arXiv subjects

E. Mavrommatis

Publications and source records attributed to E. Mavrommatis.

At least 19 recordsLinked to original sources

arXiv2017

Microscopic Study of ${}^1{S_0}$ Superfluidity in Dilute Neutron Matter

Singlet $S$-wave superfluidity of dilute neutron matter is studied within the correlated BCS method, which takes into account both pairing and short-range correlations. First, the equation of state (EOS) of normal neutron matter is calculated within the Correlated Basis Function (CBF) method in lowest cluster order using the ${}^1{S_0}$ and ${}^3P$ components of the Argonne $V_{18}$ potential, assuming trial Jastrow-type correlation functions. The ${}^1{S_0}$ superfluid gap is then calculated with the corresponding component of the Argonne $V_{18}$ potential and the optimally determined correlation functions. The dependence of our results on the chosen forms for the correlation functions is studied, and the role of the $P$-wave channel is investigated. Where comparison is meaningful, the values obtained for the ${}^1{S_0}$ gap within this simplified scheme are consistent with the results of similar and more elaborate microscopic methods.

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arXiv2013

Statistical Global Model of beta- Half-lives and r-Process Nucleosynthesis

Purpose: Our objective is to apply an improved statistical global model of beta^- decay half-life systematics [1] generated by machine-learning techniques to the prediction of beta half-lives relevant to r-process nuclei. The primary aim of this application is to complement existing r-process-clock and matter-flow studies, thereby providing additional theoretical support for the planning of future activities of the world's network of rare-isotope laboratories. Results: Results are presented for nuclides situated on the r-ladders at N=50, 82, and 126 where abundances peak, as well as for nuclides that affect abundances between peaks or may be relevant to r-processes under different astrophysical scenarios. The half-lives of some of the targeted neutron-rich nuclides have either been recently measured or will be accessible at rare-isotope laboratories in the relatively near future. The results of our large-scale data-driven half-life calculations (generated by a "theory-thin" global statistical model) are compared to available experimental data, including recent measurements on very neutron-rich nuclei along an r-process path far from the valley of $β$ stability. Comparison is also made with corresponding results from traditional global models derived by semi-phenomenological "theory-thick" approaches.

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arXiv2012

Quantum versus Classical Dynamics in a driven barrier: the role of kinematic effects

We study the dynamics of the classical and quantum mechanical scattering of a wave packet from an oscillating barrier. Our main focus is on the dependence of the transmission coefficient on the initial energy of the wave packet for a wide range of oscillation frequencies. The behavior of the quantum transmission coefficient is affected by tunneling phenomena, resonances and kinematic effects emanating from the time dependence of the potential. We show that when kinematic effects dominate (mainly in intermediate frequencies), classical mechanics provides very good approximation of quantum results. Moreover, in the frequency region of optimal agreement between classical and quantum transmission coefficient, the transmission threshold, i.e. the energy above which the transmission coefficient becomes larger than a specific small threshold value, is found to exhibit a minimum. We also consider the form of the transmitted wave packet and we find that for low values of the frequency the incoming classical and quantum wave packet can be split into a train of well separated coherent pulses, a phenomenon which can admit purely classical kinematic interpretation.

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arXiv2008

Statistical Global Modeling of Beta-Decay Halflives Systematics Using Multilayer Feedforward Neural Networks and Support Vector Machines

In this work, the beta-decay halflives problem is dealt as a nonlinear optimization problem, which is resolved in the statistical framework of Machine Learning (LM). Continuing past similar approaches, we have constructed sophisticated Artificial Neural Networks (ANNs) and Support Vector Regression Machines (SVMs) for each class with even-odd character in Z and N to global model the systematics of nuclei that decay 100% by the beta-minus-mode in their ground states. The arising large-scale lifetime calculations generated by both types of machines are discussed and compared with each other, with the available experimental data, with previous results obtained with neural networks, as well as with estimates coming from traditional global nuclear models. Particular attention is paid on the estimates for exotic and halo nuclei and we focus to those nuclides that are involved in the r-process nucleosynthesis. It is found that statistical models based on LM can at least match or even surpass the predictive performance of the best conventional models of beta-decay systematics and can complement the latter.

