Microscopic cluster study of the and nuclei
Abstract
We use a microscopic multicluster model to investigate the structure of and of . These nuclei are described by and configurations, respectively, within the Generator Coordinate Method (GCM). The 4- and 5-body models raise the problem of a large number of generator coordinates (6 for and 9 for ), which requires specific treatment. We address this issue by using the Stochastic Variational Method (SVM), which is based on an optimal choice of the basis functions, generated randomly. The model provides good energy spectra for low-lying states of both nuclei. We also compute rms radii and densities, as well as electromagnetic transition probabilities. We analyze the structure of and of by considering energy curves, where one of the generator coordinates is fixed during the minimization procedure.
I Introduction
Nuclear clustering is a well-established phenomenon. In particular, the particle, due to its large binding energy, is a typical cluster in light nuclei. About 50 years ago, the seminal paper of Ikeda and his collaborators ITH68 showed that -clustering is expected near the threshold of nuclei. This conjecture leads to the famous Ikeda diagram and was remarkably confirmed by theory and by experiment. It was even extended to nuclei (see recent reviews in Refs. HIK12 ; DD12 ; KSK16 ; KH18 . For example, C cluster states are known in 18O for a long time DB85 .
Neutron-rich nuclei, in particular in the low-mass region of the nuclear chart, require specific attention. If clustering is expected, the role of the external neutrons should be addressed by specific methods. A typical example is 6He, which requires three-body models to accurately describe the halo neutrons. Beryllium isotopes are particularly interesting: 8Be is the archetype of -cluster nuclei. Although unstable, the ground state is well known to have a marked cluster structure. Going to heavier Be isotopes require multicluster approaches, where the structure persists, but where the additional neutrons play a role. Multicluster descriptions have been proposed in the past within the Generator Coordinate Method De02 , the Antisymmetrized Molecular Dynamics KH01 ; Ka02 , the molecular model IO00 ; IOI00 ; IHO02 ; It06 ; IIM08 ; IIS08 or the Resonating Group Method Ar04 ; OAS00 . An experimental review of neutron-rich isotopes can be found in Ref. Fo18 .
In the present work, we aim to investigate the and isotopes within the and Generator Coordinate Method (GCM). A previous study on 9Be DI18 within this microscopic approach shows that the model is able to reproduce many 9Be properties. The main issue in and is a large number of independent coordinates. In other words, accurate bases require large numbers of functions. This problem can be efficiently addressed by the Stochastic Variational Method (SVM), where a random choice of the basis sets is performed, which permits optimizing the basis KK77 ; VS95 . A recent application of the SVM to 6Li, considered as a six-body system, has been performed in Ref. SH19 .
II The microscopic multicluster model
II.1 Wave functions
The and isotopes are described in a multicluster model, involving two particles and two or three external neutrons (see Fig. 1). The Hamiltonian of the system is given by
(1) |
where is the kinetic energy of nucleon , and a nucleon-nucleon interaction ( or 11). The c.m. motion is treated by removing the c.m. kinetic energy . We adopt the Minnesota interaction TLT77 as central force, complemented by a short-range spin-orbit term DI18 . The Minnesota force contains one parameter, the admixture parameter , whose standard value is , but which can be slightly modified to reproduce important properties of the system. In our work, is adjusted on the binding energies of or . The Coulomb force is treated exactly.

