Ruprecht-Karls-Universität Heidelberg

Astronomisches Rechen-Institut

Address:

Astronomisches Rechen-Institut
Mönchhofstr. 12-14
69120 Heidelberg
Germany
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The Astronomisches Rechen-Institut (ARI) is part of the newly established Centre for Astronomy of Heidelberg University (Zentrum für Astronomie der Universität Heidelberg or ZAH). The other two institutes in the ZAH are the Institute for Theoretical Astrophysics (Institut für Theoretische Astrophysik or ITA) and the State Observatory Königstuhl (Landessternwarte Königstuhl or LSW).

The scientific activities at the ARI cover a broad range of research areas including cosmology, gravitational lensing, galaxy evolution, star clusters, stellar astrophysics, the interstellar medium, astrometry, satellite missions, and calendrical calculations.

The ARI is involved in various national and international scientific networks and collaborations.  The institute plays a leading role in supporting the Gaia satellite mission of the European Space Agency and participates in the ground-based spectroscopic and photometric SDSS, 4MOST, and LSST surveys.

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Next Astro colloquia
Jun 11
11:15
Investigating Galaxy-Merger Rates in Euclid Q1 with Semi-Supervised Machine Learning
Laslo Ruhberg (ARI)
ARI Institute Colloquium
ARI, Moenchhofstrasse 12-14, Seminarraum 1.OG
Jun 12
11:00
Cosmic Cascades and Beyond: The behaviour and appearance of water in protoplanetary disks
Sebastiaan Krijt (University of Exeter)
Königstuhl Kolloquium
Max-Planck-Institut für Astronomie, Level 3 Lecture Hall (301)
Jun 16
16:30
Solving Inverse Problems in Astronomy with Invertible Neural Networks
Victor Ksoll (Heidelberg University (ZAH/ITA))
Heidelberg Joint Astronomical Colloquium
Philosophenweg 12, Main Lecture hall (gHS),

More colloquia

Recent ZAH publications
5/2026
Longa-Peña, P.; Tregloan-Reed, J. et al. (inc. Hundertmark, M.)
Brightness evolution of LEO Starlink mega-constellation satellites from 2021 to 2023: a multiyear ground-based photometric study
MNRAS 548, ag552(2026)

4/2026
Schosser, Benedikt; Röspel, Tobias; Schäfer, Björn Malte
Markov walk exploration of model spaces: Bayesian selection of dark energy models with supernovæ
JCAP 04, 079(2026)

5/2026
Kang, Y.; Paltani, S. et al. (inc. Zinchenko, I. A.)
Euclid: Improving redshift distribution reconstruction using a deep-to-wide transfer function
A&A 709, A55(2026)


More publications