
Torsten Enßlin
I am a scientist at the Max-Planck-Institut für Astrophysik (MPA), Garching (near Munich), and lecturer at the Ludwig Maximilians University, Munich in Germany. I am interested in Information Theory, especially Information Field Theory (IFT), Artificial and Other Intelligence, Cosmology, and High Energy Astrophysics.
Recent Research Highlights
Algorithmic improvements for radio interferometry

Radio telescopes observe the sky in a very indirect fashion. Sky images in the radio frequency range therefore have to be computed using sophisticated algorithms. Scientists at the MPI for Astrophysics have developed a series of improvements for these algorithms, which help to improve the telescopes' resolution considerably.
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Artificial intelligence combined

Artificial intelligence expands into all areas of the daily life, including research. Neural networks learn to solve complex tasks by training them on the basis of enormous amounts of examples. Researchers at the Max Planck Institute for Astrophysics in Garching have now succeeded in combining several networks, each one specializing in a different task, to jointly solve tasks using Bayesian logic in areas none was originally trained on. This enables the recycling of expensively trained networks and is an important step towards universally deductive artificial intelligence.
Of harps, Christmas trees, a wandering star and the mysterious streams of cosmic rays

Researchers at the Leibniz Institute for Astrophysics in Potsdam (AIP), and the Max Planck Institute for Astrophysics in Garching (MPA), have investigated galactic radio objects that adopt shapes such as Christmas trees and harps. They were able to answer the old question of the transport of cosmic rays.
Information Field Theory
Information field theory (IFT) is information theory, the logic of reasoning under uncertainty, applied to fields. A field can be any quantity defined over some space, e.g. the air temperature over Europe, the magnetic field strength in the Milky Way, or the matter density in the Universe. IFT describes how data and knowledge can be used to infer field properties. Mathematically it is a statistical field theory and exploits many of the tools developed for such. Practically, it is a framework for signal processing and image reconstruction.
Learning Machines, Extended Logik, & Intelligence
Loosly connected research lines on machine learning, information theory, as well as artificial and other intelligence. Learning Machines better reason according to logic. If uncertainties are involved, this should be extended, probabilistic, or Bayesian logic. The same is true for any form of intelligence, whether of human, artificial, or other nature.
Cosmology
The temperature fluctuations in the cosmic microwave background (CMB) and the cosmic matter distribution in the large-scale structure (LSS) are both tracers of the primordial quantum fluctuations. Those are believed to have happened during the very first moments of the Universe in the inflationary epoch. CMB and LSS are therefore our primary information sources on cosmology. Their detailed studies provide us insight into the history, geometry and composition of the Universe. IFT permits us to construct optimal methods to analyse and interpret CMB and LSS data, and to image with high fidelity the cosmic structures imprinted in those data sets.
High Energy Astrophysics
The Universe is permeated by high-energy particles and magnetic fields. Charged particles with nearly the speed of light spiraling around in the magnetic fields, which themselves are bound to the cosmic plasma. The particles and fields are important ingredients of the interstellar and intergalactic media. They transport energy, they push and heat the thermal gas, and they trace violent processes in cosmic plasmas. A number of observational windows in basically all electromagnetic wavebands, ranging from the radio to the gamma ray regime, provide us with direct and indirect vision into the high energy Universe. The IFT group develops special purpose methods to better imagine relativistic particles, magnetic fields, and even to tomographically reconstruct their distributions within the Milkey Way.
Lecture on Information Theory & Information Field Theory
Imaging in astronomy, geology and medicine require intelligent methods to obtain high fidelity images from noisy, incomplete data. The theoretical and mathematical framework in which imaging and data analysis methods are derived should be information theory to which these lectures will introduce first (first 1/3 semester, suited for Bachelor and Master students, 3 ETCS). Based on this, information theory for fields will be developed, which can be used to reconstruct signals from data (remaining 2/3 semester, more targeted at Master students, 6 ETCS).
Seminar Information Theory & Information Field Theory
The seminar is intended for participants of the lecture on Information Theory (1/3 semester) & Information Field Theory (2/3 semester), the content of which will be assumed to be known by all participants. The main seminar goal is to extend the participants' knowledge beyond the material covered in the lecture, especially with respect to concrete measurement situations, imaging, and existing algorithms. A second goal is to practice presentations and open discussions.
About Me
- 2019, Giuseppe and Vanna Cocconi of th EPS as part of the Planck Collaboration
- 2018, Hochsprung Award for my information field theory lecture that lead to a start-up by students
- 2018, Gruber prize for Cosmology as part of the Planck collaboration
- since 2014, Head of the Information Field Theory Group at MPA
- 2014, Call for full Professorship on Theoretical Astroparticle Physics (W3 level, declined) Karlsruhe Institute for Technology, Germany
- since 2014, Associate Professor (Privatdozent) at Ludwig-Maximilians-University Munich, Germany
- since 2008, Planck Scientist status in the Planck Surveyor Mission (full access to proprietary data)
- 2003- 2016, Head of the MPA Planck Analysis Centre, Garching, Germany
- since 2006, Tenured position at MPA
- 2003- 2006, Tenure-track-position at MPA
- 1999- 2003, Postdoctoral Researcher Max Planck Institute for Astrophysics (MPA), Garching, Germany
- 1999, Research Associate Physics Department of University of Toronto, Canada
- 1996- 1999, PhD “summa cum laude” on “Relativistic Particles and Magnetic Fields in Clusters and Filaments of Galaxies” Rheinische Friedrich-Wilhelms-Universität Bonn & MPI for Radioastronomy, Bonn, Germany

