scholarly journals Estimation of error on the cross-correlation, phase and time lag between evenly sampled light curves

2018 ◽  
Vol 23 ◽  
pp. 83-91 ◽  
Author(s):  
R. Misra ◽  
A. Bora ◽  
G. Dewangan
Keyword(s):  
Cross Correlation ◽  
Time Lag ◽  
Light Curves ◽  
Estimation Of Error ◽  
The Cross

scholarly journals A study of the cross-correlation and time lag in black hole X-ray binary XTE J1859+226

2017 ◽  
Vol 362 (7) ◽  
Author(s):  
Songpeng Pei ◽  
Guoqiang Ding ◽  
Zhibing Li ◽  
Yajuan Lei ◽  
Rai Yuen ◽  
...  
Keyword(s):  
Black Hole ◽  
Cross Correlation ◽  
Time Lag ◽  
X Ray ◽  
The Cross

scholarly journals EVOLUTION OF THE CROSS-CORRELATION AND TIME LAG OF 4U 1735-44 ALONG THE BRANCHES

2013 ◽  
Vol 146 (3) ◽  
pp. 60 ◽  
Author(s):  
Ya-Juan Lei ◽  
Hao-Tong Zhang ◽  
Cheng-Min Zhang ◽  
Jin-Lu Qu ◽  
Hai-Long Yuan ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Time Lag ◽  
The Cross

scholarly journals Autocorrelation and cross-correlation flow analysis along the confluence of the Kupa and Sava Rivers

2021 ◽  
Vol 36 (5) ◽  
pp. 67-77
Author(s):  
Marta Caren ◽  
Krešimir Pavlić
Keyword(s):  
Correlation Function ◽  
Cross Correlation ◽  
Time Lag ◽  
Flow Analysis ◽  
Meteorological Station ◽  
Cross Correlation Function ◽  
Maximum Value ◽  
Time Period ◽  
Cross Correlation Analysis ◽  
The Cross

In this paper, an autocorrelation and cross-correlation analysis of the flow of the Kupa and Sava rivers was performed. The analysis was performed at hydrological stations close to the confluence of these two rivers near the city of Sisak, based on data of mean daily flows and daily precipitation. The analysed time period is from 2008 to 2017, with the series being divided into two parts of five years each, from 2008 to 2012 and 2013 to 2017. Daily flow data were measured at the hydrological stations Farkašić on the Kupa River and Crnac on the Sava River, and data on precipitation at the main meteorological station and the automatic meteorological station Sisak. The maximum value of the cross-correlation function between the hydrological stations at the Kupa and Sava rivers is very high, but at a time lag of zero days. The value of the cross-correlation function remains high, up to 0.6 and up to a 4 day lag. The cross-correlation function between precipitation and hydrological data has a very low maximum value.

scholarly journals Ecology of Icerya purchasi Maskell, 1879 (Homoptera: Margarodidae) on clementine trees at Sidi Moussa (Central Mitidja, Algeria)

2020 ◽  
Vol 10 (5) ◽  
pp. 296-301
Author(s):  
L. Boukhobza ◽  
R. Belguendouz ◽  
M. Biche
Keyword(s):  
Cross Correlation ◽  
Temporal Dynamics ◽  
Statistical Tests ◽  
Integrated Control ◽  
Time Lag ◽  
Pairwise Comparison ◽  
Point Of View ◽  
Correlation Test ◽  
Larval Stages ◽  
The Cross

In order to establish better communication between applied entomology and fundamental ecology to consider an integrated control against the Australian cochineal Icerya purshasi Maskell, 1879 (Homoptera: Margarodidae) the most formidable pest for citrus fruits, a study on the Spatio-temporal dynamics of the parasite were followed for two years in a clementine orchard in Western Mitidja in Algeria. Ten-day samples of leaves and twigs were carried out from 2017 to 2018. The level of I. purchasi infestation is very high throughout the study period when the minimum threshold exceeds 400 individuals, with 3 intense periods of infestations: spring, summer and fall during the two years. The population of young larval stages is the largest during the two years of study with 13,323 individuals (62.79%) and 13,968 individuals (54.39%) in 2017 and 2018 respectively against 7896 individuals (37.21%) in 2017 and 11,715 individuals (33.50%) in 2018 for adults. Tukey's pairwise comparison test on the companion plan shows that the 2018 one is the most important from an overall effective point of view (ANOVA p≤1%, Tukey's test p≤1%). The Cross-Correlation Test shows the presence of a time lag (p=0.0371, p≤5%) and the maximum overall abundance was reported around mid-July for both campaigns. Statistical tests show that females show the same fertility during the two campaigns (ANOVA, p≤5%). peak fertility in 2017 was reported in mid-June, while peak fertility was reported in mid-July for the 2018 campaign. The Cross-Correlation Test shows a very significant time lag from one month to another (p=0.0064, p≤1%).

