Name: LISA data analysis: from classical methods to machine learning
Start: 2022-11-21T08:15:00+01:00
End: 2022-11-25T17:00:00+01:00
Location: L2IT Toulouse

LISA data analysis: from classical methods to machine learning

from Monday, November 21, 2022 (8:15 AM) to Friday, November 25, 2022 (5:00 PM)

Monday, November 21, 2022

8:15 AM Welcome coffee
Welcome coffee
8:15 AM - 9:00 AM
9:00 AM Introductory lectures
9:00 AM - 12:30 PM
Contributions

9:00 AM Introduction to LISA data analysis - Maude Le Jeune (APC)

11:00 AM Introduction to machine learning - Sylvain Caillou (L2I Toulouse, CNRS/IN2P3, UT3)
12:30 PM Lunch
Lunch
12:30 PM - 2:00 PM
2:00 PM Training session 1
2:00 PM - 5:30 PM
Contributions

2:00 PM GW Detection with Traditional vs Machine Learning Techniques - Part 1 (theory) - Joseph Bayley (Univ. of Glasgow)

4:00 PM GPU Techniques to Accelerate GW Waveforms and Data Analysis Computations - Part 1 (theory) - Michael Katz (AEI)
Tuesday, November 22, 2022
9:00 AM Training session 2
9:00 AM - 12:30 PM
Contributions

9:00 AM 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)

9:00 AM GW Detection with Traditional vs Machine Learning Techniques - Part 2 (tutorial) - Joseph Bayely (Univ. of Glasgow) Michael Williams (University of Glasgow)

11:00 AM GW Detection with Traditional vs Machine Learning Techniques - Part 2 (tutorial) - Joseph Bayely (Univ. of Glasgow) Michael Williams (University of Glasgow)

11:00 AM 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)
12:30 PM Lunch
Lunch
12:30 PM - 2:00 PM
2:00 PM Training session 3
2:00 PM - 5:30 PM
Contributions

2:00 PM GW Parameter Estimation with Bayesian Machine Learning - Part 1 (theory) - Stephen Green (Albert Einstein Institute Potsdam)

4:00 PM Gaussian Process Regression - Part 1 (theory) - Stanislav Babak (APC)
Wednesday, November 23, 2022
9:00 AM Training session 4
9:00 AM - 12:30 PM
Contributions

9:00 AM GW Parameter Estimation with Bayesian Machine Learning - Part 2 (tutorial) - Natalia Korsakova (APC) Stephen Green (Albert Einstein Institute Potsdam)

9:00 AM Gaussian Process Regression - Part 2 (tutorial) - Stanislav Babak (APC)

11:00 AM GW Parameter Estimation with Bayesian Machine Learning - Part 2 (tutorial) - Natalia Korsakova (APC) Stephen Green (Albert Einstein Institute Potsdam)

11:00 AM Gaussian Process Regression - Part 2 (tutorial) - Stanislav Babak (APC)
12:30 PM Lunch
Lunch
12:30 PM - 2:00 PM
2:00 PM Conference session 1
2:00 PM - 5:45 PM
Contributions

2:00 PM LISA status and data processing organisation - Antoine Petiteau (CEA/IRFU/DPhP)

2:30 PM Trans-dimensional sampling methods: current status and future prospects - Nikolaos Karnesis (AUTh)

3:00 PM LISA Data Challenge for the Galaxy - Kristen Lackeos (Max Planck Institute for Radio Astronomy)

4:00 PM Accelerating parameter estimation of Galactic binaries in the full LISA frequency band using Gaussian Process Regression - Stefan Strub (ETH Zurich)

4:15 PM LISA data analysis in the presence of environmental effects - Laura Sberna (Max Planck Institute for Gravit)

4:45 PM The imprint of gas on gravitational waves from LISA intermediate-mass black hole binaries - Mudit Garg (University of Zurich)

5:00 PM Investigation of Tidal Disruption Events through gravitational waves - martina toscani (L2I Toulouse, CNRS/IN2P3, UT3)
Thursday, November 24, 2022
9:00 AM Conference session 2
9:00 AM - 12:30 PM
Contributions

