Related papers: Deep learning the holographic black hole with char…
The exponential growth in the number of complex datasets every year requires more enhancement in machine learning methods to provide robust and accurate data classification. Lately, deep learning approaches have achieved surpassing results…
By utilizing the AdS/CFT correspondence, we investigate the holographic image of an AdS black hole in Einstein-power-Yang-Mills gravity. The AdS boundary hosts a Gaussian oscillation source, which induces a lensed response on the opposite…
It is shown that the hidden conformal symmetry, namely $SO(2,2) \sim SL(2,R)_L \times SL(2,R)_R$ symmetry, of the non-extremal dyonic Reissner-Nordstr\"om black hole can be probed by a charged massless scalar field at low frequencies. The…
Recording atomic-resolution transmission electron microscopy (TEM) images is becoming increasingly routine. A new bottleneck is then analyzing this information, which often involves time-consuming manual structural identification. We have…
Using the AdS/CFT correspondence, we probe the extremal black holes by studying the energy loss of a moving heavy point particle in a strongly-coupled boundary field theory at zero temperature and finite charge density. We first consider…
Photons emitted by light sources in the neighbourhood of a black hole can wind several times around it before fleeing towards the observer. For spherically symmetric black holes, two infinite sequences of images are created for any given…
We present a data-driven method for holographic bulk reconstruction that works even when the spacetime is not asymptotically AdS. Given the data of boundary Green functions within a finite frequency window, we iteratively adjust a bulk…
A holographic dual of hadrons at finite density is considered. We use the zero black-hole mass limit of Reisner-Nordstrom (RN) AdS background with hard wall to describe a confining background with finite quark density. We calculate…
The geometry very near the horizon of a near-extreme Reissner-Nordstrom black hole is described by the direct product of a near-$AdS_2$ spacetime with a two-sphere. While near-$AdS_2$ is locally diffeomorphic to $AdS_2$ the two connect…
A conjecture by Hod states that for the black hole horizon the spacing of its area spectrum is determined by the asymptotic value of its quasinormal frequencies. Recently to overcome some difficulties, Maggiore proposes some changes to the…
Machine Learning facilitates building a large variety of models, starting from elementary linear regression models to very complex neural networks. Neural networks are currently limited by the size of data provided and the huge…
We consider a Hamiltonian quantum theory of spherically symmetric, asymptotically flat electrovacuum spacetimes. The physical phase space of such spacetimes is spanned by the mass and the charge parameters $M$ and $Q$ of the…
In this paper, we study inverse scattering of massless Dirac fields that propagate in the exterior region of a Reissner-Nordstr\"om black hole. Using a stationary approach we determine precisely the leading terms of the high-energy…
We compute the spectrum of extremal nonBPS black holes in four dimensions by studying supergravity on their AdS$_2\times S^2$ near horizon geometry. We find that the spectrum exhibits significant simplifications even though supersymmetry is…
The Schwinger effect has a variety of physics applications. In the context of black hole physics, it provides a channel for the decay of charged black holes. While the Schwinger rate has been derived for extremal Reissner-Nordstr\"om (RN)…
Partial Differential Equations (PDEs) are used to model a variety of dynamical systems in science and engineering. Recent advances in deep learning have enabled us to solve them in a higher dimension by addressing the curse of…
Training deep neural networks (DNNs) in large-cluster computing environments is increasingly necessary, as networks grow in size and complexity. Local memory and processing limitations require robust data and model parallelism for crossing…
This paper presents a model based on Deep Learning algorithms of LSTM and GRU for facilitating an anomaly detection in Large Hadron Collider superconducting magnets. We used high resolution data available in Post Mortem database to train a…
The entropy of charged black hole is calculated by using the partition function evaluated at radial geodesics confined under horizons. We establish two quantum phase states inside the black hole and a transition between them.
Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level…