Abstract: A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves spatial and/or temporal correlation of photon emissions. After correlation, the analysis may further involve obtaining a likelihood that the correlated photons were emitted by a transistor. After correlation, the analysis may also further involve assigning a weight to individual photon emissions as a function of the correlation. The weight, in some instances, reflecting a likelihood that the photons were emitted by a transistor. The analysis may further involve automatically identifying transistors in a photon emission image.

Abstract: A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves spatial and/or temporal correlation of photon emissions. After correlation, the analysis may further involve obtaining a likelihood that the correlated photons were emitted by a transistor. After correlation, the analysis may also further involve assigning a weight to individual photon emissions as a function of the correlation. The weight, in some instances, reflecting a likelihood that the photons were emitted by a transistor. The analysis may further involve automatically identifying transistors in a photon emission image.

Abstract: A method for utilizing interference fringe patterns generated when milling a trench through a semiconductor substrate by a method such as FIB milling, to determine and optimize the thickness uniformity of the trench bottom. The interference fringes may be mapped and the mapping used to direct the FIB milling to those regions which are thicker to correct observed non-uniformities in the trench floor thickness by varying the pixel dwell time across the milled area. The interference fringe mapping may be used to develop computerized contour lines to automate the pixel dwell time variations as described above, for correcting non-uniformities in the trench floor thickness. The method may be applied to applications other than trench formation for backside editing, such as monitoring progress in forming a milled object.

Abstract: Methods, apparatus and data structures useful in correcting PICA image data are described. An exemplary method comprises acquiring optical image data of a target having identifiable optical-image features, acquiring PICA image data of the target having identifiable PICA-image features corresponding to the optical-image features, matching PICA-image features with corresponding optical-image features, and calculating from matched PICA-image features and optical-image features a set of coefficients defining relationships between observed positions of PICA-image features and optical-image features. Corrections are applied to the observed positions of detected photons based on the coefficients. The coefficients may provide a local correction using a bilinear relationship giving the transformation of a rectangle formed by four features of the PICA-image data to fit a corresponding rectangle in the optical-image data.

Abstract: A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves spatial and/or temporal correlation of photon emissions. After correlation, the analysis may further involve obtaining a likelihood that the correlated photons were emitted by a transistor. After correlation, the analysis may also further involve assigning a weight to individual photon emissions as a function of the correlation. The weight, in some instances, reflecting a likelihood that the photons were emitted by a transistor. The analysis may further involve automatically identifying transistors in a photon emission image.

Abstract: A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves spatial and/or temporal correlation of photon emissions. After correlation, the analysis may further involve obtaining a likelihood that the correlated photons were emitted by a transistor. After correlation, the analysis may also further involve assigning a weight to individual photon emissions as a function of the correlation. The weight, in some instances, reflecting a likelihood that the photons were emitted by a transistor. The analysis may further involve automatically identifying transistors in a photon emission image.

Abstract: A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves spatial and/or temporal correlation of photon emissions. After correlation, the analysis may further involve obtaining a likelihood that the correlated photons were emitted by a transistor. After correlation, the analysis may also further involve assigning a weight to individual photon emissions as a function of the correlation. The weight, in some instances, reflecting a likelihood that the photons were emitted by a transistor. The analysis may further involve automatically identifying transistors in a photon emission image.

Abstract: A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves spatial and/or temporal correlation of photon emissions. After correlation, the analysis may further involve obtaining a likelihood that the correlated photons were emitted by a transistor. After correlation, the analysis may also further involve assigning a weight to individual photon emissions as a function of the correlation. The weight, in some instances, reflecting a likelihood that the photons were emitted by a transistor. The analysis may further involve automatically identifying transistors in a photon emission image.

Abstract: A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves spatial and/or temporal correlation of photon emissions. After correlation, the analysis may further involve obtaining a likelihood that the correlated photons were emitted by a transistor. After correlation, the analysis may also further involve assigning a weight to individual photon emissions as a function of the correlation. The weight, in some instances, reflecting a likelihood that the photons were emitted by a transistor. The analysis may further involve automatically identifying transistors in a photon emission image.

Abstract: A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves spatial and/or temporal correlation of photon emissions. After correlation, the analysis may further involve obtaining a likelihood that the correlated photons were emitted by a transistor. After correlation, the analysis may also further involve assigning a weight to individual photon emissions as a function of the correlation. The weight, in some instances, reflecting a likelihood that the photons were emitted by a transistor. The analysis may further involve automatically identifying transistors in a photon emission image.

Abstract: Methods, apparatus and data structures useful in correcting PICA image data are described. An exemplary method comprises acquiring optical image data of a target having identifiable optical-image features, acquiring PICA image data of the target having identifiable PICA-image features corresponding to the optical-image features, matching PICA-image features with corresponding optical-image features, and calculating from matched PICA-image features and optical-image features a set of coefficients defining relationships between observed positions of PICA-image features and optical-image features. Corrections are applied to the observed positions of detected photons based on the coefficients. The coefficients may provide a local correction using a bilinear relationship giving the transformation of a rectangle formed by four features of the PICA-image data to fit a corresponding rectangle in the optical-image data.