Research on a complete model of cosmological evolution a classical scalar field with a Higgs Potential. I. Model analysis

2021 ◽  
pp. 136-143
Author(s):  
Yu.G. Ignat’ev ◽  
◽  
A.R. Samigullina ◽  
Keyword(s):  
Dynamical System ◽  
Computer Simulation ◽  
Scalar Field ◽  
Cosmological Model ◽  
Hubble Constant ◽  
Cosmological Evolution ◽  
Higgs Potential ◽  
Complete Model ◽  
Global Properties

A study and computer simulation of a complete model of the cosmological evolution of a classical scalar field with a Higgs potential is carried out without the assumption that the Hubble constant is nonnegative. A qualitative analysis of the corresponding dynamical system and a classification of the Einstein - Higgs hmpersurfaces, the topology of which determines the global properties of the phase trajectories of the cosmological model, are carried out.

Research on a complete model of cosmological evolution a classical scalar field with a Higgs potential. II. Numerical simulation

2021 ◽  
pp. 147-151
Author(s):  
Yu.G. Ignat’ev ◽  
◽  
A.R. Samigullina ◽  
Keyword(s):  
Numerical Simulation ◽  
Computer Simulation ◽  
Scalar Field ◽  
Initial Conditions ◽  
Higgs Field ◽  
Hubble Constant ◽  
Cosmological Evolution ◽  
Higgs Potential ◽  
Complete Model ◽  
Expansion Stage

A study and computer simulation of a complete model of the cosmological evolution of a classical scalar field with a Higgs potential is carried out without the assumption that the Hubble constant is nonnegative. It is shown that in most cases of initial conditions the cosmological model passes from the expansion stage to the compression stage. Thus, cosmological models based on the classical Higgs field are unstable with respect to finite perturbations.

scholarly journals SIMPLEST COSMOLOGICAL MODEL WITH THE SCALAR FIELD II.

1998 ◽  
Vol 07 (01) ◽  
pp. 129-138 ◽  
Author(s):  
A. YU. KAMENSHCHIK ◽  
I. M. KHALATNIKOV ◽  
A. V. TOPORENSKY
Keyword(s):  
Phase Space ◽  
Scalar Field ◽  
Cosmological Model ◽  
Qualitative Analysis ◽  
Cosmological Constant ◽  
Numerical Calculations ◽  
Inflaton Field ◽  
Model Combining ◽  
Friedmann Robertson Walker

Continuing the investigation of the simplest cosmological model with the massive real scalar noninteracting inflaton field minimally coupled to gravity, we study an influence of the cosmological constant on the behavior of trajectories in closed minisuperspace Friedmann–Robertson–Walker model. Combining numerical calculations with qualitative analysis both in configuration and phase space we present a convenient classification of trajectories.

scholarly journals Simplest Cosmological Model with the Scalar Field

1997 ◽  
Vol 06 (06) ◽  
pp. 673-691 ◽  
Author(s):  
A. Yu. Kamenshchik ◽  
I. M. Khalatnikov ◽  
A. V. Toporensky
Keyword(s):  
Scalar Field ◽  
Cosmological Model ◽  
Numerical Calculations ◽  
Massless Scalar ◽  
Massless Scalar Field ◽  
Fractal Nature ◽  
Inflaton Field ◽  
Exactly Solvable ◽  
Friedmann Robertson Walker

We investigate the simplest cosmological model with the massive real scalar non-interacting inflaton field minimally coupled to gravity. The classification of trajectories in closed minisuperspace Friedmann–Robertson–Walker model is presented. The possible fractal nature of a set of infinitely bounced trajectories is discussed. The results of numerical calculations are compared with those obtained by perturbative analytical calculations around the exactly solvable minisuperspace cosmological model with massless scalar field.

Decision support or autonomous artificial intelligence? The case of wrong blood in tube errors

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Christopher-John L. Farrell
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Artificial Neural Network ◽  
Computer Simulation ◽  
Clinical Chemistry ◽  
Human Interaction ◽  
Final Decision ◽  
P Values ◽  
Laboratory Staff

Abstract Objectives Artificial intelligence (AI) models are increasingly being developed for clinical chemistry applications, however, it is not understood whether human interaction with the models, which may occur once they are implemented, improves or worsens their performance. This study examined the effect of human supervision on an artificial neural network trained to identify wrong blood in tube (WBIT) errors. Methods De-identified patient data for current and previous (within seven days) electrolytes, urea and creatinine (EUC) results were used in the computer simulation of WBIT errors at a rate of 50%. Laboratory staff volunteers reviewed the AI model’s predictions, and the EUC results on which they were based, before making a final decision regarding the presence or absence of a WBIT error. The performance of this approach was compared to the performance of the AI model operating without human supervision. Results Laboratory staff supervised the classification of 510 sets of EUC results. This workflow identified WBIT errors with an accuracy of 81.2%, sensitivity of 73.7% and specificity of 88.6%. However, the AI model classifying these samples autonomously was superior on all metrics (p-values<0.05), including accuracy (92.5%), sensitivity (90.6%) and specificity (94.5%). Conclusions Human interaction with AI models can significantly alter their performance. For computationally complex tasks such as WBIT error identification, best performance may be achieved by autonomously functioning AI models.

A Single-Node Classifier Implementation on Chua Oscillator within a Physical Reservoir Computing Framework

2021 ◽  
Vol 31 (11) ◽  
pp. 2150161
Author(s):  
Uladzislau Sychou
Keyword(s):  
Computer Simulation ◽  
Control Parameter ◽  
Chaotic Oscillator ◽  
Reservoir Computing ◽  
Single Node ◽  
Short Pulses ◽  
Chaotic Mode ◽  
Computing Framework ◽  
Chua Oscillator

The study lies in the field of physical reservoir computing and aims to develop a classifier using Fisher Iris dataset for benchmark tasks. Single Chua chaotic oscillator acts as a physical reservoir. The study was performed using computer simulation. The features of Iris flowers are represented as the consequence of short pulses at a constant level of a control parameter, which is fed to the oscillator, changing its dynamics. During the classification of flowers, the oscillator works without being reset, so each pulse on the input changes the phase trajectory and makes it unique for each Iris flower. Finally, the estimation of the symmetry of an attractor makes it possible to connect each species of Iris with the properties of the attractor. The resulting architecture of the classifier includes a single-node externally-driven Chua oscillator with time-delayed input. The classifier shows two mistakes in classifying the dataset with 75 samples working in chaotic mode.

scholarly journals Autonomous dynamical system description of de Sitter evolution in scalar assisted f(R) − ϕ gravity

2018 ◽  
Vol 15 (12) ◽  
pp. 1850212 ◽  
Author(s):  
K. Kleidis ◽  
V. K. Oikonomou
Keyword(s):  
Dynamical System ◽  
Numerical Analysis ◽  
Scalar Field ◽  
Analysis Approach ◽  
Single Variable ◽  
De Sitter ◽  
Exponential Potential ◽  
System Description ◽  
Variable Formula ◽  
Autonomous Dynamical System

In this paper we will study the cosmological dynamical system of an [Formula: see text] gravity in the presence of a canonical scalar field [Formula: see text] with an exponential potential by constructing the dynamical system in a way that it is rendered autonomous. This feature is controlled by a single variable [Formula: see text], which when it is constant, the dynamical system is autonomous. We focus on the [Formula: see text] case which, as we demonstrate by using a numerical analysis approach, leads to an unstable de Sitter attractor, which occurs after [Formula: see text] [Formula: see text]-foldings. This instability can be viewed as a graceful exit from inflation, which is inherent to the dynamics of de Sitter attractors.

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