A5072079600- Astrophysics and Cosmic Phenomena
- Radio Astronomy Observations and Technology
- Gamma-ray bursts and supernovae
- Galaxies: Formation, Evolution, Phenomena
- Dark Matter and Cosmic Phenomena
- Astrophysical Phenomena and Observations
- Astronomical Observations and Instrumentation
- Medical Imaging Techniques and Applications
- Particle Detector Development and Performance
- Neutrino Physics Research
- Advanced MRI Techniques and Applications
- Advanced X-ray Imaging Techniques
- Law, Economics, and Judicial Systems
- Advanced Measurement and Metrology Techniques
- Advanced Neuroimaging Techniques and Applications
- Corruption and Economic Development
- Advanced Electron Microscopy Techniques and Applications
- Advanced X-ray and CT Imaging
- Cell Image Analysis Techniques
- Astronomy and Astrophysical Research
- MRI in cancer diagnosis
University of Würzburg
2017-2022
Kavli Institute for Particle Astrophysics and Cosmology
2021
SLAC National Accelerator Laboratory
2021
Friedrich-Alexander-Universität Erlangen-Nürnberg
2021
Ames Research Center
2021
ETH Zurich
2021
TU Dortmund University
2021
University of Geneva
2021
RWTH Aachen University
2021
Universitat de Barcelona
2020
Aims . In the framework of multi-wavelength and very long baseline interferometry (VLBI) monitoring program TANAMI (Tracking Active Nuclei with Austral Milliarcsecond Interferometry), we study evolution parsec-scale radio emission in galaxies southern hemisphere their relationship to γ -ray properties sources. Our investigates systematically, for first time, between two energy regimes galaxies. this paper, focus on Fermi -LAT-detected Methods The monitors a large sample radio-loud AGN at 8.4...
With the increased sensitivity and resolution of radio interferometry study collimation acceleration region jets in Active Galactic Nuclei (AGN) has come into focus within last years. Whereas a large fraction AGN reveal change from parabolic to conical around Bondi radius, small number sources deviate this standard picture, including galaxy NGC1052. We jet width profile, which provides valuable information about interplay between central engine accretion disk system zone jets. observed...
Signal artefacts due to Radio Frequency Interference (RFI) are a common nuisance in radio astronomy. Conventionally, the RFI-affected data tagged by an expert analyst order warrant quality. In view of increasing rates obtained with interferometric telescope arrays, automatic filtering procedures mandatory. Here, we present results from implementation RFI-detecting recurrent neural network (RNN) employing long-short term memory (LSTM) cells. For training algorithm, discrete model was used...
Context. Monthly-binned gamma-ray light curves of 236 bright sources, particularly blazars, selected from a sample 2278 high-galactic latitude objects observed with Fermi-LAT, show flux variability characterized by power spectral densities consisting single power-law component, ranging Brownian to white noise. Aims. The main goal here is assess the Ornstein-Uhlenbeck (OU) model studying range its three parameters that reproduces these statistical properties. Methods. We develop procedures...
Our goal is to study the termination of an AGN jet in young universe and deduce physical parameters intergalactic medium. We use LOFAR image long-wavelength radio emission high-redshift blazar S5 0836+710 on arcsecond scales between 120 MHz 160 MHz. The shows a compact unresolved core resolved region about 1.5 arcsec southwest core. This structure general agreement with previous higher-frequency observations MERLIN VLA. southern component moderately steep spectrum spectral index $\gtrsim -1$...
Purpose To evaluate an iterative learning approach for enhanced performance of robust artificial‐neural‐networks k‐space interpolation (RAKI), when only a limited amount training data (auto‐calibration signals [ACS]) are available accelerated standard 2D imaging. Methods In first step, the RAKI model was tailored case amount. (termed [iRAKI]), is initially trained using original and augmented ACS obtained from linear parallel imaging reconstruction. Subsequently, convolution filters refined...
TANAMI is a multiwavelength program monitoring active galactic nuclei (AGN) south of -30deg declination including high-resolution Very Long Baseline Interferometry (VLBI) imaging, radio, optical/UV, X-ray and gamma-ray studies. We have previously published first-epoch 8.4GHz VLBI images the parsec-scale structure initial sample. In this paper, we present 39 additional sources. The full sample comprises most radio- brightest AGN in southern quarter sky, overlapping with region from which...
Despite numerous detections of individual flares, the physical origin rapid variability observed from blazars remains uncertain. Using Bayesian blocks and Eisenstein-Hut HOP algorithm, we characterize flux variations high significance in $\gamma$-ray light curves two samples blazars. Daily binned long-term TeV-bright with First G-APD Cherenkov Telescope (FACT) are compared to those GeV-bright Large Area on board $Fermi$ Gamma-ray Space ($Fermi$-LAT). We find no evidence for systematic...
Following our study of the radio and high-energy properties $\gamma$-ray-emitting galaxies, here we investigate kinematic spectral parsec-scale jets galaxies that have not yet been detected by Fermi-LAT. We take advantage regular VLBI observations provided TANAMI monitoring program, explore six $\gamma$-ray-faint galaxies. include publicly available kinematics $\gamma$-ray-quiet monitored MOJAVE program perform a Fermi-LAT analysis, deriving upper limits. combine these results with those...
There are several methods to calculate the radiative and kinetic power of relativistic jets, but their results can differ by one or two orders magnitude. Therefore, it is necessary perform a calibration jet power, understand reasons for these differences (whether wrong hypotheses intrinsic source variability), if possible converge reliable measurement this physical quantity. We present preliminary project aimed at calibrating jets in active galactic nuclei (AGN) X-ray binaries (XRB). started...
Single-molecule super-resolution microscopy (SMLM) techniques like d STORM can reveal biological structures down to the nanometer scale. The achievable resolution is not only defined by localization precision of individual fluorescent molecules, but also their density, which becomes a limiting factor e.g., in expansion microscopy. Artificial deep neural networks learn reconstruct dense super-resolved such as microtubules from sparse, noisy set data points. This approach requires robust...
This research was funded in part by NASA through Fermi Guest Investigator grants NNH10ZDA001N, NNH12ZDA001N, and NNH13ZDA001N-FERMI (proposal numbers 41213, 61089, 71326, respectively). supported an appointment to the Postdoctoral Program at Goddard Space Flight Center, administered Universities Research Association a contract with NASA. This work performed in part under DOE Contract DE-AC02-76SF00515.
Recently, the Parallel Imaging method GRAPPA has been generalized by deep-learning RAKI, in which Convolutional Neural Networks are used for non-linear k-space interpolation. RAKI uses scan-specific training data, however, due to its increased parameter-space, reconstruction quality may deteriorate given a limited training-data amount. We evaluate an approach that includes augmented via initial reconstruction, and weights refinement iterative training. Thereby, severe residual artefacts...
There are several methods to calculate the radiative and kinetic power of relativistic jets, but their results can differ by one or two orders magnitude. Therefore, it is necessary perform a calibration jet power, understand reasons for these differences (whether wrong hypotheses intrinsic source variability), if possible converge reliable measurement this physical quantity. We present preliminary project aimed at calibrating jets in active galactic nuclei (AGN) X-ray binaries (XRB). started...
Purpose: To evaluate an iterative learning approach for enhanced performance of Robust Artificial-neural-networks K-space Interpolation (RAKI), when only a limited amount training data (auto-calibration signals, ACS) are available accelerated standard 2D imaging. Methods: In first step, the RAKI model was optimized case strongly amount. (termed RAKI), is initially trained using original and augmented ACS obtained from linear parallel imaging reconstruction. Subsequently, convolution filters...