Tuncay Bayram

An artificial neural network application on nuclear charge radii

Artificial neural networks (ANN) have emerged with successful applications in nuclear physics as well as in many fields of science in recent years. In this paper, ANN have been employed on experimental nuclear charge radii. Statistical modeling of nuclear charge radii using ANN are seen to be successful. Based on the outputs of ANN we have estimated a new simple mass-dependent nuclear charge radii formula. Also, the charge radii, binding energies and two-neutron separation energies of Sn isotopes have been calculated by implementation of a new estimated formula in Hartree–Fock–Bogoliubov calculations. The results of the study show that the new estimated formula is useful for describing nuclear charge radii.

A study on ground-state energies of nuclei by using neural networks

Abstract One of the fundamental ground-state properties of nuclei is binding energy. Artificial neural networks (ANN) have been performed to obtain binding energies of nuclei based on the data calculated from Hartree–Fock–Bogolibov method with two Skyrme forces SLy4 and SKP. ANN has been employed to obtain two-neutron and two-proton separation energies of nuclei. Statistical modeling of ground-state energies using ANN has been seen as to be successful in this study. Particularly, predictive power of ANN has been drawn from estimations for energies of Sr, Xe, Er and Pb isotopic chains which are not seen before by the network. The study shows that such a statistical model can be possible tool for searching in systematic of nuclei beyond existing experimental data.

TABLE OF GROUND STATE PROPERTIES OF NUCLEI IN THE RMF MODEL

The ground state energies, sizes and deformations of 1897 even–even nuclei with 10≤Z ≤110 have been carried out by using the Relativistic Mean Field (RMF) model. In the present calculations, the nonlinear RMF force NL3* recent refitted version of the NL3 force has been used. The BCS (Bardeen–Cooper–Schrieffer) formalism with constant gap approximation has been taken into account for pairing correlations. The predictions of RMF model for the ground state properties of some nuclei have been discussed in detail.

Energy Levels and Half-Lives of Gallium Isotopes Obtained by Photo-Nuclear Reaction

We have run an experiment to determine the energy levels and half-lives of Gallium nucleus by using the photonuclear reactions with end-point energy of 18 MeV bremsstrahlung photons, produced by a clinical linear accelerator. As a result of 71Ga(y,n)70Ga and 69Ga(Y,n)68Ga photonuclear reactions, the energy levels and half-lives of 70Ga and 68Ga nuclei have been determined. The results are in good agreement with the literature values.

α-decay half-life calculations of superheavy nuclei using artificial neural networks

Investigations of superheavy elements (SHE) have received much attention in the last two decades, due to the successful syntheses of SHE. In particular, ?-decay of SHEs has a great importance because most synthesized SHE have a-decay and the experimentalists have evaluated the theoretical predictions of the a-decay half-life during the experimental design. Because of this, the correct prediction of ?-decay half-life is important to investigate superheavy nuclei as well as heavy nuclei. In this work, artificial neural networks (ANN) have been employed on experimental a-decay half-lives of superheavy nuclei. Statistical modeling of a-decay half-life of superheavy nuclei have been found as to be successful.

Energy level and half-life determinations from photonuclear reaction on Ga target

Photonuclear reactions are important tools in the understanding of the nucleus. These reactions are also interesting for realizing the element creation processes in stellar environment. The use of bremsstrahlung photons generated from clinic linear accelerator is practical for performing these type of reactions. In this study, the bremsstrahlung photons with endpoint energy of 18MeV have been used for activating gallium target material. After irradiation, the transition energies and half-lives associated with the decay of 68Ga, 70Ga and 72Ga isotopes have been determined The values obtained for half-life of 68Ga, 70Ga and 72Ga isotopes are 67.5±0.9min, 21.1±0.9min and 13.8±0.4h, respectively. It has been seen that the values are consistent with the present literature values. In addition, the new measurements of gamma-ray energies for transition energies have been obtained comparable to the literature values with good uncertainties.

Photonuclear Reaction Cross Sections for Gallium Isotopes

The photon induced reactions which are named as photonuclear reactions have a great importance in many field of nuclear, radiation physics and related fields. The crosssections of neutron (photo-neutron (y,xn)) and proton (photo-proton (y,xn)) productions after photon activation have been calculated by using TALYS 1.2 computer code in this study. The target nucleus has been considered gallium which has two stable isotopes, 69Ga and 71Ga. Furthermore, the pre-equilibrium and compound process contributions to the total cross-section have been investigated.

Estimations of fission barrier heights for Ra, Ac, Rf and Db nuclei by neural networks

Accurate information about the fission barrier is important for studying of the fission process. Fission barrier is needed for discovering the island of stability in superheavy region and searching of the superheavy elements. Furthermore, the astrophysical r-process is closely related to the fission barrier of the neutron-rich nuclei. In this study, by using artificial neural network (ANN) method, we have estimated the fission barrier heights of the Rf, Db, Ra and Ac nuclei covering 230 isotopes. For inner barrier calculation, we have used Rf and Db nuclei and the barrier heights have been determined between nearly 1 MeV and 7 MeV. The related mean square error value has been obtained as 0.108 MeV. For outer barrier calculation, we have used Ra and Ac nuclei and the heights have been determined between nearly 8 MeV and 28 MeV. The related mean square error has been obtained as 0.407. The results of this study indicate that ANN is capable for the estimations of inner and outer fission barrier heights.

CONSISTENT EMPIRICAL PHYSICAL FORMULAS FOR POTENTIAL ENERGY CURVES OF 38−66 Ti ISOTOPES BY USING NEURAL NETWORKS

Nuclear shape transition has been actively studied in the past decade. In particular, the understanding of this phenomenon from a microscopic point of view is of great importance. Because of this reason, many works have been employed to investigate shape phase transition in nuclei within the relativistic and nonrelativistic mean field models by examining potential energy curves (PECs). In this paper, by using layered feed-forward neural networks (LFNNs), we have constructed consistent empirical physical formulas (EPFs) for the PECs of 38–66Ti calculated by the Hartree-Fock-Bogoliubov (HFB) method with SLy4 Skyrme forces. It has been seen that the PECs obtained by neural network method are compatible with those of HFB calculations.

An analysis of E(5) shape phase transitions in Cr isotopes with covariant density functional theory

Constrained relativistic mean field theory (RMF) has been employed for analysis of the shape phase transitions of even–even 52−66Cr isotopes. The systematic investigation of ground-state shape evolution between spherical U(5) and γ-unstable O(6) for these nuclei has been carried out by using the potential energy curves (PECs) obtained from the effective interactions NL3*, TM1, PK1 and DD-ME2. The calculated PECs have indicated that 58Cr can be a candidate for the critical-point nucleus with E(5) symmetry. A similar conclusion is also drawn from the calculated single-particle spectra of 58Cr and is supported by the experimental data via observed ratios of the excitation energies. Furthermore, the γ-independent character of 58Cr has been pointed out by using its binding energy map in the β–γ plane obtained from the triaxial RMF calculations, in agreement with the condition of E(5) symmetry.