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Record W4416118735 · doi:10.48550/arxiv.2504.05133

Control and Transient Spectroscopy of Engineered Spin-Cavity Back-Action

2025· preprint· en· W4416118735 on OpenAlexfundno aff
Fatemeh Fani Sani, George Nichols, Ivar Taminiau, Saba Sadeghi, Hamid Reza Mohebbi, David G. Cory, Troy W. Borneman

Bibliographic record

VenueArXiv.org · 2025
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsnot available
FundersCanada First Research Excellence Fund
KeywordsMesoscopic physicsMicrowaveCoupling (piping)ResonatorSpin (aerodynamics)Radiation dampingTransient (computer programming)Spectroscopy

Abstract

fetched live from OpenAlex

We present an experimental arrangement that permits engineering of cavity back-action on a mesoscopic spin ensemble. By coupling a superconducting thin-film Nb microstrip resonator to a Trityl OX63 electron spin sample, we access different regimes of spin-cavity dynamics by designing the ensemble size, effective coupling strength, cavity temperature, and spin saturation. We performed transient spectroscopy measurements under continuous microwave drive in the strong radiation damping regime. These measurements exhibit a long-lived plateau response that distinguishes important features of spin-cavity models, such as the radiation damping Bloch equations and Maxwell-Bloch equations. We demonstrate control of the plateau response through adjustment of temperature, microwave drive power, and variable spin saturation. The presented experimental arrangement serves as a robust system to explore the space of spin-cavity dynamics and develop new quantum devices that harness the complexity of mesoscopic spin ensembles coherently interacting with high quality factor cavities.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.260
Teacher spread0.242 · 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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