arXiv subjects

Shivaraj Kandhasamy

Publications and source records attributed to Shivaraj Kandhasamy.

17 recordsLinked to original sources

arXiv2026

A thorough investigation of cross-correlation estimators for stochastic gravitational-wave background searches in ground-based detector data

Detecting a stochastic gravitational-wave background represents a crucial yet challenging objective within the field of gravitational-wave astronomy. Ground-based detectors currently rely almost exclusively on cross-correlation methods to detect stochastic gravitational-wave background signals. Traditionally, these methods define and optimize a broadband estimator initially constructed in the time domain. However, a growing number of analyses require precise narrowband estimators to accurately characterize the energy density of the underlying signal in specific frequency bins. Transitioning from time-domain broadband estimators to frequency-domain narrowband estimators introduces significant complexities that have not yet been fully explored in the existing literature. In this study, we systematically revisit and rigorously reformulate the cross-correlation method in the frequency domain, explicitly addressing and resolving issues related to non-zero covariances induced by windowing and overlapping of data in the time domain. We provide new expressions for the narrowband estimators and their covariances, which differ from those used in past searches. Fortunately, we show that the expressions that have been widely used in the field nonetheless lead to correct posterior distributions for parameter estimation and correct log-Bayes factors for model selection. By establishing a robust theoretical framework, our work facilitates more accurate and physically insightful interpretations of stochastic gravitational-wave background observations, laying an essential foundation for current and future research in this field.

gr-qc↗

arXiv2023

Effects of calibration uncertainties on the detection and parameter estimation of isotropic gravitational-wave backgrounds

Gravitational-wave backgrounds are expected to arise from the superposition of gravitational wave signals from a large number of unresolved sources and also from the stochastic processes that occurred in the Early universe. So far, we have not detected any gravitational wave background, but with the improvements in the detectors' sensitivities, such detection is expected in the near future. The detection and inferences we draw from the search for a gravitational-wave background will depend on the source model, the type of search pipeline used, and the data generation in the gravitational-wave detectors. In this work, we focus on the effect of the data generation process, specifically the calibration of the detectors' digital output into strain data used by the search pipelines. Using the calibration model of the current LIGO detectors as an example, we show that for power-law source models and calibration uncertainties $\lesssim 10 \%$, the detection of isotropic gravitational wave background is not significantly affected. We also show that the source parameter estimation and upper limits calculations get biased. For calibration uncertainties of $\lesssim 5 \%$, the biases are not significant ($\lesssim 2 \%$), but for larger calibration uncertainties, they might become significant, especially when trying to differentiate between different models of isotropic gravitational-wave backgrounds.

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arXiv2023

pygwb: Python-based library for gravitational-wave background searches

The collection of gravitational waves (GWs) that are either too weak or too numerous to be individually resolved is commonly referred to as the gravitational-wave background (GWB). A confident detection and model-driven characterization of such a signal will provide invaluable information about the evolution of the Universe and the population of GW sources within it. We present a new, user-friendly Python--based package for gravitational-wave data analysis to search for an isotropic GWB in ground--based interferometer data. We employ cross-correlation spectra of GW detector pairs to construct an optimal estimator of the Gaussian and isotropic GWB, and Bayesian parameter estimation to constrain GWB models. The modularity and clarity of the code allow for both a shallow learning curve and flexibility in adjusting the analysis to one's own needs. We describe the individual modules which make up {\tt pygwb}, following the traditional steps of stochastic analyses carried out within the LIGO, Virgo, and KAGRA Collaboration. We then describe the built-in pipeline which combines the different modules and validate it with both mock data and real GW data from the O3 Advanced LIGO and Virgo observing run. We successfully recover all mock data injections and reproduce published results.

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arXiv2021

Gravitational-wave searches in the era of Advanced LIGO and Virgo

The field of gravitational-wave astronomy has been opened up by gravitational-wave observations made with interferometric detectors. This review surveys the current state-of-the-art in gravitational-wave detectors and data analysis methods currently used by the Laser Interferometer Gravitational-Wave Observatory in the United States and the Virgo Observatory in Italy. These analysis methods will also be used in the recently completed KAGRA Observatory in Japan. Data analysis algorithms are developed to target one of four classes of gravitational waves. Short duration, transient sources include compact binary coalescences, and burst sources originating from poorly modelled or unanticipated sources. Long duration sources include sources which emit continuous signals of consistent frequency, and many unresolved sources forming a stochastic background. A description of potential sources and the search for gravitational waves from each of these classes are detailed.

