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Record W4415924834 · doi:10.1103/v5g3-vthm

Relativistic effects on the ground state of positronic lithium

2025· article· en· W4415924834 on OpenAlexafffund
D.-X. Zhao, M.-S. Wu, Jun-Yi Zhang, Kedong Wang, Liming Wang, Zhiwei Yan

Bibliographic record

VenuePhysical review. A/Physical review, A · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du CanadaYouth Science Foundation of Henan Normal UniversityNatural Science Foundation of Henan ProvinceNatural Science Foundation of Hainan ProvinceNational Natural Science Foundation of China
KeywordsAnnihilationLithium (medication)Relativistic quantum chemistryBinding energyGround stateBound statePositron

Abstract

fetched live from OpenAlex

Positronic lithium, the first theoretically predicted positronic atom, has yet to be observed experimentally due to its weakly bound nature and short lifetime. Consequently, studies of its structural and annihilation properties can provide valuable guidance for future experimental efforts. In this work, we investigate the relativistic effects on positron binding to atomic lithium by evaluating the expectation values of relativistic operators. Our calculations show that while the total relativistic correction of positronic lithium is comparable in magnitude to the binding energy, the corrections for the bound and dissociated states are nearly identical and largely cancel each other, resulting in only a minor effect on the binding energy. Specifically, the inclusion of relativistic corrections alters the binding energy of positronic lithium and its isotopes by less than 0.13% for spin-triplet states and 0.04% for spin-singlet states. We also calculate the annihilation rates and lifetimes for both spin-triplet and spin-singlet states of positronic lithium.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.327
Teacher spread0.320 · 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.

Study designTheoretical or conceptual
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

Citations1
Published2025
Admission routes2
Has abstractyes

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