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Abstract We measured the production cross sections and momentum distributions of proton-rich radioactive isotopes (RIs) whose atomic numbers were 18–37. These isotopes were produced by the projectile fragmentation of a 345-MeV/nucleon $$^{78}$$Kr beam impinged on a 5-mm Be target. The cross sections close to the stability region were reproduced fairly well by the semi-empirical formulas, EPAX3.1a and FRACS1.1. However, these formulas tend to overestimate the cross sections of the RIs near the proton drip line, sometimes by as much as 100-fold. The Abrasion–Ablation model in the LISE$$^{++}$$ package was employed, using different mass table variations, to describe the experimental results in this region. The best agreement was achieved when the Weizsäcker-Skyrme microscopic-macroscopic mass formula (WS4$$_{\mathrm{RBF}}$$) and a version of the nonrelativistic Hartree–Fock–Bogoliubov mass model (HFB22) were used. The momentum distribution was represented well by an asymmetric Gaussian distribution. The width of the high-momentum side of the distribution was reproduced fairly well by the Goldhaber model, whereas the width of the low-momentum side was 1.1 times larger than that of the high-momentum side. Moreover, an exponential-shaped low-momentum tail was observed, which began from a height of approximately 1/100–1/1000 of the momentum peak. The momentum means were not reproduced well by Morrissey’s empirical formula: additional velocity loss to the formula was observed. The yield of $$^{68}$$Br was smaller than the expected yield, as estimated from the yield systematics of its neighboring RIs. Assuming an in-flight decay in the separator, the half-life of $$^{68}$$Br was estimated to be $$105^{+62}_{-25}$$ ns. 

Properties of the nuclear equation of state (EoS) can be probed by measuring the dynamical properties of nucleus-nucleus collisions. In this study, we present the directed flow (v1), elliptic flow (v2) and stopping (VarXZ) measured in fixed target Sn+ Sn collisions at 270AMeV with the S'll'RlT Time Projection Chamber. We perform Bayesian analyses in which EoS parameters are var­ied simultaneously within the Improved Quantum Molecular Dynamics-Skyrme (ImQMD-Sky) transport code to obtain a multivariate correlated constraint. The varied parameters include symmetry energy, S0, and slope of the symme­try energy, L, at saturation density, isoscalar effective mass, m;/mN, isovector effective mass, m􀀒/mN and the in-medium cross-section enhancement factor rJ. We find that the flow and VarXZ observables are sensitive to the splitting of proton and neutron effective masses and the in-medium cross-section. Compar­isons of ImQMD-Sky predictions to the S'll' RJT data suggest a narrow range of preferred values for m;/mN, m􀀕/mN and 1/· 

To tackle problems that can not be solved by current digital computers, many systems propose ideas from physics and neuroscience. The CTDS solver introduced by Ercsey-Ravasz and Toroczkai is one of such system. It solves the satisfiability problem by reducing it to a minimization of a time-varying target function. Although the possibility of an efficient electric circuit implementation of the solver has been shown, in terms of physical realizations, the solver has a problem of unbounded variations of the target function parameters. Here we propose a variant of the solver with bounded target function parameters. It includes several possible modifications of the solver in system parameter differences. We also show the basic characteristics of the solver, the upper and lower bounds of the target function parameters. 

To tackle problems that can not be solved by current digital computers, many systems propose ideas from physics and neuroscience. The CTDS solver introduced by Ercsey-Ravasz and Toroczkai is one of such system. It solves the satisfiability problem by reducing it to a minimization of a time-varying target function. Although the possibility of an efficient electric circuit implementation of the solver has been shown, in terms of physical realizations, the solver has a problem of unbounded variations of the target function parameters. Here we propose a variant of the solver with bounded target function parameters. It includes several possible modifications of the solver in system parameter differences. We also show the basic characteristics of the solver, the upper and lower bounds of the target function parameters.