Multi-Dimensional Spectroscopy with Intense Entangled Beams: Entanglement-Enabled Phase Matching in a Collinear Beam Geometry
Bibliographic record
Abstract
The experimental realization of quantum molecular spectroscopy with entangled photons remains challenging owing to the low signal-to-noise ratio resulting from the use of low-flux entangled photons. High-flux entangled photons via intense entangled beams can be used to improve the signal-to-noise ratio, but the presence of unentangled photons contaminates the quantum signal stemming from entangled photons. Here, we demonstrate how intense entangled beams can be used in multi-dimensional spectroscopy while retaining the advantage of photon entanglement. Our approach is broadly applicable to odd-ordered nonlinear spectroscopies, and it generates purely quantum spectroscopic signals. The proposed approach allows the recording of desired phase-matched signals even in a collinear beam geometry, which lifts the requirement of complicated beam geometry setups for phase matching in multi-dimensional spectroscopies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".