J. Rollins

X-Pipeline: an analysis package for autonomous gravitational-wave burst searches

Autonomous gravitational-wave searches—fully automated analyses of data that run without human intervention or assistance—are desirable for a number of reasons. They are necessary for the rapid identification of gravitational-wave burst candidates, which in turn will allow for follow-up observations by other observatories and the maximum exploitation of their scientific potential. A fully automated analysis would also circumvent the traditional by hand setup and tuning of burst searches that is both labourious and time consuming. We demonstrate a fully automated search with X-Pipeline, a software package for the coherent analysis of data from networks of interferometers for detecting bursts associated with gamma-ray bursts (GRBs) and other astrophysical triggers. We discuss the methods X-Pipeline uses for automated running, including background estimation, efficiency studies, unbiased optimal tuning of search thresholds and prediction of upper limits. These are all done automatically via Monte Carlo with multiple independent data samples and without requiring human intervention. As a demonstration of the power of this approach, we apply X-Pipeline to LIGO data to compute the sensitivity to gravitational-wave emission associated with GRB 031108. We find that X-Pipeline is sensitive to signals approximately a factor of 2 weaker in amplitude than those detectable by the cross-correlation technique used in LIGO searches to date. We conclude with comments on the status of X-Pipeline as a fully autonomous, near-real-time-triggered burst search in the current LSC-Virgo Science Run.

Bounding the Time Delay between High-energy Neutrinos and Gravitational-wave Transients from Gamma-ray Bursts

We derive a conservative coincidence time window for joint searches of gravitational-wave (GW) transients and high-energy neutrinos (HENs, with energies & 100GeV), emitted by gamma-ray bursts (GRBs). The last are among the most interesting astrophysical sources for coincident detections with current and near-future detectors. We take into account a broad range of emission mechanisms. We take the upper limit of GRB durations as the 95% quantile of the T90’s of GRBs observed by BATSE, obtaining a GRB duration upper limit of 150s. Using published results on high-energy (> 100MeV) photon light curves for 8 GRBs detected by Fermi LAT, we verify that most highenergy photons are expected to be observed within the rst 150s of the

Multimessenger Science Reach and Analysis Method for Common Sources of Gravitational Waves and High-energy Neutrinos

We present the baseline multimessenger analysis method for the joint observations of gravitational waves (GW) and high-energy neutrinos (HEN), together with a detailed analysis of the expected science reach of the joint search. The analysis method combines data from GW and HEN detectors, and uses the blue-luminosity-weighted distribution of galaxies. We derive expected GW+HEN source rate upper limits for a wide range of source parameters covering several emission models. Using published sensitivities of externally triggered searches, we derive joint upper limit estimates both for the ongoing analysis with the initial LIGO-Virgo GW detectors with the partial IceCube detector (22 strings) HEN detector and for projected results to advanced LIGO-Virgo detectors with the completed IceCube (86 strings). We discuss the constraints these upper limits impose on some existing GW+HEN emission models.

JOINT SEARCHES BETWEEN GRAVITATIONAL-WAVE INTERFEROMETERS AND HIGH-ENERGY NEUTRINO TELESCOPES: SCIENCE REACH AND ANALYSIS STRATEGIES

Many of the astrophysical sources and violent phenomena observed in our Universe are potential emitters of gravitational waves (GWs) and high-energy neutrinos (HENs). A network of GW detectors such as LIGO and Virgo can determine the direction/time of GW bursts while the IceCube and ANTARES neutrino telescopes can also provide accurate directional information for HEN events. Requiring the consistency between both, totally independent, detection channels shall enable new searches for cosmic events arriving from potential common sources, of which many extra-galactic objects.

Benefits of artificially generated gravity gradients for interferometric gravitational-wave detectors

We present an approach to experimentally evaluate gravity gradient noise, a potentially limiting noise source in advanced interferometric gravitational-wave detectors. In addition, the method can be used to provide sub-percent calibration in phase and amplitude. Knowledge of calibration to such certainties shall enhance the scientific output of the instruments in the case of an eventual detection of gravitational waves. The method relies on a rotating symmetrical two-body mass, a dynamic gravity field generator (DFG). The placement of the DFG in the proximity of one of the interferometers suspended test masses generates a change in the local gravitational field detectable with current interferometric gravitational-wave detectors.

Prospects of gravitational wave data mining and exploration via evolutionary computing

Techniques of evolutionary computing have proven useful for a diverse array of fields in science and engineering. Because of the expected low signal to noise ratio of LIGO data and incomplete knowledge of gravitational waveforms, evolutionary computing is an excellent candidate for LIGO data analysis studies. Using the evolutionary computing methods of genetic algorithms and genetic programming, we have developed, as a proof of principle, search algorithms that are effective at finding sine-gaussian signals hidden in noise while maintaining a small false alarm rate. Because we used realistic LIGO noise as a training ground, the algorithms we have evolved should be well suited to detecting signals in actual LIGO data, as well as in simulated noise. These algorithms have continuously improved during the five days of their evolution and are expected to improve further the more they are evolved. The top performing algorithms from generation 100 and 199 were benchmarked using gaussian white noise to illustrate their performance and the improvement over 100 generations.