gr-qc↗

arXiv2021

Characterization of systematic error in Advanced LIGO calibration in the second half of O3

We present the probability distribution of the systematic errors in the most accurate, high-latency version of the reconstructed dimensionless strain $h$, at the Hanford and Livingston LIGO detectors, used for gravitational-wave astrophysical analysis, including parameter estimation, in the last five months of the third observing run (O3B). This work extends the results presented in Sun et. al (2020) [1] for the first six months of the third observing run (O3A). The complex-valued, frequency-dependent, and slowly time-varying systematic error (excursion from unity magnitude and zero phase) in O3B generally remains at a consistent level as in O3A, yet changes of detector configurations in O3B have introduced a non-negligible change in the frequency dependence of the error, leading to larger excursions from unity at some frequencies and/or during some observational periods; in some other periods the excursions are smaller than those in O3A. For O3B, the upper limit on the systematic error and associated uncertainty is 11.29% in magnitude and 9.18 deg in phase (68% confidence interval) in the most sensitive frequency band 20-2000 Hz. The systematic error alone is estimated at levels of < 2% in magnitude and $\lesssim 4$ deg in phase. These errors and uncertainties are dominated by the imperfect modeling of the frequency dependence of the detector response functions rather than the uncertainty in the absolute reference, the photon calibrators.

astro-ph.IM↗

arXiv2021

Search for the stochastic gravitational-wave background induced by primordial curvature perturbations in LIGO's second observing run

Primordial density perturbations in the radiation-dominated era of the early Universe are expected to generate stochastic gravitational waves (GWs) due to nonlinear mode coupling. In this \emph{Letter}, we report on a search for such a stochastic GW background in the data of the two LIGO detectors during their second observing run (O2). We focus on the primordial perturbations in the range of comoving wavenumbers $10^{16}-10^{18}~{\rm Mpc}^{-1}$ for which the stochastic background falls within the detectors' sensitivity band. We do not find any conclusive evidence of this stochastic signal in the data, and thus place the very first GW-based constraints on the amplitude of the power spectrum at these scales. We assume a lognormal shape for the power spectrum and Gaussian statistics for the primordial perturbations, and vary the width of the power spectrum to cover both narrow and broad spectra. Derived upper limits ($95\%$) on the amplitude of the power spectrum are $0.01-0.1$. As a byproduct, we are able to infer upper limits on the fraction of the Universe's mass in ultralight primordial black holes ($M_\mathrm{PBH} \simeq 10^{-20}-10^{-19}M_{\odot}$) at their formation time to be $\lesssim 10^{-25}$.

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arXiv2021

Point absorbers in Advanced LIGO

Small, highly absorbing points are randomly present on the surfaces of the main interferometer optics in Advanced LIGO. The resulting nano-meter scale thermo-elastic deformations and substrate lenses from these micron-scale absorbers significantly reduces the sensitivity of the interferometer directly though a reduction in the power-recycling gain and indirect interactions with the feedback control system. We review the expected surface deformation from point absorbers and provide a pedagogical description of the impact on power build-up in second generation gravitational wave detectors (dual-recycled Fabry-Perot Michelson interferometers). This analysis predicts that the power-dependent reduction in interferometer performance will significantly degrade maximum stored power by up to 50% and hence, limit GW sensitivity, but suggests system wide corrections that can be implemented in current and future GW detectors. This is particularly pressing given that future GW detectors call for an order of magnitude more stored power than currently used in Advanced LIGO in Observing Run 3. We briefly review strategies to mitigate the effects of point absorbers in current and future GW wave detectors to maximize the success of these enterprises.

physics.ins-det↗

arXiv2020

Characterization of systematic error in Advanced LIGO calibration

The raw outputs of the detectors within the Advanced Laser Interferometer Gravitational-Wave Observatory need to be calibrated in order to produce the estimate of the dimensionless strain used for astrophysical analyses. The two detectors have been upgraded since the second observing run and finished the year-long third observing run. Understanding, accounting, and/or compensating for the complex-valued response of each part of the upgraded detectors improves the overall accuracy of the estimated detector response to gravitational waves. We describe improved understanding and methods used to quantify the response of each detector, with a dedicated effort to define all places where systematic error plays a role. We use the detectors as they stand in the first half (six months) of the third observing run to demonstrate how each identified systematic error impacts the estimated strain and constrain the statistical uncertainty therein. For this time period, we estimate the upper limit on systematic error and associated uncertainty to be $< 7\%$ in magnitude and $< 4$ deg in phase ($68\%$ confidence interval) in the most sensitive frequency band 20-2000 Hz. The systematic error alone is estimated at levels of $< 2\%$ in magnitude and $< 2$ deg in phase.

