Wigner-Moyal description of free variable mass Klein-Gordon fields

We establish sharp (or ’refined’) comparison theorems for the Klein–Gordon equation. We show that the condition [Formula: see text], which leads to [Formula: see text], can be replaced by the weaker assumption [Formula: see text] which still implies the spectral ordering [Formula: see text]. In the simplest case, for [Formula: see text], [Formula: see text], [Formula: see text] or [Formula: see text] and for [Formula: see text], [Formula: see text], [Formula: see text] or [Formula: see text]. We also consider sharp comparison theorems in the presence of a scalar potential [Formula: see text] (a ‘variable mass’) in addition to the vector term [Formula: see text] (the time component of a four-vector). The theorems are illustrated by a variety of explicit detailed examples.

Download Full-text

Mass Determination by Direct Measurement of Electron Scattering

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100114827 ◽

1975 ◽

Vol 33 ◽

pp. 240-241

Author(s):

M. K. Lamvik ◽

A. V. Crewe

Keyword(s):

Cross Section ◽

Electron Scattering ◽

Mass Density ◽

Variable Mass ◽

Scattering Cross Section ◽

Mass Determination ◽

Number Density ◽

Cross Sectional ◽

Thin Slice ◽

Scattering Cross

If a molecule or atom of material has molecular weight A, the number density of such units is given by n=Nρ/A, where N is Avogadro's number and ρ is the mass density of the material. The amount of scattering from each unit can be written by assigning an imaginary cross-sectional area σ to each unit. If the current I0 is incident on a thin slice of material of thickness z and the current I remains unscattered, then the scattering cross-section σ is defined by I=IOnσz. For a specimen that is not thin, the definition must be applied to each imaginary thin slice and the result I/I0 =exp(-nσz) is obtained by integrating over the whole thickness. It is useful to separate the variable mass-thickness w=ρz from the other factors to yield I/I0 =exp(-sw), where s=Nσ/A is the scattering cross-section per unit mass.

Download Full-text

Solutions of the Coupled Klein-Gordon Equation by Modified Exp-Function Method

Indian Journal Of Applied Research ◽

10.15373/2249555x/mar2013/90 ◽

2011 ◽

Vol 3 (3) ◽

pp. 276-278

Author(s):

Ram Dayal Pankaj ◽

◽

Arun Kumar

Keyword(s):

Function Method ◽

Gordon Equation ◽

Klein Gordon ◽

Klein Gordon Equation

Download Full-text

Global regularity for Einstein-Klein Gordon system with $U(1) \times \mathbb{R}$ isometry group

The Role of Metrics in the Theory of Partial Differential Equations ◽

10.2969/aspm/08510533 ◽

2020 ◽

Author(s):

Haoyang Chen ◽

Yi Zhou

Keyword(s):

Isometry Group ◽

Global Regularity ◽

Klein Gordon

Download Full-text

ANALISA PENGARUH IKLIM ORGANISASI DAN KOMPETENSI TERHADAP KINERJA PEGAWAI PT HUTAMA KARYA

Jurnal Manajemen Bisnis Krisnadwipayana ◽

10.35137/jmbk.v5i1.82 ◽

2018 ◽

Vol 5 (1) ◽

Author(s):

Erik Wardhana, MM.

Keyword(s):

Organizational Climate ◽

Employee Performance ◽

Sampling Technique ◽

Simple Random Sampling ◽

Free Variable ◽

Independent Variables ◽

Dependent Variables ◽

Correlational Approach ◽

Survey Research Methods ◽

The Relationship

This study entitled "Analysis of Effect of Climate Organization and Competence Againt Employee PT. Hutama Karya ". The purpose of this study was to obtain information on the relationship between the free variable that organizational climate (X1) and competence (X2) with the dependent variable is employee performance (Y), either partially or simultaneously, This study used survey research methods with the correlational approach and predictive, which aims for the relationship and influence between independent and dependent variables. The sampling technique can be done randomly (simple random sampling) of 852 employees, which is considered to resprentatif is 89 people. And to solve problems, to analyze and examine the relationship and influence between the independent variables on the dependent variable used models kausalistik through regression analysis with SPSS 14.0

Download Full-text