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LISA data analysis: from classical methods to machine learning

21–25 nov. 2022
L2IT Toulouse
Fuseau horaire Europe/Paris

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  1. 36. Introduction to LISA data analysis
    Maude Le Jeune (APC)
    21/11/2022 09:00
    In person talk
    Introductory lectures
  2. 35. Introduction to machine learning
    Sylvain Caillou (L2I Toulouse, CNRS/IN2P3, UT3)
    21/11/2022 11:00
    In person talk
    Introductory lectures
  3. 37. GW Detection with Traditional vs Machine Learning Techniques - Part 1 (theory)
    Joseph Bayley (Univ. of Glasgow)
    21/11/2022 14:00
    In person talk
    Training session 1
  4. 38. GPU Techniques to Accelerate GW Waveforms and Data Analysis Computations - Part 1 (theory)
    Michael Katz (AEI)
    21/11/2022 16:00
    Remote talk
    Training session 1
  5. 41. GPU Techniques to Accelerate GW Waveforms and Data Analysis Computations - Part 2 (tutorial)
    Lorenzo Speri (Max Planck Institute for Gravitational physics (Albert Einstein Institute, AEI Potsdam)), Michael Katz (AEI)
    22/11/2022 09:00
    In person talk
    Training session 2
  6. 39. GW Detection with Traditional vs Machine Learning Techniques - Part 2 (tutorial)
    Joseph Bayely (Univ. of Glasgow), Michael Williams (University of Glasgow)
    22/11/2022 09:00
    In person talk
    Training session 2
  7. 42. GPU Techniques to Accelerate GW Waveforms and Data Analysis Computations - Part 2 (tutorial)
    Lorenzo Speri (Max Planck Institute for Gravitational physics (Albert Einstein Institute, AEI Potsdam)), Michael Katz (AEI)
    22/11/2022 11:00
    In person talk
    Training session 2
  8. 40. GW Detection with Traditional vs Machine Learning Techniques - Part 2 (tutorial)
    Joseph Bayely (Univ. of Glasgow), Michael Williams (University of Glasgow)
    22/11/2022 11:00
    In person talk
    Training session 2
  9. 43. GW Parameter Estimation with Bayesian Machine Learning - Part 1 (theory)
    Stephen Green (Albert Einstein Institute Potsdam)
    22/11/2022 14:00
  10. 44. Gaussian Process Regression - Part 1 (theory)
    Stanislav Babak (APC)
    22/11/2022 16:00
    In person talk
    Training session 3
  11. 47. Gaussian Process Regression - Part 2 (tutorial)
    Stanislav Babak (APC)
    23/11/2022 09:00
  12. 45. GW Parameter Estimation with Bayesian Machine Learning - Part 2 (tutorial)
    Natalia Korsakova (APC), Stephen Green (Albert Einstein Institute Potsdam)
    23/11/2022 09:00
  13. 48. Gaussian Process Regression - Part 2 (tutorial)
    Stanislav Babak (APC)
    23/11/2022 11:00
  14. 46. GW Parameter Estimation with Bayesian Machine Learning - Part 2 (tutorial)
    Natalia Korsakova (APC), Stephen Green (Albert Einstein Institute Potsdam)
    23/11/2022 11:00
  15. 49. LISA status and data processing organisation
    Antoine Petiteau (CEA/IRFU/DPhP)
    23/11/2022 14:00
    In person talk
    Conference session 1
  16. 8. Trans-dimensional sampling methods: current status and future prospects
    Nikolaos Karnesis (AUTh)
    23/11/2022 14:30
    In person talk
    Conference session 1

    Trans-dimensional Bayesian sampling algorithms have been extensively used in the analysis of simulated LISA data. So far, tools based on Reversible Jump MCMC methods, have been proven to be a good candidate for tackling the LISA global fit problem. In this talk, I will summarize the success of the techniques that have been used to date, as well as their current limitations. These limitations...

