Net charge fluctuation and string fragmentation

We present simulation results of net charge fluctuation in $Au+Au$ collisions at $\sqrt{s_{nn}}$=130 GeV from a dynamic model, JPCIAE. The calculations are done for the quark-gluon phase before hadronization, the pion gas, the resonance pion gas from $\rho$ and $\omega$ decays and so on. The simulations of the charge fluctuation show that the discrepancy exists between the dynamic model and the thermal model for a pion gas and a resonance pion gas from $\rho$ and $\omega$ decays while the simulated charge fluctuation of the quark-gluon phase is close to the thermal model prediction. JPCIAE results of net charge fluctuation in the hardonic phase are nearly 4-5 times larger than one for the quark-gluon phase, which implies that the charge fluctuation in the quark-gluon phase may not survive the hadronization (string fragmentation) as implemented in JPCIAE.Comment: 9 pages, 3 figure

Energy and centrality dependences of charged multiplicity density in relativistic nuclear collisions

Using a hadron and string cascade model, JPCIAE, the energy and centrality dependences of charged particle pseudorapidity density in relativistic nuclear collisions were studied. Within the framework of this model, both the relativistic $p+\bar p$ experimental data and the PHOBOS and PHENIX $Au+Au$ data at $\sqrt s_{nn}$=130 GeV could be reproduced fairly well without retuning the model parameters. The predictions for full RHIC energy $Au+Au$ collisions and for $Pb+Pb$ collisions at the ALICE energy were given. Participant nucleon distributions were calculated based on different methods. It was found that the number of participant nucleons, $$, is not a well defined variable both experimentally and theoretically. Therefore, it is inappropriate to use charged particle pseudorapidity density per participant pair as a function of$$ for distinguishing various theoretical models.Comment: 10 pages, 4 figures, submitted to Phy. Lett.

Enhancement of singly and multiply strangeness in p-Pb and Pb-Pb collisions at 158A GeV/c

The idea that the reduction of the strange quark suppression in string fragmentation leads to the enhancement of strange particle yield in nucleus-nucleus collisions is applied to study the singly and multiply strange particle production in p-Pb and Pb-Pb collisions at 158A GeV/c. In this mechanism the strange quark suppression factor is related to the effective string tension, which increases in turn with the increase of the energy, of the centrality and of the mass of colliding system. The WA97 observation that the strange particle enhancement increases with the increasing of centrality and of strange quark content in multiply strange particles in Pb-Pb collisions with respect to p-Pb collisions was accounted reasonably.Comment: 8 pages, 3 PostScript figures, in Latex form. submitted to PR

Herschel-ATLAS : The spatial clustering of low and high redshift submillimetre galaxies

We present measurements of the angular correlation function of sub-millimeter (sub-mm) galaxies (SMGs) identified in four out of the five fields of the Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS) − GAMA-9h, GAMA-12h, GAMA-15h and NGP − with flux densities S250μm>30 mJy at 250 μm. We show that galaxies selected at this wavelength trace the underlying matter distribution differently at low and high redshifts. We study the evolution of the clustering finding that at low redshifts sub-mm galaxies exhibit clustering strengths of r0 ∼ 2 − 3 h−1Mpc, below z < 0.3. At high redshifts, on the other hand, we find that sub-mm galaxies are more strongly clustered with correlation lengths r0 = 8.1 ± 0.5, 8.8 ± 0.8 and 13.9 ± 3.9 h−1Mpc at z = 1 − 2, 2 − 3 and 3 − 5, respectively. We show that sub-mm galaxies across the redshift range 1 < z < 5, typically reside in dark-matter halos of mass of the order of ∼ 1012.5 − 1013.0h−1M⊙ and are consistent with being the progenitors of local massive elliptical galaxies that we see in the local Universe