Active Group
- Philipp Arras (PhD Student; Radio Aperture Synthesis)
- Vincent Eberle (PhD Student & former Master Student; Efficient representation of instrument responses)
- Gordian Edenhofer (PhD Student & former Master Student; Spatio-spectral component separation of the cosmic microwave sky)
- Philipp Frank (PhD Student & former Master Student; Field dynamics inference and simulation)
- Matteo Guardiani (Master Student; Covid-19 modeling and causial inference)
- Johannes Harth-Kitzerow (PhD Student & former Master Student; Effective description of dynamics in large RNA systems)
- Viktoria Kainz (Master Student; Interacting adaptive inference systems)
- Jongseo Kim (Master Student; Generative models for pattern formation)
- Ivan Kostyuk (PhD Student; Cosmic simulations with deep convolutional neural networks)
- Reimar Leike (Postdoc, PhD Student & former Master Student; 3D maps of Galactic dust)
- Max Newrzella (Postdoc; Machine Learning)
- David Outland (Master Student; Bioluminescence)
- Nico Reeb (Master Student; Tracing luminescent organisms)
- Jakob Roth (PhD Student & former Master Student; High contrast imaging)
- Ann-Kathrin Straub (Postdoc; Machine Learning)
- Johannes Zacherl (Master Student; Autoencoder)
- Philipp Zehetner (Master Student; Bioluminescence field reconstruction)

