The multiplicity distribution (P(nch)) of charged particles produced in a high energy collision is a key quantity to understand the mechanism of multiparticle production. This paper describes the novel application of ...The multiplicity distribution (P(nch)) of charged particles produced in a high energy collision is a key quantity to understand the mechanism of multiparticle production. This paper describes the novel application of an artificial neural network (ANN) black-box modeling approach based on the cascade correlation (CC) algorithm formulated to calculate and predict multiplicity distribution of proton-proton (antiproton) (PP and PP ) inelastic interactions full phase space at a wide range of center-mass of energy . In addition, the formulated cascade correlation neural network (CCNN) model is used to empirically calculate the average multiplicity distribution nch> as a function of . The CCNN model was designed based on available experimental data for = 30.4 GeV, 44.5 GeV, 52.6 GeV, 62.2 GeV, 200 GeV, 300 GeV, 540 GeV, 900 GeV, 1000 GeV, 1800 GeV, and 7 TeV. Our obtained empirical results for P(nch), as well as nch> for (PP and PP) collisions are compared with the corresponding theoretical ones which obtained from other models. This comparison shows a good agreement with the available experimental data (up to 7 TeV) and other theoretical ones. At full large hadron collider (LHC) energy ( = 14 TeV) we have predicted P(nch) and nch> which also, show a good agreement with different theoretical models.展开更多
This paper presents the results of analysis of the D? 1.0 fb-1 data on top-quark differential cross section measurements at the Fermilab Tevatron collider at √s= 1960 GeV in the framework of z-scaling approach. The f...This paper presents the results of analysis of the D? 1.0 fb-1 data on top-quark differential cross section measurements at the Fermilab Tevatron collider at √s= 1960 GeV in the framework of z-scaling approach. The flavor independence of scaling function Ψ(z)observed in pp and pp interactions over a wide collision energy range √s= 19-1960 GeV has been verified. This property of Ψ(z) was found for different hadrons – from π-mesons up to Υ particles. The flavor independence of Ψ(z) is used as indication on self-similarity of the top-quark production. A tendency to saturation of Ψ(z) at low z for top-quark production has been confirmed. Momentum fraction x1 of the incoming (anti)protons as a function of the scaled transverse momentum pT/m and masses of heavy mesons is studied. We anticipate that the data on low- and high-pT inclusive spectra of the top-quark production at the Tevatron and LHC energies could be of interest to verify self-similarity over a wide range of masses and different flavor content of produced particles.展开更多
文摘The multiplicity distribution (P(nch)) of charged particles produced in a high energy collision is a key quantity to understand the mechanism of multiparticle production. This paper describes the novel application of an artificial neural network (ANN) black-box modeling approach based on the cascade correlation (CC) algorithm formulated to calculate and predict multiplicity distribution of proton-proton (antiproton) (PP and PP ) inelastic interactions full phase space at a wide range of center-mass of energy . In addition, the formulated cascade correlation neural network (CCNN) model is used to empirically calculate the average multiplicity distribution nch> as a function of . The CCNN model was designed based on available experimental data for = 30.4 GeV, 44.5 GeV, 52.6 GeV, 62.2 GeV, 200 GeV, 300 GeV, 540 GeV, 900 GeV, 1000 GeV, 1800 GeV, and 7 TeV. Our obtained empirical results for P(nch), as well as nch> for (PP and PP) collisions are compared with the corresponding theoretical ones which obtained from other models. This comparison shows a good agreement with the available experimental data (up to 7 TeV) and other theoretical ones. At full large hadron collider (LHC) energy ( = 14 TeV) we have predicted P(nch) and nch> which also, show a good agreement with different theoretical models.
基金supported by the IRP AVOZ10480505by the Ministry of Education of the Czech Republic grants LA08002,LA08015.
文摘This paper presents the results of analysis of the D? 1.0 fb-1 data on top-quark differential cross section measurements at the Fermilab Tevatron collider at √s= 1960 GeV in the framework of z-scaling approach. The flavor independence of scaling function Ψ(z)observed in pp and pp interactions over a wide collision energy range √s= 19-1960 GeV has been verified. This property of Ψ(z) was found for different hadrons – from π-mesons up to Υ particles. The flavor independence of Ψ(z) is used as indication on self-similarity of the top-quark production. A tendency to saturation of Ψ(z) at low z for top-quark production has been confirmed. Momentum fraction x1 of the incoming (anti)protons as a function of the scaled transverse momentum pT/m and masses of heavy mesons is studied. We anticipate that the data on low- and high-pT inclusive spectra of the top-quark production at the Tevatron and LHC energies could be of interest to verify self-similarity over a wide range of masses and different flavor content of produced particles.
