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EMRI Search and Inference within the LISA Global Fit - Part II

13–17 juil. 2026
Fuseau horaire Asia/Singapore

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Liste des Contributions

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  1. 2. EMRI Models for Data Analysis
    Adam Pound (University of Southampton)
    13/07/2026 09:45
  2. 3. Rapid waveform generation strategies for EMRI search and parameter inference
    Christian Chapman-Bird (University of Glasgow)
    13/07/2026 11:15
  3. 4. Waveform modeling and data analysis for EMRIs with a spinning secondary
    Gabriel Andres Piovano (University College Dublin)
    13/07/2026 11:45
  4. 5. Fast, batched trajectory generation for EMRIs using JAX
    Bert Depoorter (KU Leuven - Royal Observatory of Belgium)
    13/07/2026 14:45
  5. 6. Tfwaves, a Python package for time-frequency representation of LISA signals
    Gaël Servignat (APC), Saptarshi GHOSH (Astroparticule et Cosmologie, Université Paris Cité)
    13/07/2026 15:00
  6. 8. Characterizing Bias in Multi-Source Gravitational Wave Inference with LISA
    Rishav Agrawal
    13/07/2026 15:45
  7. 9. Machine Learning for EMRI science
    Jonathan Gair (AEI Potsdam)
    14/07/2026 09:30
  8. 10. Multiscale Representations of Extreme-Mass-Ratio Inspiral Signals for Identification
    Xueting Zhang
    14/07/2026 11:00
  9. 11. Learning Robust Models for Multi-Source Gravitational-Wave Analysis
    He Wang
    14/07/2026 14:00
  10. 12. A deep learning framework for amplitude generation of general EMRIs
    Jiandong Zhang
    14/07/2026 14:30
  11. 13. Toward Efficient and Accurate EMRI Parameter Estimation: A Machine Learning-Enhanced MCMC Framework
    Bo Liang
    14/07/2026 14:45
  12. 14. (Remote) Deep Learning Denoising for Extreme-Mass-Ratio Inspiral Searches in Low-SNR LISA Data
    Stefan Strub
    14/07/2026 16:30
  13. 15. Machine learning for quasi-periodic eruptions from EMRIs
    Khurshid Karshiboev
    14/07/2026 16:45
  14. 16. Missing data and missing matter
    Philippa Cole
    15/07/2026 09:30
  15. 17. Single-harmonic search for extreme mass-ratio inspirals
    Lorenzo Speri (European Space Agency)
    15/07/2026 10:00
  16. 18. Searching for EMRIs with the one-stop function
    Davendra Hassan
    15/07/2026 11:00
  17. 19. Hierarchical CPSO Search for Extreme-Mass-Ratio Inspirals in Space-Based Gravitational-Wave Detector Data
    Haocheng Hu
    15/07/2026 11:15
  18. 21. Divide and infer: semi-coherent methods for robust gravitational-wave analysis
    Shubham Kejriwal (National University of Singapore)
    15/07/2026 11:30
  19. 22. Environmental effects and matter systematics for low-frequency
    Enrico Barausse (IAP/CNRS)
    16/07/2026 09:30
  20. 23. Rounding up the usual suspects: towards inference of beyond-vacuum effects in the LISA Global Fit
    Francisco Duque (Max Planck Institute for Gravitational Physics)
    16/07/2026 11:00
  21. 24. EMRIs in Light of QPEs: Recent Observational and Theoretical Advances
    Zhen Pan
    16/07/2026 14:00
  22. 25. "Gotta light?” Illuminating AGN Disks with LISA EMRIs
    Federico Fantoccoli
    16/07/2026 14:30
  23. 26. A consistency test for EMRIs
    Lorenzo Copparoni
    16/07/2026 14:45
  24. 27. Probing vector hair of black holes with extreme-mass-ratio inspirals
    Lijing Shao
    16/07/2026 16:30
  25. 29. EMRI Environmentalism
    Leif Lui
    16/07/2026 16:45
  26. 30. Overview of LISA WG/DDPC activities
    Leor Barack, Stanislav Babak (APC)
    17/07/2026 10:00
  27. 31. TianQin update
    Jian-dong Zhang
    17/07/2026 11:00
  28. 35. Taiji progress
    Minghui Du
    17/07/2026 11:15
  29. 32. Forecasting EMRIs: Updated Rates and Bayesian Reality Checks
    Manuel Piarulli (L2I Toulouse, Université de Toulouse, CNRS/IN2P3)
    17/07/2026 14:00
  30. 33. Multi-source analysis of extreme mass ratio inspirals in the Mojito light common dataset
    Alessandro Santini (Max Planck Institute for Gravitational Physics (AEI))
    17/07/2026 14:15
  31. 34. Analysing With(out) LISA's noise asymmetries
    Karel Plets (KU Leuven)
    17/07/2026 14:30
  32. 20. A Hierarchical Strategy for Searching Extreme Mass-Ratio Inspiral Signals Via Reduced Dimensionality Likelihood and Particle Swarm Optimization
    Xiaobo Zou
  33. 28. Modeling environmental effects with LISA
    Sajal Mukherjee
  34. 7. Observing the Milky Way Nucleus with LISA
    Lukas Arda