6 research outputs found

    Reconstruction of Chirp Mass in the Search of Compact Binaries

    Full text link
    Excess energy method is used in searches of gravitational waves (GWs) produced from sources with poorly modeled characteristics. It identifies GW events by searching for a coincidence appearance of excess energy in a GW detector network. While it is sensitive to a wide range of signal morphologies, the energy outliers can be populated by background noise events (background), thereby reducing the statistical confidence of a true signal. However, if the physics of the source is partially understood, weak model dependent constraints can be imposed to suppress the background. This letter presents a novel idea of using the reconstructed chirp mass along with two goodness of fit parameters for suppressing background when search is focused on GW produced from the compact binary coalescence

    Regression of Environmental Noise in LIGO Data

    Get PDF
    We address the problem of noise regression in the output of gravitational-wave (GW) interferometers, using data from the physical environmental monitors (PEM). The objective of the regression analysis is to predict environmental noise in the gravitational-wave channel from the PEM measurements. One of the most promising regression method is based on the construction of Wiener-Kolmogorov filters. Using this method, the seismic noise cancellation from the LIGO GW channel has already been performed. In the presented approach the Wiener-Kolmogorov method has been extended, incorporating banks of Wiener filters in the time-frequency domain, multi-channel analysis and regulation schemes, which greatly enhance the versatility of the regression analysis. Also we presents the first results on regression of the bi-coherent noise in the LIGO data

    BIOLOGICAL STUDY AND CHEMICAL COMPOSITION OF MONARDA FISTULOSA L. ESSENTIAL OIL

    Get PDF
    The importance and the identity of aromatic plants are reflected by the chemical composition of essential oils, which are used for various purposes. The biosynthesis of these substances determines the characteristic features of each plant species, which depends on genetic factors and pedoclimatic factors. They influence the quality as well as the proportion in which the chemical components are found in oil.This paper, written in collaboration with our colleagues from the "Stejarul" Biological Research Centre (Piatra NeamÈ›, Romania), is focused on a study on the chemical composition of the essential oil, prepared from Monarda fistulosa L., commonly known as wild bergamot or bee balm, a perennial herbaceous species. In many European countries, Monarda fistulosa has been cultivated for a long time as spice and aromatic plant. In the Botanical Garden, it has been studied as an aromatic plant, which is rich in biologically active substances and is a great source of essential oil. Plants develop successfully in warm and humid climate, as well as in relatively harsh climatic conditions. Monarda fistulosa contains Vitamin C (29,3%), B1 and B2. Monarda essential oil possesses bactericidal and anthelmintic properties. As a spice, bee balm is used in the production of vermouth and can be added to meat dishes. The plants have a pleasant smell, similar to bergamot orange. </p

    Semantic Web Tools and Decision-Making

    Get PDF
    Semantic Web technologies are intertwined with decision-making processes. In this paper the general objectives of the semantic web tools are reviewed and characterized, as well as the categories of decision support tools, in order to establish an intersection of utility and use. We also elaborate on actual and foreseen possibilities for a deeper integration, considering the actual implementation, opportunities and constraints in the decision-making context.info:eu-repo/semantics/publishedVersio

    coherent WaveBurst, a pipeline for unmodeled gravitational-wave data analysis

    Get PDF
    coherent WaveBurst (cWB) is a highly configurable pipeline designed to detect a broad range of gravitational-wave (GW) transients in the data of the worldwide network of GW detectors. The algorithmic core of cWB is a time\u2013frequency analysis with the Wilson\u2013Daubechies\u2013Meyer wavelets aimed at the identification of GW events without prior knowledge of the signal waveform. cWB has been in active development since 2003 and it has been used to analyze all scientific data collected by the LIGO-Virgo detectors ever since. On September 14, 2015, the cWB low-latency search detected the first gravitational-wave event, GW150914, a merger of two black holes. In 2019, a public open-source version of cWB has been released with GPLv3 license

    coherent WaveBurst, a pipeline for unmodeled gravitational-wave data analysis

    Get PDF
    coherent WaveBurst (cWB) is a highly configurable pipeline designed to detect a broad range of gravitational-wave (GW) transients in the data of the worldwide network of GW detectors. The algorithmic core of cWB is a time–frequency analysis with the Wilson–Daubechies–Meyer wavelets aimed at the identification of GW events without prior knowledge of the signal waveform. cWB has been in active development since 2003 and it has been used to analyze all scientific data collected by the LIGO-Virgo detectors ever since. On September 14, 2015, the cWB low-latency search detected the first gravitational-wave event, GW150914, a merger of two black holes. In 2019, a public open-source version of cWB has been released with GPLv3 license
    corecore