Results 61 to 70 of about 32,361 (211)

Observational Constraints on the Self Interacting Dark Matter Scenario and the Growth of Supermassive Black Holes

open access: yes, 2001
We consider the consequences of SIDM for a velocity dependent cross section per unit mass. Accretion of SIDM onto seed black holes can produce supermassive black holes that are too large for certain combinations of parameters,which is used to obtain a ...
Dalcanton J. J.   +7 more
core   +1 more source

Kretschmann Scalar for a Kerr-Newman Black Hole [PDF]

open access: yes, 1999
I have derived the Kretschmann scalar for a general black hole of mass m, angular momentum per unit mass a, and electric charge Q. The Kretschmann scalar gives the amount of curvature of spacetime, as a function of position near (and within) a black hole.
Henry, Richard C.
core   +3 more sources

Observational Evidence for a Correlation between the Magnetic Field of Jets and Star Formation Rate in Host Galaxies

open access: yesThe Astrophysical Journal
Accretion supermassive black holes in the center of active galaxies usually produce “jet”-collimated bipolar outflows of relativistic particles. Magnetic fields near the black hole event horizon may play a crucial role in the formation of jets/outflows ...
Yongyun Chen   +6 more
doaj   +1 more source

A Unified Model for the Evolution of Galaxies and Quasars [PDF]

open access: yes, 1999
We incorporate a simple scheme for the growth of supermassive black holes into semi-analytic models that follow the formation and evolution of galaxies in a cold dark matter dominated Universe.
G. Kauffmann, M. Haehnelt, Rees
core   +2 more sources

Supermassive black holes in galactic bulges [PDF]

open access: yesMonthly Notices of the Royal Astronomical Society: Letters, 2008
Abstract Growing evidence indicate supermassive black holes (SMBHs) in a mass range of MBH∼ 106–1010 M⊙ lurking in central stellar bulges of galaxies. Extensive observations reveal fairly tight power laws of MBH versus the mean stellar velocity dispersion σ of the host stellar bulge.
Lou, Yu-Qing, Jiang, Yan-Fei
openaire   +2 more sources

Deep Space Network Radio Science and Ground‐Based Planetary Radar in the Next Decade

open access: yesRadio Science, Volume 60, Issue 7, July 2025.
Abstract The Deep Space Network (DSN) has been a core operational element of NASA's crewed and robotic exploration of the Solar System since the early 1960s. The primary role of the DSN has been to acquire telemetry and navigation data, but over the years, its radiometric and radar capabilities have expanded to form a system for obtaining unique ...
R. S. Park   +13 more
wiley   +1 more source

Threshold drop in accretion density if dark energy is accreting onto a supermassive black hole

open access: yesEuropean Physical Journal C: Particles and Fields, 2019
Recent studies of galactic cores tell us that supermassive black holes are hosted at each of these cores. We got some evidences even. Besides, dark energy is expected to be distributed all over in our universe.
Ritabrata Biswas, Sandip Dutta
doaj   +1 more source

Gravitational Wave Bursts from Collisions of Primordial Black Holes in Clusters

open access: yes, 2010
The rate of gravitational wave bursts from the mergers of massive primordial black holes in clusters is calculated. Such clusters of black holes can be formed through phase transitions in the early Universe.
A. Cattaneo   +15 more
core   +1 more source

Binary Black Hole Accretion Flows in Merged Galactic Nuclei [PDF]

open access: yes, 2006
We study the accretion flows from the circumbinary disks onto the supermassive binary black holes in a subparsec scale of the galactic center, using a smoothed particles hydrodynamics (SPH) code.
Hayasaki, Kimitake   +2 more
core   +4 more sources

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

open access: yesAstronomische 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

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