Reducing the number of templates for aligned-spin compact binary coalescence gravitational wave searches using metric-agnostic template nudging

Efficient multi-dimensional template placement is crucial in computationally intensive matched-filtering searches for Gravitational Waves (GWs). Here, we implement the Neighboring Cell Algorithm (NCA) to improve the detection volume of an existing Compact Binary Coalescence (CBC) template bank. This algorithm has already been successfully applied for a binary millisecond pulsar search in data from the Fermi satellite. It repositions templates from over-dense regions to under-dense regions and reduces the number of templates that would have been required by a stochastic method to achieve the same detection volume. Our method is readily generalizable to other CBC parameter spaces. Here we apply this method to the aligned--single-spin neutron-star--black-hole binary coalescence inspiral-merger-ringdown gravitational wave parameter space. We show that the template nudging algorithm can attain the equivalent effectualness of the stochastic method with 12% fewer templates

Improved Stack-Slide Searches for Gravitational-Wave Pulsars

We formulate and optimize a computational search strategy for detecting gravitational waves from isolated, previously-unknown neutron stars (that is, neutron stars with unknown sky positions, spin frequencies, and spin-down parameters). It is well known that fully coherent searches over the relevant parameter-space volumes are not computationally feasible, and so more computationally efficient methods are called for. The first step in this direction was taken by Brady & Creighton (2000), who proposed and optimized a two-stage, stack-slide search algorithm. We generalize and otherwise improve upon the Brady-Creighton scheme in several ways. Like Brady & Creighton, we consider a stack-slide scheme, but here with an arbitrary number of semi-coherent stages and with a coherent follow-up stage at the end. We find that searches with three semi-coherent stages are significantly more efficient than two-stage searches (requiring about 2-5 times less computational power for the same sensitivity) and are only slightly less efficient than searches with four or more stages. We calculate the signal-to-noise ratio required for detection, as a function of computing power and neutron star spin-down-age, using our optimized searches.Comment: 19 pages, 7 figures, RevTeX

Search strategies for long gravitational-wave transients: hidden Markov model tracking and seedless clustering

A number of detections have been made in the past few years of gravitational waves from compact binary coalescences. While there exist well-understood waveform models for signals from compact binary coalescences, many sources of gravitational waves are not well modeled, including potential long-transient signals from a binary neutron star post-merger remnant. Searching for these sources requires robust detection algorithms that make minimal assumptions about any potential signals. In this paper, we compare two unmodeled search schemes for long-transient gravitational waves, operating on cross-power spectrograms. One is an efficient algorithm first implemented for continuous wave searches, based on a hidden Markov model. The other is a seedless clustering method, which has been used in transient gravitational wave analysis in the past. We quantify the performance of both algorithms, including sensitivity and computational cost, by simulating synthetic signals with a special focus on sources like binary neutron star post-merger remnants. We demonstrate that the hidden Markov model tracking is a good option in model-agnostic searches for low signal-to-noise ratio signals. We also show that it can outperform the seedless method for certain categories of signals while also being computationally more efficient.Comment: 10 pages, 7 figure

An all-sky search algorithm for continuous gravitational waves from spinning neutron stars in binary systems

Rapidly spinning neutron stars with non-axisymmetric mass distributions are expected to generate quasi-monochromatic continuous gravitational waves. While many searches for unknown, isolated spinning neutron stars have been carried out, there have been no previous searches for unknown sources in binary systems. Since current search methods for unknown, isolated neutron stars are already computationally limited, expanding the parameter space searched to include binary systems is a formidable challenge. We present a new hierarchical binary search method called TwoSpect, which exploits the periodic orbital modulations of the continuous waves by searching for patterns in doubly Fourier-transformed data. We will describe the TwoSpect search pipeline, including its mitigation of detector noise variations and corrections for Doppler frequency modulation caused by changing detector velocity. Tests on Gaussian noise and on a set of simulated signals will be presented.Comment: 22 pages, 10 figures, 1 table, Submitted to Classical and Quantum Gravit

The PyCBC search for gravitational waves from compact binary coalescence

We describe the PyCBC search for gravitational waves from compact-object binary coalescences in advanced gravitational-wave detector data. The search was used in the first Advanced LIGO observing run and unambiguously identified two black hole binary mergers, GW150914 and GW151226. At its core, the PyCBC search performs a matched-filter search for binary merger signals using a bank of gravitational-wave template waveforms. We provide a complete description of the search pipeline including the steps used to mitigate the effects of noise transients in the data, identify candidate events and measure their statistical significance. The analysis is able to measure false-alarm rates as low as one per million years, required for confident detection of signals. Using data from initial LIGO's sixth science run, we show that the new analysis reduces the background noise in the search, giving a 30% increase in sensitive volume for binary neutron star systems over previous searches.Comment: 29 pages, 7 figures, accepted by Classical and Quantum Gravit

Gravitational waves: search results, data analysis and parameter estimation

The Amaldi 10 Parallel Session C2 on gravitational wave (GW) search results, data analysis and parameter estimation included three lively sessions of lectures by 13 presenters, and 34 posters. The talks and posters covered a huge range of material, including results and analysis techniques for ground-based GW detectors, targeting anticipated signals from different astrophysical sources: compact binary inspiral, merger and ringdown; GW bursts from intermediate mass binary black hole mergers, cosmic string cusps, core-collapse supernovae, and other unmodeled sources; continuous waves from spinning neutron stars; and a stochastic GW background. There was considerable emphasis on Bayesian techniques for estimating the parameters of coalescing compact binary systems from the gravitational waveforms extracted from the data from the advanced detector network. This included methods to distinguish deviations of the signals from what is expected in the context of General Relativity

A stochastic template placement algorithm for gravitational wave data analysis

This paper presents an algorithm for constructing matched-filter template banks in an arbitrary parameter space. The method places templates at random, then removes those which are "too close" together. The properties and optimality of stochastic template banks generated in this manner are investigated for some simple models. The effectiveness of these template banks for gravitational wave searches for binary inspiral waveforms is also examined. The properties of a stochastic template bank are then compared to the deterministically placed template banks that are currently used in gravitational wave data analysis.Comment: 14 pages, 11 figure