Abstract: An extreme ultraviolet radiation (EUV) source, including: a vessel having an inner vessel wall and an intermediate focus (IF) region; an EUV collector disposed inside the vessel, the EUV collector including a reflective surface configured to reflect EUV radiation toward the intermediate focus region, the reflective surface configured to directionally face the IF region of the vessel; a showerhead disposed along at least a portion of the inner vessel wall, the showerhead including a plurality of nozzles configured to introduce gas into the vessel; and one or more exhausts configured to remove gas introduced into the vessel, the one or more exhausts being oriented along at least a portion of the inner vessel wall so that the gas is caused to flow away from the EUV collector.

Abstract: A method and machine for validating an investigated sensor within a sensor group includes receiving sensor data from sensors of the sensor group measuring the same physical property, calculating a deviation of the sensor data received from the investigated sensor within the sensor group from sensor data reconstructed based on the sensor data received from all other sensors of the sensor group, and signaling a sensor fault of the investigated sensor if the calculated deviation is outside of a trusted range.

Abstract: A method and machine for validating an investigated sensor within a sensor group includes receiving sensor data from sensors of the sensor group measuring the same physical property, calculating a deviation of the sensor data received from the investigated sensor within the sensor group from sensor data reconstructed based on the sensor data received from all other sensors of the sensor group, and signaling a sensor fault of the investigated sensor if the calculated deviation is outside of a trusted range.

Abstract: A method for computer-assisted analyzing of a technical system is provided. The technical system is described by a case base including multiple cases, each case including a state vector with a number of attributes, the state vector referring to an operation state of the technical system, wherein a class from a number of classes is assigned to each case, each class referring to an operation condition of the technical system. Each case is processed by extracting a local information vector depending on the classes of one or more neighboring cases in the case base, the neighboring cases being similar to the case being processed according to a neighborhood measure. Subsequently, machine learning of a classification is performed based on the extracted local information vectors of the cases in the case base, resulting in a learned adaptation function providing a class depending on a local information vector extracted for a case.