Results 81 to 90 of about 132,127 (279)

Tidal disruption flares from stars on eccentric orbits

EPJ Web of Conferences, 2012
We study tidal disruption and subsequent mass fallback for stars approaching supermassive black holes on bound orbits, by performing three dimensional Smoothed Particle Hydrodynamics simulations with a pseudo-Newtonian potential.
Loeb A., Stone N., Hayasaki K.
doaj   +1 more source

The persistent shadow of the supermassive black hole of M 87

Astronomy & Astrophysics
In April 2019, the Event Horizon Telescope (EHT) Collaboration reported the first-ever event-horizon-scale images of a black hole, resolving the central compact radio source in the giant elliptical galaxy M 87. These images reveal a ring with a southerly
K. Akiyama, A. Alberdi, W. Alef, J. Algaba, R. Anantua, K. Asada, R. Azulay, U. Bach, A. Baczko, D. Ball, M. Baloković, B. Bandyopadhyay, J. Barrett, M. Bauböck, B. Benson, D. Bintley, L. Blackburn, R. Blundell, K. Bouman, G. Bower, H. Boyce, M. Bremer, R. Brissenden, S. Britzen, A. Broderick, D. Broguiere, T. Bronzwaer, S. Bustamante, J. Carlstrom, A. Chael, Chi-kwan Chan, Dominic O. Chang, K. Chatterjee, S. Chatterjee, Ming-Tang Chen, Yongjun Chen, Xiaopeng Cheng, I. Cho, P. Christian, N. S. Conroy, J. Conway, T. Crawford, G. Crew, A. Cruz-Osorio, Yuzhu Cui, R. Dahale, J. Davelaar, M. De Laurentis, R. Deane, J. Dempsey, G. Desvignes, J. Dexter, Vedant Dhruv, I. K. Dihingia, S. Doeleman, S. Dzib, R. Eatough, R. Emami, H. Falcke, J. Farah, V. Fish, E. Fomalont, H. Ford, M. Foschi, R. Fraga-Encinas, W. Freeman, P. Friberg, C. Fromm, A. Fuentes, P. Galison, C. Gammie, Roberto García, O. Gentaz, B. Georgiev, C. Goddi, R. Gold, A. I. Gómez-Ruiz, J. Gómez, Minfeng Gu, M. Gurwell, K. Hada, D. Haggard, R. Hesper, D. Heumann, L. C. Ho, P. Ho, M. Honma, Chih-Wei L. Huang, Lei Huang, David H. Hughes, Shiro Ikeda, C. M. Violette Impellizzeri, Makoto Inoue, S. Issaoun, D. J. James, B. Jannuzi, M. Janssen, B. Jeter, Wu Jiang, A. Jiménez-Rosales, Michael D. Johnson, S. Jorstad, A. C. Jones, A. Joshi, T. Jung, R. Karuppusamy, T. Kawashima, G. Keating, M. Kettenis, Dong-Jin Kim, Jae-Young Kim, Jongsoo Kim, Junhan Kim, M. Kino, J. Koay, Prashant Kocherlakota, Y. Kofuji, P. M. Koch, S. Koyama, C. Kramer, J. Kramer, M. Kramer, T. Krichbaum, C. Kuo, N. La Bella, Sang-Sung Lee, A. Levis, Zhiyuan Li, R. Lico, Greg Lindahl, M. Lindqvist, M. Lisakov, Jun Liu, Kuo Liu, E. Liuzzo, Wen-Ping Lo, A. Lobanov, L. Loinard, C. Lonsdale, A. Lowitz, Ruohan Lu, N. MacDonald, J. Mao, N. Marchili, S. Markoff, D. Marrone, A. Marscher, I. Martí-Vidal, S. Matsushita, L. Matthews, L. Medeiros, K. Menten, I. Mizuno, Y. Mizuno, J. Montgomery, J. M. Moran, K. Moriyama, M. Mościbrodzka, W. Mulaudzi, C. Müller, H. Müller, A. Mus, G. Musoke, I. Myserlis, H. Nagai, N. Nagar, M. Nakamura, G. Narayanan, I. Natarajan, A. Nathanail, S. N. Fuentes, J. Neilsen, C. Ni, M. Nowak, J. Oh, H. Okino, H. Olivares, T. Oyama, F. Özel, D. Palumbo, G. Paraschos, Jongho Park, H. Parsons, N. Patel, U. Pen, D. Pesce, V. Piétu, A. PopStefanija, O. Porth, B. Prather, D. Psaltis, Hung-Yi Pu, V. Ramakrishnan, R. Rao, M. Rawlings, A. Raymond, L. Rezzolla, Angelo Ricarte, B. Ripperda, F. Roelofs, C. Romero-Cañizales, E. Ros, A. Roshanineshat, H. Rottmann, A. Roy, I. Ruiz, C. Ruszczyk, K. Rygl, S. Sánchez, D. Sánchez-Argüelles, M. Sánchez-Portal, M. Sasada, K. Satapathy, T. Savolainen, F. Schloerb, J. Schonfeld, K. Schuster, Lijing Shao, Z. Shen, D. Small, B. Sohn, J. SooHoo, L. Salas, K. Souccar, J. S. Stanway, He Sun, F. Tazaki, A. Tetarenko, P. Tiede, R. Tilanus, M. Titus, K. Toma, P. Torne, T. Toscano, E. Traianou, T. Trent, S. Trippe, M. Turk, I. van Bemmel, H. V. van Langevelde, D. V. van Rossum, J. Vos, J. Wagner, D. Ward-Thompson, J. Wardle, J. Washington, J. Weintroub, R. Wharton, M. Wielgus, K. Wiik, G. Witzel, M. Wondrak, G. Wong, Qingwen Wu, N. Yadlapalli, P. Yamaguchi, A. Yfantis, D. Yoon, A. Young, Z. Younsi, Wei Yu, F. Yuan, Ye-Fei Yuan, J. Anton Zensus, Shuo Zhang, Guangyao Zhao, Shan-Shan Zhao, Alexander Allardi, Shu-Hao Chang, Chih-Cheng Chang, Song-Chu Chang, Chung-Chen Chen, R. Chilson, A. Faber, David M. Gale, C. Han, Kuo-Chang Han, Y. Hasegawa, J. L. Hernandez-Rebollar, Yau-De Huang, Homin Jiang, Jinchi Hao, K. Kimura, D. Kubo, Chao-Te Li, L. Lin, C. Liu, Kuan-Yu Liu, Li‐Ming Lu, P. Martin-Cocher, Z. Meyer-Zhao, A. Montaña, A. Moraghan, Marcos Emir Moreno-Nolasco, H. Nishioka, T. Norton, G. Nystrom, Hideo Ogawa, P. Oshiro, N. Pradel, G. Principe, P. Raffin, I. Rodríguez-Montoya, P. Shaw, William Snow, Sridharan T. K., R. Srinivasan, T. Wei, Chen-Yu Yu   +308 more
semanticscholar   +1 more source