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  17. 24. LISA Data Challenge for the Galaxy
    Kristen Lackeos (Max Planck Institute for Radio Astronomy)
    23/11/2022 15:00
    In person talk
    Conference session 1

    The Laser Interferometer Space Antenna will open a window to gravitational waves (GW) between 0.1 mHz and 1 Hz. The instrument will monitor the entire sky and observe a variety of overlapping signals. GWs from the population ultra compact binaries, numbering millions in our
    Galaxy, are predicted to dominate the milli-Hertz frequency band. Galactic binaries are millions of years from merger,...

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  18. 19. Accelerating parameter estimation of Galactic binaries in the full LISA frequency band using Gaussian Process Regression
    Stefan Strub (ETH Zurich)
    23/11/2022 16:00
    In person talk
    Conference session 1

    We present an end-to-end pipeline using Gaussian Process Regression to model the log-likelihood function for parameters of Galactic binaries. It is expected that tens of millions of Galactic binaries will be the dominant sources of observed gravitational waves, emitting quasi monochromatic gravitational waves, which will be constantly measured by LISA. To resolve as many Galactic binaries as...

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  19. 6. LISA data analysis in the presence of environmental effects
    Laura Sberna (Max Planck Institute for Gravit)
    23/11/2022 16:15
    In person talk
    Conference session 1

    While negligible for ground-based observatories, environmental effects (peculiar motion, accretion, etc.) will be detectable by LISA in a variety of sources. I will give on overview of the specific effects that are likely to be detected by LISA, the challenges these effects pose for parameter estimation and detection, and some ways to address them.

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  20. 1. The imprint of gas on gravitational waves from LISA intermediate-mass black hole binaries
    Mudit Garg (University of Zurich)
    23/11/2022 16:45
    In person talk
    Conference session 1

    We study the effect of torques on circular inspirals of intermediate-mass black hole binaries (IMBHBs) embedded in gas discs, wherein both BH masses are in the range 10^2-10^5~MSun, up to redshift z = 10. We focus on how torques impact the detected gravitational wave (GW) waveform in the Laser Interferometer Space Antenna (LISA) frequency band when the binary separation is within a few hundred...

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  21. 30. Investigation of Tidal Disruption Events through gravitational waves
    martina toscani (L2I Toulouse, CNRS/IN2P3, UT3)
    23/11/2022 17:00
    In person talk
    Conference session 1

    Stars tidally disrupted (TDEs, Rees 1988) by massive black holes (BHs) represent an unprecedented powerful tool to unveil the presence of otherwise quiescent compact objects in the cores of galaxies.
    More recently, the scientific community has become aware also of the potential of these events as gravitational wave (GW) sources (Kobayashi et al. 2004, Stone et al. 2013, Toscani et al. 2019,...

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  22. 7. Towards a complete L0-to-L2 pipeline – Progress in simulation, processing and analysis (part 1)
    Jean-Baptiste Bayle (University of Glasgow), Olaf Hartwig (SYRTE, Observatoire de Paris)
    24/11/2022 09:00

    LISA will allow the simultaneous observation and characterization of thousands of gravitational-wave sources, which presents unique data analysis challenges. Preparing for these challenges requires realistic simulations of the data streams entering the final astrophysical data analysis (L1 data).

    First steps towards such demonstrations have been made as part of the LISA Data challenges...

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  23. 25. Towards a complete L0-to-L2 pipeline – Progress in simulation, processing and analysis (part 2)
    Jean-Baptiste Bayle (University of Glasgow), Olaf Hartwig (SYRTE, Observatoire de Paris)
    24/11/2022 09:30
    In person talk
    Conference session 2

    This is the second part of the talk 'Towards a complete L0-to-L2 pipeline – Progress in simulation, processing and analysis' proposed by J.-B. Bayle.

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  24. 12. On the effectiveness of null TDI channels as instrument noise monitors in LISA
    Martina Muratore (AEI (Potsdam))
    24/11/2022 10:00
    In person talk
    Conference session 2

    I will present a recent paper we submitted on the use and limits of the Time-Delay Interferometry null channels for in flight estimation of the Laser Interferometer Space Antenna instrumental noise. In the talk I will consider how the two main limiting noise sources, test-mass acceleration noise and interferometric phase measurement noise, propagate through different Time-Delay Interferometry...

