Related papers: Artificial Neural Network in Cosmic Landscape
We propose a method to extract predictions from quantum cosmology for inflation that can be confronted with observations. Employing the tunneling boundary condition in quantum geometrodynamics, we derive a probability distribution for the…
In this paper, the solution of the problem of identification of thermal properties of investigated multi-layer structure is presented. In order of that, artificial neural network was used to find the set of thermal properties for which the…
Generic models of cosmological inflation and the recently proposed scenarios of a recycling universe and the string theory landscape predict spacetimes whose global geometry is a stochastic, self-similar fractal. To visualize the…
This article provides an introductory review of inflation and cosmological perturbation theory. I begin by motivating the need for an epoch of inflation during the early stages of the radiation dominated era, and describe how inflation is…
The fields of neural computation and artificial neural networks have developed much in the last decades. Most of the works in these fields focus on implementing and/or learning discrete functions or behavior. However, technical, physical,…
We approach the cosmological inflation thought symmetries of differential equations. We consider the general inflaton field in a homogeneous Friedmann--Lema\^{\i}tre--Robertson--Walker spacetime and with the use of conformal transformations…
The inflationary scenario has become the paradigm of early universe cosmology, and - in conjuction with ideas from superstring theory - has led to speculations about an "inflationary multiverse". From a point of view of phenomenology, the…
In the past decade, the importance of dissipation and fluctuation to inflationary dynamics has been realized and has led to a new picture of inflation called warm inflation. Although these phenomena are common to condensed matter systems,…
The Universe is currently in a phase of accelerated expansion, a fact that was experimentally proven in the late 1990s. Cosmological models involving scalar fields allow the description of this accelerated expansion regime in the Cosmos and…
Machine learning, and eventually true artificial intelligence techniques, are extremely important advancements in astrophysics and astronomy. We explore the application of deep learning using neural networks in order to automate the…
Object detection in aerial images is an important task in environmental, economic, and infrastructure-related tasks. One of the most prominent applications is the detection of vehicles, for which deep learning approaches are increasingly…
Inflationary cosmology provides a natural mechanism for the generation of primordial perturbations which seed the formation of observed cosmic structure and lead to specific signals of anisotropy in the cosmic microwave background…
We obtain a new class of exact cosmological solutions for multi-scalar fields with exponential potentials. We generalize the assisted inflation solutions previously obtained, and demonstrate how they are modified when there exist…
We investigate cosmology with complex scalar field. It is shown that such models can describe two stages of inflation and the oscillatory regime. Thus we don't need both quintessence and $\Lambda$-term. It is enough to have single complex…
Multilayer perceptron is the most common used class of feed-forward artificial neural network. It contains many applications in diverse fields such as speech recognition, image recognition, and machine translation software. To cater for the…
Artificial neural networks are simple and efficient machine learning tools. Defined originally in the traditional setting of simple vector data, neural network models have evolved to address more and more difficulties of complex real world…
Deep convolutional neural networks have been a popular tool for image generation and restoration. The performance of these networks is related to the capability of learning realistic features from a large dataset. In this work, we applied…
Observations of the cosmic microwave sky are revealing the primordial non-uniformities from which all structure in the Universe grew. The only known physical mechanism for generating the inhomogeneities we see involves the amplification of…
The current status of early universe cosmology can be summarized as precision, but inherently limited, data requiring explanation from precision and robust theory. Specifically inflation is presently the single concrete hope for solving the…
Many machine learning methods operate by inverting a neural network at inference time, which has become a popular technique for solving inverse problems in computer vision, robotics, and graphics. However, these methods often involve…