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Models for differential cross section in neutron-proton scattering and their implications

Muhammad Saad Ashraf, Nosheen Akbar

TL;DR

The study develops five purely phenomenological models to describe the neutron-proton elastic differential cross section $\frac{d\sigma}{dt}$ over $\sqrt{s}=3.36$–$26.02$ GeV. Each model embeds a Regge-inspired forward diffractive core with energy-dependent slopes and localized $t$-dependent corrections, complemented by additive C-odd and isospin terms to reproduce the dip–bump structures. Fitting to NP data via $\chi^2$ minimization, the models accurately describe the forward peak, dip evolution, and large-$|t|$ behavior, while predicting total, elastic, and inelastic cross sections and the slope parameter $B(s)$ in agreement with Regge expectations. The results yield analytically well-behaved parameterizations that capture diffractive shrinkage and can be extended to other NN channels and higher energies, contributing a compact phenomenological tool for elastic scattering analyses.

Abstract

A few analytic exponential models of elastic differential cross section, constructed as purely phenomenological models, are proposed and tested. The models incorporate energy-dependent exponential slopes, power-law prefactors, and localized Gaussian modifications which are built to reproduce the observed dip region, supplemented in some cases by logarithmic $t$-dependent slopes. Simple additive sub-leading exponential contributions that represent charge conjugation and isospin roles are introduced in the models to increase applicability and quality of fit across elastic differential cross section data of $np$, $n\bar{p}$, $pp$, and $p\bar{p}$ elastic scattering. The models reproduce the characteristic features of the elastic scattering data such as the dip-bump structure, shrinkage of the forward peak, and controlled curvature that is localized around the dip. Parameters of the models are found by fitting the experimental data of elastic $np$ differential cross section in an energy range of $\sqrt{s}$ = 3.36 GeV to 26.02 GeV, across a momentum range of $0.065 \leq \mid t\mid \leq 5.341 \textrm{GeV}^{2}$. The parameter values and their ranges, obtained by $χ^{2}$ minimization are found within their assumed expected bounds with the $np$ data fitting. The total cross section, the slope parameter, the interaction radius, the total elastic cross section, the inelastic cross section, the ratios $σ_{el}/σ_{tot}$, and $σ_{inel}/σ_{tot}$ are predicted by the models for the $np$ scattering at all the energies, which show accurate quantitative agreement with their reference values. The results show that the proposed models not only provide accurate quantitative description of $np$ elastic differential cross section but also yield estimates of the observables that are consistent with theoretical expectations from Regge phenomenology and high-energy scattering constraints.

Models for differential cross section in neutron-proton scattering and their implications

TL;DR

The study develops five purely phenomenological models to describe the neutron-proton elastic differential cross section over GeV. Each model embeds a Regge-inspired forward diffractive core with energy-dependent slopes and localized -dependent corrections, complemented by additive C-odd and isospin terms to reproduce the dip–bump structures. Fitting to NP data via minimization, the models accurately describe the forward peak, dip evolution, and large- behavior, while predicting total, elastic, and inelastic cross sections and the slope parameter in agreement with Regge expectations. The results yield analytically well-behaved parameterizations that capture diffractive shrinkage and can be extended to other NN channels and higher energies, contributing a compact phenomenological tool for elastic scattering analyses.

Abstract

A few analytic exponential models of elastic differential cross section, constructed as purely phenomenological models, are proposed and tested. The models incorporate energy-dependent exponential slopes, power-law prefactors, and localized Gaussian modifications which are built to reproduce the observed dip region, supplemented in some cases by logarithmic -dependent slopes. Simple additive sub-leading exponential contributions that represent charge conjugation and isospin roles are introduced in the models to increase applicability and quality of fit across elastic differential cross section data of , , , and elastic scattering. The models reproduce the characteristic features of the elastic scattering data such as the dip-bump structure, shrinkage of the forward peak, and controlled curvature that is localized around the dip. Parameters of the models are found by fitting the experimental data of elastic differential cross section in an energy range of = 3.36 GeV to 26.02 GeV, across a momentum range of . The parameter values and their ranges, obtained by minimization are found within their assumed expected bounds with the data fitting. The total cross section, the slope parameter, the interaction radius, the total elastic cross section, the inelastic cross section, the ratios , and are predicted by the models for the scattering at all the energies, which show accurate quantitative agreement with their reference values. The results show that the proposed models not only provide accurate quantitative description of elastic differential cross section but also yield estimates of the observables that are consistent with theoretical expectations from Regge phenomenology and high-energy scattering constraints.

