Related papers: Electrostatics in semiconducting devices I : The P…
In this work we study a charged particle in the presence of both a continuous distribution of disclinations and a continuous distribution of edge dislocations in the framework of the geometrical theory of defects. We obtain the self-energy…
The nanoscale charge environment critically influences semiconductor physics and device performance. While conventional bulk characterization techniques provide volume-averaged defect properties, they lack the spatial resolution to resolve…
We have calculated the exchange, correlation, and total electronic energy of a realistic InAs self-assembled quantum dot embedded in a GaAs matrix as a function of the number of electrons in the dot. The many-body interactions have been…
An insight into bispinor analysis makes it possible to describe the electron in selfaction as a fundamental steady state. The electromagnetic theory, and the Dirac equation for the study of an electron in presence of external potentials,…
Motivated by a number of recent experimental studies we have revisited the problem of the microscopic calculation of the quasiparticle self-energy and many-body effective mass enhancement in a two-dimensional electron liquid. Our systematic…
Principal component analysis (PCA) is a widely used dimension reduction technique in machine learning and multivariate statistics. To improve the interpretability of PCA, various approaches to obtain sparse principal direction loadings have…
In the present work we undertake a re-examination of effective mass theory (EMT) for a semiconductor quantum dot. We take into account the fact that the effective mass ($m_i$) of the carrier inside the dot of radius R is distinct from the…
The binding of clusters of metal nanoparticles is partly electrostatic. We address difficulties in calculating the electrostatic energy when high charging energies limit the total charge to a single quantum, entailing unequal potentials on…
We introduce a new statistical and variational approach to the phase estimation algorithm (PEA). Unlike the traditional and iterative PEAs which return only an eigenphase estimate, the proposed method can determine any unknown…
Principal components analysis (PCA) is a widely used dimension reduction technique with an extensive range of applications. In this paper, an online distributed algorithm is proposed for recovering the principal eigenspaces. We further…
The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is…
Power dissipation is known as the most notable limiting factor in all nano-electronic design techniques including Quantum-dot Cellular Automata (QCA). The familiar reversible computing approach is used as a reasonably reliable solution,…
Principal Component Analysis (PCA) is a method for estimating a subspace given noisy samples. It is useful in a variety of problems ranging from dimensionality reduction to anomaly detection and the visualization of high dimensional data.…
A general framework for principal component analysis (PCA) in the presence of heteroskedastic noise is introduced. We propose an algorithm called HeteroPCA, which involves iteratively imputing the diagonal entries of the sample covariance…
An independent control of the flux and energy of ions impacting on an object immersed in a plasma is often desirable for many industrial processes such as microelectronics manufacturing. We demonstrate that a simultaneous control of these…
Electrostatic interactions make a large contribution to solvation free energy in ionic fluids such as electrolytes and colloidal dispersions. The electrostatic contribution to solvation free energy has been ascribed to the self-energy of a…
A crucial factor determining charge transport in organic semiconductors is the electronic coupling between the molecular constituents, which is heavily influenced by the relative arrangement of the molecules. This renders quinacridone, with…
A common way to analyze electrostatic microelectromechanical systems (MEMS) actuators is to use their energy-displacement landscape. Here, we describe an alternative approach to analyze electrostatic MEMS actuators using their energy-charge…
In this paper the nonperturbative analysis of the spectrum for one-particle excitations of the electron-positron field (EPF) is considered in the paper. A standard form of the quantum electrodynamics (QED) is used but the charge of the…
System energy models are important for energy optimization and management in mobile systems. However, existing system energy models are built in lab with the help from a second computer. Not only are they labor-intensive; but also they will…