A magnetic distribution detection method includes the steps of providing a magnetic sensor and a sample, selecting a multiple of measuring points on the sample, sensing the measuring points by the magnetic sensor, obtaining a multiple of sense data and a series of the heights of the magnetic sensor from each measuring point, using a signal decomposition algorithm to convert these sense data into data groups, and selecting one of the data groups as the magnetic distribution data of the sample.

An atomic-force-microscope-based apparatus and method including hardware and software, configured to collect, in a dynamic fashion, and analyze data representing mechanical properties of soft materials on a nanoscale, to map viscoelastic properties of a soft-material sample. The use of the apparatus as an addition to the existing atomic-force microscope device.

System and Methods may be provided for performing chemical spectroscopy on samples from the scale of nanometers with surface sensitivity even on very thick sample. In the method, a signal indicative of infrared absorption of the surface layer is constructed by illuminating the surface layer with a beam of infrared radiation and measuring a probe response comprising at least one of a resonance frequency shift and a phase shift of a resonance of a probe in response to infrared radiation absorbed by the surface layer.

System and Methods may be provided for performing chemical spectroscopy on samples from the scale of nanometers with surface sensitivity even on very thick sample. In the method, a signal indicative of infrared absorption of the surface layer is constructed by illuminating the surface layer with a beam of infrared radiation and measuring a probe response comprising at least one of a resonance frequency shift and a phase shift of a resonance of a probe in response to infrared radiation absorbed by the surface layer.

In one embodiment, a method for detecting edge positions in a pattern structure is disclosed. The method includes detecting the edge positions of features within the pattern structure of an image without filtering the image, wherein the detecting is performed by: applying a model to a single linescan, adjusting, based on the single linescan, one or more parameters of the model, obtaining, using the one or more adjusted parameters, a best fit of the model to the single linescan.

In one embodiment, a method for detecting edge positions in a pattern structure is disclosed. The method includes detecting the edge positions of features within the pattern structure of an image without filtering the image, wherein the detecting is performed by: applying a model to a single linescan, adjusting, based on the single linescan, one or more parameters of the model, obtaining, using the one or more adjusted parameters, a best fit of the model to the single linescan.

In one embodiment, a method includes determining, by a processor, a measurement of edge detection noise; receiving a measurement of a biased parameter including measurement noise; based on the measurement of edge detection noise and a number of measurement points, determining a contribution of edge detection noise to the biased parameter; determining an unbiased parameter by subtracting the contribution of noise from the biased parameter including the measurement noise; and outputting the unbiased parameter.

In one embodiment, a method includes determining, by a processor, a measurement of edge detection noise; receiving a measurement of a biased parameter including measurement noise; based on the measurement of edge detection noise and a number of measurement points, determining a contribution of edge detection noise to the biased parameter; determining an unbiased parameter by subtracting the contribution of noise from the biased parameter including the measurement noise; and outputting the unbiased parameter.

A method of operating an atomic force microscope (AFM), using a denoising algorithm, real-time, during AFM data acquisition. Total Variation and Non-Local Means denoising are preferred. Real time images with minimized sensor noise needing no post-image acquisition processing to account for noise as described herein results.

A method of operating an atomic force microscope (AFM), using a denoising algorithm, real-time, during AFM data acquisition. Total Variation and Non-Local Means denoising are preferred. Real time images with minimized sensor noise needing no post-image acquisition processing to account for noise as described herein results.