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  25. 33. The impact data gaps have on parameter estimation
    Ollie Burke (L2I Toulouse, CNRS/IN2P3, UT3)
    24/11/2022 10:15
    In person talk
    Conference session 2

    For the LISA instrument, data gaps are entirely unavoidable. We will expect to have scheduled data gaps due to antennae repointing or enforced data gaps to mask out instrumental artefacts. It is absolutely essential that the probabilistic models used to describe the data must be consistent with the data generating process itself. By including gaps in the data stream, the resultant noise...

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  26. 27. Extracting gravitational-wave backgrounds in noise of unknown spectral shape
    Quentin Baghi (CEA Saclay)
    24/11/2022 11:00
    In person talk
    Conference session 2

    Measuring stochastic gravitational-wave backgrounds (SGWBs), particularly primordial ones, is one of LISA’s most hoped-for outcomes. However, this task is difficult with a single flying detector because it requires an accurate characterisation of the instrumental noise. Assuming that its shape is known or highly constrained is a dangerous bet. In order to make any discovery possible, it is...

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  27. 50. LISA data analysis: status and challenges
    Stanislav Babak (APC)
    24/11/2022 11:30
    In person talk
    Conference session 2
  28. 22. Inference for LISA with Normalising flows and data representation through source separation
    Natalia Korsakova (APC)
    24/11/2022 12:00
    In person talk
    Conference session 2

    In my talk I am going to concentrate on the models of machine learning which allow us to learn the probability distributions and apply it to the important unsolved problems in the LISA data analysis.
    The most common approach to do parameter estimation is through defining the likelihood function and producing posterior samples with some form of sampling technique. The disadvantage of sampling...

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  29. 52. MCMC parameter estimation methods for LISA massive black holes
    Sylvain Marsat (L2I Toulouse, CNRS/IN2P3, UT3)
    24/11/2022 14:00
    In person talk
    Conference session 3
  30. 28. Importance nested sampling with nessai for gravitational-wave inference
    Michael Williams (University of Glasgow)
    24/11/2022 14:30
    In person talk
    Conference session 3

    Nested sampling is a crucial tool for gravitational-wave data analysis. However, it is often computationally expensive, especially for high-dimensional and complex parameter spaces. This poses a challenge for applications to LISA data analysis. It has been shown that nessai, a nested sampling algorithm that incorporates normalising flows, can accelerate gravitational-wave inference...

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  31. 26. Massive Black Hole Binary parameter estimation using Masked Autoregressive Flows
    Ivan Martin Vilchez (Institute of Space Science (ICE, CSIC and IEEC))
    24/11/2022 14:45
    In person talk
    Conference session 3

    One of the sources which we expect to be detected by the Laser Interferometer Space Antenna (LISA) are Massive Black Hole Binaries (MBHBs). Detection for these sources should be relatively easy, since their signal to noise ratio (SNR) will be large.

    Once a detection has been made, parameter estimation is typically done with Bayesian sampling methods, such as nested sampling or variations of...

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  32. 23. Learning-based models for gravitational wave analysis
    Elie Leroy (DRF-IRFU)
    24/11/2022 15:00
    In person talk
    Conference session 3

    The LISA space-interferometer will simultaneously acquire gravitational waves emitted from thousands of sources through three time series.
    The disentanglement of these signals poses a challenging underdetermined source separation problem.
    To isolate signals based on their individual signatures, we introduce a new source separation algorithm based on learning signal representations in a...

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  33. 18. LISA Data Analysis - A Deep Learning Approach
    Mlle Florentina-Crenguta Pislan (Institute of Space Science, Faculty of Physics)
    24/11/2022 15:15
    In person talk
    Conference session 3

    With LISA Mission being now in phase B1, its requirements have been consolidated and we are more and more able to tailor the mission, including the methods to scientifically analyse the data during operations.
    Also, to fulfil one of LISA’s role as an actor in enabling multi-messenger astronomy, we need to analyse the data in a fast and reliable way in order to quickly identify important...

