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For over a decade, the density dependence of symmetry energy has been a focal point in nuclear physics. Its significance lies in understanding the properties of radioactive isotopes, the dynamics of evolution in low and intermediate energy heavy ion collisions, and various astrophysical phenomena. [1−6]. Although the asymmetry energy term is well constrained at saturation density, its evolution away from the saturation density is still unclear. Isoscaling parameters, which are denoted by α and β, are one of the important probes to examine the symmetry energy at sub-saturation [7−9]. A generalized formula for isoscaling can be obtained via thermodynamic models of nuclear reactions, i.e., for a specific fragment with neutron number N and proton number Z in two systems that share the same environment of reactions (mainly in similar temperatures),
$ \begin{array}{*{20}{l}} R_{21}(N,Z)=Y_{2}(N,Z)/Y_{1}(N,Z)=Ce^{(\alpha N + \beta Z)},\\ \end{array} $
(1) or
$ \begin{array}{*{20}{l}} \ln R_{21}(N,Z)=\ln[Y_{2}(N,Z)/Y_{1}(N,Z)]=\alpha N + \beta Z +\ln C, \end{array} $
(2) where
$ Y_2 $ and$ Y_1 $ denote the yield of a specific fragment$ (N,Z) $ in reactions with sub-indices 2 and 1 denoting$ n/p $ asymmetric and symmetric indices, respectively. Parameters C, α, and β are fitting parameters to yield ratio$ R_{21}(N,Z) $ . It is generally known that α and β are sensitive to the$ n/p $ composition of emitting sources. Furthermore, α and β are in forms of$ \begin{aligned}[b]& \alpha=(\mu_{n}^{(2)}-\mu_{n}^{(1)})/T, \\ &\beta=(\mu_{p}^{(2)}-\mu_{p}^{(1)})/T, \end{aligned} $
(3) where
$ \mu_n $ ($ \mu_p $ ) is the chemical potential of free neutrons (protons) in the reaction system, and thus, α (β) denotes the difference in the neutron (proton) chemical potential between two reaction systems. Numerous experiments and theoretical models demonstrated that isoscaling applies to a variety of reaction mechanisms dominated by phase spaces, including evaporation, multi-fragmentation, and deeply inelastic scattering and fission [7−10]. In statistical and dynamical models [9, 11, 12], the isoscaling parameter α is related to the symmetry energy coefficient$ C_{\rm sym} $ and isotopic composition of the compound system ($ N_{s} $ ,$ Z_{s} $ ),$ \begin{split}& \alpha(Z)=4C_{\rm sym}(A,Z,T)\Delta(Z_{s}/A_{s})^2/T,\\ &\Delta[(Z_{s}/A_{s})^2]=(Z_{s}/A_{s})_{1}^2-(Z_{s}/A_{s})_{2}^2. \end{split} $
(4) In a similar fashion,
$ \begin{split}& \beta(N)=4C_{\rm sym}(A,Z,T)\Delta(N_{s}/A_{s})^2/T,\\& \Delta[(N_{s}/A_{s})^2]=(N_{s}/A_{s})_{1}^2-(N_{s}/A_{s})_{2}^2. \end{split} $
(5) The value of
$C_{\rm sym}$ is determined by the average nuclear density and the temperature T of the emitting source [12, 13]. Hence, measuring$ R_{21}(N,Z) $ can probe the density dependence of symmetry energy [9, 14].A quantity η is defined to label the ratio
$ \beta(N)/\alpha(Z) $ related to a specific fragment,$ \eta=\frac{\beta(N)}{\alpha(Z)}=\frac{(N_{s}/A_{s})_{1}^2-(N_{s}/A_{s})_{2}^2}{(Z_{s}/A_{s})_{1}^2-(Z_{s}/A_{s})_{2}^2}, $
(6) where
$ \beta(N) $ and$ \alpha(Z) $ are determined from its isotonic and isotopic chains, respectively. By definition, η reflects the degree of difference between the proton density and neutron density of the colliding source where the fragment is formed. According to Refs. [12, 15], in the absence of isospin symmetry breaking,$ \begin{array}{*{20}{l}} |\beta(N)| = \alpha(Z). \end{array} $
(7) Various experimental and theoretical studies have shown that isoscaling can work very well when