Suppressing star formation in quiescent galaxies with supermassive black hole winds [PDF]

Nature, 2016
Quiescent galaxies with little or no ongoing star formation dominate the population of galaxies with masses above 2 × 1010 times that of the Sun; the number of quiescent galaxies has increased by a factor of about 25 over the past ten billion years (refs
Edmond Cheung, K. Bundy, M. Cappellari, S. Peirani, S. Peirani, W. Rujopakarn, W. Rujopakarn, K. Westfall, R. Yan, M. Bershady, J. Greene, T. Heckman, N. Drory, D. Law, K. Masters, D. Thomas, D. Wake, D. Wake, A. Weijmans, K. Rubin, F. Belfiore, B. Vulcani, Yan Chen, Kai Zhang, J. Gelfand, J. Gelfand, D. Bizyaev, D. Bizyaev, A. Roman-Lopes, D. Schneider   +29 more
semanticscholar   +1 more source

Signatures of primordial black holes as seeds of supermassive black holes [PDF]

Journal of Cosmology and Astroparticle Physics, 2018
It is broadly accepted that Supermassive Black Holes (SMBHs) are located in the centers of most massive galaxies, although there is still no convincing scenario for the origin of their massive seeds. It has been suggested that primordial black holes (PBHs) of masses $\gtrsim 10^{2} M_\odot$ may provide such seeds, which would grow to become SMBHs.
Licia Verde, Alvise Raccanelli, Joseph Silk, Joseph Silk, Joseph Silk, José Luis Bernal   +5 more
openaire   +5 more sources

On the High-Energy Neutrino Emission from Active Galactic Nuclei

Universe, 2018
We review observational aspects of the active galactic nuclei and their jets in connection with the detection of high-energy neutrinos by the Antarctic IceCube Neutrino Observatory.
Emma Kun, Peter L. Biermann, Silke Britzen, László Á. Gergely   +3 more
doaj   +1 more source

A Population of Short-Period Variable Quasars from PTF as Supermassive Black Hole Binary Candidates [PDF]

, 2016
Supermassive black hole binaries (SMBHBs) at sub-parsec separations should be common in galactic nuclei, as a result of frequent galaxy mergers. Hydrodynamical simulations of circum-binary discs predict strong periodic modulation of the mass accretion ...
M. Charisi, I. Bartos, Z. Haiman, A. Price-Whelan, M. Graham, E. Bellm, R. Laher, S. Márka   +7 more
semanticscholar   +1 more source

A DISPLACED SUPERMASSIVE BLACK HOLE IN M87 [PDF]

The Astrophysical Journal, 2010
ApJ Letters ...
David J. Axon, David J. Axon, Eric S. Perlman, Andrew Robinson, Dan Batcheldor, David Merritt   +5 more
openaire   +3 more sources

Modeling Polarized Emission from Black Hole Jets: Application to M87 Core Jet

Galaxies, 2017
We combine three-dimensional general-relativistic numerical models of hot, magnetized Advection Dominated Accretion Flows around a supermassive black hole and the corresponding outflows from them with a general relativistic polarized radiative transfer ...
Monika Mościbrodzka
doaj   +1 more source

Evolution of Supermassive Black Holes [PDF]

, 2007
Supermassive black holes (SMBHs) are nowadays believed to reside in most local galaxies, and the available data show an empirical correlation between bulge luminosity - or stellar velocity dispersion - and black hole mass, suggesting a single mechanism for assembling black holes and forming spheroids in galaxy halos. The evidence is therefore in favour
openaire   +3 more sources

Redshift‐Agnostic Machine Learning Classification: Unveiling Peak Performance in Galaxy, Star, and Quasar Classification (Using SDSS DR17)

Astronomische Nachrichten, Volume 346, Issue 5, June 2025.
ABSTRACT Classification of galaxies, stars, and quasars using spectral data is fundamental to astronomy, but often relies heavily on redshift. This study evaluates the performance of 10 machine learning algorithms on SDSS data to classify these objects, with a particular focus on scenarios where redshift information is unavailable.
Debashis Chatterjee, Prithwish Ghosh
wiley   +1 more source