Importance

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Abstract

Methods, a non-transitory computer-readable storage medium, devices, and a system in relation to training a convolutional neural network for deriving corrected digital pattern descriptions from digital pattern descriptions for use in a process for producing photomasks are disclosed. A reinforcement learning agent is trained to derive corrected digital pattern descriptions from respective digital pattern descriptions. The training is based on a first plurality of generated digital pattern descriptions and an obtained physical model using which predicted binary patterns of photomasks can be derived that would result from inputting digital pattern descriptions to the process for producing photomasks. A second plurality of digital pattern descriptions is then generated, and corresponding corrected digital pattern descriptions are generated using the trained reinforcement learning agent, thereby generating training data. The training data can be used to train a convolutional neural network to derive corrected digital pattern descriptions from digital pattern descriptions, the trained neural network can be used to derive a corrected digital pattern description, and the corrected digital pattern description can be used to produce a photomask according to the corrected digital pattern description.

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First Claim