$ N/N_{s} $ and$ Z/Z_{s} $ are small ($ \leq $ 0.35) [7−9]. If one extends observations to a smaller system ($ N_{s} $ ,$ Z_{s} $ ) or larger fragment ($ N,Z $ ), more precisely, to larger$ N/N_{s} $ and$ Z/Z_{s} $ , deviations are expected. Historically, isoscaling has been primarily interpreted and implemented within the context of the grand canonical ensemble, based on the assumption that fragment production occurs after a statistical equilibrium state is attained. However, the influence of the asymmetry energy may lead to differences in the neutron and density distribution in neutron-rich nuclei, potentially impacting α and β, especially for small systems subject to volume effects. In Ref. [16], the phenomenon of deviation from isoscaling was discussed. The authors successfully explained the deviations in the experimental data based on small systems via canonical model as opposed to the grand canonical model. Some experimental observations suggested a strong decrease in isoscaling parameters with increasing centrality to values smaller than 50% of those obtained for the peripheral groups [17]. Additionally, it was shown that the isoscaling parameters were different for emitted and projectile-like fragments [18]. Various molecular dynamics simulation studies have shown that isoscaling parameters vary wildly with the evolution of the reaction system [19]. These experimental and theoretical results underscore the significance of comprehending how isoscaling parameters vary with fragments originating from distinct collision zones, which may exhibit diverse production mechanisms or nuclear density distributions.In this study, the isoscaling properties for neutron-rich fragments produced in highly asymmetric systems were examined. The analysis was conducted based on the inclusive experimental results by Mocko et al. [20]. The fragments were grouped based on their neutron-excess (
$I \equiv N-Z$ ). Specifically, the fragments within the same group were assumed to share the same environment, i.e., the same colliding region, temperature, and nuclear density. We employed experimental data (if available), the Heavy Ion Phase Space Exploration model (HIPSE) plus SIMON simulations, and the Antisymmetrized Molecular Dynamic (AMD) model plus GEMINI simulations to investigate the variations in the isoscaling parameters derived from fragments belonging to different groups. Furthermore, the$ |\beta(N)| \sim \alpha(Z) $ correlation for a specific fragment was adopted to explore the degree of difference between proton density and neutron density of two collision sources where the fragment is formed.This paper is structured as follows. First, the HIPSE and AMD models, as well as the decay codes, SIMON and GEMINI, are briefly introduced in Sec. II. The isotopic distributions are compared in Sec. III.A. The isoscaling behaviors of fragments in the measured 140 MeV/u
$ ^{58,64} $ Ni +$ ^9 $ Be projectile fragmentation reactions are discussed in Sec. III.B. The$ |\beta(N)| \sim \alpha(Z) $ correlations for$^{40, 48}$ Ca,$^{58, 64}$ Ni, and$^{78, 86}$ Kr induced projectile fragmentation reactions are discussed in Sec. III.C. The results are summarized in Sec. IV. -
The HIPSE model was proposed to examine the reaction process with few important parameters in a fully microscopic manner based on a macroscopic-microscopic "phenomenology" and accounts for both the dynamical and statistical properties of nuclear collisions [21]. It has been employed to narrow the divide between statistical models and molecular dynamics models, simplifying the reaction's description to a handful of key parameters and reducing CPU computation time. Leveraging the sudden approximation and geometric hypothesis, it efficiently models heavy-ion interactions across the intermediate energy spectrum for any impact parameter. The HIPSE model breaks down a nuclear reaction into three distinct stages: the collision's approach phase, formation of partitions, and exit channel along with the after-burner phase leading to the detectors.
