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LISA Data Challenge Workshop

25–27 juil. 2022
Online
Fuseau horaire Europe/Paris

LDC chairs

Liste des Contributions

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  1. 1. Data generation
    Jean-Baptiste Bayle (University of Glasgow), Maude Le Jeune (APC)
    25/07/2022 17:45

    This tutorial is meant to show the general process followed to generate LDC data, including gravitational-wave (GW) signal and noise.

    The objective is to:
    - Display source parameter: get the first MBHB from spritz
    - Compute h+,hx with the LDC
    - Compute projected strain with gw-response and save to file
    - Compute projected strain with the LDC
    - Inject GW signal in lisa-instrument or in pyTDI

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  2. 3. Fast waveform generation
    Natalia Korsakova (APC), Michael Katz (Albert Einstein Institute)
    25/07/2022 18:40

    This tutorial shows how to use the fast waveform generators to match signals injected in LDC datasets.

    The objective is to:
    - Generate fast waveforms in the frequency domain for Galactic binaries (GB)
    - Generate fast waveforms in the frequency domain for massive black hole binaries (MBHB)
    - Generate fast waveforms for EMRI (if time permits)
    - Plot the waveform against simulated data

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  3. 2. Detection and parameter estimation of Galactic binaries
    Dr Quentin Baghi (CEA Saclay)
    27/07/2022 17:45

    This tutorial shows the general process to follow when analysing LDC data to detect and characterize gravitational-waves from Galactic compact binaries sources.

    The objective is to:
    1. Load and plot the TDI data in time and frequency domain
    2. Compute a source SNR
    3. Compute a likelihood
    4. Compute the F-statistics
    5. Detect sources using the F-statistics
    6. Perform parameter estimation

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  4. 4. MBHB parameter estimation
    Sylvain Marsat (L2I Toulouse, CNRS/IN2P3), Stanislav Babak (APC)
    27/07/2022 18:40

    This tutorial shows the general process to follow when analyzing LDC data to detect and characterize gravitational-waves from massive black hole binary sources.

    The objective is to:
    1. Load and plot the TDI data in time and frequency domain
    2. Compute a source SNR
    3. Compute a likelihood
    4. Transformation to LISA frame and how it helps
    6. Perform parameter estimation in the noiseless case

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