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Title: Constraining the symmetry energy with heavy-ion collisions and Bayesian analyses

Journal Article · · Physics Letters. B
 [1];  [1];  [2];  [1];  [1]; ORCiD logo [3];  [1];  [4];  [4];  [5];  [1];  [6];  [7];  [1];  [1]; ORCiD logo [3]
  1. Michigan State Univ., East Lansing, MI (United States)
  2. China Inst. of Atomic Energy (CIAE), Beijing (China)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. Western Michigan Univ., Kalamazoo MI (United States)
  5. Variable Energy Cyclotron Centre, Kolkata (India)
  6. Hong Kong Univ. (Hong Kong)
  7. Univ. of Texas, Austin, TX (United States)

Efficiency corrected single ratios of neutron and proton spectra in central Sn 112 + 112 Sn and Sn 124 + 124 Sn collisions at 120 MeV/u are combined with double ratios to provide constraints on the density and momentum dependencies of the isovector mean-field potential. Bayesian analyses of these data reveal that the isoscalar and isovector nucleon effective masses, m s m v are strongly correlated. The linear correlation observed in m s m v yields a nearly independent constraint on the effective mass splitting Δ m n p = ( m n m p ) / m N = 0.05 0.09 + 0.09 δ . The correlated constraint on the standard symmetry energy, $$S_0$$ and the slope, L at saturation density yields the values of symmetry energy S ( ρ s ) = 16.8 1.2 + 1.2 MeV at a sensitive density of ρ s / ρ 0 = 0.43 0.05 + 0.05 .

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
89233218CNA000001
OSTI ID:
1623431
Report Number(s):
LA-UR-19-31567; TRN: US2106880
Journal Information:
Physics Letters. B, Vol. 799, Issue C; ISSN 0370-2693
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 38 works
Citation information provided by
Web of Science

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Cited By (2)

Decoding the density dependence of the nuclear symmetry energy journal July 2022
Report from the A.I. For Nuclear Physics Workshop preprint January 2020

Figures / Tables (6)