Justification of rotation curves of galaxies without dark matter, based on the new gravitation theory, starting from the ether presence after correcting Michelson’s analysis errors from 1881/87 experiments.Has, Ioan; Miclaus, Simona; Has, Aurelian
doi: 10.1088/1742-6596/3027/1/012018pmid: N/A
Sections 2-6, constitute actualizations of our previous works necessary to identify the electric dipole force FDC that creates the current velocities of bodies in galaxies, replacing the Newtonian gravitational force FN. The new theory of gravitation (NTG16) is part of a new physics theory (NTP16), which emerged from our discovery, of Errors 1 and 2 in Michelson’s analysis, of his interferometer experiment from 1881/1887. By correcting Michelson’s Errors we were able to reintroduce the ether into physics in the form of the model proposed in 2016, HM16. From HM16 now completed, resulted the NTG16, which led to the modification of the calculation method of the current gravitational force FN as Newton’s law, between two masses resulting in a new force of universal attraction, created between the electric dipoles of the masses, FDC, based on completed Coulomb force FCC. According to the NTG16, the new dipoles force FDC, turned out to have higher values by approx. 60% (preliminary) than the gravitational force FN when applied to two masses located at galactic distances. By applying the new force FDC, some changes will also result in the theoretical rotational velocities vr curves of galaxies, and the new curves of the theoretical velocities will correspond better with those of the real velocities of the galaxies measured by astronomers. The ad hoc hypothesis of the existence of dark matter (DM) in the universe, which was introduced by astronomers after 1930, in order to explain the real velocity curves of galaxies, is therefore called into question.
Modified Cubic Transmuted Sujatha Distribution (MCT-SUJATHA)Khudhair, Eftekhar Baqir; Razaq Qasim, Bahaa Abdul
doi: 10.1088/1742-6596/3027/1/012064pmid: N/A
As a result of the tremendous technological development, single and classical probability distributions have become unable to represent apparent data well, which prompted researchers to build new probability models based on these single and classical distributions, which are characterized by being more flexible in modeling and representing data. There are several methods for building probabilistic models, including the modified cubic transmuted methodTherefore, the research aims to propose a new modified cubic transmuted Sujatha distribution (MCT-SUJATHA) as a member belongs to the modified cubic transmuted family (MCT-G FAMILY), using the Sujatha distribution (SD), the probability and cumulative density functions of the distribution are derived, and its structural properties represented by (The Non-Central Moment, The Central Moment, Coefficient of Skewness, Coefficient of Kurtosis, and Coefficient of Variation), in addition to estimating the distribution parameters using the Maximum Likelihood Estimation method (MLE) and the (Cran) method And compare them using simulation.
Particle Modelling: an educational perspectiveÁvila García, G
doi: 10.1088/1742-6596/3027/1/012045pmid: N/A
The high school curriculum in Mexico integrates the contents of particle physics for the training of students in physical-mathematical sciences. However, there are not enough laboratory inputs for experimentation, in this inquiry the ADDIE model is used for the implementation of didactic strategies of the model: mental and conceptual through the modeling of a fog chamber and the use of technology with a Minipix particle detector that works with a semiconductor sensor and reading electronics for data processing. The objective of the study focuses on the design of the ADDIE model for students to understand and interpret the scientific procedure of the phenomenon with the visualization of subatomic particles. The work considered a convenience sample of 60 students with a qualitative approach based on the analysis of the arguments established by the students during the development of the classes. The design of the didactic strategy demonstrates that the use of mental, conceptual and experimental models are incentives for the development of scientific thinking and the understanding of abstract concepts.
Connection between the q-Deformed Quantum Mechanics and the position-dependent mass Schrödinger equationOvando, G.; Peña, J. J.; Morales, J.
doi: 10.1088/1742-6596/3027/1/012022pmid: N/A
The q-deformed quantum mechanics has gained recent interest as an alternative formalism for quantum mechanics. In this work the connection that this formalism has with the position-dependent mass (PDM) quantum problem is stablished. To that, we pay attention to the quantum momentum operators used in both formalisms and as consequence of recognizing their connection, both formalisms can be put in correspondence. We first introduce the PDM formalism as it is required. Next, we revisit the q-deformed quantum mechanics as it is exposed in the framework of q-statistics introduced by C. Tsallis, which allows us to expose important correlations as they are the definitions of the inner product or the connection between the Schrödinger equations for both formalisms. As an application of the resulting correspondence, the explicit solution for the harmonic oscillator case is discussed. Furthermore, the approach will allow to elaborate alternative versions of the q-deformed quantum formalism, so finally, we outline a version based on the G. Kaniadakis’s κ-statistics as well as two new proposals of q-deformed position dependent mass, exponential and hyperbolic.
Theoretical Modeling of the Optical and Electronic Properties of 3,3′-Di(9H-carbazol-9-yl)-1,1′-biphenyl (mCBP)Aldaghri, Osamah
doi: 10.1088/1742-6596/3027/1/012062pmid: N/A
The 3,3′-Di(9H-carbazol-9-yl)-1,1′-biphenyl (mCBP) is a bipolar host material that has gained significant attention in the OLED research community due to its favorable properties such as high mobility energy level and thermal stability. This study utilizes Density Functional Theory (DFT) to examine the optical and electrical characteristics of mCBP. The optimal structure, total density of states, dipole moment, and hyperpolarizability of the host material were analyzed. The HOMO-LUMO energy of the mCBP molecules in two distinct solvents was obtained, and the theoretical absorption spectra was computed using TD-DFT theory.