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  34. 10. Characterizing Anisotropic Stochastic Gravitational Wave Backgrounds and Foregrounds with the Bayesian LISA Pipeline (BLIP)
    Alexander Criswell (University of Minnesota)
    24/11/2022 16:00
    In person talk
    Conference session 3

    LISA data is expected to feature at least one significant anisotropic stochastic gravitational wave (GW) signal: a galactic foreground comprised of the GW contribution from millions of unresolved double white dwarf (DWD) binaries throughout our galaxy. However, the Milky Way itself is not the only local host of such systems. For instance, the Large Magellanic Cloud (LMC) is expected to contain...

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  35. 34. Searching for primordial features with LISA
    Jacopo Fumagalli (IAP)
    24/11/2022 16:15
    In person talk
    Conference session 3

    Observational constraints and prospects for detection of features, i.e. physically motivated oscillations in the primordial power spectrum, have so far concentrated on the CMB and Large Scale Structure surveys. Probing these features could, for instance, establish the existence of heavy particles beyond the reach of terrestrial experiments, and even test the inflationary paradigm or point to...

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  36. 20. Detecting Gravitational Waves from Cosmic Strings with LISA
    Namitha Suresh (Cornell University)
    24/11/2022 16:30
    Remote talk
    Conference session 3

    The detection of a stochastic gravitational wave background (SGWB) by LISA is an exciting prospect, especially in the light of the recent NANOGrav results. One of the many possible sources of cosmological SGWB signals which could be detected by LISA is cosmic strings. An important ingredient in the calculation of this contribution is the loop power spectrum which characterizes the emission...

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  37. 31. Bayesian inference methods in cosmology with LISA standard sirens
    Dr Danny Laghi (CNES, L2I Toulouse, CNRS/IN2P3, UT3)
    24/11/2022 16:45

    One of the main scientific objectives of LISA is to probe the expansion rate of the Universe. In this talk, we examine the problem of measuring cosmological parameters through gravitational wave observations using LISA standard sirens. We discuss a Bayesian framework to do cosmological parameter inference with LISA dark and bright sirens, presenting forecasts based on simulated catalogs of...

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  38. 32. Modified Gravity Forecasting with Large Scale Structure in the LISA era, including a Machine Learning analysis
    Alexander Bonilla Rivera (UFJF)
    24/11/2022 17:00
    Remote talk
    Conference session 3

    In the present work we explore how modified gravity theories affect the propagation of gravitational waves produced by the merger of binary massive black holes (MBH) and also by a stochastic background. For this purpose we developed a mock of catalogs that are expected to be observed in the operating frequency band of the Laser Interferometer Space Antenna (LISA). For this proposal we develop...

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  39. 9. Merger-ringdown test -- A novel test of GR using a machine learning implementation
    Swetha Bhagwat (University of Birmingham)
    24/11/2022 17:15
    In person talk
    Conference session 3

    The gravitational waves emitted during the coalescence of binary black holes are an excellent probe to test the behaviour of strong gravity. We propose a new test called the merger-ringdown consistency test` that focuses on probing the imprints of the dynamics in strong-gravity around the black-holes during the plunge-merger and ringdown phase. We demonstrate the feasibility of our test on a...

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  40. 16. On the edge of quantum black holes
    Jahed Abedi (University of Stavanger)
    24/11/2022 17:30
    In person talk
    Conference session 3

    Black holes are potential gateways to groundbreaking discoveries. Black hole astrophysics has undergone an observational renaissance in the past 6 years. Notably, the observation of gravitational waves has provided an exciting new window to probe as close as possible to the event horizon of observed binary black hole mergers. In this talk, I will provide an overview of the strong motivations...

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  41. 14. Determining the Individual Masses of Accreting White Dwarf Binaries
    Sophia Yi (University of Virginia)
    24/11/2022 17:45
    Remote talk
    Conference session 3

    Accreting binary white dwarf systems are among the sources expected to emanate gravitational waves that will be detectable by LISA. We attempt to ascertain whether the individual masses of such a binary can be determined from LISA’s measurements of the frequency and frequency time derivative of gravitational waves emanated by the binary. We present analytic expressions for the gravitational...

