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Record W7027881897

On the determination of absolute nuclear charge radii for elements without stable isotopes via precision x-ray spectroscopy of lithium-like ions

2018· dissertation· en· W7027881897 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2018
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsEffective nuclear chargeIsotopeCharge radiusRADIUSSpectroscopyCharge (physics)IonAtomic numberCharge density
DOInot available

Abstract

fetched live from OpenAlex

There is currently no method to experimentally determine the absolute charge radius of nuclei for elements that have no stable or extremely long-lived isotope: The standard methods, electron scattering and muonic atom spectroscopy, require macroscopic amounts of the isotope under investigation. Thus, for nuclei with charge $Z > 83$, (uranium is the exception), there are no experimental data for the absolute nuclear charge radius. We are currently developing a technique to measure the absolute charge radius of any heavy isotope of sufficient half-life (order of seconds) using precise x-ray spectroscopy of the electronic 2s-2p transition in lithium-like ions. The finite nuclear size shifts the transition energy by more than 10 eV in these systems, whereas experimentally, the transition energy can be measured absolutely with an accuracy below 100 meV (Beiersdorfer (1998)). In addition, recent progress in QED theory allows us to account for radiative corrections at a comparable level as well (Yerokhin (2006)). As a result, the contribution by the finite nuclear charge distribution can be extracted at the 100 meV level. In this thesis, we will develop a computational approach that allows us to obtain general relationships between the nuclear charge radius of a particular ion, and its 2s-2p transition energy. This is done for every element between lead (Z = 82, A = 208) and uranium (Z = 92, A = 238). Some conclusions are made about the future prospects of the method as experimental and theoretical techniques improve.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.223
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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