Regge-Pole Fit to the Serpukhovπ−pTotal Cross-Section Data

1970 ◽  
Vol 1 (11) ◽  
pp. 3185-3187
Author(s):  
William Rarita
Keyword(s):  
Cross Section ◽  
Regge Pole ◽  
Cross Section Data ◽  
Section Data

Regge Pole Plus Background Model of Backward πp Scattering

1974 ◽  
Vol 52 (13) ◽  
pp. 1155-1159
Author(s):  
S. Kogitz ◽  
R. K. Logan
Keyword(s):  
Differential Cross Section ◽  
Cross Section ◽  
Charge Exchange ◽  
Differential Cross ◽  
Regge Pole ◽  
Background Model ◽  
Cross Section Data ◽  
Section Data ◽  
The Cross ◽  
Exchange Scattering

We present a model of backward π+p, π−p, and π−p charge exchange scattering consistent with our earlier approach to forward π−p charge exchange and backward π+p. We consider two body differential cross section data which exhibits a dip–bump structure as well as nonzero polarization. This is explained in terms of a dominant Regge pole vanishing at the dip accompanied by a background. The background is primarily responsible for the large u behavior of the cross section which includes the rise after the dip. It is assumed that the presence of nonzero polarization dictates this behavior. We isolate the I = 3/2 amplitude in π−p backwards and determine the I = 1/2 amplitude from π+p backwards. A prediction for π−p → nπ0 follows.

scholarly journals The Regge Pole Model and Forward Elastic Data at High Energies ? An Analysis

1981 ◽  
Vol 34 (6) ◽  
pp. 611
Author(s):  
Mujahid Kamran
Keyword(s):  
Cross Section ◽  
Regge Pole ◽  
Pole Model ◽  
Exchange Degeneracy ◽  
Cross Section Data ◽  
Regge Pole Model ◽  
Section Data ◽  
High Energies ◽  
Elastic Data ◽  
Parameter Values

Using O"to" Re/lm and relevant forward differential cross-section data up to the highest available energies we determine the P, f, p, OJ, A2 intercepts and forward residues in nN, NN and KN scattering. We find evidence for low-lying contributions in the nN and NN non-flip amplitudes including the 0" trajectory in the nN case. We also test various phenomenological notions like exchange degeneracy (EXD) , p universality, OJ universality etc. against our parameter values. Comparison is made with other works.

Pooling of Time Series and Cross Section Data

Econometrica ◽  
1969 ◽  
Vol 37 (3) ◽  
pp. 552
Author(s):  
V. K. Chetty
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Cross Section Data ◽  
Section Data

Applications of cross section data for nuclear geochemical well logging

1986 ◽  
Vol 94 (1-4) ◽  
pp. 49-52 ◽  
Author(s):  
R. C. Hertzog ◽  
P. D. Soran ◽  
J. S. Schweitzer
Keyword(s):  
Cross Section ◽  
Well Logging ◽  
Cross Section Data ◽  
Section Data ◽  
Geochemical Well Logging

An Am/Be neutron source and its use in integral tests of differential neutron reaction cross-section data

2010 ◽  
Vol 68 (9) ◽  
pp. 1656-1661 ◽  
Author(s):  
M.S. Uddin ◽  
M.R. Zaman ◽  
S.M. Hossain ◽  
I. Spahn ◽  
S. Sudár ◽  
...  
Keyword(s):  
Cross Section ◽  
Neutron Source ◽  
Reaction Cross Section ◽  
Reaction Cross ◽  
Cross Section Data ◽  
Section Data ◽  
Neutron Reaction

scholarly journals Unions and Productivity in the Public Sector: A Study of Municipal Libraries

ILR Review ◽  
1983 ◽  
Vol 36 (2) ◽  
pp. 199-213 ◽  
Author(s):  
Ronald G. Ehrenberg ◽  
Daniel R. Sherman ◽  
Joshua L. Schwarz
Keyword(s):  
Public Sector ◽  
Collective Bargaining ◽  
Empirical Analysis ◽  
Cross Section ◽  
Cross Section Data ◽  
The Public ◽  
Section Data ◽  
The Empirical Analysis

This paper develops and illustrates the use of two methodologies to analyze the effect of unions on productivity in the public sector. Although the methodologies are applicable to a wide variety of public sector functions, the focus of the paper is on municipal libraries because of the availability of relevant data. The empirical analysis, which uses 1977 cross-section data on 260 libraries, suggests that collective bargaining coverage has not significantly affected productivity in municipal libraries.

scholarly journals Testing for Unit Roots and Cointegration in Spatial Cross-Section Data

2012 ◽  
Vol 7 (2) ◽  
pp. 203-222 ◽  
Author(s):  
Michael Beenstock ◽  
Dan Feldman ◽  
Daniel Felsenstein
Keyword(s):  
Cross Section ◽  
Unit Roots ◽  
Cross Section Data ◽  
Section Data

Time is Not A Theoretical Variable

2010 ◽  
Vol 18 (3) ◽  
pp. 293-294 ◽  
Author(s):  
Nathaniel Beck
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Duration Dependence ◽  
Cross Section Data ◽  
Section Data ◽  
Data Analyst ◽  
Binary Time Series ◽  
Simple Cubic ◽  
Cubic Polynomial

Carter and Signorino (2010) (hereinafter “CS”) add another arrow, a simple cubic polynomial in time, to the quiver of the binary time series—cross-section data analyst; it is always good to have more arrows in one's quiver. Since comments are meant to be brief, I will discuss here only two important issues where I disagree: are cubic duration polynomials the best way to model duration dependence and whether we can substantively interpret duration dependence.

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