Binary matrices of optimal autocorrelations as alignment marks
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Results for “AUTOCORRELATION”
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An autocorrelation method for three-dimensional strain analysis
Abstract not provided
Thissen, Christopher J.↗
An Overdetermined System for Improved Autocorrelation Based Spectral Moment Estimator Performance
Autocorrelation based spectral moment estimators are typically derived using the Fourier transform relationship between the power spectrum and the autocorrelation function along with using either an assumed form of the autocorrelation function, e.g., Gaussian, or a generic complex form and applying properties of the characteristic function. Passarelli has used a series expansion of the general complex autocorrelation function and has expressed the coefficients in terms of central moments of the power spectrum. A truncation of this series will produce a closed system of equations which can be solved for the central moments of interest. The autocorrelation function at various lags is estimated from samples of the random process under observation. These estimates themselves are random variables and exhibit a bias and variance that is a function of the number of samples used in the estimates and the operational signal-to-noise ratio. This contributes to a degradation in performance of the moment estimators. This dissertation investigates the use autocorrelation function estimates at higher order lags to reduce the bias and standard deviation in spectral moment estimates. In particular, Passarelli's series expansion is cast in terms of an overdetermined system to form a framework under which the application of additional autocorrelation function estimates at higher order lags can be defined and assessed. The solution of the overdetermined system is the least squares solution. Furthermore, an overdetermined system can be solved for any moment or moments of interest and is not tied to a particular form of the power spectrum or corresponding autocorrelation function. As an application of this approach, autocorrelation based variance estimators are defined by a truncation of Passarelli's series expansion and applied to simulated Doppler weather radar returns which are characterized by a Gaussian shaped power spectrum. The performance of the variance estimators determined from a closed system is shown to improve through the application of additional autocorrelation lags in an overdetermined system. This improvement is greater in the narrowband spectrum region where the information is spread over more lags of the autocorrelation function. The number of lags needed in the overdetermined system is a function of the spectral width, the number of terms in the series expansion, the number of samples used in estimating the autocorrelation function, and the signal-to-noise ratio. The overdetermined system provides a robustness to the chosen variance estimator by expanding the region of spectral widths and signal-to-noise ratios over which the estimator can perform as compared to the closed system.
Keel, Byron M.↗
MEASUREMENTS OF STELLAR MAGNETIC FIELDS USING AUTOCORRELATION OF SPECTRA
We present a novel technique that uses the autocorrelation of the spectrum of a star to measure the line broadening caused by the modulus of its average surface magnetic field. The advantage of the autocorrelation comes from the fact that it can detect very small spectral line broadening effects because it averages over many spectral lines and therefore gives an average with a very high signal-to-noise ratio. We validate the technique with the spectra of known magnetic stars and obtain autocorrelation curves that are in full agreement with published magnetic curves obtained with Zeeman splitting. The autocorrelation also gives less noisy curves so that it can be used to obtain very accurate curves. We degrade the resolution of the spectra of these magnetic stars to lower spectral resolutions where the Zeeman splitting is undetectable. At these resolutions, the autocorrelation still gives good quality curves, thereby showing that it can be used to measure magnetic fields in spectra where the Zeeman splitting is significantly smaller than the width of the spectral line. This would therefore allow observing magnetic fields in very faint Ap stars with low-resolution spectrographs, thereby greatly increasing the number of known magnetic stars. It also demonstrates that the autocorrelation can measure magnetic fields in rapidly rotating stars as well as weak magnetic fields that give a Zeeman splitting smaller than the intrinsic width of the spectral lines. Finally, it shows that the autocorrelation can be used to find unknown magnetic stars in low-resolution spectroscopic surveys.
79 ASTRONOMY AND ASTROPHYSICS↗
Global Autocorrelation Scales of the Partial Pressure of Oceanic CO2
A global database of approximately 1.7 million observations of the partial pressure of carbon dioxide in surface ocean waters (pCO2) collected between 1970 and 2003 is used to estimate its spatial autocorrelation structure. The patterns of the lag distance where the autocorrelation exceeds 0.8 is similar to patterns in the spatial distribution of the first baroclinic Rossby radius of deformation indicating that ocean circulation processes play a significant role in determining the spatial variability of pCO2. For example, the global maximum of the distance at which autocorrelations exceed 0.8 averages about 140 km in the equatorial Pacific. Also, the lag distance at which the autocorrelation exceed 0.8 is greater in the vicinity of the Gulf Stream than it is near the Kuroshio, approximately 50 km near the Gulf Stream as opposed to 20 km near the Kuroshio. Separate calculations for times when the sun is north and south of the equator revealed no obvious seasonal dependence of the spatial autocorrelation scales. The pCO2 measurements at Ocean Weather Station (OWS) 'P', in the eastern subarctic Pacific (50 N, 145 W) is the only fixed location where an uninterrupted time series of sufficient length exists to calculate a meaningful temporal autocorrelation function for lags greater than a few days. The estimated temporal autocorrelation function at OWS 'P', is highly variable. A spectral analysis of the longest four pCO2 time series indicates a high level of variability occurring over periods from the atmospheric synoptic to the maximum length of the time series, in this case 42 days. It is likely that a relative peak in variability with a period of 3-6 days is related to atmospheric synoptic period variability and ocean mixing events due to wind stirring. However, the short length of available time series makes identifying temporal relationships between pCO2 and atmospheric or ocean processes problematic.