scholarly journals A novel method for quantifying periodicity and time delay in dynamic neural networks using unstable subaction potential threshold depolarizations

2020 ◽  
Vol 123 (3) ◽  
pp. 1236-1246
Author(s):  
Julian Sorensen ◽  
Nick J. Spencer
Keyword(s):  
Neural Networks ◽  
Correlation Function ◽  
Time Delay ◽  
Action Potentials ◽  
Cross Correlation ◽  
Time Lag ◽  
Cross Correlation Function ◽  
Electrical Signals ◽  
The Cross

Techniques to identify and correlate the propagation of electrical signals (like action potentials) along neural networks are well described, using multisite recordings. In these cases, the waveform of action potentials is usually relatively stable and discriminating relevant electrical signals straightforward. However, problems can arise when attempting to identify and correlate the propagation of signals when their waveforms are unstable (e.g., fluctuations in amplitude or time course). This makes correlation of the degree of synchronization and time lag between propagating electrical events across two or more recording sites problematic. Here, we present novel techniques for the determination of the periodicity of electrical signals at individual sites. When recording from two independent sites, we present novel analytical techniques for joint determination of periodicity and time delay. The techniques presented exploit properties of the cross-correlation function, rather than utilizing the time lag at which the cross-correlation function is maximized. The approach allows determination of directionality of the spread of excitation along a neural network based on measurements of the time delay between recording sites. This new method is particularly applicable to analysis of signals in other biological systems that have unstable characteristics in waveform that show dynamic variability. NEW & NOTEWORTHY The determination of frequency(s) at which two sources are synchronized, and relative time delay between them, is a fundamental problem for a wide a range of signal-processing applications. In this methodology paper, we present novel procedures for periodicity estimation for single time series and joint periodicity and time delay estimation for two time series. The methods use properties of the cross-correlation function rather than the cross-correlation function explicitly.

scholarly journals The relation between seismicity and water level changes in the Koyna–Warna region, India

2012 ◽  
Vol 12 (3) ◽  
pp. 813-817 ◽  
Author(s):  
J. Pavan Kumar ◽  
D. V. Ramana ◽  
R. K. Chadha ◽  
C. Singh ◽  
M. Shekar
Keyword(s):  
Water Level ◽  
Cross Correlation ◽  
Time Lag ◽  
Hydraulic Diffusivity ◽  
Water Level Changes ◽  
Daily Water ◽  
The Cross

Abstract. The analysis of the cross-correlation between the seismicity and the daily water level changes in both the Koyna and Warna (India) reservoirs is studied. The time lag between both datasets is calculated and is applied to estimate the hydraulic diffusivity. The range of the hydraulic diffusivity estimated between 0.1 m2 s−1 and 10 m2 s−1.

scholarly journals Emission-Line Variability in AGN

1989 ◽  
Vol 134 ◽  
pp. 100-102
Author(s):  
Dan Maoz
Keyword(s):  
Emission Line ◽  
Cross Correlation ◽  
Time Lag ◽  
Correlation Method ◽  
Seyfert Galaxy ◽  
Light Curves ◽  
Broad Line ◽  
Line Region ◽  
Order Of Magnitude

It has been apparent for some time that comparison of continuum and emission-line light curves of AGN may enable determination of the dimensions and structure of the Broad Line Region (BLR)(see Peterson 1988, and references therein). Observations to this end (Antonucci and Cohen 1983, Peterson et al. 1985, Clavel et al. 1987) and their analysis using cross-correlation to find the time lag between line and continuum variations (Gaskell and Sparke 1986), indicate BLR sizes an order of magnitude smaller than allowed by standard photoionization models for several AGN. Gaskell and Peterson (1987) analyzed errors in the cross-correlation method as applied to AGN time series in general and specifically to the Seyfert galaxy Akn120. In order to generalize and extend their analysis we investigated the significance of BLR sizes derived by cross-correlation under different model assumptions and observational circumstances (Maoz and Netzer 1988).

scholarly journals Fast infrared variability from the black hole candidate MAXI J1535−571 and tight constraints on the modelling

2021 ◽  
Vol 503 (1) ◽  
pp. 614-624
Author(s):  
F M Vincentelli ◽  
P Casella ◽  
D M Russell ◽  
M C Baglio ◽  
A Veledina ◽  
...  
Keyword(s):  
Black Hole ◽  
Cross Correlation ◽  
Light Curves ◽  
X Rays ◽  
X Ray ◽  
Black Hole Candidate ◽  
Near Ir ◽  
The Cross ◽  
Short Time ◽  
Ir Light

