相关论文: Deep learning the holographic black hole with char…

Deep neural networks (DNN) with a huge number of adjustable parameters remain largely black boxes. To shed light on the hidden layers of DNN, we study supervised learning by a DNN of width $N$ and depth $L$ consisting of $NL$ perceptrons…

We use the global embedding Minkowski space (GEMS) geometries of a (3+1)-dimensional curved Reissner-Nordstr\"om(RN)-AdS black hole spacetime into a (5+2)-dimensional flat spacetime to define a proper local temperature, which remains finite…

We explore the gravitational properties of a nonlinear electromagnetic extension of an AdS Reissner-Nordstr\"om black hole. Our study begins with an analysis of the metric function and horizon structure, followed by calculations of the…

The well-known instability of the inner horizon of a Reissner-Nordstr\"om black hole, first suggested by Simpson and Penrose, although studied extensively, has remained illusive so far as several studies led to varied conclusions about the…

We introduce a machine learning model designed to rapidly and accurately predict the time domain gravitational wave emission of non-precessing binary black hole coalescences, incorporating the effects of higher order modes of the multipole…

We study the observation of a thin dust shell, radially freely falling to a Reissner-Nordstrom black hole, by an observer who is also freely and radially falling into this black hole. Considered and resolved are several common paradoxes and…

In this paper, thermodynamic properties of the Reissner-Nordstr\"om-de Sitter (RN-dS) black hole have been studied on the basis of the correlation between the black hole and cosmological horizons. It is found that the RN-dS black hole…

We investigate extremal Reissner-Nordstrom-AdS black holes in four-dimensional N=2 abelian gauged supergravity. We find a new attractor equation which is not reduced to the one in the asymptotically flat spacetime. Focusing on so-called the…

The growing field of nano nuclear magnetic resonance (nano-NMR) seeks to estimate spectra or discriminate between spectra of minuscule amounts of complex molecules. While this field holds great promise, nano-NMR experiments suffer from…

We consider deep inelastic scattering (DIS) on a dense nucleus described as an extremal RN-AdS black hole with holographic quantum fermions in the bulk. We evaluate the 1-loop fermion contribution to the R-current on the charged black hole,…

The Black-Scholes model, defined under the assumption of a perfect financial market, theoretically creates a flawless hedging strategy allowing the trader to evade risks in a portfolio of options. However, the concept of a "perfect…

Hashing methods have been recently found very effective in retrieval of remote sensing (RS) images due to their computational efficiency and fast search speed. The traditional hashing methods in RS usually exploit hand-crafted features to…

The expression of the impact parameter, in the analysis for classical and semiclassical scattering cross sections for black holes, is obtained with nonlinear electrodynamics (NLED) while the absorption section is studied with the sinc…

In this paper, we investigate the strong gravitational lensing effects around the Reissner-Nordstr{\"o}m-like black hole (RN-like BH) in bumblebee gravity. We calculate the lensing quantities such as deflection angle, radius of the photon…

Using deep neural networks for identifying physics objects at the Large Hadron Collider (LHC) has become a powerful alternative approach in recent years. After successful training of deep neural networks, examining the trained networks not…

In this work, we present some applications of random matrix theory for the training of deep neural networks. Recently, random matrix theory (RMT) has been applied to the overfitting problem in deep learning. Specifically, it has been shown…

Artificial Neuronal Networks are models widely used for many scientific tasks. One of the well-known field of application is the approximation of high-dimensional problems via Deep Learning. In the present paper we investigate the Deep…

We study nearly extreme black holes with nearly AdS$_2$ horizon geometry in various settings inspired by string theory. Our focus is on the scales of the nAdS$_2$ region and their relation to microscopic theory. These scales are determined…

We show that the entropy of extremal $D=4$ Reissner--Nordstrom black holes can be computed from horizon CFTs with central charges and conformal weights fixed by the dimensionless Rindler energy. This is possible in the simultaneous extremal…

In this work, we demonstrate that a major limitation of regression using a mean-squared error loss is its sensitivity to the scale of its targets. This makes learning settings consisting of target's whose values take on varying scales…