Regularly alternating fractional up/down quark charges model the nuclear fusion potential and Coulomb barrierWalsh, Ray
doi: 10.1088/1742-6596/3027/1/012007pmid: N/A
The nucleus contains protons and neutrons, each combining three fractionally-charged +2/3e up and −1/3e down quarks. Fusion occurs when small nuclei collide with sufficient kinetic energy to overcome the repulsive Coulomb barrier, at which point the strong nuclear force binds the nuclei together. Fusion is thus understood as an interplay between two fundamental forces, the electrostatic at far range and the strong nuclear force at close range. Here, we mathematically model the entire fusion potential curve based solely on the geometry of electrostatic interactions and without recruiting the strong nuclear force. The deuteron is modelled as a linear sequence of six alternating, equally-spaced quark charges. The linear geometry derives from the accepted prolate spheroid shape of the nucleon, wherein spin-spin forces repel like-flavored quarks to opposite positions (qualitatively) within the cigar-shaped nucleon, leaving the unlike-flavored quark in the center. The Argonne v18 nucleon-nucleon potential (≈the proton's radius) accounts for the nucleon-nucleon separation. The Coulomb barrier height is quantified from the electrostatic potentials between the quarks on one deuteron with the quarks on the other as the nuclei approach at incremental distances. The net positive charge on each deuteron results in far-range repulsion. Within ≈1 fm, however, close-range attraction results from regularly alternating/unequal charge geometry as the +2/3e charges on one deuteron align with the −1/3e charges on the other. The model-predicted Coulomb barrier height Vc=0.57 MeV approximates the textbook calculation Vc=0.34 MeV (which assumes a spherical nucleus). This compares with a proton-deuteron barrier prediction Vc=0.88 MeV (0.48 MeV textbook). A negligible neutron-deuteron barrier prediction Vc=0.00946 MeV is consistent with the empirical knowledge of neutron fusion (i.e., strong close-range attraction, but Vc=0). The model may prove helpful in parameterizing nuclear fusion, indicating a 46% difference in Coulomb barrier height depending on deuteron orientation (axial versus antiparallel) at the time of collision/fusion.
Leveraging Continuous-Time Echo State Networks to Accelerate Computing Nonlinear Stiff Dynamics through Parareal in Time SimulationHamdan, Juman; Riahi, Mohamed Kamel
doi: 10.1088/1742-6596/3027/1/012036pmid: N/A
In this paper, we address the challenge of solving nonlinear stiff ordinary differential equations by integrating Continuous-Time Echo State Networks with the Parareal method. Nonlinear stiff systems present significant difficulties due to the presence of rapid and slow dynamics, leading to complex behaviors and numerical instabilities. The Parareal method, while effective for parallel processing of time-dependent problems, often struggles with high discrepancies in approximation for nonlinear stiff parametrized ODEs due to low-high order numerical schemes. Stiff problems require error control, hence adaptive time stepping, complicating task balancing within the classical Parareal framework. By leveraging CTESNs as initial predictors that approximate solutions in a lower-dimensional vector space, we enhance the convergence rate and accuracy of the classical Parareal method. Preliminary experimental results demonstrate that our integrated approach significantly reduces computational time while maintaining high accuracy in solving nonlinear stiff ODEs. This integration not only addresses the limitations of the Parareal method in handling stiff systems but also offers a robust framework for solving complex dynamical systems, highlighting the potential of hybrid computational approaches in advancing numerical simulations and predictive modeling.
Guidelines to design the architecture of Artificial Neural Networks for application in physical chemistryLecca, Paola
doi: 10.1088/1742-6596/3027/1/012032pmid: N/A
Physical chemistry relies on physical and chemical principles, such as the conservation of mass, momentum, and energy, that are described in the mathematical structure of differential equations, whose solution simulates the behaviour of chemical processes. From a computational perspective, such differential equations present some challenges for both reaching the required level of calculation accuracy and the numerical techniques utilised to approximate them, especially in presence of stiffness and/or non-linearities.The use of deep neural network to handle these problems is gaining popularity especially in the industrial applications of physical chemistry such as processes modelling and control of chemical reactions. The paper focuses on popular systems of differential equation in chemical kinetics and, through some examples, offers guidelines for choosing a suitable artificial neural network architecture and training strategy (i.e. numbers of layers, number of neurons, activation function, and number of epochs). Indeed, the paper shows how the choice of neural network architecture for chemical engineering process modelling depends on various factors, including primarily the nature of the process under consideration, the quantity and kind of input and output variables, and, finally, the unique features of the physico-chemical process. The experiments carried out in this study were performed on a notebook MacBook Pro (Monterey 12.7.5), with a Dual-Core Intel Core i5 processor of 2.7 GHz with 1 processor, and 2 cores, just to give the reader an idea of what a user who does not have computers dedicated to artificial intelligence techniques can do.
Algorithms for increasing the efficiency of information processing in continuous channelsJumaev, O A; Ismoilov, M T; Pulatov, V B; Turaboev, Sh R
doi: 10.1088/1742-6596/3027/1/012034pmid: N/A
The article analyses discrete information transmission channels based on a structural model. Key properties of discrete information channels are considered, including coding, modulation, decoding, and demodulation. A discrete transmission channel covers a variety of methods and devices designed to transmit discrete data from a sender to a recipient. The article also presents graphs of functional dependencies between the input and output data of a discrete system interface, both in the absence of interference and in its presence. The presented calculations and analysis of the channel capacity, as well as the optimization of information transmission settings, confirmed by graphs and analytical expressions, are the most important elements in the design of reliable communication systems. These calculations allow us to identify the optimal channel operating parameters, ensuring high data transmission efficiency.