the pupil facet mirror based on a symmetry criterion, and converting mirror assignment information and source map information corresponding to the selected facet into a form recognizable by an EUV scanner.

A method for operating an optical system comprises the following steps: (a) using sensors to measure values of at least one physical quantity at a plurality of different sensor positions in the optical system; and (b) diagnosing an existing or expected malfunction of the optical system on the basis of this measurement. The values measured in step (a) are used to perform model-based determination of at least one parameter at other positions, none of which correspond to the sensor positions. The diagnosis in step (b) also being carried out on the basis of this model-based determination.

A projection system model is configured to predict optical aberrations of a projection system based upon a set of projection system characteristics and to determine and output a set of optical element adjustments based upon a merit function. The merit function comprises a set of parameters and corresponding weights. The method comprises receiving an initial merit function and executing an optimization algorithm to determine a second merit function. The optimization algorithm scores different merit functions based upon projection system characteristics of a projection system adjusted according to the output of the projection system model using a merit function having that set of parameters and weights.

A machine learning model may employ in situ chemical composition information, as an input, to characterize processes in real time, and optionally assist in process control. Chemical composition information may be obtained from an in situ emission spectrometer such an optical emission spectrometer.

A method of predicting thermally induced aberrations of a projection system for projecting a radiation beam, the method comprising: calculating a change in temperature of the projection system from a power of the radiation beam output from the projection system using a dynamic linear function; and calculating the thermally induced aberrations from the calculated change in temperature using a static non-linear function.

A method for calibrating a manipulable optical module for a microlithographic projection exposure apparatus, which comprises at least one manipulation element for setting an at least one-dimensional local variation profile of an optical property of the optical module is provided. The method comprises: applying a temporally varying excitation signal to the at least one manipulation element; determining a raw measurement data set via a measurement device measuring the respective local variation profile resulting at different times during the variation of the excitation signal; estimating a temporally varying scaling, caused by the temporal variation of the excitation signal, in the variation profiles of the raw measurement data set; determining a full effect profile of the optical property by fitting the temporally varying scaling to the variation profiles of the raw measurement data set; and determining calibration data of the manipulable optical module on the basis of the full effect profile.