This School assisted Ph.D. students and other early-stage career researchers to develop their quantitative understanding of the fundamental processes that produce the observed behaviour and properties of plasmas; through lectures and practical computing sessions they also gained skills in the application of modern data science techniques to the calculation and evaluation of data on these processes. Scientists in developing countries without extensive experimental research facilities particularly benefit from such training in modern, data-driven computational physics.

Further practical details are available at the ICTP webpage for this event.

Directors

• Christian Hill (IAEA)
• Ludmila Marian (IAEA)
• Hyun-Kyung Chung (Korea Institute of Fusion Energy, Republic of Korea)
• Manuel Bautista (Western Michigan University, USA)
• Yuri Ralchenko (National Institute of Standards and Technology, USA)
• Udo von Toussaint (Max Planck Institute for Plasma Physics, Garching, Germany)

Local Organiser

• George Thompson

Speakers

• Manuel Bautista (Western Michigan University, USA)
• Marie-Lise Dubernet (Paris Observatory, Paris Sciences et Lettres University, France)
• Christian Hill (IAEA)
• Ludmila Marian (IAEA)
• Yuri Ralchenko (National Institute of Standards and Technology, USA)
• Evgeny Stambulchik (Weizmann Institute of Science, Israel)
• Udo von Toussaint (Max Planck Institute for Plasma Physics, Garching, Germany)

Participants by Application

Successful participants by application are expected to be early-stage career researchers (at about the postgraduate student and post-doc level) working in the field of computational plasma physics and/or plasma-material interaction. Applications for participation are accepted through the ICTP webpage for this event.

There is no registration fee for this Workshop.

Useful Links and Further Reading

Database Services

• AMD Unit Databases
• A list of data services relevant to plasma physics
• The NIST Atomic Spectra Database
• NIST FLYCHK Interface (login required)
• The VAMDC Portal for querying databases within the Virtual Atomic and Molecular Data Centres consortium

Molecular Dynamics Simulation

• Home page of the LAMMPS Molecular Dynamics Simulator
• LAMMPS files:
  • Al_zhou.eam.alloy (Al interatomic potential from Zhu et al., Acta Materialia 49, 4005 (2001).)
  • Input files: in.stretch_tutorial_03.lammps, in.stretch_tutorial_03.lammps, in.stretch_tutorial_03.lammps.

Uncertainty Quantification

• Bruno Sudret, Uncertainty propagation using polynomial chaos expansions, Summer school, Weimar (2016): Recommended introduction into PCE.
• N. Lüthen, S. Marelli, B. Sudret, Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark (2021)
• R. C. Smith Uncertainty quantification, SIAM (2014)
• O. P. Le Maitre, O. M. Knio, Spectral Methods for Uncertainty Quantification, Springer (2010)
• Software:
  • UQLab (ETH Zürich)
  • DAKOTA
  • VECMA VVUQ
  • chaospy

Bayesian Inference

• D. S. Sivia, Data Analysis - A Bayesian Tutorial, Oxford University Press (2006)
• W. von der Linden Bayesian Probability Theory: Applications in the Physical Sciences, Cambridge University Press (2014)
• U. von Toussaint, Bayesian Inference in Physics, Rev. Mod. Phys 83(3), 943-999 (2011)
• C. Bishop, Pattern Recognition and Machine Learning, Springer (2006)

Line Shapes

• Stark broadening parameters for neutral and singly charged ions
• The STARK-B database for broadening of isolated lines of atoms and ions in the impact approximation
• The interactive Plasma Formulary at the Weizmann Institute of Science's Plasma Laboratory
• The NIST Atomic Spectral Line Broadening Bibliographic Database