Abstract: Disclosed are methods and systems for estimating a reticle bias state for a process system, that include computing a difference between control data provided to the process system and error data based on a process system output(s), and estimating the reticle bias state based on weighted measures associated with the control data, the weighted measures being based on the number of data points included in the difference. The methods and systems include associating the reticle bias state estimate with a first quality factor, computing at least one weighted measure based on a number of data elements associated with the reticle, using the weighted measure(s) to provide a computed reticle bias state estimate and an associated computed quality factor, and, comparing the computed quality factor with the first quality factor to determine whether to update the reticle bias state estimate with the computed reticle bias state estimate.

Abstract: Systems and methods for controlling at least one reticle-induced error in a process system, the systems and methods including adjusting measurement data associated with the process system, where the adjustment can be based on at least one reticle identifier (ID) associated with the measurement data, and reticle-induced error data associated with the at least one reticle ID. The methods and systems also include combining the adjusted measurement data to compute at least one control for the process system.

Abstract: Disclosed are methods, systems, and processor program products for filtering overlay measurements, including generating a residual between a measured overlay displacement and an overlay displacement based on a model of reticle errors relative to an exposure field, grouping the residuals based on location, normalizing residuals within a group based on at least one normalization factor, and, filtering the overlay measurements by comparing the normalized residuals to a threshold.

Abstract: Disclosed are methods and systems for estimating a reticle bias state for a process system, that include computing a difference between control data provided to the process system and error data based on a process system output(s), and estimating the reticle bias state based on weighted measures associated with the control data, the weighted measures being based on the number of data points included in the difference. The methods and systems include associating the reticle bias state estimate with a first quality factor, computing at least one weighted measure based on a number of data elements associated with the reticle, using the weighted measure(s) to provide a computed reticle bias state estimate and an associated computed quality factor, and, comparing the computed quality factor with the first quality factor to determine whether to update the reticle bias state estimate with the computed reticle bias state estimate.

Abstract: Systems and methods for controlling at least one reticle-induced error in a process system, the systems and methods including adjusting measurement data associated with the process system, where the adjustment can be based on at least one reticle identifier (ID) associated with the measurement data, and reticle-induced error data associated with the at least one reticle ID. The methods and systems also include combining the adjusted measurement data to compute at least one control for the process system.

Abstract: Methods and systems for controlling critical dimension (CD) in a process system, including computing an exposure dose error based on at least one output of the process system, normalizing the computed exposure dose error based on a target exposure dose, and providing an exposure dose to the process system based on at least one normalized exposure dose error. The target exposure dose can be associated with a process system characteristic(s) and can be updated based on normalized computed exposure dose errors.