Publications

First Author Publications on Quantum Theory and its Applications

In this work, we improved the capability of reconstructing the radial distribution function (RDF) of amorphous solids based on wavelet transformation by incorporating machine learning. In this approach, we trained the parameters within the wavelet reconstruction theory using machine learning techniques. As a result, the RDF amplitude and overall trends became increasingly precise. The first and second peaks of the RDF profile, which correspond to the nearest-neighbor interatomic distances, were also determined with greater accuracy. This enhancement enables the derivation and reconstruction of other physical variables, such as the coordination number. 

In this study, we consider the case of a non-relativistic quantum particle confined to the surface of a cylinder of radius Ro and length L, subjected to a Stark-like perturbation along the z-axis. This system serves as a representative model for the extra-dimensional theory proposed by Kaluza–Klein, which aims to unify electromagnetic theory with gravity. The analysis focuses on whether the Stark-like perturbation along the z-axis can induce energy splitting, and how the curvature geometry of the cylinder influences this splitting. The objective is to provide insight into whether it may be possible to detect extra dimensions through such perturbations, and whether a split mass spectrum could emerge within the framework of KK theory.

We investigated the validity of a new theoretical formulation for reconstructing the radial distribution function of amorphous solids based on wavelet transformation (D. Senjaya, A. Supardi, and A. Zaidan, 2020), using classical density functional theory with Born–Meyer type interatomic potentials (appropriate for short-range interactions). In this study, the comparison between our formulation and classical density functional theory with Born–Meyer potentials shows consistency across both the repulsive and attractive coefficients. This demonstrates that our model is theoretically valid.

We (Senjaya–Zaidan–Adri) have developed a new theoretical formulation to reconstruct the radial distribution function profile of amorphous solids based on wavelet transformation. The wavelet transform serves as a mathematical microscope, allowing us to analyze the scattering function profile of X-ray radiation by the corresponding amorphous material, using wavelet functions that can be designed according to our needs. In this work, we design such wavelet functions based on the general theory of wavelets and employ a mean-field quantum mechanical model similar to the Kohn–Sham framework. The wavelet function derived from this mean-field model consists of two components: the known part, obtained from the Schrödinger equation with a simple potential well, and the unknown part, derived from a semi-empirical model to correct interatomic interactions.  

In this thesis, we attempt to design an auxiliary potential that can be used to accelerate the adiabatic dynamics of massless Dirac fermions in a one-dimensional Dirac–Weyl semimetal (with graphene nanoribbons as an example) containing a single impurity, by employing the fast-forward (1+1) theory, with the aim of enhancing its electrical conductance. The results show that, through the fast-forward (1+1) framework, electrical conductance can be slightly improved during the manipulation process with the addition of the auxiliary potential. 

This work marks the initial development of a theoretical method for determining the radial distribution function (RDF) of amorphous solids based on wavelet transformation. In this thesis, the Paul wavelet of order two, a previously established function, was employed. The Paul wavelet was applied to the structure factor data of amorphous Ge–Te systems, namely (GeTe4)5In95 and (GeTe5). The results show that the Paul wavelet could only predict the first and second peaks of the RDF profile of (GeTe4)5In95, with deviations of 0.40 Å and 0.70 Å compared to AIMD SIESTA results, respectively. For (GeTe5), the deviations were 0.68 Å and 1.02 Å. These findings indicate that the Paul wavelet method was still limited in predictive accuracy. Nevertheless, this study represents the first attempt to employ wavelet transformation in determining the RDF of amorphous solids. In 2017, the author designed a new wavelet function involving a mean-field model inspired by the Kohn–Sham scenario in DFT, which achieved higher accuracy and was published in 2020. Further validation of the theoretical development using classical DFT was carried out and published in 2023.

First Author Publications on Theoretical Physics Methods for Robotics

In this study, we examine a planar robot manipulator with two degrees of freedom, where each joint is subjected to identical Stokes-type friction. The equations of motion of the robot are derived using Lagrangian mechanics, and stability analysis is performed through the Jacobian method and eigenvalue evaluation in the case of slow motion. The results yield the appropriate torque criteria required for stable motion. Furthermore, under the conditions of slow motion and identical friction, stability is shown to be independent of the friction coefficient. 

First Author Publications on Theoretical and Computational Astrophysics

Co-author publications