Cross correlation anomaly detection system

This invention provides a method for automatically inspecting the surface of an object, such as an integrated circuit chip, whereby the data obtained by the light reflected from the surface, caused by a scanning light beam, is automatically compared with data representing acceptable values for each unique surface. A signal output provided indicated of acceptance or rejection of the chip. Acceptance is based on predetermined statistical confidence intervals calculated from known good regions of the object being tested, or their representative values. The method can utilize a known good chip, a photographic mask from which the I.C. was fabricated, or a computer stored replica of each pattern being tested

Cross-correlation cosmography with HI intensity mapping

The cross-correlation of a foreground density field with two different background convergence fields can be used to measure cosmographic distance ratios and constrain dark energy parameters. We investigate the possibility of performing such measurements using a combination of optical galaxy surveys and HI intensity mapping surveys, with emphasis on the performance of the planned Square Kilometre Array (SKA). Using HI intensity mapping to probe the foreground density tracer field and/or the background source fields has the advantage of excellent redshift resolution and a longer lever arm achieved by using the lensing signal from high redshift background sources. Our results show that, for our best SKA-optical configuration of surveys, a constant equation of state for dark energy can be constrained to $\simeq 8\%$ for a sky coverage $f_{\rm sky}=0.5$ and assuming a $\sigma(\Omega_{\rm DE})=0.03$ prior for the dark energy density parameter. We also show that using the CMB as the second source plane is not competitive, even when considering a COrE-like satellite.Comment: 10 pages, 8 figures, 1 table; version accepted for publication in Physical Review

Multifractal detrending moving average cross-correlation analysis

There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross-correlations. The multifractal detrended cross-correlation analysis (MF-DCCA) approaches can be used to quantify such cross-correlations, such as the MF-DCCA based on detrended fluctuation analysis (MF-X-DFA) method. We develop in this work a class of MF-DCCA algorithms based on the detrending moving average analysis, called MF-X-DMA. The performances of the MF-X-DMA algorithms are compared with the MF-X-DFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving average processes and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents $h_{xy}$ extracted from the MF-X-DMA and MF-X-DFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross-correlation is independent of the cross-correlation coefficient between two time series and the MF-X-DFA and centered MF-X-DMA algorithms have comparative performance, which outperform the forward and backward MF-X-DMA algorithms. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MF-X-DMA algorithm gives the best estimates of $h_{xy}(q)$ since its $h_{xy}(2)$ is closest to 0.5 as expected, and the MF-X-DFA algorithm has the second best performance. For the volatilities, the forward and backward MF-X-DMA algorithms give similar results, while the centered MF-X-DMA and the MF-X-DFA algorithms fails to extract rational multifractal nature.Comment: 15 pages, 4 figures, 2 matlab codes for MF-X-DMA and MF-X-DF

A cross-correlation of WMAP and ROSAT

We cross-correlate the recent CMB WMAP 1 year data with the diffuse soft X-ray background map of ROSAT. We look for common signatures due to galaxy clusters (SZ effect in CMB, bremsstrahlung in X-rays) by cross-correlating the two maps in real and in Fourier space. We do not find any significant correlation and we explore the different reasons for this lack of correlation. The most likely candidates are the possibility that we live in a low $\sigma _8$ universe ($\sigma_8 < 0.9$) and/or systematic effects in the data especially in the diffuse X-ray maps which may suffer from significant cluster signal subtraction during the point source removal process.Comment: To appear in New Astronomy Reviews, Proceedings of the CMBNET Meeting, 20-21 February, 2003, Oxford, U

Cross-Correlation Studies with CMB Polarization Maps

The free-electron population during the reionized epoch rescatters CMB temperature quadrupole and generates a now well-known polarization signal at large angular scales. While this contribution has been detected in the temperature-polarization cross power spectrum measured with WMAP data, due to the large cosmic variance associated with anisotropy measurements at tens of degree angular scales only limited information related to reionization, such as the optical depth to electron scattering, can be extracted. The inhomogeneities in the free-electron population lead to an additional secondary polarization anisotropy contribution at arcminute scales. While the fluctuation amplitude, relative to dominant primordial fluctuations, is small, we suggest that a cross-correlation between arcminute scale CMB polarization data and a tracer field of the high redshift universe, such as through fluctuations captured by the 21 cm neutral Hydrogen background or those in the infrared background related to first proto-galaxies, may allow one to study additional details related to reionization. For this purpose, we discuss an optimized higher order correlation measurement, in the form of a three-point function, including information from large angular scale CMB temperature anisotropies in addition to arcminute scale polarization signal related to inhomogeneous reionization. We suggest that the proposed bispectrum can be measured with a substantial signal-to-noise ratio and does not require all-sky maps of CMB polarization or that of the tracer field. A measurement such as the one proposed may allow one to establish the epoch when CMB polarization related to reionization is generated and to address if the universe was reionized once or twice.Comment: 13 pages, 7 figures; Version in press with Phys. Rev.

