PaperPanorama

Nuclear Experiment·nucl-ex

Mon·Sep 6, 2021

4 papers—1 primary·3 cross-listed·reconstructed*

  1. 01*

    System size and energy dependence of resonance production in ALICE

    Vikash Sumberia (for the ALICE Collaboration)🇮🇳

    Hadronic resonances, thanks to their relatively short lifetimes, can be used to probe the properties of the hadronic phase in ultrarelativistic heavy-ion collisions. In particular their lifetimes are exploited to investigate the interplay between particle rescattering and regeneration after hadronization. In this contribution we present recent results on , (892), (1020), (1385), and production in pp, pPb, PbPb and XeXe collisions at LHC energies.

    nucl-exhep-exEPJ Web Conf.(2022)·0 citations
  2. 02*

    Search for Majoron-emitting modes of Xe double beta decay with the complete EXO-200 dataset

    S. Al Kharusi🇨🇦 · G. Anton🇩🇪 · I. Badhrees🇨🇦 · P.S. Barbeau🇺🇸 · D. Beck🇺🇸 · V. Belov🇷🇺 · T. Bhatta🇺🇸 · M. Breidenbach🇺🇸 · T. Brunner🇨🇦 · G.F. Cao🇨🇳 · W.R. Cen🇨🇳 · C. Chambers🇨🇦 and 94 other authors

    A search for Majoron-emitting modes of the neutrinoless double-beta decay of Xe is performed with the full EXO-200 dataset. This dataset consists of a total Xe exposure of 234.1 kgyr, and includes data with detector upgrades that have improved the energy threshold relative to previous searches. A lower limit of T4.310 yr at 90\% C.L. on the half-life of the spectral index Majoron decay was obtained, a factor of 3.6 more stringent than the previous limit from EXO-200, corresponding to a constraint on the Majoron-neutrino coupling constant of -. The lower threshold and the additional data taken resulted in a factor 8.4 improvement for the mode compared to the previous EXO search. This search provides the most stringent limits to-date on the Majoron-emitting decays of Xe with spectral indices and 7.

    ↳ hep-exnucl-exPRD(2021)·38 citations
  3. 03*

    Bayesian evaluation of residual production cross sections in proton induced spallation reactions

    Peng Dan · Hui-Ling Wei🇨🇳 · Xi-Xi Chen · Xiao-Bao Wei · Yu-Ting Wang🇨🇳 · Jie Pu🇨🇳 · Kai-Xuan Cheng · Chun-Wang Ma🇨🇳

    The Bayesian neural network (BNN) method is used to construct a predictive model for fragment prediction of proton induced spallation reactions with the guidance of a simplified EPAX formula. Compared to the experimental data, it is found that the BNN + sEPAX model can reasonably extrapolate with less information compared with BNN method. The BNN + sEPAX method provides a new approach to predict the energy-dependent residual cross sections produced in proton-induced spallation reactions from tens of MeV/u up to several GeV/u.

    ↳ nucl-thnucl-exJ.Phys.G(2022)·19 citations
  4. 04*

    Evidence of quadrupole and octupole deformations in Zr+Zr and Ru+Ru collisions at ultra-relativistic energies

    Chunjian Zhang🇺🇸 · Jiangyong Jia🇺🇸

    In the hydrodynamic model description of heavy ion collisions, the elliptic flow and triangular flow are sensitive to the quadrupole deformation and octupole deformation of the colliding nuclei. The relations between and have recently been clarified and were found to follow a simple parametric form. The STAR Collaboration have just published precision data from isobaric Ru+Ru and Zr+Zr collisions, where they observe large differences in central collisions and . Using a transport model simulation, we show that these orderings are a natural consequence of and . We reproduce the centrality dependence of the ratio qualitatively and ratio quantitatively, and extract values of and that are consistent with those measured at low energy nuclear structure experiments. STAR data provide the first direct evidence of strong octupole correlations in the ground state of Zr in heavy ion collisions. Our analysis demonstrates that flow measurements in high-energy heavy ion collisions, especially using isobaric systems, are a new precision tool to study nuclear structure physics.

    ↳ nucl-thhep-phnucl-exPRL(2022)·160 citations

* Reconstructed cohort: no mailing for this day survives in the archive. Papers are grouped by their submission times and arXiv's announcement cut-off, assuming announcement without delay; positions follow identifier order. Validated at ~91% exact-day agreement against the archived era.