Go to the Indico Home Page Oldest event Older event Up to category Newer event Newest event
  • Compact style
  • Indico style
  • Indico style - inline minutes
  • Indico style - numbered
  • Indico style - numbered + minutes
  • Indico Weeks View
    • Switch to the management area of this event
    Login

    ML4Jets2023

    6–10 Nov 2023
    DESY
    Europe/Zurich timezone

    Contact

    Session

    Astrophysics and Astronomy

    8 Nov 2023, 09:00
    Main Auditorium (DESY)

    Main Auditorium

    DESY

    Conveners

    Astrophysics and Astronomy

    • David Shih

    Presentation materials

    Zoom link
    1. 137. Machine Learning in Astrophysics and Astronomy
      Caroline Heneka
      08/11/2023, 09:00
    2. 82. Mapping Dark Matter in the Milky Way using Normalizing Flows and Gaia DR3
      Eric Putney (Rutgers, The State University of New Jersey)
      08/11/2023, 09:30

      We present a novel, data-driven analysis of Galactic dynamics, using unsupervised machine learning -- in the form of density estimation with normalizing flows -- to learn the underlying phase space distribution of 6 million nearby stars from the Gaia DR3 catalog. Solving the collisionless Boltzmann equation with the assumption of approximate equilibrium, we calculate -- for the first time ever...

      Go to contribution page
    3. 49. Bayesian Insights into the high-redshift Universe with 21cmPIE-cINN
      Benedikt Schosser (Heidelberg University), Theo Heimel (Heidelberg University)
      08/11/2023, 09:45

      Utilizing 21cm tomography provides a unique opportunity to directly investigate the astrophysical and fundamental aspects of early stages of our Universe's history, spanning the Epoch of Reionization (EoR) and Cosmic Dawn (CD). Due to the non-Gaussian nature of signals that trace this period of the Universe, methods based on summary statistics omit important information about the underlying...

      Go to contribution page
    4. 41. PINNflation solving the dynamics of Inflation using Physics Informed Neural Nets
      Lennart Röver (Heidelberg University)
      08/11/2023, 10:00

      Cosmic inflation is a process in the early Universe responsible for the generation of cosmic structures. The dynamics of the scalar field driving inflation is determined by its self-interaction potential and is coupled to the gravitational dynamics of the FLRW-background. In addition, perturbations of the inflaton field can be computed by numerical solution of the so-called mode equations....

      Go to contribution page
    5. 117. ML Approach to Infer Galaxy Cluster Masses from eROSITA X-ray Images
      Nicolas Barón Pérez
      08/11/2023, 10:15

      We have developed a neural network-based pipeline for estimating galaxy cluster masses directly from X-ray photon data, using known redshift information. Our approach involves training convolutional neural networks on eROSITA simulations, with a focus on the Final Equatorial Depth Survey (eFEDS) dataset. Unlike previous methods, our approach incorporates additional cluster information,...

      Go to contribution page
    6. 91. Searching for stellar streams with machine learning
      Anna Maria Cecilia Hallin (University of Hamburg), Dr Claudius Krause (Rutgers University), David Shih

      Some machine learning methods that have been developed for particle physics applications are actually completely general with regards to the data. In this talk, I will show how ANODE and CATHODE, originally created to search for anomalies in particle physics, can be used to search for stellar streams in the Milky Way using data from the Gaia space telescope. Stellar streams are important...

      Go to contribution page
    Building timetable...