Cosmic String Cusps with Small-Scale Structure: Their Forms and Gravitational Waveforms

We present a method for the introduction of small-scale structure into strings constructed from products of rotation matrices. We use this method to illustrate a range of possibilities for the shape of cusps that depends on the properties of the small-scale structure. We further argue that the presence of structure at cusps under most circumstances leads to the formation of loops at the size of the smallest scales. On the other hand we show that the gravitational waveform of a cusp remains generally unchanged; the primary effect of small-scale structure is to smooth out the sharp waveform emitted in the direction of cusp motion.Comment: RevTeX, 8 pages. Replaced with version accepted for publication by PR

On the size of the smallest scales in cosmic string networks

We present a method for the calculation of the gravitational back reaction cutoff on the smallest scales of cosmic string networks taking into account that not all modes on strings interact with all other modes. This results in a small scale structure cutoff that is sensitive to the initial spectrum of perturbations present on strings. From a simple model, we compute the cutoffs in radiation- and matter-dominated universes.Comment: 4 pages, revte

GravEn: Software for the simulation of gravitational wave detector network response

Physically motivated gravitational wave signals are needed in order to study the behaviour and efficacy of different data analysis methods seeking their detection. GravEn, short for Gravitational-wave Engine, is a MATLAB software package that simulates the sampled response of a gravitational wave detector to incident gravitational waves. Incident waves can be specified in a data file or chosen from among a group of pre-programmed types commonly used for establishing the detection efficiency of analysis methods used for LIGO data analysis. Every aspect of a desired signal can be specified, such as start time of the simulation (including inter-sample start times), wave amplitude, source orientation to line of sight, location of the source in the sky, etc. Supported interferometric detectors include LIGO, GEO, Virgo and TAMA.Comment: 10 Pages, 3 Figures, Presented at the 10th Gravitational Wave Data Analysis Workshop (GWDAW-10), 14-17 December 2005 at the University of Texas, Brownsvill

Common-spectrum process versus cross-correlation for gravitational-wave searches using pulsar timing arrays

The North American Nanohertz Observatory for Gravitational Waves (NANOGrav) has recently reported strong statistical evidence for a common-spectrum red-noise process for all pulsars, as seen in their 12.5-yr analysis for an isotropic stochastic gravitational-wave signal. However, there is currently very little evidence for quadrupolar spatial correlations across the pulsars in the array, which is needed to make a confident claim of detection of a stochastic gravitational-wave background. In this paper, we provide a “back-of-the-envelope” illustration of the NANOGrav 12.5-yr results for the nonexpert reader, using a very simple signal+noise model and frequentist statistics. We show that the current lack of evidence for spatial correlations is consistent with the magnitude of the correlation coefficients for pairs of Earth-pulsar baselines in the array and the fact that pulsar timing arrays are most likely operating in the intermediate-signal regime. We derive analytic expressions that allow one to compare the expected values of the signal-to-noise ratios for both common-spectrum and cross-correlation estimators

The stochastic background: scaling laws and time to detection for pulsar timing arrays

We derive scaling laws for the signal-to-noise ratio of the optimal cross-correlation statistic, and show that the large power-law increase of the signal-to-noise ratio as a function of the observation time T that is usually assumed holds only at early times. After enough time has elapsed, pulsar timing arrays enter a new regime where the signal to noise only scales as . In addition, in this regime the quality of the pulsar timing data and the cadence become relatively unimportant. This occurs because the lowest frequencies of the pulsar timing residuals become gravitational-wave dominated. Pulsar timing arrays enter this regime more quickly than one might naively suspect. For T = 10 yr observations and typical stochastic background amplitudes, pulsars with residual root-mean-squares of less than about 1 μs are already in that regime. The best strategy to increase the detectability of the background in this regime is to increase the number of pulsars in the array. We also perform realistic simulations of the NANOGrav pulsar timing array, which through an aggressive pulsar survey campaign adds new millisecond pulsars regularly to its array, and show that a detection is possible within a decade, and could occur as early as 2016

Gravitational-Wave Stochastic Background from Kinks and Cusps on Cosmic Strings

We compute the contribution of kinks on cosmic string loops to stochastic background of gravitational waves (SBGW).We find that kinks contribute at the same order as cusps to the SBGW.We discuss the accessibility of the total background due to kinks as well as cusps to current and planned gravitational wave detectors, as well as to the big bang nucleosynthesis (BBN), the cosmic microwave background (CMB), and pulsar timing constraints. As in the case of cusps, we find that current data from interferometric gravitational wave detectors, such as LIGO, are sensitive to areas of parameter space of cosmic string models complementary to those accessible to pulsar, BBN, and CMB bounds.Comment: 24 pages, 3 figure

Chi-square test on candidate events from CW signal coherent searches

In a blind search for continuous gravitational wave signals scanning a wide frequency band one looks for candidate events with significantly large values of the detection statistic. Unfortunately, a noise line in the data may also produce a moderately large detection statistic. In this paper, we describe how we can distinguish between noise line events and actual continuous wave (CW) signals, based on the shape of the detection statistic as a function of the signal's frequency. We will analyze the case of a particular detection statistic, the F statistic, proposed by Jaranowski, Krolak, and Schutz. We will show that for a broad-band 10 hour search, with a false dismissal rate smaller than 1e-6, our method rejects about 70 % of the large candidate events found in a typical data set from the second science run of the Hanford LIGO interferometer.Comment: proceedings of GWDAW8, 2003 conference, 12pages, 6 figure

Scaling in the Lattice Gas Model

A good quality scaling of the cluster size distributions is obtained for the Lattice Gas Model using the Fisher's ansatz for the scaling function. This scaling identifies a pseudo-critical line in the phase diagram of the model that spans the whole (subcritical to supercritical) density range. The independent cluster hypothesis of the Fisher approach is shown to describe correctly the thermodynamics of the lattice only far away from the critical point.Comment: 4 pages, 3 figure

Reconstructing the calibrated strain signal in the Advanced LIGO detectors

Advanced LIGO's raw detector output needs to be calibrated to compute dimensionless strain h(t). Calibrated strain data is produced in the time domain using both a low-latency, online procedure and a high-latency, offline procedure. The low-latency h(t) data stream is produced in two stages, the first of which is performed on the same computers that operate the detector's feedback control system. This stage, referred to as the front-end calibration, uses infinite impulse response (IIR) filtering and performs all operations at a 16384 Hz digital sampling rate. Due to several limitations, this procedure currently introduces certain systematic errors in the calibrated strain data, motivating the second stage of the low-latency procedure, known as the low-latency gstlal calibration pipeline. The gstlal calibration pipeline uses finite impulse response (FIR) filtering to apply corrections to the output of the front-end calibration. It applies time-dependent correction factors to the sensing and actuation components of the calibrated strain to reduce systematic errors. The gstlal calibration pipeline is also used in high latency to recalibrate the data, which is necessary due mainly to online dropouts in the calibrated data and identified improvements to the calibration models or filters.Comment: 20 pages including appendices and bibliography. 11 Figures. 3 Table