Ahmed Salman, Jianrong Zhou, Jianqing Yang, Junpei Zhang, Chuyi Huang, Fan Ye, Zecong Qin, Xingfen Jiang, Syed Mohd Amir, Wolfgang Kreuzpaintner, Zhijia Sun, Tianhao Wang, and Xin Tong

Chin. Phys. Lett.
2022, 39 (6):
062901
.
DOI: 10.1088/0256-307X/39/6/062901

A time-of-flight polarized neutron imaging setup was realized by integrating an in situ pumped polarized $^3$He spin filter and energy dispersive neutron camera on the neutron technique development beamline (BL-20) of the China Spallation Neutron Source (CSNS). Test experiments were performed with a solenoid with aluminum wire as a sample. These demonstrated that polarized radiography with a field of view in diameter 2.0 cm at different wavelengths can be obtained. The wavelength-dependent polarization was used to distinguish the neutron polarization behavior for different positions inside and outside the solenoid. The results of this work show the possibility of applying the technique at CSNS and marks a milestone for future polarized neutron imaging developments.

We investigate the medium modifications of momentum splitting fraction and groomed jet radius with both dynamical grooming and soft drop algorithms in heavy-ion collisions. In the calculation, the partonic spectrum of initial hard scattering in p+p collisions is provided by the event generator PYTHIA8, and the energy loss of fast parton traversing in a hot/dense quantum-chromodynamic medium is simulated with the linear Boltzmann transport model. We predict the normalized distributions of the groomed jet radius $\theta_{\rm g}$ and momentum splitting fraction $z_{\rm g}$ with the dynamical grooming algorithm in Pb+Pb collisions at $\sqrt{s_{\scriptscriptstyle{\rm NN}}}$ = 5.02 TeV, then compare these quantities in dynamical grooming at $a=0.1$, with that in soft drop at $z_{\mathrm{cut}} = 0.1$ and $\beta = 0$. It is found that the normalized distribution ratios Pb+Pb/p+p with respect to $z_{\rm g}$ in $z_{\mathrm{cut}} = 0.1$, $\beta = 0$ soft drop case are close to unity, those in $a=0.1$ dynamical grooming case show enhancement at small $z_{\rm g}$, and Pb+Pb/p+p with respect to $\theta_{\rm g}$ in the dynamical grooming case demonstrate weaker modification than those in the soft drop counterparts. We further calculate the groomed jet number averaged momentum splitting fraction $\langle z_{\rm g} \rangle_{\rm jets}$ and averaged groomed jet radius $\langle \theta_{\rm g} \rangle_{\rm jets}$ in p+p and A+A for both grooming cases in three $p^{\rm ch~jet}_{\scriptscriptstyle{\rm T}}$ intervals, and find that the originally generated well balanced groomed jets will become more momentum imbalanced and jet size less narrowed due to jet quenching, and weaker medium modification of $z_{\rm g}$ and $\theta_{\rm g}$ in the $a =0.1$ dynamical grooming case than in the soft drop counterparts.

Valuable information on dynamics of expanding fluids can be inferred from the response of such systems to perturbations in their initial geometry. We apply this technique in high-energy $^{96}$Ru+$^{96}$Ru and $^{96}$Zr+$^{96}$Zr collisions to scrutinize the expansion dynamics of the quark-gluon plasma, where the initial geometry perturbations are sourced by the differences in deformations and radial profiles between $^{96}$Ru and $^{96}$Zr, and the collective response is captured by the change in anisotropic flow $V_n$ between the two collision systems. Using a transport model, we analyze how the nonlinear coupling between lower-order flow harmonics $V_2$ and $V_3$ to the higher-order flow harmonics $V_4$ and $V_5$, expected to scale as $V_{4\mathrm{NL}}=\chi_4 V_2^2$ and $V_{5\mathrm{NL}}=\chi_5 V_2V_3$, gets modified as one moves from $^{96}$Ru+$^{96}$Ru to $^{96}$Zr+$^{96}$Zr systems. We find that these scaling relations are valid to high precision: variations of order 20% in $V_{4\mathrm{NL}}$ and $V_{5\mathrm{NL}}$ due to differences in quadrupole deformation, octupole deformation, and nuclear skin modify $\chi_{4}$ and $\chi_5$ by about 1–2%. Percent-level deviations are however larger than the expected experimental uncertainties and could be measured. Therefore, collisions of isobars with different nuclear structures are a unique tool to isolate subtle nonlinear effects in the expansion of the quark-gluon plasma that would be otherwise impossible to access in a single collision system.

A two-stage cascade magnetic compression scheme based on field reversed configuration plasma is proposed. The temperature and density of plasma before and after magnetic compression are analyzed. In addition, the suppression of the two-fluid effect and the finite Larmor radius effect on the tilting mode and the rotating mode of major magnetic hydrodynamic instability is studied, and finally, the key physical and engineering parameters of the deuterium–deuterium fusion pulse device are introduced. Further analysis shows that the fusion neutrons can be produced at an energy flux of more than 2 MW/m$^{2}$ per year, which meets the material testing requirements for the fusion demonstration reactor (DEMO). If the recovery of magnetic field energy is taken into account, net energy outputs may be achieved, indicating that the scheme has a potential application prospect as a deuterium–deuterium pulse fusion energy.

We studied the fission properties of neutron-rich nuclei $^{278, 286}$Cf around the end point of $r$-process by microscopic self-consistent approaches. The fission barriers and potential energy surfaces are obtained by constrained static Skyrme Hartree–Fock-BCS calculations. Fission fragments are studied by dynamical time-dependent Hartree–Fock+BCS calculations. Results show that $^{286}$Cf has an octupole deformation at ground state, which can increase the fission barrier height by 1.1 MeV and enhance significantly the spontaneous fission half-life. To search possible fission channels, dynamical calculations with a broad coverage of initial deformations result in two slightly asymmetric peaks around $A=128$ and 150 for $^{278}$Cf, and $A=133$ and 153 for $^{286}$Cf. Very asymmetric fission channels as given by semi-empirical models are not found in our results.

In recent years, machine learning (ML) techniques have emerged as powerful tools for studying many-body complex systems, and encompassing phase transitions in various domains of physics. This mini review provides a concise yet comprehensive examination of the advancements achieved in applying ML to investigate phase transitions, with a primary focus on those involved in nuclear matter studies.