astro-ph.IM↗

arXiv2017

Calibration Uncertainty for Advanced LIGO's First and Second Observing Runs

Calibration of the Advanced LIGO detectors is the quantification of the detectors' response to gravitational waves. Gravitational waves incident on the detectors cause phase shifts in the interferometer laser light which are read out as intensity fluctuations at the detector output. Understanding this detector response to gravitational waves is crucial to producing accurate and precise gravitational wave strain data. Estimates of binary black hole and neutron star parameters and tests of general relativity require well-calibrated data, as miscalibrations will lead to biased results. We describe the method of producing calibration uncertainty estimates for both LIGO detectors in the first and second observing runs.

astro-ph.IM↗

arXiv2017

Transient Classification in LIGO data using Difference Boosting Neural Network

Detection and classification of transients in data from gravitational wave detectors are crucial for efficient searches for true astrophysical events and identification of noise sources. We present a hybrid method for classification of short duration transients seen in gravitational wave data using both supervised and unsupervised machine learning techniques. To train the classifiers we use the relative wavelet energy and the corresponding entropy obtained by applying one-dimensional wavelet decomposition on the data. The prediction accuracy of the trained classifier on 9 simulated classes of gravitational wave transients and also LIGO's sixth science run hardware injections are reported. Targeted searches for a couple of known classes of non-astrophysical signals in the first observational run of Advanced LIGO data are also presented. The ability to accurately identify transient classes using minimal training samples makes the proposed method a useful tool for LIGO detector characterization as well as searches for short duration gravitational wave signals.

astro-ph.IM↗

arXiv2015

A Mock Data and Science Challenge for Detecting an Astrophysical Stochastic Gravitational-Wave Background with Advanced LIGO and Advanced Virgo

The purpose of this mock data and science challenge is to prepare the data analysis and science interpretation for the second generation of gravitational-wave experiments Advanced LIGO-Virgo in the search for a stochastic gravitational-wave background signal of astrophysical origin. Here we present a series of signal and data challenges, with increasing complexity, whose aim is to test the ability of current data analysis pipelines at detecting an astrophysically produced gravitational-wave background, test parameter estimation methods and interpret the results. We introduce the production of these mock data sets that includes a realistic observing scenario data set where we account for different sensitivities of the advanced detectors as they are continuously upgraded toward their design sensitivity. After analysing these with the standard isotropic cross-correlation pipeline we find that we are able to recover the injected gravitational-wave background energy density to within $2σ$ for all of the data sets and present the results from the parameter estimation. The results from this mock data and science challenge show that advanced LIGO and Virgo will be ready and able to make a detection of an astrophysical gravitational-wave background within a few years of operations of the advanced detectors, given a high enough rate of compact binary coalescing events.

astro-ph.HE↗

arXiv2015

Chasing 5-sigma: Prospects for searches for long-duration gravitational-waves without time slides

The detection of unmodeled gravitational-wave bursts by ground-based interferometric gravitational-wave detectors is a major goal for the advanced detector era. These searches are commonly cast as pattern recognition problems, where the goal is to identify statistically significant clusters in spectrograms of strain power when the precise signal morphology is unknown. In previous work, we have introduced a clustering algorithm referred to as "seedless clustering," and shown that it is a powerful tool for detecting weak long-lived (10-1000s) signals in background. However, as the algorithm is currently conceived, in order to carry out an all-sky search on a $\approx$ year of data, significant computational resources may be required in order to carry out background estimation. Alternatively, some of the sensitivity of the search must be sacrificed to control computational costs. The sensitivity of the algorithm is limited by the amount of computing resources due to the requirement of performing background studies to assign significance in gravitational-wave searches. In this paper, we present an analytic method for estimating the background generated by the seedless clustering algorithm and compare the performance to both Monte Carlo Gaussian noise and time-shifted gravitational-wave data from a week of LIGO's 5th Science Run. We demonstrate qualitative agreement between the model and measured distributions and argue that the approximation will be useful to supplement conventional background estimation techniques for advanced detector searches for long-duration gravitational-wave transients.

gr-qc↗

arXiv2014

Wiener filtering with a seismic underground array at the Sanford Underground Research Facility

