MétaCan
Menu
Back to cohort
Record W4388963633 · doi:10.48550/arxiv.2311.13345

Many-body physics-induced selection rules: application to Raman spectroscopy

2023· preprint· en· W4388963633 on OpenAlexafffund
Igor Benek-Lins, Saurabh Maiti

Bibliographic record

VenuearXiv (Cornell University) · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRaman spectroscopySelection (genetic algorithm)Symmetry (geometry)Theoretical physicsPhysicsHomogeneous spaceSpace (punctuation)Subject (documents)Statistical physicsQuantum mechanicsComputer scienceMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

Spectroscopic measurements in quantum systems are subject to selection rules, usually based on space-time symmetries, that allow or disallow transitions between states. In many-body systems, in addition to the single-particle states, there emerge new ones due to collective excitations of the system. Here we demonstrate the existence of a "fragile" selection rule that emerges as a manifestation of many-body effects and outlines the conditions for collective excitations to couple to a given spectroscopic probe beyond the usual symmetry considerations. As an example, we apply the rule to Raman spectroscopy of multiband superconductors and settle some unresolved features in experiments.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.049
GPT teacher head0.214
Teacher spread0.165 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuearXiv (Cornell University)Same topicCold Atom Physics and Bose-Einstein CondensatesFrench-language works237,207