ABSTRACT We present the results regarding the analysis of the fast X-ray/infrared (IR) variability of the black hole transient MAXI J1535−571. The data studied in this work consist of two strictly simultaneous observations performed with XMM–Newton (X-rays: 0.7–10 keV), VLT/HAWK-I (Ks band, 2.2 μm) and VLT/VISIR (M and PAH2_2 bands, 4.85 and 11.88 μm, respectively). The cross-correlation function between the X-ray and near-IR light curves shows a strong asymmetric anticorrelation dip at positive lags. We detect a near-IR QPO (2.5σ) at 2.07 ± 0.09 Hz simultaneously with an X-ray QPO at approximately the same frequency (f0 = 2.25 ± 0.05). From the cross-spectral analysis, a lag consistent with zero was measured between the two oscillations. We also measure a significant correlation between the average near-IR and mid-IR fluxes during the second night, but find no correlation on short time-scales. We discuss these results in terms of the two main scenarios for fast IR variability (hot inflow and jet powered by internal shocks). In both cases, our preliminary modelling suggests the presence of a misalignment between the disc and jet.

Polarity Change Extraction of GPR Data for Under-road Cavity Detection: Application on Sudeoksa Testbed Data

2019 ◽  
Vol 24 (3) ◽  
pp. 419-431
Author(s):  
Jongha Hwang ◽  
Donggeon Kim ◽  
Xiangyue Li ◽  
Dong-Joo Min
Keyword(s):  
Phase Shift ◽  
Power Spectrum ◽  
Cross Correlation ◽  
Survey Methods ◽  
Time Lag ◽  
Background Signal ◽  
Data Set ◽  
Air Ground Interface ◽  
The Cross ◽  
Polarity Change

Ground penetrating radar (GPR) is one of the most widely used geophysical survey methods to locate cavities under roads due to its speedy exploration and high-resolution imaging. To locate underground cavities using GPR, we need to distinguish between cavity-induced reflections and other reflections, which can be achieved by examining the polarity change in reflections compared to the polarity of the transmitted signal. The polarity change can be measured from the phase shift between the target and first reflections. To estimate the phase shift in reflections, the method of computing the power spectrum difference between the original trace and background signal was proposed, but the method has a limitation for shallow reflectors. As an alternative method to avoid this limitation, we propose using only one component of the power spectrum difference, the cross-correlation between the target reflection and background signal. The cross-correlation has its maximum peak at a time lag between the target and first reflection (from the air-ground interface). Additionally, the phase at that time lag represents a phase shift between the two reflections. We compare our cross-correlation-based method with the conventional method of computing the whole power spectrum difference and investigate the feasibility of our method for distinguishing cavity-induced reflections using a 2D field data set acquired in a testbed in Sudeoksa, Korea.

scholarly journals Peering at the outflow mechanisms in the transitional pulsar PSR J1023+0038: simultaneous VLT, XMM-Newton, and Swift high-time resolution observations

2019 ◽  
Vol 631 ◽  
pp. A104 ◽  
Author(s):  
M. C. Baglio ◽  
F. Vincentelli ◽  
S. Campana ◽  
F. Coti Zelati ◽  
P. D’Avanzo ◽  
...  
Keyword(s):  
Correlation Function ◽  
Light Curve ◽  
Cross Correlation ◽  
Near Infrared ◽  
Light Curves ◽  
High Mode ◽  
Cross Correlation Function ◽  
X Ray ◽  
The Cross ◽  
Mode Transitions

We report on a simultaneous near-infrared, optical, and X-ray campaign performed in 2017 with the XMM-Newton and Swift satellites and the HAWK-I instrument mounted on the Very Large Telescope (VLT) on the transitional millisecond pulsar PSR J1023+0038. Near-infrared observations were performed in fast-photometric mode (0.5 s exposure time) in order to detect any fast variation of the flux and correlate this with the optical and X-ray light curves. The optical light curve shows the typical sinusoidal modulation at the system orbital period (4.75 h). No significant flaring or flickering is found in the optical, nor any signs of transitions between active and passive states. On the contrary, the near-infrared light curve displays a bimodal behaviour, showing strong flares in the first part of the curve, and an almost flat trend in the rest. The X-ray light curves instead show a few low-high mode transitions, but no flaring activity is detected. Interestingly, one of the low-high mode transitions occurs at the same time as the emission of an infrared flare. This can be interpreted in terms of the emission of an outflow or a jet: the infrared flare could be due to the evolving spectrum of the jet, which possesses a break frequency that moves from higher (near-infrared) to lower (radio) frequencies after the launching, which has to occur at the low-high mode transition. We also present the cross-correlation function between the optical and near-infrared curves. The near.infrared curve is bimodal, therefore we divided it into two parts (flaring and quiet). While the cross-correlation function of the quiet part is found to be flat, the function that refers to the flaring part shows a narrow peak at ∼10 s, which indicates a delay of the near-infrared emission with respect to the optical. This lag can be interpreted as reprocessing of the optical emission at the light cylinder radius with a stream of matter spiraling around the system due to a phase of radio ejection. This strongly supports a different origin of the infrared flares that are observed for PSR J1023+0038 with respect to the optical and X-ray flaring activity that has been reported in other works on the same source.

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