A nonparametric, small-sample-size test for the homogeneity of two psychometric functions against the left-and right-shift alternatives has been developed. The test is designed to determine whether it is safe to amalgamate psychometric functions obtained in different experimental sessions. The sum of the lower and upper pvalues of the exact (conditional) Fisher test for several 2 × 2 contingency tables (one for each point of the psychometric function) is employed as the test statistic. The probability distribution of the statistic under the null (homogeneity) hypothesis is evaluated to obtain corresponding p-values. Power functions of the test have been computed by randomly generating samples from Weibull psychometric functions. The test is free of any assumptions about the shape of the psychometric function; it requires only that all observations are statistically independent.

Recently, an original method for the statistical modeling of surface topography of state-of-the-art mirrors for usage in xray optical systems at light source facilities and for astronomical telescopes [Opt. Eng. 51(4), 046501, 2012; ibid. 53(8), 084102 (2014); and ibid. 55(7), 074106 (2016)] has been developed. In modeling, the mirror surface topography is considered to be a result of a stationary uniform stochastic polishing process and the best fit time-invariant linear filter (TILF) that optimally parameterizes, with limited number of parameters, the polishing process is determined. The TILF model allows the surface slope profile of an optic with a newly desired specification to be reliably forecast before fabrication. With the forecast data, representative numerical evaluations of expected performance of the prospective mirrors in optical systems under development become possible [Opt. Eng., 54(2), 025108 (2015)]. Here, we suggest and demonstrate an analytical approach for accounting the imperfections of the used metrology instruments, which are described by the instrumental point spread function, in the TILF modeling. The efficacy of the approach is demonstrated with numerical simulations for correction of measurements performed with an autocollimator based surface slope profiler. Besides solving this major metrological problem, the results of the present work open an avenue for developing analytical and computational tools for stitching data in the statistical domain, obtained using multiple metrology instruments measuring significantly different bandwidths of spatial wavelengths.

The design and evaluation of the expected performance of optical systems require sophisticated and reliable information about the surface topography for planned optical elements before they are fabricated. Modern x-ray source facilities are reliant upon the availability of optics with unprecedented quality (surface slope accuracy <0.1 μrad). The problem is especially complex in the case of x-ray optics, particularly for the X-ray Surveyor under development and other missions. The high angular resolution and throughput of future xray space observatories requires hundreds of square meters of high-quality optics. The uniqueness of the optics and limited number of proficient vendors makes the fabrication extremely time consuming and expensive, mostly due to the limitations in accuracy and measurement rate of metrology used in fabrication. We discuss improvements in metrology efficacy via comprehensive statistical analysis of a compact volume of metrology data. The data are considered stochastic, and a statistical model called invertible time-invariant linear filter (InTILF) is developed now for two-dimensional (2-D) surface profiles to provide compact description of the 2-D data in addition to one-dimensional data treated so far. The InTILF model captures stochastic patterns in the data and can be used as a quality metric and feedback to polishing processes, avoiding high-resolution metrology measurements over the entire optical surface. The modeling, implemented in our BeatMark™ software, allows simulating metrology data for optics made by the same vendor and technology. The data are vital for reliable specification for optical fabrication, to be exactly adequate for the required system performance.

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