scholarly journals Random time series in astronomy

2013 ◽  
Vol 371 (1984) ◽  
pp. 20110549 ◽  
Author(s):  
Simon Vaughan
Keyword(s):  
Time Series ◽  
Black Holes ◽  
Time Domain ◽  
Gamma Ray ◽  
Power Spectra ◽  
Polarization Angle ◽  
Noise Power ◽  
Future Challenges ◽  
Nearby Galaxies ◽  
The Time Domain

Progress in astronomy comes from interpreting the signals encoded in the light received from distant objects: the distribution of light over the sky (images), over photon wavelength (spectrum), over polarization angle and over time (usually called light curves by astronomers). In the time domain, we see transient events such as supernovae, gamma-ray bursts and other powerful explosions; we see periodic phenomena such as the orbits of planets around nearby stars, radio pulsars and pulsations of stars in nearby galaxies; and we see persistent aperiodic variations (‘noise’) from powerful systems such as accreting black holes. I review just a few of the recent and future challenges in the burgeoning area of time domain astrophysics, with particular attention to persistently variable sources, the recovery of reliable noise power spectra from sparsely sampled time series, higher order properties of accreting black holes, and time delays and correlations in multi-variate time series.

scholarly journals Lightweight Unmanned Aerial System for Time-Domain Electromagnetic Prospecting—The Next Stage in Applied UAV-Geophysics

2021 ◽  
Vol 11 (5) ◽  
pp. 2060 ◽  
Author(s):  
Alexander Parshin ◽  
Ayur Bashkeev ◽  
Yuriy Davidenko ◽  
Marina Persova ◽  
Sergey Iakovlev ◽  
...  
Keyword(s):  
Time Domain ◽  
Gamma Ray ◽  
Pulse Generator ◽  
Measuring System ◽  
Electromagnetic Sounding ◽  
Mountainous Regions ◽  
Time Domain Electromagnetic ◽  
Unmanned System ◽  
Classical Triad ◽  
The Time Domain

Nowadays in solving geological problems, the technologies of UAV-geophysics, primarily magnetic and gamma surveys, are being increasingly used. However, for the formation of the classical triad of airborne geophysics methods in the UAV version, there was not enough technology for UAV-electromagnetic sounding, which would allow studying the geological environment at depths of tens and hundreds of meters with high detail. This article describes apparently the first technology of UAV-electromagnetic sounding in the time domain (TDEM, TEM), implemented as an unmanned system based on a light multi-rotor UAV. A measuring system with an inductive sensor—an analogue of a 20 × 20 or 50 × 50 m receiving loop is towed by a UAV, and a galvanically grounded power transmitter is on the ground and connected to a pulse generator. The survey is carried out along a network of parallel lines at low altitude with a terrain draping at a speed of 7–8 m/s, the maximum distance of the UAV’s departure from the transmitter line can reach several kilometers, thus the created technology is optimal for performing detailed areal electromagnetic soundings in areas of several square kilometers. The results of the use of the unmanned system (UAS) in real conditions of the mountainous regions of Eastern Siberia are presented. Based on the obtained data, the sensitivity of the system was simulated and it was shown that the developed technology allows one to collect informative data and create geophysical sections and maps of electrical resistivity in various geological situations. According to the authors, the emergence of UAV-TEM systems in the near future will significantly affect the practice of geophysical work, as it was earlier with UAV-magnetic prospecting and gamma-ray survey.

scholarly journals ROLE OF THE 3.6M DOT TO INVESTIGATE CONNECTIONS BETWEEN LONG-GRBS AND CORE-COLLAPSE SNE

2021 ◽  
Vol 53 ◽  
pp. 127-133
Author(s):  
A. Kumar ◽  
S. B. Pandey ◽  
R. Gupta ◽  
A. Aryan ◽  
A. J. Castro-Tirado ◽  
...  
Keyword(s):  
Time Domain ◽  
Gamma Ray ◽  
Gamma Ray Bursts ◽  
Global Network ◽  
Core Collapse ◽  
Robotic Telescopes ◽  
The Time Domain ◽  
Time Critical ◽  
Near Future

Newly installed 3.6m DOT at Nainital (Uttarakhand) is a novel facility for the time domain astronomy. Because of the longitudinal advantage of India, it could be used to study new transients reported by a global network of robotic telescopes. Observations with the 4K × 4K CCD Imager at the axial port of the 3.6m DOT will be very helpful in the near future towards understanding the different physical aspects of time-critical events, e.g., Gamma-ray bursts (GRBs), Supernovae, Gravitational wave candidates, etc. Using the Imager with broadband filters (Bessel UBVRI and SDSS ugriz), ~6.5' × 6.5' images could be obtained to attempt various science goals in synergy with other multi-band facilities. In this study, we present an analysis of unpublished R-band data of GRB 171205A/SN 2017iuk spanning between ~12 to 105 days since burst, that observed using the 3.6m DOT with 4K × 4K CCD Imager. In the R-band light curve, a bump appears to start from ~3 days, which shows the peak at ~15 days after the burst, clearly indicates photometric evidence of association of SN with GRB 171205A.