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  42. 21. A neoclassical approach to coherent gravitational-wave search
    Alvin Chua (National University of Singapore)
    25/11/2022 09:00
    Remote talk
    Conference session 4

    The low instantaneous signal-to-noise ratio for most classes of gravitational-wave source necessitates the use of coherent search, which looks for signals in some length of data through phase comparisons against modeled templates. Such comparisons are statistics of the data, defined as functions on the model space. Coherent statistics suffer from uncontrolled variations over the space, which...

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  43. 11. Detecting gravitational waves from extreme mass ratio inspirals using convolutional neural networks
    Xue-Ting Zhang (School of Physics and Astronomy, Sun Yat-sen University)
    25/11/2022 09:30
    Remote talk
    Conference session 4

    Extreme mass ratio inspirals (EMRIs) are among the most interesting gravitational wave (GW) sources for space-borne GW detectors. However, successful GW data analysis remains challenging due to many issues, ranging from the difficulty of modeling accurate waveforms, to the impractically large template bank required by the traditional matched filtering search method. In this work, we introduce...

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  44. 15. FastEMRIWaveforms: New tools for millihertz gravitational-wave data analysis
    Lorenzo Speri (Max Planck Institute for Gravitational physics (Albert Einstein Institute, AEI Potsdam))
    25/11/2022 09:45
    In person talk
    Conference session 4

    The observations of gravitational wave signals from extreme-mass-ratio inspirals (EMRIs) have a huge scientific potential for the LISA mission because the system's parameters will be constrained to unprecedented precision. However, high precision comes with new challenges. EMRIs are the only sources that combine the challenges of strong-field complexity with that of long-lived signals. The...

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  45. 4. Progress towards a semi-coherent search for EMRI signals
    Diganta Bandopadhyay (University of Birmingham)
    25/11/2022 10:00
    In person talk
    Conference session 4

    The search for extreme mass ratio inspiral (EMRI) event signatures in the LISA data-stream necessitated new data analysis strategies to search for and to characterise EMRIs in parameter space. While elements of EMRI data analysis have been demonstrated before, they have typically involved simplifying assumptions and have tended to separate the 'search' and 'characterisation' parts of the...

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  46. 29. Love and EMRIs in SPA
    Gabriel Andres Piovano (University College Dublin)
    25/11/2022 10:15
    In person talk
    Conference session 4

    The capture of stellar-mass compact objects by a supermassive black hole is one of the most exciting sources detectable by future space-borne interferometers like LISA. The parameters of these extreme-mass-ratio inspirals (EMRIs) binaries are expected to be inferred with excellent accuracy, allowing for unprecedented tests on the nature of their components. Measuring the tidal Love number of...

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  47. 13. GPry - Fast Bayesian inference with Gaussian Processes
    Jonas El Gammal (University of Stavanger)
    25/11/2022 11:00
    In person talk
    Conference session 4

    LISA will offer a window into many different, simultaneously observed sources in a long, narrow band signal. Inferring source parameters will - for complex waveforms - require computationally expensive simulations, especially if those waveforms are generated in time domain.
    This in turn makes Bayesian inference using such codes extremely expensive: typical sampling algorithms like Markov...

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  48. 51. Infrastructure for Lisa Data Analysis
    Antoine Tran (CNES), Hong-Nga Nguyen, Marseille Matthieu (CNES)
    25/11/2022 11:15
    In person talk
    Conference session 4
  49. 53. Final remarks
    25/11/2022 11:45
  50. 5. Identifying LISA verification binaries amongst the Galactic population of double white dwarfs
    Christopher Moore (University of Birmingham)
    In person talk
    Conference session 1

    Double white dwarfs (DWDs) will be the most numerous GW sources for LISA. Most Galactic DWDs will be unresolved and will form a confusion noise foreground, the dominant LISA noise source around $\sim 0.5-3$ mHz. Around 1% of these sources will stand out from the background and be individually detectable. An even smaller fraction (approximately one in a million) will be known in advance from...

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