The wave functions are defined within the GCM Ho77 ; Ta81 ; DD12 . In this microscopic multicluster model, the 10,11Be isotopes are described by various parameters, referred to as the generator coordinates DD12 ; Ho77 , which are illustrated in Fig. 1. As a general statement, the number of generator coordinates increases with the number of clusters . For 9Be DI18 , we have . For , this number increases to . These parameters are: is the distance between the particles, is the distance between the neutron and center-of-mass, is the distance between the external neutrons; three angles () complement the list. For the nucleus, the additional neutron introduces three new generator coordinates ( - see Fig. 1).
For the sake of clarity, we denote as the set of generator coordinates. In other words, for and for . Of course these large numbers of generator coordinates raise the problem of the basis selection. This is addressed by the Stochastic Variational Method (SVM) KK77 ; VS95 which will be briefly presented in the next subsection.
We first discuss the GCM matrix elements. Let us consider a multicluster wave function as
(2) |
where are the locations of the clusters, defined from the generator coordinates and from the Euler angles . In this definition, is an cluster wave function defined as a Slater determinant, and is a neutron spinor with spin projection . The -body antisymmetrization is taken into account through the operator . In Eq. (2), stands for the set of spin projections, i.e. for and for . To simplify the calculations we assume which represents the dominant component.
In a second step, the basis function (2) is projected an angular momentum and on parity. A projected basis function is therefore given by
(3) |
where is a Wigner function, the rotation operator, and is the projection on the intrinsic axis. The parity projection is performed by superposing another function where the center locations are inverted; in a schematic notation, we have
(4) |
Finally, the total wave function of the system is given by superposition of many projected basis functions (4), as
(5) |
where is the generator function, and is obtained from the diagonalization of the Hamiltonian and overlap kernels
(6) |
These matrix elements, as well as those of other operators (rms radii, densities, electromagnetic operators) are obtained from three-dimensional integrals over the Euler angles. As a large number of matrix elements (6) is necessary, in particular when we optimize the basis with the SVM, a special attention must be paid to the efficiency and to the parallelization of the codes.
II.2 Brief description of the SVM
The main issue in the present model is to find an optimal set of basis functions, keeping the total number within reasonable limits. The and nuclei are described by 6 and 9 generator coordinates, respectively. Obviously, using a standard mesh over each coordinate is not feasible. This problem can be efficiently addressed by using the SVM, widely used in problems dealing with large bases (see, for example, Ref. SH19 for a recent application).
The SVM has been described in previous references KK77 ; VS95 , and we only give here a brief overview. The SVM is based on a random selection of the basis set. A first set is determined by generating randomly sets and by choosing the minimum energy. The second basis set is obtained in the same way but is coupled to the first set. The process is then repeated until the energy remains nearly constant. Of course, the computer times rapidly increase when the size of the basis increases. In practice, we found that gives a fair convergence. The calculations can be tested by repeating the process with another initial set of basis functions. Obtaining close results is a reliable indication that the energy is converged. This method allows to significantly reduce the computer times and memory requirements.
III The nucleus
The energy convergence is illustrated in Fig. 2 for several values. We use the Minnesota parameter which reproduces the experimental binding energy with respect to the threshold ( MeV). Experimental states are shown on the right part of the figure. The calculation predicts a excitation energy in excellent agreement with the experiment, although a state is found below the experimental energy. The convergence is reasonable with about 400 basis functions. We find and states whose energies differ by MeV from the experiment. The state is known to have an He cluster structure FBD99 , and its theoretical energy might be slightly improved by constraining the random selection to such configurations. For the negative-parity states, a different value would permit to reproduce more precisely the experimental energy.

The ground-state proton and neutron densities of the ground state are presented in Fig. 3. The transition density between an initial state and a final state is defined as
(7) |
where is the isposin of nucleon , and the signs ”+” and ”-” correspond to the neutron and proton densities, respectively. These densities are expanded in multipoles Ka81 as
(8) |
and are computed as explained in Ref. DI18 . The monopole () densities of the ground state are normalized such that
(9) |
where and for the nucleus.

As expected, the neutron density extends to larger distances, owing to the presence of the external neutrons. From these densities, we obtain the rms radii presented in Table 1, and compared with the experimental data of Ref. THH85 . The proton radius is an excellent agreement with experiment, but the matter radius is slightly larger. Notice that the experimental values are partly model dependent.
With the GCM wave functions, we can also compute the E2 transition probability. Our value is lower than experiment, which suggests that an effective charge is necessary. This is not surprising in neutron-rich nuclei, where polarization effects usually require an effective charge which simulates neutron effects.
To have a deeper insight on the structure, we have investigated energy curves, where one of the generator coordinate is fixed. The energy curves are presented in Fig. 4 for and . Figure 4(a) shows that the minimum of the energy is obtained for fm, which is lower than in 9Be ( fm) but still significant. The -cluster structure is stronger for , in agreement with the He configuration suggested in Ref. FBD99 . For , the minimum is found near fm. For , however, the energy is minimum near fm. This result stresses the importance of a 4-body model for . A simple dineutron approximation for the external neutrons would not provide accurate wave functions.