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arXiv2008

Decoding Beta-Decay Systematics: A Global Statistical Model for Beta^- Halflives

Statistical modeling of nuclear data provides a novel approach to nuclear systematics complementary to established theoretical and phenomenological approaches based on quantum theory. Continuing previous studies in which global statistical modeling is pursued within the general framework of machine learning theory, we implement advances in training algorithms designed to improved generalization, in application to the problem of reproducing and predicting the halflives of nuclear ground states that decay 100% by the beta^- mode. More specifically, fully-connected, multilayer feedforward artificial neural network models are developed using the Levenberg-Marquardt optimization algorithm together with Bayesian regularization and cross-validation. The predictive performance of models emerging from extensive computer experiments is compared with that of traditional microscopic and phenomenological models as well as with the performance of other learning systems, including earlier neural network models as well as the support vector machines recently applied to the same problem. In discussing the results, emphasis is placed on predictions for nuclei that are far from the stability line, and especially those involved in the r-process nucleosynthesis. It is found that the new statistical models can match or even surpass the predictive performance of conventional models for beta-decay systematics and accordingly should provide a valuable additional tool for exploring the expanding nuclear landscape.

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arXiv2008

A nonlinear classical model for the decay widths of Isoscalar Giant Monopole Resonances

The decay of the Isoscalar Giant Monopole Resonance (ISGMR) in nuclei is studied by means of a nonlinear classical model consisting of several noninteracting nucleons (particles) moving in a potential well with an oscillating nuclear surface (wall). The motion of the nuclear surface is described by means of a collective variable which appears explicitly in the Hamiltonian as an additional degree of freedom. The total energy of the system is therefore conserved. Although the particles do not directly interact with each other, their motions are indirectly coupled by means of their interaction with the moving nuclear surface. We consider as free parameters in this model the degree of collectivity and the fraction of nucleons that participate to the decay of the collective excitation. Specifically, we have calculated the decay width of the ISGMR in the spherical nuclei $^{208}\rm{Pb}$, $^{144}\rm{Sm}$, $^{116}\rm{Sn}$ and $^{90}\rm{Zr}$. Despite its simplicity and its purely classical nature, the model reproduces the trend of the experimental data which show that with increasing mass number the decay width decreases. Moreover the experimental results (with the exception of $^{90}\rm{Zr}$) can be well fitted using appropriate values for the free parameters mentioned above. It is also found that these values allow for a good description of the experimentally measured $^{112}\rm{Sn}$ and $^{124}\rm{Sn}$ decay widths. In addition, we give a prediction for the decay width of the exotic isotope $^{132}Sn$ for which there is experimental interest. The agreement of our results with the corresponding experimental data for medium-heavy nuclei is dictated by the underlying classical mechanics i.e. the behaviour of the maximum Lyapunov exponent as a function of the system size.

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arXiv2007

The Effect of the Short-Range Correlations on the Generalized Momentum Distribution in Finite Nuclei

The effect of dynamical short-range correlations on the generalized momentum distribution $n(\vec{p},\vec{Q})$ in the case of $Z=N$, $\ell$-closed shell nuclei is investigated by introducing Jastrow-type correlations in the harmonic-oscillator model. First, a low order approximation is considered and applied to the nucleus $^4$He. Compact analytical expressions are derived and numerical results are presented and the effect of center-of-mass corrections is estimated. Next, an approximation is proposed for $n(\vec{p}, \vec{Q})$ of heavier nuclei, that uses the above correlated $n(\vec{p},\vec{Q})$ of $^4$He. Results are presented for the nucleus $^{16}$O. It is found that the effect of short-range correlations is significant for rather large values of the momenta $p$ and/or $Q$ and should be included, along with center of mass corrections for light nuclei, in a reliable evaluation of $n(\vec{p},\vec{Q})$ in the whole domain of $p$ and $Q$.

