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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