Sebastian Hutschenreuter

Astrophysicist

I am a PostDoc at the Vienna Observatory in the group of João Alves. My research is focussed on mapping and understanding the Milky Way in its many facets. In particular, I am interested in the Galactic magnetic field and observables related to it, such as Faraday rotation, synchrotron radiation and dust polarization. As a consequence of the close entanglement of the different components of the interstellar medium (ISM), my work also investigates the dynamics and the three-dimensional structure of gas and ionized matter. To constrain all these quantities, I employ large scale Bayesian inference engines which allow me to combine various data sets and to disentangle the physical quantities encoded in them. Apart from my main research field in Galactic ISM studies, I also have worked in cosmology with a focus on primordial magnetic fields. I have started my career with a Master's degree in Physics at the Universities of Munich (LMU) and Copenhagen, before pursuing a PhD at the Max Planck Institute for Astrophysics in Garching under the supervision of Torsten Enßlin. I have then worked with Marijke Haverkorn in the Galactic Ecosystem group at the Radboud University Nijmegen in the Netherlands, before moving to Vienna to be part of the ISM-FLOW project, with the goal to map the 3D motion of the nearby ISM.

Science

The Galactic Faraday sky

The Faraday effect is the rotation of linearly polarized light by a magnetized plasma and is an excellent tracer of the magnetic field along the line-of-sight. The goal of this project is to reconstruct the Galactic Faraday screen of the Milky Way from extra-galactic polarized point sources.

Disentangling the Galactic Faraday sky (Hutschenreuter et al.; Astronomy and Astrophysics, Arxiv)

The Galactic Faraday rotation sky 2020 (Hutschenreuter et al.; Astronomy and Astrophysics, Arxiv)

The Galactic Faraday depth sky revisited (Hutschenreuter & Enßlin; Astronomy and Astrophysics, Arxiv)

Primordial magnetic fields

I have led an international research collaboration on the reconstruction of primordial magnetic fields in the Local Universe. In this project, we have used the distribution of matter in the nearby Universe to reconstruct the residual magnetic fields stemming from a battery effect occurring shortly after the Big Bang.

The primordial magnetic field in our cosmic backyard (Hutschenreuter et al.; Classical and Quantum Gravity, Arxiv)

IMAGINE

I am part of the IMAGINE technical development team. This collaboration aims at inferring the Galactic magnetic field, combining tracers such as synchrotron radiation, dust polarization and Faraday rotation using Bayesian sampling techniques.

Code repository: Github

Selected project contributions

Outflow from Sco-Cen

Sco-Cen is a nearby complex of star forming regions that has strongly influenced our immediate Galactic neighborhood. To this day, there is an outflow of gaseous material coming to Earth from Sco-Cen, which we have studied in a project under the lead of Martin Piecka.

Towards a complete picture of the Sco-Cen outflow (Piecka et al.; Astronomy and Astrophysics, Arxiv)

Bioluminescence in the Deep Sea

This is a project lead by former students (Nico Reeb & Philipp Zehetner) under my co-supervision. We used data from the ANTARES detector (originally designed to observe neutrinos in the deep sea) to locate and characterize fish via their emitted bioluminescence.

Studying Bioluminescence Flashes with the ANTARES Deep Sea Neutrino Telescope (Reeb et al.; Limnology and Oceanography, Arxiv)

Circular polarisation

The information contained in the Faraday effect and synchtrotron radiation can be used to constrain the circular polarization of the radio sky. In this small series of projects, we make predictions for the circular polarization emitted by the Milky Way and extra-galactic radio jets.

The Galaxy in circular polarization (Ensslin et al.; PhysRevD, Arxiv)

Determining the composition of radio plasma via circular polarization: the prospects of the Cygnus A hot spots (Ensslin et al.; JCAP, Arxiv)

Nifty

I have been part of the Nifty developer team. Nifty (Numerical Information Field Theory) is a Bayesian inference engine based on Information Field Theory. It can be used to employ variational inference techniques with a focus on high dimensional noisy settings.

Code repository: Gitlab