Function mining for the < P T > -N ch correlations in pp and pp(bar) collisions based on symbolic regression

El-sayed EL-DAHSHAN

Makale detayları

Function mining for the < P T > -N ch correlations in pp and pp(bar) collisions based on symbolic regression

Yazarlar:

El-sayed EL-DAHSHAN

Yayıncı:

TUBITAK

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Turkish Journal of Physics 2018 Vol.42 Issue 3, pp.273-282

Belge Tipi:

Makale

Yayın Tarihi:

5/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000759385

Sıklık:

İki Aylık

eISSN:

1303-6122

pISSN:

1300-0101

Özet:

 


 
                         The investigation and analysis of the correlation between 
the mean transverse momentum (  P   T    PTNchP_{T}>) of charged particles and the 
charged particle multiplicity (NchNchNch  N   c  h    NchPTN_{ch}) allow physicists to 
understand the contribution of multiple-parton interactions to the particle 
production mechanism. A symbolic regression (SR) method, based on gene 
expression programming (GEP), is proposed for mining a function that 
describes the   P   T    PTNchP_{T}>-Nch  N   c  h    Nchs1/2N_{ch} correlation in proton-proton and 
proton-antiproton (pp and pp(bar)) collisions at collision energies from 
IRS to LHC. The discovered function simulates and models the correlation 
between   P   T    PTPTP_{T}> and Nch  N   c  h    Nch−NchN_{ch} in wide energy range s1/2 s   1   /   2   s1/2PTs^{1/2}. In the 
framework of the proposed GEP model for   P   T    PT−NchP_{T}>−Nch −   N   c  h    −Nch-N_{ch} correlation, the 
equation obtained describes the main features of the experimental data. 
Predictions for   P   T    PTP_{T}>−Nch −   N   c  h    −Nch-N_{ch} correlations at the future LHC collision 
energy of 14 TeV are obtained. The accuracy of the calculated and predicted 
results is assessed by comparing them with the available experimental data 
and the theoretical ones.
                    

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Makale detayları

Function mining for the < P T > -N ch correlations in pp and pp(bar) collisions based on symbolic regression

Yazarlar: El-sayed EL-DAHSHAN

Yayıncı: TUBITAK

Ana Başlıklar: Uygulamalı fizik

Dergi: Turkish Journal of Physics 2018 Vol.42 Issue 3, pp.273-282

Belge Tipi: Makale

Yayın Tarihi: 5/2018

Belge Dili: İngilizce

Document ID (Org No.): 2000759385

Sıklık: İki Aylık

eISSN: 1303-6122

pISSN: 1300-0101

Sayı

Yazarlar:

El-sayed EL-DAHSHAN

Yayıncı:

TUBITAK

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Turkish Journal of Physics 2018 Vol.42 Issue 3, pp.273-282

Belge Tipi:

Makale

Yayın Tarihi:

5/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000759385

Sıklık:

İki Aylık

eISSN:

1303-6122

pISSN:

1300-0101