First simultaneous measurement of the γ-ray and neutron emission probabilities in inverse kinematics at a heavy-ion storage ring
Bibliographic record
Abstract
The probabilities for γ-ray and particle emission as a function of the excitation energy of a decaying nucleus are valuable observables for constraining the ingredients of the models that describe the deexcitation of nuclei near the particle emission threshold. These models are essential in nuclear astrophysics and applications. In this paper, we have for the first time simultaneously measured the γ-ray and neutron emission probabilities of <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"> <a:mmultiscripts> <a:mi>Pb</a:mi> <a:mprescripts/> <a:none/> <a:mn>208</a:mn> </a:mmultiscripts> </a:math> . The measurement was performed in inverse kinematics at the Experimental Storage Ring (ESR) of the GSI/FAIR facility, where a <b:math xmlns:b="http://www.w3.org/1998/Math/MathML"> <b:mmultiscripts> <b:mi>Pb</b:mi> <b:mprescripts/> <b:none/> <b:mn>208</b:mn> </b:mmultiscripts> </b:math> beam interacted through the <c:math xmlns:c="http://www.w3.org/1998/Math/MathML"> <c:mrow> <c:mmultiscripts> <c:mi>Pb</c:mi> <c:mprescripts/> <c:none/> <c:mn>208</c:mn> </c:mmultiscripts> <c:mo>(</c:mo> <c:mi>p</c:mi> <c:mo>,</c:mo> <c:msup> <c:mrow> <c:mi>p</c:mi> </c:mrow> <c:mo>′</c:mo> </c:msup> <c:mo>)</c:mo> </c:mrow> </c:math> reaction with a hydrogen gas jet target. Instead of detecting the γ rays and neutrons emitted by <d:math xmlns:d="http://www.w3.org/1998/Math/MathML"> <d:mmultiscripts> <d:mi>Pb</d:mi> <d:mprescripts/> <d:none/> <d:mn>208</d:mn> </d:mmultiscripts> </d:math> , we detected the heavy beamlike residues produced after γ and neutron emission. These heavy residues were fully separated by a dipole magnet of the ESR and were detected with outstanding efficiencies. The comparison of the measured probabilities with model calculations has allowed us to test and select different descriptions of the γ-ray strength function and the nuclear level density available in the literature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".