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arXiv2007

A Global Model of $β^-$-Decay Half-Lives Using Neural Networks

Statistical modeling of nuclear data using artificial neural networks (ANNs) and, more recently, support vector machines (SVMs), is providing novel approaches to systematics that are complementary to phenomenological and semi-microscopic theories. We present a global model of $β^-$-decay halflives of the class of nuclei that decay 100% by $β^-$ mode in their ground states. A fully-connected multilayered feed forward network has been trained using the Levenberg-Marquardt algorithm, Bayesian regularization, and cross-validation. The halflife estimates generated by the model are discussed and compared with the available experimental data, with previous results obtained with neural networks, and with estimates coming from traditional global nuclear models. Predictions of the new neural-network model are given for nuclei far from stability, with particular attention to those involved in r-process nucleosynthesis. This study demonstrates that in the framework of the $β^-$-decay problem considered here, global models based on ANNs can at least match the predictive performance of the best conventional global models rooted in nuclear theory. Accordingly, such statistical models can provide a valuable tool for further mapping of the nuclidic chart.

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arXiv2006

Modeling Nuclear Properties with Support Vector Machines

We have made initial studies of the potential of support vector machines (SVM) for providing statistical models of nuclear systematics with demonstrable predictive power. Using SVM regression and classification procedures, we have created global models of atomic masses, beta-decay halflives, and ground-state spins and parities. These models exhibit performance in both data-fitting and prediction that is comparable to that of the best global models from nuclear phenomenology and microscopic theory, as well as the best statistical models based on multilayer feedforward neural networks.

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arXiv2006

The one-body and two-body density matrices of finite nuclei with an appropriate treatment of the center-of-mass motion

The one-body and two-body density matrices in coordinate space and their Fourier transforms in momentum space are studied for a nucleus (a nonrelativistic, self-bound finite system). Unlike the usual procedure, suitable for infinite or externally bound systems, they are determined as expectation values of appropriate intrinsic operators, dependent on the relative coordinates and momenta (Jacobi variables) and acting on intrinsic wavefunctions of nuclear states. Thus, translational invariance (TI) is respected. When handling such intrinsic quantities, we use an algebraic technique based upon the Cartesian representation, in which the coordinate and momentum operators are linear combinations of the creation and annihilation operators a^+ and a for oscillator quanta. Each of the relevant multiplicative operators can then be reduced to the form: one exponential of the set {a^+} times other exponential of the set {a}. In the course of such a normal-ordering procedure we offer a fresh look at the appearance of "Tassie-Barker" factors, and point out other model-independent results. The intrinsic wavefunction of the nucleus in its ground state is constructed from a nontranslationally-invariant (nTI) one via existing projection techniques. As an illustration, the one-body and two-body momentum distributions (MDs) for the 4He nucleus are calculated with the Slater determinant of the harmonic-oscillator model as the trial, nTI wavefunction. We find that the TI introduces important effects in the MDs.

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arXiv2005

The One-Body and Two-Body Density Matrices of Finite Nuclei and Center-of-Mass Correlations

A method is presented for the calculation of the one-body and two-body density matrices and their Fourier transforms in momentum space, that is consistent with the requirement for translational invariance, in the case of a nucleus (a finite self-bound system). We restore translational invariance by using the so-called fixed center-of-mass approximation for constructing an intrinsic nuclear ground state wavefunction by starting from a non-translationally invariant wavefunction and applying a projection prescription. We discuss results for the one-body and two-body momentum distributions of the 4He nucleus calculated with the Slater determinant of the harmonic oscillator orbitals, as the initial non-translationally invariant wavefunction. Effects of such an inclusion of CM correlations are found to be quite important in the momentum distributions.

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arXiv2005

Nuclear mass systematics by complementing the Finite Range Droplet Model with neural networks

A neural-network model is developed to reproduce the differences between experimental nuclear mass-excess values and the theoretical values given by the Finite Range Droplet Model. The results point to the existence of subtle regularities of nuclear structure not yet contained in the best microscopic/phenomenological models of atomic masses. Combining the FRDM and the neural-network model, we create a hybrid model with improved predictive performance on nuclear-mass systematics and related quantities.