Li, Zhen↗
Measurements of the z > 5 Lyman-α forest flux autocorrelation functions from the extended XQR-30 data set
We present the first observational measurements of the Lyman-α (Ly α) forest flux autocorrelation functions in ten redshift bins from 5.1 ≤ z ≤ 6.0. We use a sample of 35 quasar sightlines at z > 5.7 from the extended XQR-30 data set; these data have signal-to-noise ratios of >20 per spectral pixel. We carefully account for systematic errors in continuum reconstruction, instrumentation, and contamination by damped Ly α systems. With these measurements, we introduce software tools to generate autocorrelation function measurements from any simulation. Our measurements of the smallest bin of the autocorrelation function increase with redshift when normalizing by the mean flux, $\langle{F}\rangle$. This increase may come from decreasing $\langle{F}\rangle$ or increasing mean free path of hydrogen-ionizing photons, λmfp. Recent work has shown that the autocorrelation function from simulations at z > 5 is sensitive to λmfp, a quantity that contains vital information on the ending of reionization. For an initial comparison, we show our autocorrelation measurements with simulation models for recently measured λmfp values and find good agreements. Further work in modelling and understanding the covariance matrices of the data is necessary to get robust measurements of λmfp from this data.
79 ASTRONOMY AND ASTROPHYSICS↗
A relation between the Lagrangian and Eulerian turbulent velocity autocorrelations
Direct computation of the Lagrangian autocorrelation is not feasible since generally one cannot measure the turbulent velocity of each fluid particle. A model whereby the Lagrangian autocorrelation is determined in terms of a domain integral of a set of regular Eulerian autocorrelations is advanced. The Eulerian autocorrelations are to be acquired concurrently at all positions in the flow field. Three novel averaging procedures are utilized for obtaining the relationship between the Lagrangian and Eulerian autocorrelations. This relationship is not constrained to either homogeneous or isotropic turbulence.
Koper, C. A., Jr.↗
Assessment of drug-induced arrhythmic risk using limit cycle and autocorrelation analysis of human iPSC-cardiomyocyte contractility
Cardiac safety assays incorporating label-free detection of human stem-cell derived cardiomyocyte contractility provide human relevance and medium throughput screening to assess compound-induced cardiotoxicity. In an effort to provide quantitative analysis of the large kinetic datasets resulting from these real-time studies, we applied bioinformatic approaches based on nonlinear dynamical system analysis, including limit cycle analysis and autocorrelation function, to systematically assess beat irregularity. The algorithms were integrated into a software program to seamlessly generate results for 96-well impedance-based data. Our approach was validated by analyzing dose- and time-dependent changes in beat patterns induced by known proarrhythmic compounds and screening a cardiotoxicity library to rank order compounds based on their proarrhythmic potential. We demonstrate a strong correlation for dose-dependent beat irregularity monitored by electrical impedance and quantified by autocorrelation analysis to traditional manual patch clamp potency values for hERG blockers. In addition, our platform identifies non-hERG blockers known to cause clinical arrhythmia. Our method provides a novel suite of medium-throughput quantitative tools for assessing compound effects on cardiac contractility and predicting compounds with potential proarrhythmia and may be applied to in vitro paradigms for pre-clinical cardiac safety evaluation. - Highlights: • Impedance-based monitoring of human iPSC-derived cardiomyocyte contractility • Limit cycle analysis of impedance data identifies aberrant oscillation patterns. • Nonlinear autocorrelation function quantifies beat irregularity. • Identification of hERG and non-hERG inhibitors with known risk of arrhythmia • Automated software processes limit cycle and autocorrelation analyses of 96w data.
