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Record W4392988812 · doi:10.1103/physrevb.109.094515

Electronic Raman response of a superconductor across a time reversal symmetry breaking phase transition

2024· article· en· W4392988812 on OpenAlexafffund
Surajit Sarkar, Saurabh Maiti

Bibliographic record

VenuePhysical review. B./Physical review. B · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSuperconductivityCondensed matter physicsSymmetry (geometry)Symmetry breakingPhase transitionRaman spectroscopyPhysicsPhase (matter)Quantum mechanics

Abstract

fetched live from OpenAlex

Polarization-resolved electronic Raman spectroscopy is an important experimental tool to investigate collective excitations in superconductors. In this paper, we present a general theory that allows us to study the evolution of all Raman active collective modes in multiple symmetry channels across a time reversal symmetry (TRS) breaking superconducting transition. This comprehensive approach reveals that multiple modes belonging to different symmetry channels show a tendency to soften, even when the interactions in the subleading channel are held constant. This indicates an increased competition induced by the proximity to the TRS breaking transition. The entry into the TRS broken phase is marked by the introduction of an additional mode into the gap in multiple symmetry channels. This additional modes have a phase character complementary to the ones that are already present. Even though all the modes in the TRS broken phase acquire an amplitude character, we explicitly demonstrate that the coupling to the Raman probe is exclusively through the phase sector. We demonstrate that the Raman spectrum collected in lower symmetry channels shows a selective sensitivity to the sign of the ground-state order parameters and the sign of the interband interactions. Finally, we demonstrate the applicability of an interaction induced selection rule that clearly explains the spectral weights of various modes in various irreducible representations, including the possible of dark Leggett and Bardasis-Schrieffer modes.

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 studies0.0000.000
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 head0.011
GPT teacher head0.392
Teacher spread0.381 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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