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H. Kaya

Publications and source records attributed to H. Kaya.

6 recordsLinked to original sources
arXiv2022

First Excited 2+ Energy State Estimations of Even-even Nuclei by Using Artificial Neural Networks

The first excited 2+ energy states of nuclei give many substantial information related to the nuclear structure. Including these levels, all excited states of nuclei are shown regularities in spin, parity and energy. In the even-even nuclei, the first excited state is generally 2+ and the energy values of them increase as the closed shells are approached. The excited levels in nuclei can be investigated by using theoretical nuclear models such nuclear shell model. In the present study for the first time, we have used artificial neural networks for the determination of the energies of first 2+ states in the even-even nuclei in nuclidic chart as a function of Z, N and A numbers. We have used adopted literature values for the estimations. According to the results, the method is convenient for this goal and one can confidently use the method for the determination of first 2+ state energy values whose experimental values do not exist in the literature.

nucl-th↗
arXiv2020

Estimations of Cross-Sections for Photonuclear Reaction on Calcium Isotopes by Artificial Neural Networks

The nuclear reaction induced by photon is one of the important tools in the investigation of atomic nuclei. In the reaction, a target material is bombarded by photons with high-energies in the range of gamma-ray energy range. In the bombarding process, the photons can statistically be absorbed by a nucleus in the target material. Then the excited nucleus can decay by emitting proton, neutron, alpha and light particles or photons. By performing photonuclear reaction on the target, it can be easily investigated low-lying excited states of the nuclei. In the present work, (γ, n) photonuclear reaction cross-sections on different calcium isotopes have been estimated by using artificial neural network method. The method is a mathematical model that mimics the brain functionality of the creatures. The correlation coefficient values of the method for both training and test phases being 0.99 indicate that the method is very suitable for this purpose.

nucl-th↗
arXiv2000

Delocalization Transition of a Rough Adsorption-Reaction Interface

We introduce a new kinetic interface model suitable for simulating adsorption-reaction processes which take place preferentially at surface defects such as steps and vacancies. As the average interface velocity is taken to zero, the self- affine interface with Kardar-Parisi-Zhang like scaling behaviour undergoes a delocalization transition with critical exponents that fall into a novel universality class. As the critical point is approached, the interface becomes a multi-valued, multiply connected self-similar fractal set. The scaling behaviour and critical exponents of the relevant correlation functions are determined from Monte Carlo simulations and scaling arguments.

cond-mat.stat-mech↗
arXiv1999

Novel Position-Space Renormalization Group for Bond Directed Percolation in Two Dimensions

A new position-space renormalization group approach is investigated for bond directed percolation in two dimensions. The threshold value for the bond occupation probabilities is found to be $p_c=0.6443$. Correlation length exponents on time (parallel) and space (transverse) directions are found to be $ν_\parallel=1.719$ and $ν_\perp=1.076$, respectively, which are in very good agreement with the best known series expansion results.

cond-mat.stat-mech↗