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Record W4408719397 · doi:10.1080/23746149.2025.2476417

Integrated topological photonics in one dimension

2025· article· en· W4408719397 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Physics X · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTopological Materials and Phenomena
Canadian institutionsConcordia University
Fundersnot available
KeywordsDimension (graph theory)PhotonicsTopology (electrical circuits)Computer scienceMathematicsEngineeringPhysicsOptoelectronicsPure mathematicsElectrical engineering

Abstract

fetched live from OpenAlex

The field of topological photonics, where the topological properties of an array of photonic structures are used to manipulate and confine light, has become very active. Part of this activity is justified by the potential impact on applications, but a significant interest on the topic comes from the relative ease for understanding fundamental topological physics, particularly through experiments, using light. One-dimensional (and quasi-one dimensional) topological systems are simple enough that they can be understood analytically, but they still present a rich behaviour. The approachable theory, combined with advances in photonic fabrication that allow for making devices that can be modelled as one-dimensional arrays showing topological behaviours, has led to devices like these becoming the go-to platform for achieving a deep understanding of topological features. This short review aims to givereaders a brief introduction to the topic, showcasing implementations based mostly on integrated on-chip-photonics.

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.

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 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: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.278
Teacher spread0.265 · 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