Inclusive and Direct Photons in S + Au Central Collisions at 200A GeV/c

A hadron and string cascade model, JPCIAE, which is based on LUND string model, PYTHIA event generator especially, is used to study both inclusive photon production and direct photon production in 200A GeV S + Au central collisions. The model takes into account the photon production from the partonic QCD scattering process, the hadronic final-state interaction, and the hadronic decay and deals with them consistently. The results of JPCIAE model reproduce successfully both the WA93 data of low p_T inclusive photon distribution and the WA80 data of transverse momentum dependent upper limit of direct photon. The photon production from different decay channels is investigated for both direct and inclusive photons. We have discussed the effects of the partonic QCD scattering and the hadronic final-state interaction on direct photon production as well.Comment: 6 pages with 5 figure

Search for lepton flavor violation in supersymmetric models via meson decays

Considering the constraints from the experimental data on $\mu\rightarrow e\gamma$, $\mu\rightarrow3e$, $\mu-e$ conversion etc., we analyze the Lepton Flavor Violating decays $\phi(J/\Psi,\Upsilon(1S)) \rightarrow e^+\mu^-(\mu^+\tau^-)$ in the scenarios of the minimal supersymmetric extensions of Standard Model with seesaw Mechanism. Numerically, there is parameter space that the LFV processes of $J/\Psi(\Upsilon)\rightarrow\mu^+\tau^-$ can reach the upper experimental bounds, meanwhile the theoretical predictions on $\mu\rightarrow e\gamma$, $\mu\rightarrow3e$, $\mu-e$ conversion satisfy the present experimental bounds. For searching of new physics, Lepton Flavor Violating processes $J/\Psi(\Upsilon)\rightarrow\mu^+\tau^-$ may be more promising and effective channels.Comment: 30 pages, 13 figure

Effects of sand burial and overstory tree age on seedling establishment in coastal Pinus thunbergii forests in the northern Shandong Peninsula, China

Coastal Pinus thunbergii (Japanese black pine) forests in the northern Shandong Peninsula of China recently experienced widespread natural regeneration failure. This study identifies critical factors that affect natural regeneration of P. thunbergii. Seeds from trees of various ages (13-32 years) were used to investigate the effects of age and burial depth in sand on germination and seedling establishment. Results show that seed density in 2-5 cm soil decreased with increased distance from the shoreline. Sand burial decreased seed germination but did not affect the relative growth rate of seedlings at depths from 0.5 to 3 cm. Germination, leaf mass ratio, and relative growth rates were higher with seedlings originating from older trees, all of which enhanced seedling resistance to sand burial. Tree age and seed burial were found to be determining factors for natural regeneration of the coastal P. thunbergii forest. Silvicultural treatments that promote quality of seed sources and mitigation of sand burial can be used in the future to improve the regeneration of these coastal forests

Solving a class of multi-scale elliptic PDEs by Fourier-based mixed physics informed neural networks

Deep neural networks have garnered widespread attention due to their simplicity and flexibility in the fields of engineering and scientific calculation. In this study, we probe into solving a class of elliptic partial differential equations (PDEs) with multiple scales by utilizing Fourier-based mixed physics informed neural networks (dubbed FMPINN), its solver is configured as a multi-scale deep neural network. In contrast to the classical PINN method, a dual (flux) variable about the rough coefficient of PDEs is introduced to avoid the ill-condition of neural tangent kernel matrix caused by the oscillating coefficient of multi-scale PDEs. Therefore, apart from the physical conservation laws, the discrepancy between the auxiliary variables and the gradients of multi-scale coefficients is incorporated into the cost function, obtaining a satisfactory solution of PDEs by minimizing the defined loss through some optimization methods. Additionally, a trigonometric activation function is introduced for FMPINN, which is suited for representing the derivatives of complex target functions. Handling the input data by Fourier feature mapping will effectively improve the capacity of deep neural networks to solve high-frequency problems. Finally, to validate the efficiency and robustness of the proposed FMPINN algorithm, we present several numerical examples of multi-scale problems in various dimensional Euclidean spaces. These examples cover low-frequency and high-frequency oscillation cases, demonstrating the effectiveness of our approach. All code and data accompanying this manuscript will be publicly available at https://github.com/Blue-Giant/FMPINN