60 APPLIED LIFE SCIENCES↗
Adaptive non-collinear autocorrelation of few-cycle pulses with an angular tunable bi-mirror
Adaptive autocorrelation with an angular tunable micro-electro-mechanical system is reported. A piezo-actuated Fresnel bi-mirror structure was applied to measure the second order autocorrelation of near-infrared few-cycle laser pulses in a non-collinear setup at tunable superposition angles. Because of enabling measurements with variable scaling and minimizing the influence of distortions by adaptive self-reconstruction, the approach extends the capability of autocorrelators. Flexible scaling and robustness against localized amplitude obscurations are demonstrated. The adaptive reconstruction of temporal frequency information by the Fourier analysis of autocorrelation data is shown. Experimental results and numerical simulations of the beam propagation and interference are compared for variable angles.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Forecasting constraints on the mean free path of ionizing photons at z ≥ 5.4 from the Lyman-α forest flux autocorrelation function
ABSTRACT Fluctuations in Lyman-α (Ly α) forest transmission towards high-z quasars are partially sourced from spatial fluctuations in the ultraviolet background, the level of which are set by the mean free path of ionizing photons (λmfp). The autocorrelation function of Ly α forest flux characterizes the strength and scale of transmission fluctuations and, as we show, is thus sensitive to λmfp. Recent measurements at z ∼ 6 suggest a rapid evolution of λmfp at z > 5.0 which would leave a signature in the evolution of the autocorrelation function. For this forecast, we model mock Ly α forest data with properties similar to the XQR-30 extended data set at 5.4 ≤ z ≤ 6.0. At each z, we investigate 100 mock data sets and an ideal case where mock data matches model values of the autocorrelation function. For ideal data with λmfp = 9.0 cMpc at z = 6.0, we recover $\lambda _{\text{mfp}}=12^{+6}_{-3}$ cMpc. This precision is comparable to direct measurements of λmfp from the stacking of quasar spectra beyond the Lyman limit. Hypothetical high-resolution data leads to a $\sim 40~{{\ \rm per\ cent}}$ reduction in the error bars over all z. The distribution of mock values of the autocorrelation function in this work is highly non-Gaussian for high-z, which should caution work with other statistics of the high-z Ly α forest against making this assumption. We use a rigorous statistical method to pass an inference test, however future work on non-Gaussian methods will enable higher precision measurements.
Astronomy & Astrophysics↗
The autocorrelation structure of Tausworthe pseudorandom number generators
An algorithm for determining the autocorrelation structure of a new sequence generated from an original sequence by proper decimation (a shift with each q-th term of the original sequence used) is presented, once autocorrelations for any repeating number sequence are known. The autocorrelation structure of the Tausworthe random number generator (RNG), based on proper decimation by q, is accepted as a RNG structure in which a proper decimation generates a long interval over which autocorrelations are small for all shifts. It is shown that if L bits of an N-bit Tausworthe RNG are L-bit binary numbers, L + 1 levels of correlation will exist, and L levels of correlation will each occur twice per RNG cycle length.
Neuman, F.↗
Effects of autocorrelation upon LANDSAT classification accuracy
Richmond, Virginia and Denver, Colorado were study sites in an effort to determine the effect of autocorrelation on the accuracy of a parallelopiped classifier of LANDSAT digital data. The autocorrelation was assumed to decay to insignificant levels when sampled at distances of at least ten pixels. Spectral themes developed using blocks of adjacent pixels, and using groups of pixels spaced at least 10 pixels apart were used. Effects of geometric distortions were minimized by using only pixels from the interiors of land cover sections. Accuracy was evaluated for three classes; agriculture, residential and "all other"; both type 1 and type 2 errors were evaluated by means of overall classification accuracy. All classes give comparable results. Accuracy is approximately the same in both techniques; however, the variance in accuracy is significantly higher using the themes developed from autocorrelated data. The vectors of mean spectral response were nearly identical regardless of sampling method used. The estimated variances were much larger when using autocorrelated pixels.
Craig, R. G.↗
Rough surface scattering results based on bandpass autocorrelation forms
Surface-height autocorrelation forms such as Gaussian and exponential are often used in studies of near-normal incidence rough-surface scattering. Such models require the existence of a constant, or DC, value in the spectrum. The consequences of autocorrelation forms that correspond to spectral processes that are essentially bandpass in nature are examined. One such process is that of ocean wind waves. In this case, the spectral components do not extend down to zero frequency. The physical optics backscatter theory is reexamined relative to such autocorrelation functions. Experimental results obtained from a wavetank are compared to the autocorrelation model used in the analysis. The analysis indicates that Gaussian correlation length or mean-square slope is not an appropriate parameter for narrowband conditions and that significant slope is a more relevant parameter. Inherent in the deep-phase assumption is some form of slope dependency. The analysis given (and variants thereof) can be used to provide insight into the physical effects of separate spectral components and of spectral directionality.