The interaction between the projectile (
$ A_{P},Z_{P} $ ) and target ($ A_{T},Z_{T} $ ) is simplified as two classical particles, following the evolution associated with the Hamiltonian,$ E_{0}=\frac{p^{2}}{2\mu}+V_{A_{T}A_{P}}(r), $
(8) where
$ E_{0} $ denotes the available energy in the center of mass, p denotes the relative momentum, and μ denotes the reduced mass. Furthermore,$ V_{A_{T}A_{P}}(r) $ denotes the interaction potential between the target and projectile with$ r=|r_{T}-r_{P}| $ , indicating the relative distance. When$ r > (R_{T}+R_{P}) $ ($ R_{T} $ and$ R_{P} $ denote radii of the target and the projectile respectively), use the proximity potential. When$ r \leq (R_{T}+R_{P}) $ , use a simple approximation for the construction of the potential. It is assumed that$ V_{A_{T}A_{P}} $ depends uniquely on r even for a small relative distance. The potential between$ r=0 $ and$ r=R_{T}-R_{P} $ is interpolated using a third-order polynomial and assuming continuity of the derivative of the potential at each point. The value retained at r = 0 is conveniently expressed as$ \begin{array}{*{20}{l}} V(r=0)=\alpha_{a}V_{A_{T}A_{P}}^{\rm Froz}(r=0), \end{array} $
(9) where
$ \alpha_{a} $ denotes an adjustable parameter.$V_{A_{T}A_{P}}^{\rm Froz}(r=0)$ denotes the energy of the system given that the two densities of the system overlap completely in the froze density approximation.The coalescence algorithm is used to create fragments from nucleons. First, one of the nucleons is randonly selected, and it constitutes a coalescence point from which a fragment is built; the other nucleon i in the overlap region is then selected at random. The nucleon i can be captured by the cluster labeled 1 based on the existence condition and position and momentum conditions. First, we check whether the nuclear exists in the experimental mass table, and then the fragment is formed based on the position
$ r_{i} $ and momentum$ p_{i} $ of the nucleon as follows$ \frac{p_{i}^{2}}{2m}+\frac{V_{\rm cut}}{1+\exp\left[\dfrac{r_{i}-d_{f}}{a}\right]}<0, $
(10) where m denotes the nucleon mass, and
$ d_{f} $ ,$V_{\rm cut}$ , a denote adjustable parameters.During the final state interaction and reaggregation phase, the motion of each cluster is determined by the Hamiltonian,
$ H=\sum\frac{P_{i}^{2}}{2mA_{i}}+\sum V_{AiAj}(|R_{i}-R_{j}|). $
(11) After this first propagation at high density and the reaggregation phase, the clusters recombine and only the Coulomb interaction between fragments is considered. Subsequently, the model can be coupled with SIMON decay code, an event generator code based on Weisskopf emission rates first proposed by D. Durand [22]. The physics used to describe the decay of the various fragments is based on the statistical model considering the narrowest discrete states for
$ Z \leq $ 9 as well as in-flight evaporation. The HIPSE model directly incorporates the SIMON code to account for the de-excitation process of fragments, completing the entire nuclear reaction process.The HIPSE model is based on providing a generator of events where it is expected that parameters do not change with the entrance channel. It only includes three adjustable parameters
$ \alpha_{a} $ ,$ x_{ex} $ , and$x_{\rm coll}$ , which denote the hardness of the potential, percentage of exchange between projectile and target, and percentage of nuclear-nuclear collisions, respectively. These parameters only depend on beam energy. The values of the parameters are adjusted for beam energies of 10, 25, 50, and 80 MeV/u. In the study, values of$ \alpha_{a}= $ 0.55,$ x_{ex}= $ 0.09, and$x_{\rm coll}=$ 0.18 were chosen for the beam energy of 140 MeV/u [23]. Approximately 1,000,000 events were simulated for collisions involving Ca isotopes ($ ^{40} $ Ca,$ ^{48} $ Ca) and Ni isotopes ($ ^{58} $ Ni,$ ^{64} $ Ni) with a$ ^{9} $ Be target. The impact parameter ranges from 0 to 6 fm for$ ^{40,48} $ Ca +$ ^{9} $ Be collisions and from 0 to 8 fm for$ ^{58,64} $ Ni and$ ^{78,86} $ Kr +$ ^{9} $ Be collisions. The SIMON code was coupled with the HIPSE model at 300 fm/c for$ ^{40,48} $ Ca +$ ^{9} $ Be collisions and at 500 fm/c for$ ^{58,64} $ Ni and$ ^{78,86} $ Kr +$ ^{9} $ Be collisions. -
The Antisymmetrized molecular dynamics (AMD) model [24] is a microscopic model for nuclear collision that describes the nuclear reaction at the microscopic level of interactions of individual nucleons. In AMD, the nuclear many body system can be expressed by a Slater determinant of Gaussian wave packets as follows:
$ \begin{array}{*{20}{l}} <{{\bf{r}}}_{1}\cdot\cdot\cdot {\bf{r}}_{A}|\Phi({\bf{Z}})>= {\rm det}\,[\varphi_{{\bf{Z}}_{i}}({\bf{r}}_{j})\chi_{\alpha_{i}}(j)], \end{array}$
(12) where the spatial wave functions of nucleons can be expressed:
$ <{{\bf{r}}}|\varphi_{{\bf{Z}}}>=\left(\frac{2\nu}{\pi}\right)^{3/4}\exp \left\{-\nu\left({{\bf{r}}}-\frac{{\bf{Z}}}{\sqrt{\nu}}\right)^{2}+ \frac{1}{2}{\bf{Z}}^{2}\right\}, $
(13) Furthermore,
$ \chi_{\alpha} = p\uparrow, p\downarrow, n\uparrow, $ or$ n\downarrow $ denotes the spin-isospin wave function. Additionally,$ \varphi_{Z} $ denotes the wave function in phase space. The width parameter$\nu=2.5~\rm fm^{-2}$ is treated as constant parameter common to all the wave packets. The complex variables${{\bf{Z}}\equiv \{{\bf{Z}}_{i};\;i=1,\,2,...,A\}}$ , where A denotes the number of nucleons in the system, are the centroids of the wave packets. The equation of motion for Z derived from the time-dependent variational principle can be expressed as follows:$ {\rm i} \hbar \sum\limits_{j\tau}C_{i\sigma,j\tau}\frac{{\rm d} Z_{j\tau}}{{\rm d}t}=\frac{\partial H}{\partial Z_{i\sigma}^{\ast}}, $
(14) where
$ C_{i\sigma,j\tau} $ denotes a Hermitian matrix, and H denotes the expectation value of the effective Hamiltonian after the subtraction of the spurious kinetic energy of the zero-point oscillation of the center of masses of fragments [25],$ H(Z)=\frac{<\Phi(Z)|H|\Phi(Z)>}{<\Phi(Z)|\Phi(Z)>}-\frac{3\hbar^{2}\nu}{2M}A+T_{0}(A-N_{F}(Z)), $
(15) where
$ N_{F}(Z) $ denotes the fragment number and$ T_{0} $ is treated as a free parameter to adjust the binding energies of nuclei. The quantum Hamiltonian,$ H=\sum\limits_{i}^{A}\frac{{\bf{p}}_{i}^{2}}{2M}+\sum\limits_{i<j}v_{ij} $
(16) includes an effective nucleon-nucleon interaction such as the Gogny force and the Skyrme force. All AMD simulations discussed in this paper are based on the Gogny interaction force [26].
The original AMD model has been extended to enhance the prediction of fragment production in heavy-ion collision. The AMD-V [27, 28] or AMD/D elsewhere [29] utilized in this study represents the first extended version of AMD with quantum branching process. This introduces the diffusion process, triple-loop approximation, and wave packet shrinking process by the mean field field propagation to improve the reproduction of the fragmentation data and significantly reduce computation time for heavier collision systems [30]. The comparable production cross sections of α particles to nucleons in heavy-ion collisions indicate a strong cluster correlation effect in reality. To more explicitly account for cluster correlations in AMD, Ono developed the AMD-Cluster and introduced inter-cluster correlation as a stochastic process of inter-cluster binding in the AMD-Cluster [31, 32], which was not considered in this study.
To compare the results with the experimental data, it is usually necessary to perform some simulations with various impact parameters to obtain the production cross sections of the fragments, the particle energy spectra, and so on. The statistical decay code is based on the GEMINI code [33], which is a widely used code to treat the sequential decay of hot fragments. A Monte Carlo technique is employed to follow the decay chains of individual compound nuclei via sequential binary decays until the products cannot undergo further decay. The Hauser-Feshbach formalism [34] is adopted to calculate the decay width for the evaporation of fragments with
$ Z \leq $ 2. In this study, we performed the AMD-V simulations of$ ^{40} $ Ca,$ ^{48} $ Ca,$ ^{58} $ Ni and$ ^{64} $ Ni projectile on the$ ^{9} $ Be target at 140 MeV/u, adopting the same impact parameters and coupled time as the HIPSE plus SIMON simulation.$ ^{78,86} $ Kr+$ ^{9} $ Be collisions were not simulated due to the time-consuming nature of AMD simulation.
Isoscaling properties for neutron-rich fragments in highly asymmetric heavy ion collision systems
- Received Date: 2023-12-22
- Available Online: 2024-06-15
Abstract: Traditionally, isoscaling has been interpreted and applied within the framework of the grand canonical ensemble, based on the assumption that fragment production occurs following the attainment of a statistical equilibrium state. However, the influence of the symmetry energy can lead to differences in the neutron and density distribution in neutron-rich nuclei. This in turn may impact the isoscaling parameters (usually denoted by α and β). We examine the isoscaling properties for neutron-rich fragments produced in highly asymmetric systems on inverse kinematics, namely