A method to search for long duration gravitational wave transients from isolated neutron stars using the generalized FrequencyHough

We describe a method to detect gravitational waves lasting $O(hours-days)$ emitted by young, isolated neutron stars, such as those that could form after a supernova or a binary neutron star merger, using advanced LIGO/Virgo data. The method is based on a generalization of the FrequencyHough (FH), a pipeline that performs hierarchical searches for continuous gravitational waves by mapping points in the time/frequency plane of the detector to lines in the frequency/spindown plane of the source. We show that signals whose spindowns are related to their frequencies by a power law can be transformed to coordinates where the behavior of these signals is always linear, and can therefore be searched for by the FH. We estimate the sensitivity of our search across different braking indices, and describe the portion of the parameter space we could explore in a search using varying fast Fourier Transform (FFT) lengths.Comment: 15 figure

The Adaptive Transient Hough method for long-duration gravitational wave transients

This paper describes a new semi-coherent method to search for transient gravitational waves of intermediate duration (hours to days). In order to search for newborn isolated neutron stars with their possibly very rapid spin-down, we model the frequency evolution as a power law. The search uses short Fourier transforms from the output of ground-based gravitational wave detectors and applies a weighted Hough transform, also taking into account the signal's amplitude evolution. We present the technical details for implementing the algorithm, its statistical properties, and a sensitivity estimate. A first example application of this method was in the search for GW170817 post-merger signals, and we verify the estimated sensitivity with simulated signals for this case.Comment: 13 pages, 14 figure

Analysis of a biologically-inspired system for real-time object recognition

We present a biologically-inspired system for real-time, feed-forward object recognition in cluttered scenes. Our system utilizes a vocabulary of very sparse features that are shared between and within different object models. To detect objects in a novel scene, these features are located in the image, and each detected feature votes for all objects that are consistent with its presence. Due to the sharing of features between object models our approach is more scalable to large object databases than traditional methods. To demonstrate the utility of this approach, we train our system to recognize any of 50 objects in everyday cluttered scenes with substantial occlusion. Without further optimization we also demonstrate near-perfect recognition on a standard 3-D recognition problem. Our system has an interpretation as a sparsely connected feed-forward neural network, making it a viable model for fast, feed-forward object recognition in the primate visual system

All-sky search for periodic gravitational waves in LIGO S4 data

We report on an all-sky search with the LIGO detectors for periodic gravitational waves in the frequency range 50-1000 Hz and with the frequency's time derivative in the range -1.0E-8 Hz/s to zero. Data from the fourth LIGO science run (S4) have been used in this search. Three different semi-coherent methods of transforming and summing strain power from Short Fourier Transforms (SFTs) of the calibrated data have been used. The first, known as "StackSlide", averages normalized power from each SFT. A "weighted Hough" scheme is also developed and used, and which also allows for a multi-interferometer search. The third method, known as "PowerFlux", is a variant of the StackSlide method in which the power is weighted before summing. In both the weighted Hough and PowerFlux methods, the weights are chosen according to the noise and detector antenna-pattern to maximize the signal-to-noise ratio. The respective advantages and disadvantages of these methods are discussed. Observing no evidence of periodic gravitational radiation, we report upper limits; we interpret these as limits on this radiation from isolated rotating neutron stars. The best population-based upper limit with 95% confidence on the gravitational-wave strain amplitude, found for simulated sources distributed isotropically across the sky and with isotropically distributed spin-axes, is 4.28E-24 (near 140 Hz). Strict upper limits are also obtained for small patches on the sky for best-case and worst-case inclinations of the spin axes.Comment: 39 pages, 41 figures An error was found in the computation of the C parameter defined in equation 44 which led to its overestimate by 2^(1/4). The correct values for the multi-interferometer, H1 and L1 analyses are 9.2, 9.7, and 9.3, respectively. Figure 32 has been updated accordingly. None of the upper limits presented in the paper were affecte

Real-time edge tracking using a tactile sensor

Object recognition through the use of input from multiple sensors is an important aspect of an autonomous manipulation system. In tactile object recognition, it is necessary to determine the location and orientation of object edges and surfaces. A controller is proposed that utilizes a tactile sensor in the feedback loop of a manipulator to track along edges. In the control system, the data from the tactile sensor is first processed to find edges. The parameters of these edges are then used to generate a control signal to a hybrid controller. Theory is presented for tactile edge detection and an edge tracking controller. In addition, experimental verification of the edge tracking controller is presented