Search results for "Ligo"
showing 10 items of 1427 documents
Progress in the characterization of insulin-like peptides in aphids: Immunohistochemical mapping of ILP4.
2021
Aphids were the first animals described as photoperiodic due to their seasonal switch from viviparous parthenogenesis to sexual reproduction (cyclical parthenogenesis) caused by the shortening of the photoperiod in autumn. This switch produces a single sexual generation of oviparous females and males that mate and lay diapausing cold-resistant eggs that can overcome the unfavourable environmental conditions typical of winter in temperate regions. Previous studies have hinted at a possible implication of two insulin-like peptides (ILP1 and ILP4) in the aphid seasonal response, changing their expression levels between different photoperiodic conditions. Moreover, in situ localization of their…
Enhanced effects of variation of the fundamental constants in laser interferometers and application to dark matter detection
2015
We outline new laser interferometer measurements to search for variation of the electromagnetic fine-structure constant $\alpha$ and particle masses (including a non-zero photon mass). We propose a strontium optical lattice clock -- silicon single-crystal cavity interferometer as a novel small-scale platform for these new measurements. Multiple passages of a light beam inside an interferometer enhance the effects due to variation of the fundamental constants by the mean number of passages ($N_{\textrm{eff}} \sim 10^2$ for a large-scale gravitational-wave detector, such as LIGO, Virgo, GEO600 or TAMA300, while $N_{\textrm{eff}} \sim 10^5$ for a strontium clock -- silicon cavity interferomete…
GW190412: Observation of a binary-black-hole coalescence with asymmetric masses
2020
LIGO Scientific Collaboration and Virgo Collaboration: et al.
All-sky search for long-duration gravitational wave transients in the first Advanced LIGO observing run
2018
Made available in DSpace on 2018-11-26T17:45:14Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-03-22 Australian Research Council Council of Scientific and Industrial Research of India Department of Science and Technology, India Science AMP; Engineering Research Board (SERB), India Ministry of Human Resource Development, India Spanish Agencia Estatal de Investigacion Vicepresidencia i Conselleria d'Innovacio, Recerca i Turisme Conselleria d'Educacio i Universitat del Govern de les Illes Balears Conselleria d'Educacio, Investigacio, Cultura i Esport de la Generalitat Valenciana National Science Centre of Poland Swiss National Science Foundation (SNSF) Russian Foundation for Basic Rese…
Exploring gravitational-wave detection and parameter inference using deep learning methods
2020
The data that support the findings of this study are openly available at the following URL/DOI: https://arxiv.org/abs/2011.10425.
Classification of gravitational-wave glitches via dictionary learning
2018
We present a new method for the classification of transient noise signals (or glitches) in advanced gravitational-wave interferometers. The method uses learned dictionaries (a supervised machine learning algorithm) for signal denoising, and untrained dictionaries for the final sparse reconstruction and classification. We use a data set of 3000 simulated glitches of three different waveform morphologies, comprising 1000 glitches per morphology. These data are embedded in non-white Gaussian noise to simulate the background noise of advanced LIGO in its broadband configuration. Our classification method yields a 96% accuracy for a large range of initial parameters, showing that learned diction…
Application of dictionary learning to denoise LIGO’s blip noise transients
2020
Data streams of gravitational-wave detectors are polluted by transient noise features, or ``glitches,'' of instrumental and environmental origin. In this work we investigate the use of total variation methods and learned dictionaries to mitigate the effect of those transients in the data. We focus on a specific type of transient, ``blip" glitches, as this is the most common type of glitch present in the LIGO detectors and their waveforms are easy to identify. We randomly select 100 blip glitches scattered in the data from advanced LIGO's O1 run, as provided by the citizen-science project Gravity Spy. Our results show that dictionary-learning methods are a valid approach to model and subtrac…
New method to observe gravitational waves emitted by core collapse supernovae
2018
While gravitational waves have been detected from mergers of binary black holes and binary neutron stars, signals from core collapse supernovae, the most energetic explosions in the modern Universe, have not been detected yet. Here we present a new method to analyse the data of the LIGO, Virgo, and KAGRA network to enhance the detection efficiency of this category of signals. The method takes advantage of a peculiarity of the gravitational wave signal emitted in the core collapse supernova and it is based on a classification procedure of the time-frequency images of the network data performed by a convolutional neural network trained to perform the task to recognize the signal. We validate …
Total-variation methods for gravitational-wave denoising: Performance tests on Advanced LIGO data
2018
We assess total-variation methods to denoise gravitational-wave signals in real noise conditions, by injecting numerical-relativity waveforms from core-collapse supernovae and binary black hole mergers in data from the first observing run of Advanced LIGO. This work is an extension of our previous investigation where only Gaussian noise was used. Since the quality of the results depends on the regularization parameter of the model, we perform an heuristic search for the value that produces the best results. We discuss various approaches for the selection of this parameter, either based on the optimal, mean, or multiple values, and compare the results of the denoising upon these choices. Mor…
OPTICAL SPECTROSCOPY OF CANDIDATES IN THE LIGO/VIRGO BINARY MERGER ERROR BOXES
2021
We performed optical spectroscopy of the candidates inside the gravitational wave errorboxes (S190408an, S190425z, S190426c, S190510g, S190728q, S190814bv). The spectral classification of 34 transients observed with the 10.4m Gran Telescopio de Canarias prior to 1 Sep 2019 is presented. We ruled out the association of these candidates with gravitational wave events.