The variable shadow of M87*. (arXiv:2002.05218v1 [astro-ph.IM])
<a href="http://arxiv.org/find/astro-ph/1/au:+Arras_P/0/1/0/all/0/1">Philipp Arras</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Frank_P/0/1/0/all/0/1">Philipp Frank</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Haim_P/0/1/0/all/0/1">Philipp Haim</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Knollmuller_J/0/1/0/all/0/1">Jakob Knollmüller</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Leike_R/0/1/0/all/0/1">Reimar Leike</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Reinecke_M/0/1/0/all/0/1">Martin Reinecke</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Ensslin_T/0/1/0/all/0/1">Torsten Enßlin</a>
Observing the dynamics of compact astrophysical objects provides insights
into their inner workings and allows to probe physics under extreme conditions.
The immediate vicinity of an active supermassive black hole with its event
horizon, photon ring, accretion disk, and relativistic jets is a perfect place
to study general relativity, magneto-hydrodynamics, and high energy plasma
physics. The recent observations of the black hole shadow of M87* with Very
Long Baseline Interferometry (VLBI) by the Event Horizon Telescope (EHT) open
the possibility to investigate dynamical processes there on timescales of days.
In this regime, radio astronomical imaging algorithms are brought to their
limits. Compared to regular radio interferometers, VLBI networks have fewer
antennas. The resulting sparser sampling of the Fourier sky can only be partly
compensated by co-adding observations from different days, as the source
changes. Here, we present an imaging algorithm that copes with the data
scarcity and the source’s temporal evolution, while simultaneously providing
uncertainty quantification on all results. Our algorithm views the imaging task
as a Bayesian inference problem of a time-varying flux density, exploits the
correlation structure between time frames, and reconstructs a whole,
$(2+1+1)$-dimensional time-variable and spectral-resolved image at once. We
apply the method to the EHT observation of M87* and validate our approach on
synthetic data. The obtained first time-resolved reconstruction of M87*
indicates varying structures on and outside the emission ring on a time scale
of days.
Observing the dynamics of compact astrophysical objects provides insights
into their inner workings and allows to probe physics under extreme conditions.
The immediate vicinity of an active supermassive black hole with its event
horizon, photon ring, accretion disk, and relativistic jets is a perfect place
to study general relativity, magneto-hydrodynamics, and high energy plasma
physics. The recent observations of the black hole shadow of M87* with Very
Long Baseline Interferometry (VLBI) by the Event Horizon Telescope (EHT) open
the possibility to investigate dynamical processes there on timescales of days.
In this regime, radio astronomical imaging algorithms are brought to their
limits. Compared to regular radio interferometers, VLBI networks have fewer
antennas. The resulting sparser sampling of the Fourier sky can only be partly
compensated by co-adding observations from different days, as the source
changes. Here, we present an imaging algorithm that copes with the data
scarcity and the source’s temporal evolution, while simultaneously providing
uncertainty quantification on all results. Our algorithm views the imaging task
as a Bayesian inference problem of a time-varying flux density, exploits the
correlation structure between time frames, and reconstructs a whole,
$(2+1+1)$-dimensional time-variable and spectral-resolved image at once. We
apply the method to the EHT observation of M87* and validate our approach on
synthetic data. The obtained first time-resolved reconstruction of M87*
indicates varying structures on and outside the emission ring on a time scale
of days.
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