A seismic array has been deployed at the Sanford Underground Research Facility in the former Homestake mine, South Dakota, to study the underground seismic environment. This includes exploring the advantages of constructing a third-generation gravitational-wave detector underground. A major noise source for these detectors would be Newtonian noise, which is induced by fluctuations in the local gravitational field. The hope is that a combination of a low-noise seismic environment and coherent noise subtraction using seismometers in the vicinity of the detector could suppress the Newtonian noise to below the projected noise floor for future gravitational-wave detectors. In this paper, we use Wiener filtering techniques to subtract coherent noise in a seismic array in the frequency band 0.05 -- 1\,Hz. This achieves more than an order of magnitude noise cancellation over a majority of this band. We show how this subtraction would benefit proposed future low-frequency gravitational wave detectors. The variation in the Wiener filter coefficients over the course of the day, including how local activities impact the filter, is analyzed. We also study the variation in coefficients over the course of a month, showing the stability of the filter with time. How varying the filter order affects the subtraction performance is also explored. It is shown that optimizing filter order can significantly improve subtraction of seismic noise, which gives hope for future gravitational-wave detectors to address Newtonian noise.

gr-qc↗

arXiv2014

Method for estimation of gravitational-wave transient model parameters in frequency-time maps

A common technique for detection of gravitational-wave signals is searching for excess power in frequency-time maps of gravitational-wave detector data. In the event of a detection, model selection and parameter estimation will be performed in order to explore the properties of the source. In this paper, we develop a Bayesian statistical method for extracting model-dependent parameters from observed gravitational-wave signals in frequency-time maps. We demonstrate the method by recovering the parameters of model gravitational-wave signals added to simulated advanced LIGO noise. We also characterize the performance of the method and discuss prospects for future work.

gr-qc↗

arXiv2012

Identification of noise artifacts in searches for long-duration gravitational-wave transients

We present an algorithm for the identification of transient noise artifacts (glitches) in cross-correlation searches for long O(10s) gravitational-wave transients. The algorithm utilizes the auto-power in each detector as a discriminator between well-behaved Gaussian noise (possibly including a gravitational-wave signal) and glitches. We test the algorithm with both Monte Carlo noise and time-shifted data from the LIGO S5 science run and find that it is effective at removing a significant fraction of glitches while keeping the vast majority (99.6%) of the data. Using an accretion disk instability signal model, we estimate that the algorithm is accidentally triggered at a rate of less than 10^-5% by realistic signals, and less than 3% even for exceptionally loud signals. We conclude that the algorithm is a safe and effective method for cleaning the cross-correlation data used in searches for long gravitational-wave transients.

astro-ph.IM↗

arXiv2011

Long gravitational-wave transients and associated detection strategies for a network of terrestrial interferometers

Searches for gravitational waves (GWs) traditionally focus on persistent sources (e.g., pulsars or the stochastic background) or on transients sources (e.g., compact binary inspirals or core-collapse supernovae), which last for timescales of milliseconds to seconds. We explore the possibility of long GW transients with unknown waveforms lasting from many seconds to weeks. We propose a novel analysis technique to bridge the gap between short O(s) burst analyses and persistent stochastic analyses. Our technique utilizes frequency-time maps of GW strain cross-power between two spatially separated terrestrial GW detectors. The application of our cross-power statistic to searches for GW transients is framed as a pattern recognition problem, and we discuss several pattern-recognition techniques. We demonstrate these techniques by recovering simulated GW signals in simulated detector noise. We also recover environmental noise artifacts, thereby demonstrating a novel technique for the identification of such artifacts in GW interferometers. We compare the efficiency of this framework to other techniques such as matched filtering.

astro-ph.IM↗

arXiv2010

Characterization of the seismic environment at the Sanford Underground Laboratory, South Dakota

An array of seismometers is being developed at the Sanford Underground Laboratory, the former Homestake mine, in South Dakota to study the properties of underground seismic fields and Newtonian noise, and to investigate the possible advantages of constructing a third-generation gravitational-wave detector underground. Seismic data were analyzed to characterize seismic noise and disturbances. External databases were used to identify sources of seismic waves: ocean-wave data to identify sources of oceanic microseisms, and surface wind-speed data to investigate correlations with seismic motion as a function of depth. In addition, sources of events contributing to the spectrum at higher frequencies are characterized by studying the variation of event rates over the course of a day. Long-term observations of spectral variations provide further insight into the nature of seismic sources. Seismic spectra at three different depths are compared, establishing the 4100-ft level as a world-class low seismic-noise environment.

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