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arXiv2005

One and two proton separation energies from nuclear mass systematics using neural networks

We deal with the systematics of one and two proton separation energies as predicted by our latest global model for the masses of nuclides developed with the use of neural networks. Among others, such systematics is useful as input to the astrophysical rp-process and to the one and two proton radioactive studies. Our results are compared with the experimental separation energies referred to in the 2003 Atomic Mass Evaluation and with those evaluated from theoretical models for the masses of nuclides, like the FRDM of Möller et al. and the HFB2 of Pearson et al. We focus in particular on the proton separation energies for nuclides that are involved in the rp-process (29<=Z<=40) but they have not yet been studied experimentally.

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arXiv2005

Lyapunov Instability versus Relaxation Time in two Coupled Oscillators

We consider the relation between relaxation time and the largest Lyapunov exponent in a system of two coupled oscillators, one of them being harmonic. It has been found that in a rather broad region of parameter space, contrary to the common expectation, both Lyapunov exponent and relaxation time increase as a function of the total energy. This effect is attributed to the fact that above a critical value of the total energy, although the Lyapunov exponent increases, KAM tori appear and the chaotic fraction of phase space decreases. We examine the required conditions and demonstrate the key role of the dispersion relation for this behaviour to occur. This study is useful, among others, in the understanding of the damping of nuclear giant resonances.

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arXiv2004

A microscopic investigation of the transition form factor in the region of collective multipole excitations of stable and unstable nuclei

We have used a self-consistent Skyrme-Hartree-Fock plus Continuum-RPA model to study the low-multipole response of stable and neutron/proton-rich Ni and Sn isotopes. We focus on the momentum-transfer dependence of the strength distribution, as it provides information on the structure of excited nuclear states and in particular on the variations of the transition form factor (TFF) with the energy. Our results show, among other things, that the TFF may show significant energy dependence in the region of the isoscalar giant monopole resonance and that the TFF corresponding to the threshold strength in the case of neutron-rich nuclei is different compared to the one corresponding to the respective giant resonance. Perspectives are given for more detailed future investigations.

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arXiv2004

Nuclear vorticity and the low-energy nuclear response - Towards the neutron drip line

The transition density and current provide valuable insight into the nature of nuclear vibrations. Nuclear vorticity is a quantity related to the transverse transition current. In this work, we study the evolution of the strength distribution, related to density fluctuations, and the vorticity strength distribution, as the neutron drip line is approached. Our results on the isoscalar, natural-parity multipole response of Ni isotopes, obtained by using a self-consistent Skyrme-Hartree-Fock + Continuum RPA model, indicate that, close to the drip line, the low-energy response is dominated by L>1 vortical transitions.

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arXiv2004

Nuclear mass systematics using neural networks

New global statistical models of nuclidic (atomic) masses based on multilayered feedforward networks are developed. One goal of such studies is to determine how well the existing data, and only the data, determines the mapping from the proton and neutron numbers to the mass of the nuclear ground state. Another is to provide reliable predictive models that can be used to forecast mass values away from the valley of stability. Our study focuses mainly on the former goal and achieves substantial improvement over previous neural-network models of the mass table by using improved schemes for coding and training. The results suggest that with further development this approach may provide a valuable complement to conventional global models.

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arXiv2002

The Two-Body Momentum Distribution in Finite Nuclei

The two-body momentum distribution n2(p1,p2) of nuclei is studied. First, a compact analytical expression is derived for Z=N l-closed nuclei, within the context of the independent-particle shell model. Application to the light closed-shell nucleus 16O is included and discussed. Next, the effect of dynamical, short-range correlations is investigated in the case of 4He, by including Jastrow-type correlations in the formalism. The effect is significant for large values of p1 and p2 and for angles between the vectors p1 and p2 close to 180 deg. and 0.

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