Far-UV Spectral Variability in the Gravitational Lens Candidate UM 425

1996 ◽  
Vol 458 ◽  
pp. 67 ◽  
Author(s):  
A. G. Michalitsianos ◽  
R. J. Oliversen ◽  
S. P. Maran
Keyword(s):  
Gravitational Lens ◽  
Spectral Variability

scholarly journals 1146+111B,C: A Giant Gravitational Lens?

1987 ◽  
Vol 124 ◽  
pp. 755-760 ◽  
Author(s):  
E.L. Turner
Keyword(s):  
Ir Spectra ◽  
Time Delays ◽  
Gravitational Lens ◽  
Spectral Variability ◽  
Positive Evidence ◽  
Spectroscopic Observations ◽  
Uv And Ir Spectra ◽  
Observational Status

The history and current observational status of the giant gravitational lens candidate 1146+111B,C are reviewed. In the absence of any new positive evidence and in the presence of reported differences in the UV and IR spectra of B and C, the lens hypothesis is clearly much weaker than previously. Nevertheless, given the substantial similarity of the spectra over a broad range of wavelengths, discrepancies among various spectroscopic observations of C, and the possibility of spectral variability plus large differential time delays, the data do not yet support any definite conclusion as to the nature of 1146+111B,C.

Seti Space Missions

1997 ◽  
Vol 161 ◽  
pp. 761-776 ◽  
Author(s):  
Claudio Maccone
Keyword(s):  
Electromagnetic Waves ◽  
Space Missions ◽  
Gravitational Lens ◽  
The Sun ◽  
Space Antenna ◽  
Focal Distance ◽  
Large Space ◽  
The Earth ◽  
Space Antennas ◽  
New Space

AbstractSETI from space is currently envisaged in three ways: i) by large space antennas orbiting the Earth that could be used for both VLBI and SETI (VSOP and RadioAstron missions), ii) by a radiotelescope inside the Saha far side Moon crater and an Earth-link antenna on the Mare Smythii near side plain. Such SETIMOON mission would require no astronaut work since a Tether, deployed in Moon orbit until the two antennas landed softly, would also be the cable connecting them. Alternatively, a data relay satellite orbiting the Earth-Moon Lagrangian pointL2would avoid the Earthlink antenna, iii) by a large space antenna put at the foci of the Sun gravitational lens: 1) for electromagnetic waves, the minimal focal distance is 550 Astronomical Units (AU) or 14 times beyond Pluto. One could use the huge radio magnifications of sources aligned to the Sun and spacecraft; 2) for gravitational waves and neutrinos, the focus lies between 22.45 and 29.59 AU (Uranus and Neptune orbits), with a flight time of less than 30 years. Two new space missions, of SETI interest if ET’s use neutrinos for communications, are proposed.

A Spectroscopic Study of the Environments of Gravitational Lens Galaxies

2006 ◽  
Vol 20 ◽  
pp. 289-290
Author(s):  
I. Momcheva ◽  
K. Williams ◽  
C. Keeton ◽  
A. Zabludoff
Keyword(s):  
Spectroscopic Study ◽  
Gravitational Lens ◽  
Lens Galaxies

Simulation of a gravitational lens in a lecture demonstration

1982 ◽  
Vol 138 (9) ◽  
pp. 147 ◽  
Author(s):  
G.S. Egorov ◽  
Nikolai S. Stepanov
Keyword(s):  
Gravitational Lens ◽  
Lecture Demonstration

scholarly journals Rapid spectral variability of a giant flare from a magnetar in NGC 253

Nature ◽  
2021 ◽  
Vol 589 (7841) ◽  
pp. 207-210 ◽  
Author(s):  
O. J. Roberts ◽  
P. Veres ◽  
M. G. Baring ◽  
M. S. Briggs ◽  
C. Kouveliotou ◽  
...  
Keyword(s):  
Spectral Variability ◽  
Giant Flare

Hypersharpening by an NMF-Unmixing-Based Method Addressing Spectral Variability

2021 ◽  
pp. 1-5
Author(s):  
Salah Eddine Brezini ◽  
Moussa Sofiane Karoui ◽  
Fatima Zohra Benhalouche ◽  
Yannick Deville ◽  
Abdelaziz Ouamri
Keyword(s):  
Spectral Variability

scholarly journals Quantifying the structure of strong gravitational lens potentials with uncertainty-aware deep neural networks

2020 ◽  
Vol 499 (4) ◽  
pp. 5641-5652
Author(s):  
Georgios Vernardos ◽  
Grigorios Tsagkatakis ◽  
Yannis Pantazis
Keyword(s):  
Confidence Intervals ◽  
Galaxy Evolution ◽  
Gravitational Lensing ◽  
Probability Distributions ◽  
Mass Density ◽  
Ground Truth ◽  
Gaussian Random Fields ◽  
Training Data ◽  
Gravitational Lens ◽  
Data Set

ABSTRACT Gravitational lensing is a powerful tool for constraining substructure in the mass distribution of galaxies, be it from the presence of dark matter sub-haloes or due to physical mechanisms affecting the baryons throughout galaxy evolution. Such substructure is hard to model and is either ignored by traditional, smooth modelling, approaches, or treated as well-localized massive perturbers. In this work, we propose a deep learning approach to quantify the statistical properties of such perturbations directly from images, where only the extended lensed source features within a mask are considered, without the need of any lens modelling. Our training data consist of mock lensed images assuming perturbing Gaussian Random Fields permeating the smooth overall lens potential, and, for the first time, using images of real galaxies as the lensed source. We employ a novel deep neural network that can handle arbitrary uncertainty intervals associated with the training data set labels as input, provides probability distributions as output, and adopts a composite loss function. The method succeeds not only in accurately estimating the actual parameter values, but also reduces the predicted confidence intervals by 10 per cent in an unsupervised manner, i.e. without having access to the actual ground truth values. Our results are invariant to the inherent degeneracy between mass perturbations in the lens and complex brightness profiles for the source. Hence, we can quantitatively and robustly quantify the smoothness of the mass density of thousands of lenses, including confidence intervals, and provide a consistent ranking for follow-up science.

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