Gamma-ray bursts: the time domain

1995 ◽  
Vol 231 (1-2) ◽  
pp. 95-102 ◽  
Author(s):  
Jay P. Norris
Keyword(s):  
Time Domain ◽  
Gamma Ray ◽  
Gamma Ray Bursts ◽  
The Time Domain

scholarly journals Characteristic Variability Time Scales of Long Gamma-Ray Bursts

2003 ◽  
Vol 214 ◽  
pp. 339-340
Author(s):  
Rongfeng Shen ◽  
Liming Song
Keyword(s):  
Power Density ◽  
Time Scales ◽  
Time Domain ◽  
Time Scale ◽  
Gamma Ray ◽  
Gamma Ray Bursts ◽  
Time Dilation ◽  
Dilation Effect ◽  
The Time Domain ◽  
Intrinsic Characteristic

We determine the characteristic variability time scales for 410 bright long GRBs by locating the maximums of their Power Density Spectra (PDSs) defined and calculated in the time domain. The averaged characteristic variability time scale decreases with peak fluxe. This is consistent with the time dilation effect expected by cosmological origin of GRBs. The occurrence distribution of the characteristic variability time scale shows bimodality, which might be interpreted as that the long GRB sample is composed of two sub-classes with different intrinsic characteristic variability time scales.

scholarly journals A New Method for Time Series Filtering near Endpoints

2008 ◽  
Vol 25 (4) ◽  
pp. 534-546 ◽  
Author(s):  
Anthony Arguez ◽  
Peng Yu ◽  
James J. O’Brien
Keyword(s):  
Time Series ◽  
Least Squares ◽  
Time Domain ◽  
Southern Oscillation ◽  
Fundamental Property ◽  
Great Promise ◽  
Constraint Forces ◽  
Variance Method ◽  
Equal Variance ◽  
The Time Domain

Abstract Time series filtering (e.g., smoothing) can be done in the spectral domain without loss of endpoints. However, filtering is commonly performed in the time domain using convolutions, resulting in lost points near the series endpoints. Multiple incarnations of a least squares minimization approach are developed that retain the endpoint intervals that are normally discarded due to filtering with convolutions in the time domain. The techniques minimize the errors between the predetermined frequency response function (FRF)—a fundamental property of all filters—of interior points with FRFs that are to be determined for each position in the endpoint zone. The least squares techniques are differentiated by their constraints: 1) unconstrained, 2) equal-mean constraint, and 3) an equal-variance constraint. The equal-mean constraint forces the new weights to sum up to the same value as the predetermined weights. The equal-variance constraint forces the new weights to be such that, after convolved with the input values, the expected time series variance is preserved. The three least squares methods are each tested under three separate filtering scenarios [involving Arctic Oscillation (AO), Madden–Julian oscillation (MJO), and El Niño–Southern Oscillation (ENSO) time series] and compared to each other as well as to the spectral filtering method—the standard of comparison. The results indicate that all four methods (including the spectral method) possess skill at determining suitable endpoints estimates. However, both the unconstrained and equal-mean schemes exhibit bias toward zero near the terminal ends due to problems with appropriating variance. The equal-variance method does not show evidence of this attribute and was never the worst performer. The equal-variance method showed great promise in the ENSO project involving a 5-month running mean filter, and performed at least on par with the other realistic methods for almost all time series positions in all three filtering scenarios.