Paper Structure

This paper contains 17 sections, 23 equations, 9 figures, 22 tables.

Figures (9)

  • Figure 1: (a) Model 1 fits on the $np$ elastic differential cross section data of Dataset 1 ($3.363 \leq \sqrt{s} \leq 4.935 \textrm{GeV}$) of Table \ref{['tab:expdata']}. Filled squares, filled rectangles, filled up triangles, filled circles, filled right triangles, filled down triangles, filled diamonds, and filled six-sided stars represent the experimental data of Dataset of \ref{['tab:expdata']} at 4.935, 4.741, 4.54, 4.329, 4.109, 3.876 , 3.628, and 3.363 GeV respectively. The data and model values are multiplied by $10^{-3(n-1)}$, where $n$ is the number of curve and corresponding data set starting from the top. The solid line represents the fit of our model to the data. (b) Model 1 fits on the $np$ elastic differential cross section data of Dataset 2 ($4.74 \leq \sqrt{s} \leq 6.704 \textrm{GeV}$) of Table \ref{['tab:expdata']}. Filled squares, filled rectangles, filled up triangles, filled circles, filled right triangles, filled down triangles, and filled diamonds represent the experimental data of Dataset of Table \ref{['tab:expdata']} at 6.704, 6.418, 6.119, 5.805, 5.473, 5.12, and 4.74 GeV, respectively. The data and model values are multiplied by $10^{-3(n-1)}$, where $n$ is the number of curve and corresponding data set starting from the top. The solid line represents the fit of our model to the data. (c) Model 1 fits on the $np$ elastic differential cross section data of Dataset 3 ($3.466-4.409 \leq \sqrt{s} \leq 7.024-7.538 \textrm{GeV}$) of Table \ref{['tab:expdata']}. Filled squares, filled rectangles, filled up triangles, filled circles, filled right triangles, and filled down triangles, represent the experimental data of Dataset of Table \ref{['tab:expdata']} at 7.024-7.538, 6.47-7.024, 5.863-6.47, 5.187-5.863, 4.409-5.187, and 3.466-4.409 GeV, respectively. Data and model values are multiplied by $10^{-3(n-1)}$, where $n$ is the number of curve and corresponding data set starting from the top. The solid line represents the fit of our model to the data. (d) Model 1 fits on the $np$ elastic differential cross section data of Dataset 4 ($13.748 \leq \sqrt{s} \leq 26.019 \textrm{GeV}$) of Table \ref{['tab:expdata']}. Filled squares, filled rectangles, filled up triangles, filled circles, filled right triangles, filled down triangles, and filled diamonds represent the experimental data of Dataset of Table \ref{['tab:expdata']} at 26.019, 24.536, 22.956, 21.471, 19.416, 16.823, and 13.748 GeV, respectively. Data and model values are multiplied by $10^{-3(n-1)}$, where $n$ is the number of curve and corresponding data set starting from the top. The solid line represents the fit of our model to the data.
  • Figure 2: Model 2 fits on the $np$ elastic differential cross section data of Dataset 1 of Table \ref{['tab:expdata']}. Same legend for parts (a), (b), (c), and (d) as in the Figure 1.
  • Figure 3: Model 3 fits on the $np$ elastic differential cross section data of Dataset 1 of Table \ref{['tab:expdata']}. Same legend for parts (a), (b), (c), and (d) as in the Figure 1
  • Figure 4: Model 4 fits on the $np$ elastic differential cross section data of Dataset 1 of Table \ref{['tab:expdata']}. Same legend for parts (a), (b), (c), and (d) as in the Figure 1.
  • Figure 5: Model 5 fits on the $np$ elastic differential cross section data of Dataset 1 of Table \ref{['tab:expdata']}. Same legend for the parts (a), (b), (c), and (d) as in the Figure 1.
  • ...and 4 more figures