1 January 2025 to 28 February 2025
Online
Europe/Berlin timezone

Identifying and characterizing spectral lines

1 Jan 2025, 10:05
5m
Online

Online

Speaker

Prof. Peter Schilke (University of Cologne)

Description

Our specific interest is the analysis of both laboratory and astronomical molecular spectra using ML methods. The speed and quality of data gathered today, both in the laboratory and by astronomical instruments (e.g. ALMA) demand new and faster methods of both generating molecular line catalog entries and of analyzing astronomical data cubes. For the latter, there have been ongoing efforts in the framework of the German ALMA ARC (funded through ErUM Pro), but this funding line is not really suitable, and a new effort to make use of efficient ML methods is necessary. This could of course be extended to other wavelength ranges, since the principles are similar.

Please describe areas in which you would like to improve your knowledge / skills.

Machine Learning Methods, especially Neural Networks

My current most burning research question, I like to find partners for, is:

Spectral line analysis and characterization

What is your field and role?

Professor for Astrophysics

Please describe your expertise/areas in which you would like to contribute / advise.

Spectral line modeling

Please describe areas in which you can contribute to “data handling” teaching.

Handling complex molecular data cubes.

What is your expertise in computing and / or software development?

Original developer of XCLASS https://xclass.astro.uni-koeln.de/

In ErUM-Data, what kind of data are you dealing with?

Spectral data cubes from interferometers

Your ErUM - Committee is RDS - Rat Deutscher Sternwarten
Do you consent to the data usage and public abstract data posting in the ErUM-Data Community Information Exchange? Yes

Primary author

Prof. Peter Schilke (University of Cologne)

Presentation materials

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