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Record W4416504077 · doi:10.1103/x7ly-x5vy

Effects of small-chain superexchange dynamics on spin-orbit-coupled clock spectroscopy

2025· article· en· W4416504077 on OpenAlexaff
Mikhail Mamaev, Ana María Rey, William R. Milner

Bibliographic record

VenuePhysical review. A/Physical review, A · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Frequency and Time Standards
Canadian institutionsUniversity of Toronto
FundersAir Force Office of Scientific ResearchDepartment of Physics, Massachusetts Institute of TechnologyU.S. Department of EnergyNational Science Foundation
KeywordsObservableSpectroscopySuperexchangeOptical latticeLattice (music)Atomic clock

Abstract

fetched live from OpenAlex

Optical lattice clocks have set records in clock precision and accuracy. Continuing to advance their performance, via probing as many atoms as possible for the longest interrogation time affordable, requires experimentally and theoretically studying a many-body lattice system. Motivated by recent experimental results on a Fermi-degenerate three-dimensional optical lattice clock [W. R. Milner et al., Science 388, 503 (2025)], we present a theoretical overview of Ramsey and Rabi spectroscopy in one-dimensional chains. At realistic experimental temperatures and confinement conditions, atoms are spatially localized into small chains of approximately one to five atoms. We show that in the presence of spin-orbit coupling induced by the clock laser, the spectroscopy observables are modified by superexchange interactions within each chain, and depend strongly on the length of the chain. The thermal distribution of chain lengths thus plays a key role in the spectroscopy measurements. Our results offer insight into observable many-body effects in state-of-the-art lattice clocks and suggest new directions for optimizing clock performance.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.346
Teacher spread0.339 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes1
Has abstractyes

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