DETECTION AND MODELING OF REGRESSION PARAMETER VARIATION ACROSS FREQUENCIES

1999 ◽  
Vol 3 (1) ◽  
pp. 69-83 ◽  
Author(s):  
Hui Boon Tan ◽  
Richard Ashley
Keyword(s):  
Time Series ◽  
Regression Model ◽  
Time Domain ◽  
Simple Technique ◽  
Parameter Variation ◽  
Missing Observations ◽  
Regression Parameter ◽  
Time Series Regression ◽  
Parameter Instability ◽  
The Time Domain

A simple technique for directly testing the parameters of a time-series regression model for instability across frequencies is presented. The method can be implemented easily in the time domain, so that parameter instability across frequency bands can be conveniently detected and modeled in conjunction with other econometric features of the problem at hand, such as simultaneity, cointegration, missing observations, and cross-equation restrictions. The usefulness of the new technique is illustrated with an application to a cointegrated consumption-income regression model, yielding a straightforward test of the permanent income hypothesis.

scholarly journals Clustering revisited: A spectral analysis of microseismic events

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. KS41-KS49 ◽  
Author(s):  
Deborah Fagan ◽  
Kasper van Wijk ◽  
James Rutledge
Keyword(s):  
Oil Recovery ◽  
Time Domain ◽  
Power Spectra ◽  
Fault System ◽  
Microseismic Events ◽  
The Fourier Transform ◽  
The Time Domain ◽  
The Relationship ◽  
Single Cluster ◽  
Full Body

Identifying individual subsurface faults in a larger fault system is important to characterize and understand the relationship between microseismicity and subsurface processes. This information can potentially help drive reservoir management and mitigate the risks of natural or induced seismicity. We have evaluated a method of statistically clustering power spectra from microseismic events associated with an enhanced oil recovery operation in southeast Utah. Specifically, we were able to provide a clear distinction within a set of events originally designated in the time domain as a single cluster and to identify evidence of en echelon faulting. Subtle time-domain differences between events were accentuated in the frequency domain. Power spectra based on the Fourier transform of the time-domain autocorrelation function were used, as this formulation results in statistically independent intensities and is supported by a full body of statistical theory upon which decision frameworks can be developed.

scholarly journals A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship

2020 ◽  
Vol 24 (11) ◽  
pp. 5473-5489 ◽  
Author(s):  
Justin Schulte ◽  
Frederick Policielli ◽  
Benjamin Zaitchik
Keyword(s):  
Time Series ◽  
Time Domain ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Wavelet Coherence ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
The Time Domain ◽  
Time Domain Correlation

Abstract. Wavelet coherence is a method that is commonly used in hydrology to extract scale-dependent, nonstationary relationships between time series. However, we show that the method cannot always determine why the time-domain correlation between two time series changes in time. We show that, even for stationary coherence, the time-domain correlation between two time series weakens if at least one of the time series has changing skewness. To overcome this drawback, a nonlinear coherence method is proposed to quantify the cross-correlation between nonlinear modes embedded in the time series. It is shown that nonlinear coherence and auto-bicoherence spectra can provide additional insight into changing time-domain correlations. The new method is applied to the El Niño–Southern Oscillation (ENSO) and all-India rainfall (AIR), which is intricately linked to hydrological processes across the Indian subcontinent. The nonlinear coherence analysis showed that the skewness of AIR is weakly correlated with that of two ENSO time series after the 1970s, indicating that increases in ENSO skewness after the 1970s at least partially contributed to the weakening ENSO–AIR relationship in recent decades. The implication of this result is that the intensity of skewed El Niño events is likely to overestimate India's drought severity, which was the case in the 1997 monsoon season, a time point when the nonlinear wavelet coherence between AIR and ENSO reached its lowest value in the 1871–2016 period. We determined that the association between the weakening ENSO–AIR relationship and ENSO nonlinearity could reflect the contribution of different nonlinear ENSO modes to ENSO diversity.

scholarly journals Hydrological model performance and parameter estimation in the wavelet-domain

2009 ◽  
Vol 6 (2) ◽  
pp. 2451-2498 ◽  
Author(s):  
B. Schaefli ◽  
E. Zehe
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
Time Domain ◽  
Model Performance ◽  
Time Varying ◽  
Wavelet Domain ◽  
Frequency Content ◽  
Time Varying Frequency ◽  
The Time Domain

Abstract. This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series) of a simulated discharge series to the one of the corresponding observed time series. As discussed in this paper, calibrating hydrological models so as to reproduce the time-varying frequency content of the observed signal can lead to different results than parameter estimation in the time-domain. Therefore, wavelet-domain parameter estimation has the potential to give new insights into model performance and to reveal model structural deficiencies. We apply the proposed method to synthetic case studies and a real-world discharge modeling case study and discuss how model diagnosis can benefit from an analysis in the wavelet-domain. The results show that for the real-world case study of precipitation – runoff modeling for a high alpine catchment, the calibrated discharge simulation captures the dynamics of the observed time series better than the results obtained through calibration in the time-domain. In addition, the wavelet-domain performance assessment of this case study highlights which frequencies are not well reproduced by the model, which gives specific indications about how to improve the model structure.

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