A broadband light source includes a rotatable drum coated with plasma-forming target material, a rotational actuator configured to rotate the rotatable drum, and a rotary encoder connected to the rotatable drum. The broadband light source may include a linear actuator configured to axially translate the rotatable drum and linear encoder connected to the rotatable drum. The broadband light source includes a pulsed laser source configured to direct pulsed illumination to a set of spots on the material-coated portion of the rotatable drum for exciting the plasma-forming target material and emitting broadband light as the drum is actuated. The broadband light source includes a control system. The control system is configured to receive one or more rotational position indicators from the rotary indicator and control triggering of the laser source based on the one or more rotational position indicators from rotary encoder.

A method for evaluating images of a printed pattern. The method includes obtaining a first averaged image of the printed pattern, where the first averaged image is generated by averaging raw images of the printed pattern. The method also includes identifying one or more features of the first averaged image. The method further includes evaluating the first averaged image, using an image quality classification model and based at least on the one or more features. The evaluating includes determining, by the image quality classification model, whether the first averaged image satisfies a metric.

A method of determining a contribution of a process feature to the performance of a process of patterning substrates. The method may include obtaining a first model trained on first process data and first performance data. One or more substrates may be identified based on a quality of prediction of the first model when applied to process data associated with the one or more substrates. A second model may be trained on second process data and second performance data associated with the identified one or more substrates. The second model may be used to determine the contribution of a process feature of the second process data to the second performance data associated with the one or more substrates.

A system includes a radiation source and a phased array. The phased array includes optical elements, waveguides and phase modulators. The phased array generates a beam of radiation. The optical elements radiate radiation waves. The waveguides guide radiation from the radiation source to the optical elements. The phase modulators adjust phases of the radiation waves such that the radiation waves accumulate to form the beam. An amount of incoherence of the beam is based on randomization of the phases.

To efficiently search a processing condition of giving a desired target processing result, there is provided a processing condition determination system including a processing apparatus that processes a sample, a processing monitor system that monitors the state of the processing in the processing apparatus, and an analysis system that sets the processing condition of the processing apparatus of giving a target processing result, wherein the system includes a processing condition and result database that stores a set of an explanatory variable that is a processing condition under which the processing apparatus processes a sample and an objective variable that is the processing result obtained by the processing apparatus' processing the sample, and when the processing apparatus processes the sample under the processing condition set using the correlation model derived from the database and it is determined that a probability of failure occurrence becomes high, based on the monitor data of the processing monitor system, the processing apparatus stops the processing under the present processing condition and the analysis system resets a new processing condition.

Described herein is a method of training a model configured to predict whether a feature associated with an imaged substrate will be defective after etching of the imaged substrate and determining etch conditions based on the trained model. The method includes obtaining, via a metrology tool, (i) an after development image of the imaged substrate at a given location, the after development image including a plurality of features, and (ii) an after etch image of the imaged substrate at the given location; and training, using the after development image and the after etch image, the model configured to determine defectiveness of a given feature of the plurality of features in the after development image. In an embodiment, the determining of defectiveness is based on comparing the given feature in the after development image with a corresponding etch feature in the after etch image.

A method for improving the yield of a lithographic process, the method including: determining a parameter fingerprint of a performance parameter across a substrate, the parameter fingerprint including information relating to uncertainty in the performance parameter; determining a process window fingerprint of the performance parameter across the substrate, the process window being associated with an allowable range of the performance parameter; and determining a probability metric associated with the probability of the performance parameter being outside an allowable range. Optionally a correction to the lithographic process is determined based on the probability metric.

A field-of-view at a first modeled target location of a first target disposed on a specimen can be configured, which can include moving the stage relative to the detector. The first modeled target location is determined by summing a first design target location and a navigational error provided by an online model. A first image of the field-of-view is grabbed using the detector. The field-of-view at a second modeled target location of a second target disposed on the specimen is configured. Concurrent with configuring the field-of-view at the second modeled target location, using a processor, the position of a first actual target location is determined using the first image. The online model is updated with a difference between the first design target location and the first actual target location.

A method for determining process window limiting patterns based on aberration sensitivity associated with a patterning apparatus. The method includes obtaining (i) a first set of kernels and a second set of kernels associated with an aberration wavefront of the patterning apparatus and (ii) a design layout to be printed on a substrate via the patterning apparatus; and determining, via a process simulation using the design layout, the first set of kernels, and the second set of kernels, an aberration sensitivity map associated with the aberration wavefront, the aberration sensitivity map indicating how sensitive one or more portions of the design layout are to an individual aberrations and an interaction between different aberrations; determining, based on the aberration sensitivity map, the process window limiting pattern associated with the design layout having relatively high sensitivity compared to other portions of the design layout.

The instant disclosure includes an alignment system. The alignment system includes a first set of alignment marks, a second set of alignment marks, and a third set of alignment marks. The first, second and third alignment marks correspondingly includes a plurality of segments separated into groups. Each of the group being symmetric to a respective other group. The third set of alignment marks are diagonal to the first set of alignment marks and the second set of alignment marks.