string_data: workshop on data science and string theory

Europe/Berlin
ASC

ASC

Theresienstr. 37 80333 München
Description

workshop (March 26-28) - hackathon (March 29)

The goal is to bring together string theorists and data scientists to discuss how big data techniques can be utilised to understand the "string landscape". This meeting will feature talks, specialised discussion groups, and the first string theory hackathon.

One objective of this workshop is to present the status of data science methods applied to string theory and to survey our current understanding of the landscape. Another objective is to provide an opportunity for string theorists and data scientists to identify optimal future targets.
 

Organizers:
Thomas Grimm
Sven Krippendorf
Dieter Lüst
 

ASC

Previous workshop 2017: Northeastern, Boston (link)

 

Poster
    • 1
      Counting String Standard Models
      Speaker: Prof. Andre Lukas (University of Oxford)
      Slides
    • 2
      Machine Learning Calabi-Yau Volumes
      Speaker: Prof. Rak-Kyeong Seong (Tsinghua University)
    • 12:00
      Lunch Break
    • 3
      Machine learning in astrophysics & cosmology
      I present an overview of machine learning methods as they are applied in astrophysics and cosmology, and highlight both new developments and real problems that are facing the field.
      Speaker: Dr Ben Hoyle (MPE/USM Munich)
      Slides
    • 4
      Topological Data Analysis for Cosmology and String Theory
      Speaker: Prof. Gary Shiu (University of Wisconsin-Madison)
    • 15:30
      Coffee Break 449

      449

      ASC

    • 5
      The Early Universe Information Bottleneck
      Speaker: Dr Jonathan Frazer (DESY)
      Slides
    • 6
      Classification of Quasi-Realistic Heterotic String Vacua
      Speaker: Mr Glyn Harries (University of Liverpool)
      Slides
    • 7
      Data in (F-theory) flux
      Speaker: Dr Timo Weigand (CERN)
    • 8
      Data creation with Generative Adversarial Networks
      Speaker: Dr Fabian Ruehle (University of Oxford)
      Slides
    • 10:30
      Coffee Break 449

      449

      ASC

    • 9
      Big Data and Machine Learning in the Heterotic Orbifold Landscape
      Speaker: Dr Patrick Vaudrevange (TU Munich)
      Slides
    • 10
      Deeping-learning the Landscape
      Speaker: Prof. Yang-Hui He (City, University of London, Merton College, Oxford & Nankai University)
      Slides
    • 12:30
      Lunch Break
    • 11
      Applications of Machine Learning techniques at the ATLAS Collaboration
      Speaker: Mr David Handl (LMU Munich)
      Slides
    • 12
      Classifying fibration structures in Calabi-Yau constructions
      Speaker: Prof. James Gray (Virginia Tech)
      Slides
    • 15:30
      Coffee Break 449

      449

      ASC

    • 13
      Learning the non-Higgsable gauge groups in 4D F-theory
      Speaker: Yinan Wang (MIT)
      Slides
    • 14
      Persistent Homology and Flux Vacua
      Speaker: Alex Cole (University of Wisconsin-Madison)
    • 19:00
      Conference Dinner Georgenhof

      Georgenhof

      Friedrichstraße 180801 München
    • 15
      Axion hierarchies from Kahler cones
      Speaker: Prof. Liam McAllister (Cornell University)
    • 16
      Vacuum selection from Cosmology on Networks of String Vacua
      Speaker: Dr Cody Long (Northeastern University)
      Slides
    • 10:30
      Coffee Break 449

      449

      ASC

    • 17
      Anomaly Detection: Mapping the IIB Lamppost with Reinforcement Learning
      Speaker: Prof. James Halverson (Northeastern University)
      Slides
    • 18
      Machine learning at Belle II
      Speaker: Mr James Kahn (The University of Melbourne)
      Slides
    • 12:15
      Lunch Break
    • 19
      Landscape and Complexity Catastrophe & Report on developments in mathematical software
      Speaker: Prof. Michael Douglas (Stony Brook University)
      Slides
    • 20
      Challenging the Refined Swampland Distance Conjecture in Calabi-Yau Moduli Spaces
      Speaker: Daniel Klaewer (Max Planck for Physics)
    • 15:15
      Coffee Break 449

      449

      ASC

    • 21
      History and perspectives
      Speaker: Prof. Bert Schellekens (Nikhef)
      Slides
    • 22
      Discussion
    • 23
      WG1: Datasets in String Theory
      Speakers: Dr Christoph Mayrhofer (LMU Munich), Dr Cody Long (Northeastern University)
    • 10:30
      Coffee Break
    • 24
      WG2: Quo vadis string landscape?
      Speakers: Prof. Liam McAllister (Cornell University), Dr Timo Weigand (CERN)
    • 12:30
      Lunch Break
    • 25
      WG3: Machine learning tools for string theory
      Speakers: Dr Fabian Ruehle (University of Oxford), Prof. James Halverson (Northeastern University)
      Slides
    • 15:30
      Coffee Break