9:00 AM 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)

9:30 AM 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)

10:00 AM On the effectiveness of null TDI channels as instrument noise monitors in LISA - Martina Muratore (AEI (Potsdam))

10:15 AM The impact data gaps have on parameter estimation - Ollie Burke (L2I Toulouse, CNRS/IN2P3, UT3)

11:00 AM Extracting gravitational-wave backgrounds in noise of unknown spectral shape - Quentin Baghi (CEA Saclay)

11:30 AM LISA data analysis: status and challenges - Stanislav Babak (APC)

12:00 PM Inference for LISA with Normalising flows and data representation through source separation - Natalia Korsakova (APC)
12:30 PM Lunch
Lunch
12:30 PM - 2:00 PM
2:00 PM Conference session 3
2:00 PM - 6:00 PM
Contributions

2:00 PM MCMC parameter estimation methods for LISA massive black holes - Sylvain Marsat (L2I Toulouse, CNRS/IN2P3, UT3)

2:30 PM Importance nested sampling with nessai for gravitational-wave inference - Michael Williams (University of Glasgow)

2:45 PM Massive Black Hole Binary parameter estimation using Masked Autoregressive Flows - Ivan Martin Vilchez (Institute of Space Science (ICE, CSIC and IEEC))

3:00 PM Learning-based models for gravitational wave analysis - Elie Leroy (DRF-IRFU)

3:15 PM LISA Data Analysis - A Deep Learning Approach - Florentina-Crenguta Pislan (Institute of Space Science, Faculty of Physics)

4:00 PM Characterizing Anisotropic Stochastic Gravitational Wave Backgrounds and Foregrounds with the Bayesian LISA Pipeline (BLIP) - Alexander Criswell (University of Minnesota)

4:15 PM Searching for primordial features with LISA - Jacopo Fumagalli (IAP)

4:30 PM Detecting Gravitational Waves from Cosmic Strings with LISA - Namitha Suresh (Cornell University)

4:45 PM Bayesian inference methods in cosmology with LISA standard sirens - Danny Laghi (CNES, L2I Toulouse, CNRS/IN2P3, UT3)

5:00 PM Modified Gravity Forecasting with Large Scale Structure in the LISA era, including a Machine Learning analysis - Alexander Bonilla Rivera (UFJF)

5:15 PM Merger-ringdown test -- A novel test of GR using a machine learning implementation - Swetha Bhagwat (University of Birmingham)

5:30 PM On the edge of quantum black holes - Jahed Abedi (University of Stavanger)

5:45 PM Determining the Individual Masses of Accreting White Dwarf Binaries - Sophia Yi (University of Virginia)
Friday, November 25, 2022
9:00 AM Conference session 4
9:00 AM - 12:15 PM
Contributions

9:00 AM A neoclassical approach to coherent gravitational-wave search - Alvin Chua (National University of Singapore)

9:30 AM Detecting gravitational waves from extreme mass ratio inspirals using convolutional neural networks - Xue-Ting Zhang (School of Physics and Astronomy, Sun Yat-sen University)

9:45 AM FastEMRIWaveforms: New tools for millihertz gravitational-wave data analysis - Lorenzo Speri (Max Planck Institute for Gravitational physics (Albert Einstein Institute, AEI Potsdam))

10:00 AM Progress towards a semi-coherent search for EMRI signals - Diganta Bandopadhyay (University of Birmingham)

10:15 AM Love and EMRIs in SPA - Gabriel Andres Piovano (University College Dublin)

11:00 AM GPry - Fast Bayesian inference with Gaussian Processes - Jonas El Gammal (University of Stavanger)

11:15 AM Infrastructure for Lisa Data Analysis - Antoine Tran (CNES) Hong-Nga Nguyen Marseille Matthieu (CNES)

11:45 AM Final remarks
12:15 PM Lunch + LIROCOS meeting (organisers only)

12:15 PM - 3:30 PM

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