Alumni
- Sara Milosevic (Master Student; Astrophysical data analysis with variational autoencoders)
- Andrija Kostić (Master Student; Bayesian Causal Inference and Quasi Periodic Signal analysis)
- Jakob Knollmüller (PhD Student & Master Student; Metric Gaussian Variational Inference, Bayesian component separation)
- Morten Giese (Master Student; Inference of the atmospheric electron density with LOFAR data)
- Fabian Kapfer (Master Student; Multi-frequency radio calibration)
- Sebastian Hutschenreuter (PhD Student & Master Student; Primordial magnetism; Galactic structures)
- Sebastian Kehl (Postdoc; Machine Learning)
- Natalia Porqueres (PhD Students & Master Student; Large-scale structure reconstruction)
- Lukas Platz (Master Student; Spatio-spetral imaging of the Fermi gamma-ray sky)
- Maxim Wandrowski (Master Student; Denoising, Deconvolving and Decomposing the COMPTEL Gamma-Ray Sky)
- Julian Rüstig (Master Student; Combined Inference of Single Dish and Interferometric Radio Data)
- Margret Westerkamp (Master Student; Dynamical Field Inference by Ghost Fields)
- Philipp Haim (Master Student; Medical imaging)
- Christoph Lienhard (Master Student; Hamiltonian Monte-Carlo Sampling)
- Max Kurthen (Master Student; Causal Inference)
- Andreas Koch (Bachelor Student; Bayesian spectral and temporal feature inspection in magnetar giant flare SGR 1806-20)
- Marvin Baumann (Bachelor Student; Bayesian multidimensional lightcurve reconstruction of the giant magnetar flare SGR 1806-20)
- Tobias Aschenbrenner (Master Student; Adaptive Grids for NIFTy)
- Fatos Gashi (Master Student; Stochastic Expectation Propagation in Information Field Theory)
- Johannes Oberpriller (Master Student; Bayesian parameter estimation of miss-specified models)
- Silvan Streit (Master Student; Fast representation of field covariances)
- Martin Dupont (Master Student; Information field dynamics for cosmic rays)
- Felix Wichmann (Master Student; Advanced aperture synthesis)
- Matevz Sraml (Master Student; Gamma ray astronomy)
- Theo Steininger (PhD Student; Galactic tomography)
- Daniel Pumpe (PhD Student & former Master Student; Towards multifrequency imaging)
- Vanessa Böhm (PhD Student; Gravitational lensing of the Cosmic Microwave Background)
- Mahsa Ghaempanah (PhD Student; Information field theory for INTEGRAL gamma ray data)
- Maximilian Kurthen (Bachelor Student; Discrete spherical harmonics)
- Maksim Greiner (PhD Student; The Galactic free electron density -- a Bayesian reconstruction / Master Student; Signal Inference in Radio Astronomy)
- Fotis Megas (Bachelor Student; Distinguishing Gravitational Wave Signals by Their Correlation Structures)
- Sebastian Dorn (PhD Student; Bayesian Inference of Early-Universe Signals; Master Student; Non-Gaussianity in the Cosmic Microwave Background)
- Valentina Vacca (Postdoc; Radio astronomy)
- David Butler (Master Student; Resolving polarised emission in radio interferometry)
- Gasper Senk (Master Student; Detecting Cosmic Ray artifacts in astronomical images)
- Marco Selig (PhD Student; Information field theory for gamma ray astronomy / Master Student; Information field theory based high energy photon imaging)
- Christian Muench (Master Student; Mathematical foundation of Information Field Dynamics)
- Hendrik Junklewitz (PhD Student; Radio astronomy and information field theory)
- Niels Oppermann (PhD Student; Signal inference in Galactic astrophysics)
- Lars Winderling (Master Student; On the theory calibration)
- Helin Weingartner (Master Student; Statistische Modellierung und Rekonstruktion von diffuser Roentgenstrahlung von Galaxienhaufen)
- Maximilian Uhlig (Master Student; Cosmic ray driven Winds in Galaxies)
- Maximilian Ullher (Bachelor Student; Eine Faradaykarte der Milchstrasse unter der Annahme approximativer Symmetrien)
- Michael Bell (Postdoc; Radio Astronomy)
- Jens Jasche (PhD Student; Bayesian Methods for analyzing the large scale structure of the Universe / Master Student; On the coupling between cosmic rays and primordial gas)
- Mona Frommert (PhD Student; Temperatur and Polarization of the Cosmic Microwave Background)
- Cornelius Weig (Master Student; Information Field Theory applied to a spatially distorted log-normal field with Poissonian noise)
- Petr Kuchar (Master Student; TCharacteristics of magnetic fields in galaxy clusters from Faraday rotation data REALMAF and its use on Hydra A)
- Andre Walkens (Master Student; Studying magnetic turbulence with radio polarimetry)
- Herbert Kaiser (Master Student; Cosmic Rays and primordial chemistry)
- Francisco-Shu Kitaura (PhD Student; Cosmic Cartography Bayesian Reconstruction of the Cosmological Large-Scale Structure with ARGO, an Algorithm for the Reconstruction of Galaxy-traced Over-densities)
- Gordana Stojceska (Master Student; Statistical Sampling in Multidimensional Parameter Spaces Algorithms and Applications)
- Ilya Saverchenko (Master Student; Interacting Galaxies - Matching Simulations to Observations)
- Christop Pfrommer (PhD Student; On the role of cosmic rays in clusters of galaxies)
- Corina Vogt (PhD Student; Investigations of Faraday Rotation Maps of Extended Radio Sources in order to determine Cluster Magnetic Field Properties)
Meetings
Recorded Talks
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Künstliche Intelligenz kombiniert +
Q&A Session
Cafe & Kosmos (Muffatkaffee, 10.3.2020) -
Information Field Theory: from astrophysical imaging to artificial intelligence
Joint Astronomical Colloquium (ESO Garching, 13.2.2020) -
Wahrheit und Wahrscheinlichkeit in All und Alltag
Cafe & Kosmos (Muffatkaffee, Munich, 9.12.2017) -
Vom Anfang der Zeit - unser Kosmos im Mikrowellenlicht
Edgar-Lüscher-Seminar am Gymnasium Zwiesel (29.4.2017) -
Scharfer Blick zurück
HYPERRAUMTV, May 17, 2017 -
Logik trifft Wahrscheinlichkeit
HYPERRAUMTV, May 17, 2017 -
Vom Anfang der Zeit: Unser Kosmos im Mikrowellenlicht ,
Slides
Einstein Symposium 2015 (13.11.2015 Zürich) -
Information field theory
Cannadian Institute for Theoretical Astrophysics, Toronto (20.3.2015) -
Our Universe - Cosmological Results of the Planck Mission
Heidelberg Joint Astronomical Colloquium (20.1.2015) -
Unsichtbare Astronomie, Radiostrahlung, zerstrahlende Materie
Gesprächsreihe mit Raoul Schrott, BR 2011-2016 (Munich, 11.03.13)
Contact
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Address
MPA
Karl-Schwarzschild-Str. 1
85748 Garching
Germany
Office: 010 -
Email
ensslin@mpa-garching.mpg.de -
Phone
+49 (0) 89 30000 2243