IV The nucleus
The nucleus has attracted much interest over the last decades, owing to the well-known parity inversion TU60 and to the low binding energy of the ground state. This property makes an ideal example of a one-neutron halo nucleus. Many microscopic studies have been devoted to : the GCM De97 ; De02 , the AMD KHD01 and, more recently the No Core Shell Model CNR16 where it is shown an explicit treatment of the cluster structure is necessary to reproduce the large transition probability between the ground state and the first excited state. In most models, however, the parity inversion cannot be reproduced with a common interaction. A parity-dependent interaction must be adopted.
In the present work, we aim to investigate the structure in the framework of a multicluster approach. An improvement with respect to Ref. De02 is the use of a more efficient method to select the optimal basis, and therefore to get more precise properties of . As mentioned in the introduction, the GCM description of involves 9 generator coordinates, and the use of the SVM turns out to be quite useful to keep the basis within reasonable sizes.
We first illustrate the energy convergence of various states in Fig. 5. The admixture parameter has been adjusted to the experimental neutron separation energy. With for positive parity and for negative parity, we reproduce the energy of the and states ( MeV and MeV, respectively, with respect to the threshold). Reproducing the experimental binding energies is crucial for the asymptotic part of the wave functions. Figure 5 shows that a fair convergence can be achieved with about basis functions. A similar number of basis functions has been employed for the 6-nucleon description of 6Li SH19 . The model not only provides the ground state and the first excited state, but a realistic description of low-lying resonances is also obtained. For these resonances, the energies are in reasonable agreement with the experiment.

Figure 6 presents the proton and neutron densities for the and states. For both states, the proton density is rather peaked near the origin. In contrast, the neutron densities extend to large distances. This is a well-known effect, due to the weak binding energy of the last neutron. The rms radii, obtained from the densities, are displayed in Table 2. The proton and matter radii of the ground state are smaller than the experimental values, a result consistent with the previous study of Ref. De02 . Most likely, other configurations are necessary to improve the comparison with experiment. The value is also underestimated by the GCM. This was already observed in previous multicluster calculations KHD01 ; De02 , and in the NCSM CNR16 . The authors of Ref. CNR16 suggest that an explicit account of configurations is necessary to reproduce the large experimental value.

In Fig. 7, we analyse various energy curves of . In each case, a generator coordinate is kept fixed, and the SVM is applied to the eight remaining generator coordinates. Although these curves cannot be strictly considered as potentials, they provide a valuable insight into the structure of . The minimum for is found near fm, i.e. a value smaller than in . This result confirms that the distance decreases when the number of external nucleon increases De02 . For , the minimum is rather flat up to fm. Large values are therefore unlikely. The dependence is quite interesting: it shows a weak variation of the total energy. Consequently, it is important to include several configurations covering a wide interval. This conclusion holds for all considered states. The dependence on , i.e. on the distance between the c.m. and the third neutron, presents a flat minimum around 2 fm.

V Conclusion
The main goal of this paper is to investigate the and nuclei within a microscopic multicluster model. The only adjustable parameter is the admixture parameter , involved in the Minnesota interaction, and fitted on the binding energy of the ground states. A challenge with many-body approaches is to cope with a large number of generator coordinates or, in other words, with a large number of degrees of freedom. We have confirmed that the SVM provides an excellent framework to address this issue. Although computer times are still quite long, they remain within reasonable limits on modern computers.
The multicluster model is based on two clusters, and 2 or 3 surrounding neutrons. It provides an excellent description of the low-energy spectrum of both nuclei. In particular, is nicely reproduced, not only for bound states but also for resonances. The stability of the energies with the number of basis functions (see Fig. 5) shows that we also have a fair description of the continuum.
We have used the GCM wave functions to compute various properties. In particular, the and densities could be used to determine folding potentials. In , the rms radii are in good agreement with the experiment. A small effective charge should be introduced to improve the agreement for the value. The rms radii in , however, are somewhat underestimated, and the value is much smaller than the experiment. This is not surprising in a multicluster model De02 ; KHD01 , and even in the NCSM CNR16 . As suggested in Ref. CNR16 , couplings to configurations should be introduced explicitly.
Finally, we have analysed the structure of and with the energy curves, where one of the generator coordinates is fixed. This approach provides a qualitative overview of the nucleus. The clustering decreases from to . It should likely disappear for heavier Be isotopes, such as 14Be.
Acknowledgement
P. D. acknowledges the hospitality of the Yukawa Institute for Theoretical Physics, where most of this work was performed. This work was supported by the Fonds de la Recherche Scientifique - FNRS under Grant Numbers 4.45.10.08 and J.0049.19. Computational resources have been provided by the Consortium des Équipements de Calcul Intensif (CÉCI), funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S.-FNRS) under Grant No. 2.5020.11 and by the Walloon Region. P. D. is Directeur de Recherches of F.R.S.-FNRS, Belgium.
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