Precision Mass Measurements on Neutron-Rich Rare-Earth Isotopes at JYFLTRAP: Reduced Neutron Pairing and Implications for 
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-Process Calculations

Vilén, M.; Kelly, James; Kankainen, A.; Brodeur, M.; Aprahamian, A.; Cañete, L.; Eronen, T.; Jokinen, A.; Kuta, Trenton; Moore, I. D.; Mumpower, Matthew; Nesterenko, D. A.; Penttilä, H.; Pohjalainen, I.; Porter, William; Rinta‐Antila, S.; Surman, Rebecca; Voss, A.; Äystö, J.

doi:10.1103/physrevlett.120.262701

Cited by 55 publications

(65 citation statements)

References 81 publications

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“…Our dataset combines all experimental masses from AME2003 [42] and AME2016 [43] augmented by the recently measured masses from Refs. [44][45][46][47][48][49][50]. For nuclei where experiments have been repeated, we take the most recent value.…”

Section: Datasetsmentioning

confidence: 99%

Quantified limits of the nuclear landscape

et al. 2020

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Background: The chart of the nuclides is limited by particle drip lines beyond which nuclear stability to proton or neutron emission is lost. Predicting the range of particle-bound isotopes poses an appreciable challenge for nuclear theory as it involves extreme extrapolations of nuclear masses well beyond the regions where experimental information is available. Still, quantified extrapolations are crucial for a wide variety of applications, including the modeling of stellar nucleosynthesis.Purpose: We use microscopic nuclear global mass models, current mass data, and Bayesian methodology to provide quantified predictions of proton and neutron separation energies as well as Bayesian probabilities of existence throughout the nuclear landscape all the way to the particle drip lines. Methods:We apply nuclear density functional theory with several energy density functionals. We also consider two global mass models often used in astrophysical nucleosynthesis simulations. To account for uncertainties, Bayesian Gaussian processes are trained on the separation-energy residuals for each individual model, and the resulting predictions are combined via Bayesian model averaging. This framework allows to account for systematic and statistical uncertainties and propagate them to extrapolative predictions. Results:We establish and characterize the drip-line regions where the probability that the nucleus is particlebound decreases from 1 to 0. In these regions, we provide quantified predictions for one-and two-nucleon separation energies. According to our Bayesian model averaging analysis, 7759 nuclei with Z ≤ 119 have a probability of existence ≥ 0.5. Conclusions:The extrapolation results obtained in this study will be put through stringent tests when new experimental information on existence and masses of exotic nuclei becomes available. In this respect, the quantified landscape of nuclear existence obtained in this study should be viewed as a dynamical prediction that will be fine-tuned when new experimental information and improved global mass models become available.

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Section: Datasetsmentioning

confidence: 99%

Quantified limits of the nuclear landscape

et al. 2020

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“…Our dataset combines all experimental masses from AME2003 [52] and AME2016+, which contains the AME2016 dataset [59] augmented by masses from Refs. [60][61][62][63][64][65][66]. For nuclei where experiments have been repeated, we keep the most recent value.…”

Section: B Datasetsmentioning

confidence: 99%

Beyond the proton drip line: Bayesian analysis of proton-emitting nuclei

et al. 2020

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Background: The limits of the nuclear landscape are determined by nuclear binding energies. Beyond the proton drip lines, where the separation energy becomes negative, there is not enough binding energy to prevent protons from escaping the nucleus. Predicting properties of unstable nuclear states in the vast territory of proton emitters poses an appreciable challenge for nuclear theory as it often involves far extrapolations. In addition, significant discrepancies between nuclear models in the proton-rich territory call for quantified predictions.Purpose: With the help of Bayesian methodology, we mix a family of nuclear mass models corrected with statistical emulators trained on the experimental mass measurements, in the proton-rich region of the nuclear chart.Methods: Separation energies were computed within nuclear density functional theory using several Skyrme and Gogny energy density functionals. We also considered mass predictions based on two models used in astrophysical studies. Quantified predictions were obtained for each model using Bayesian Gaussian processes trained on separation-energy residuals and combined via Bayesian model averaging. Results:We obtained a good agreement between averaged predictions of statistically corrected models and experiment. In particular, we quantified model results for one-and two-proton separation energies and derived probabilities of proton emission. This information enabled us to produce a quantified landscape of proton-rich nuclei. The most promising candidates for two-proton decay studies have been identified. Conclusions:The methodology used in this work has broad applications to model-based extrapolations of various nuclear observables. It also provides a reliable uncertainty quantification of theoretical predictions.

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“…The r-process impact factors F of masses in the region of interest [22]. Mass measurements from this work are circled in red, while black circles indicate those from an earlier study at JYFLTRAP [26]. In total, 22 ground-state masses and two isomeric states in this region have been measured at JYFLTRAP, of which 14 go beyond the limit of known nuclei in AME16 [20].…”

Section: Figmentioning

confidence: 99%

“…The new JYFLTRAP measurements resulted in a smoothening of the calculated rprocess abundance pattern making it closer to the observed solar pattern. After the successful first campaign at JYFLTRAP [26], a second campaign of mass measurements was launched aiming to better understand the formation of the rare-earth abundance peak in the r-process as well as the underlying changes in nuclear structure, in particular beyond N = 100, which has been proposed as a subshell closure by Hartree-Fock calculations [5,33,34]. In this article, we report on the results of the second measurement campaign at JYFLTRAP and study the impact of JYFLTRAP measurements on the r process and nuclear structure in this neutron-rich rare-earth region.…”

Section: Figmentioning

confidence: 99%

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Exploring the mass surface near the rare-earth abundance peak via precision mass measurements at JYFLTRAP

et al. 2020

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The JYFLTRAP double Penning trap at the Ion Guide Isotope Separator On-Line (IGISOL) facility has been used to measure the atomic masses of 13 neutron-rich rare-earth isotopes. Eight of the nuclides, 161 Pm, 163 Sm, 164,165 Eu, 167 Gd, and 165,167,168 Tb, were measured for the first time. The systematics of the mass surface has been studied via one-and two-neutron separation energies as well as neutron pairing-gap and shell-gap energies. The proton-neutron pairing strength has also been investigated. The impact of the new mass values on the astrophysical rapid neutron capture process has been studied. The calculated abundance distribution results in a better agreement with the solar abundance pattern near the top of the rare-earth abundance peak at around A ≈ 165.

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Precision Mass Measurements on Neutron-Rich Rare-Earth Isotopes at JYFLTRAP: Reduced Neutron Pairing and Implications for r -Process Calculations

Cited by 55 publications

References 81 publications

Quantified limits of the nuclear landscape

Quantified limits of the nuclear landscape

Beyond the proton drip line: Bayesian analysis of proton-emitting nuclei

Exploring the mass surface near the rare-earth abundance peak via precision mass measurements at JYFLTRAP

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