Miller, Lee S.↗
Autocorrelation and Multifractal Detrended Fluctuation Analyses Reveal Superdiffusive Mass Transport in Solvent-Filled Nanoporous Media
Fluorescence fluctuation spectroscopy experiments were conducted to better understand the complex mass transport dynamics of organic molecules in liquid-filled nanoporous media. Anodic aluminum oxide (AAO) membranes incorporating 10 and 20 nm diameter cylindrical pores were employed as model materials. Nile red (NR) dye was used as a fluorescent tracer. The dye was dissolved separately in ethanol and toluene at a concentration of 20 nM and used to fill the membrane nanopores. Confocal fluorescence microscopy was employed to capture photon intensity time series data reflecting apparent diffusion of the dye within the pores. Autocorrelation of these data revealed that NR diffusion within the membranes occurred over a broad range of time scales. The autocorrelation decays were fit to a model for one-dimensional diffusion incorporating both fast and slow components having apparent diffusion coefficients, D f and D s , differing by a factor of ∼100. The fast mechanism was attributed to hindered bulk-like diffusion in the central pore cavity, while slow diffusion likely involved absorption of the dye to the pore surfaces. Unfortunately, important evidence of diffusion anomalies is lost in the broad autocorrelation decays obtained. The method of multifractal detrended fluctuation analysis (MF-DFA) was applied to the same data as a means to overcome this limitation. MF-DFA revealed that time series acquired from within the nanopores were multifractal and exhibited evidence of anomalous superdiffusion, likely resulting from the participation of a desorption-mediated diffusion mechanism. Monte Carlo simulations of time series modeling desorption-mediated diffusion in cylindrical nanopores provided support for this assignment. Here, the new knowledge gained affords an improved understanding of hydrocarbon dynamics within nanoporous oil and gas shales.
Diffusion↗
Forecasting constraints on the high-z IGM thermal state from the Lyman-α forest flux autocorrelation function
ABSTRACT The autocorrelation function of the Lyman-$\alpha$ (Ly $\alpha$) forest flux from high-z quasars probes the small-scale structure of the intergalactic medium (IGM). The thermal state of the IGM, determined by the physics of reionization, sets the small-scale power observed in the Ly $\alpha$ forest. To explore the sensitivity of the autocorrelation function to the IGM’s thermal state, we compute the autocorrelation function from a cosmological hydrodynamical simulation with an instantaneous reionization model and 135 post-processed thermal states. Using mock data sets of 20 quasars, we forecast constraints on $T_0$ and $\gamma$, which characterize the post-processed IGM thermal state, at $5.4 \le z \le 6$. While this model simplifies the IGM’s thermal state, it serves as a key first step in assessing future observational prospects. We also perform an inference test on mocks and re-weight out posterior distributions to guarantee that they exhibit statistically correct behaviour. At $z = 5.4$, we find that an idealized data set constrains $T_0$ to 59 per cent and $\gamma$ to 16 per cent at the 1$\sigma$ equivalent confidence level. To explore more realistic, non-instantaneous reionization scenarios, we analyse four models combining temperature and ultraviolet background (UVB) fluctuations at $z = 5.8$. We find that mock data generated from a model with both temperature and UVB fluctuations can rule out a model with only temperature fluctuations at the $> 1\sigma$ level 73.9 per cent of the time.
Wolfson, Molly↗
Method of expanding noise autocorrelation function in a power series
Under certain conditions the normalized autocorrelation function ρ(τ) of stationary random noise may be expanded as a power series about the point τ = 0. This paper indicates that the coefficients of the expansion are rather simply related to the average rate of occurrence of zeros in the noise function and its derivatives. The expansion of academic interest in providing another perspective of the relationships among the noise function, its power spectrum, and its autocorrelation function. It may also be of practical interest in providing a quick means of estimating the normalized autocorrelation function from a noise record over the range of τ in which the power series converges rapidly. The class of noise spectrum for which convergent series expansion is not possible is of interest in pointing up necessary physical characteristics of noise signals which have such spectra.
F W Lehan↗
Precision in the evaluation of Landsat autocorrelation - The terrain effect
The autocorrelation present in Landsat data can be described by a two-parameter model. Presence of this autocorrelation seriously inflates estimates of the variance of a set of pixels. The degree of inflation is always serious but varies markedly according to the values of the parameters phi and Theta. Thus corrections of the effects of the model require precise estimates of these parameters. Two hypotheses are proposed to explain the variation of phi with location. Several lines of evidence are presented which support the idea that phi is induced directly by the autocorrelation structure of the terrain being sensed. It is suggested that use of this relation will allow economical estimates of phi for any scene of interest.
Craig, R. G.↗