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Record W4405627340 · doi:10.1103/dcxb-ql1r

Generation of the complete Bell basis via Hong-Ou-Mandel interference of vector modes

2025· preprint· en· W4405627340 on OpenAlexafffund
Xiaoqin Gao, Dilip Paneru, Francesco Di Colandrea, Yingwen Zhang, Ebrahim Karimi

Bibliographic record

VenuePhysical review. A/Physical review, A · 2025
Typepreprint
Languageen
FieldComputer Science
TopicCellular Automata and Applications
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
FundersMinistero dell'Università e della RicercaGovernment of Jiangsu ProvinceNatural Science Foundation of Jiangsu ProvinceCanada Research ChairsUniversity of Ottawa
KeywordsBasis (linear algebra)Interference (communication)Computer scienceMathematicsTelecommunications

Abstract

fetched live from OpenAlex

Optical vector modes (VMs), characterized by spatially varying polarization distributions, have become essential tools across microscopy, metrology, optical trapping, nanophotonics, and optical communications. Here, we investigate the Hong-Ou-Mandel (HOM) interference of VMs providing a full spatial characterization of the output state. We find that, by carefully selecting the input VMs, it is possible to simultaneously observe all four polarization Bell states and their superpositions in the spatially varying polarization pattern of the two photons. These results represent a significant step in advancing our understanding of HOM interference within structured photons, offering promising avenues for high-dimensional quantum information processing and, in particular, high-dimensional quantum communication, quantum sensing, and advanced photonic technologies reliant on tailored quantum states of light.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.070
GPT teacher head0.370
Teacher spread0.300 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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