Atmospheric Stellar Parameters from Cross-Correlation Functions

The increasing number of spectra gathered by spectroscopic sky surveys and transiting exoplanet follow-up has pushed the community to develop automated tools for atmospheric stellar parameters determination. Here we present a novel approach that allows the measurement of temperature ($T_{\rm eff}$), metallicity ($[{\rm Fe}/{\rm H}]$) and gravity ($\log g$) within a few seconds and in a completely automated fashion. Rather than performing comparisons with spectral libraries, our technique is based on the determination of several cross-correlation functions (CCFs) obtained by including spectral features with different sensitivity to the photospheric parameters. We use literature stellar parameters of high signal-to-noise ($\textrm{SNR}$), high-resolution HARPS spectra of FGK Main Sequence stars to calibrate $T_{\rm eff}$, $[{\rm Fe}/{\rm H}]$ and $\log g$ as a function of CCFs parameters. Our technique is validated using low $\textrm{SNR}$ spectra obtained with the same instrument. For FGK stars we achieve a precision of $\sigma_{T_{\rm eff}} = 50$ K, $\sigma_{\log g} = 0.09~ \textrm{dex}$ and $\sigma_{\textrm{Fe}/\textrm{H}]} =0.035~ \textrm{dex}$ at $\textrm{SNR}=50$, while the precision for observation with $\textrm{SNR} \gtrsim 100$ and the overall accuracy are constrained by the literature values used to calibrate the CCFs. Our approach can be easily extended to other instruments with similar spectral range and resolution, or to other spectral range and stars other than FGK dwarfs if a large sample of reference stars is available for the calibration. Additionally, we provide the mathematical formulation to convert synthetic equivalent widths to CCF parameters as an alternative to direct calibration. We have made our tool publicly available.Comment: Accepted by MNRAS. 12 pages, 12 figures. The code to retrieve the atmospheric stellar parameters from HARPS and HARPS-N spectra is available "at this url, https://github.com/LucaMalavolta/CCFpams

Cross-Correlation in cricket data and RMT

We analyze cross-correlation between runs scored over a time interval in cricket matches of different teams using methods of random matrix theory (RMT). We obtain an ensemble of cross-correlation matrices $C$ from runs scored by eight cricket playing nations for (i) test cricket from 1877 -2014 (ii)one-day internationals from 1971 -2014 and (iii) seven teams participating in the Indian Premier league T20 format (2008-2014) respectively. We find that a majority of the eigenvalues of C fall within the bounds of random matrices having joint probability distribution $P(x_1...,x_n)=C_{N \beta} \, \prod_{j<k}w(x_j)| x_j-x_k |^\beta$ where $w(x)=x^{N\beta a}\exp(-N\beta b x)$ and $\beta$ is the Dyson parameter. The corresponding level density gives Marchenko-Pastur (MP) distribution while fluctuations of every participating team agrees with the universal behavior of Gaussian Unitary Ensemble (GUE). We analyze the components of the deviating eigenvalues and find that the largest eigenvalue corresponds to an influence common to all matches played during these periods.Comment: 12 pages, 6 figure

A Modified Cross Correlation Algorithm for Reference-free Image Alignment of Non-Circular Projections in Single-Particle Electron Microscopy

In this paper we propose a modified cross correlation method to align images from the same class in single-particle electron microscopy of highly non-spherical structures. In this new method, First we coarsely align projection images, and then re-align the resulting images using the cross correlation (CC) method. The coarse alignment is obtained by matching the centers of mass and the principal axes of the images. The distribution of misalignment in this coarse alignment can be quantified based on the statistical properties of the additive background noise. As a consequence, the search space for re-alignment in the cross correlation method can be reduced to achieve better alignment. In order to overcome problems associated with false peaks in the cross correlations function, we use artificially blurred images for the early stage of the iterative cross correlation method and segment the intermediate class average from every iteration step. These two additional manipulations combined with the reduced search space size in the cross correlation method yield better alignments for low signal-to-noise ratio images than both classical cross correlation and maximum likelihood(ML) methods.Comment: 29page