Leveraging Reactant Entanglement in the Coherent Control of Ultracold Bimolecular Chemical Reactions
Bibliographic record
Abstract
Entanglement is a crucial resource for achieving quantum advantages in quantum computation, quantum sensing, and quantum communication. As shown in this Letter, entanglement is also a valuable resource for the coherent control of the large class of bimolecular chemical reactions. We utilize an entanglement-enhanced coherent control scheme, in which the initial preparation of the superposition state is divided into two steps: the first entangles the reactants, and the second is responsible for coherent control. This approach can overcome the limitations of traditional coherent control of scattering caused by noninterfering pathways, known as satellite terms. By tuning the amount of entanglement between reactants, the visibility of coherent control in chemical reactions can be modulated and optimized. Significantly, there exists an optimal amount of entanglement, which ensures complete indistinguishability of the reaction pathways, maximizing the extent of control. This entanglement-enhanced coherent control scheme is computationally illustrated using the ultracold KRb + KRb reaction, where perfect control over the parity of the product rotational states is achieved.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".