Narrow Results

We describe and present the first observational evidence that light propagating near a rotating black hole is twisted in phase and carries orbital angular momentum. The novel use of this physical observable as an additional tool for the previously known techniques of gravitational lensing allows us to directly measure, for the first time, the spin parameter of a black hole. With the additional information encoded in the orbital angular momentum, not only can we reveal the actual rotation of the compact object, but we can also use rotating black holes as probes to test general relativity.

The search for grand unification, the understanding and identifying the relations of forces of physics, has been the interest of many particle physicist for many decades. The present paper investigates the validity of a previous paper that proposed two possible equations for both the strong force and the weak force. It investigates the magnitude of these equations for the Hydrogen atom. Also, the coupling constant are determined and compared with known values. Both the forces and coupling constants show good agreement with existing known results. Other elements on the periodic table are used to further evaluate the validity of the equations. It is also shown that the four forces of strong, weak, gravitational and Coulomb converge to the expected energy and corresponding length identified by the Standard model and Super Symmetry models. It is believed that these equations represent the dominate terms in a perturbation series solution. The work is extended to include a strong force pressure with comparison to recent data and single degree of freedom frequency equations for each of the four forces. In addition periodic table numerical results for pressure and frequencies are included.

Strongly Lensed systems, and in particular gravitational arcs, are useful tools for a variety of astrophysical applications. Finding arcs in wide-field surveys such as the Dark Energy Survey (DES) requires automated algorithms to select arc candidates due to the large amount of data. In this contribution we present a new arcfinding method that uses the Mediatrix filamentation method coupled to a neural network to select arc candidates. We carry out a systematic comparison between this method and three other arcfinders available in the literature — Lenzen et al. (2004), Horesh et al. (2005), and More et al. (2012) — on a sample of arc simulated with the PaintArcs method.