Mechanisms of proton spin dephasing in a system of magnetic particles
Bibliographic record
Abstract
For protons diffusing among a system of magnetic particles, the process by which initial phase coherence is lost depends substantially on particle size. In this article, evidence for three dephasing mechanisms is presented: an incremental process at small particle sizes (motional averaging regime), a discrete process at intermediate particle sizes (visit limited regime), and a continuous process at large particle sizes (static dephasing regime). While motional averaging regime and static dephasing regime are well known, the distinct dynamics in visit limited regime are often overlooked. Revisiting earlier analytic treatments for the dynamics in this regime, Monte Carlo simulations are performed to extract the details of dephasing and to test the concept of an inner zone of rapid dephasing herein named the full dephasing zone. It is shown that the emergence of a full dephasing zone marks the transition from motional averaging regime to visit limited regime since protons can be fully dephased in a single encounter. Moving from the visit limited regime to the static dephasing regime, a crossover between a purely discrete process and a purely continuous process occurs. Developing a simple model of the dephasing process, the average dephasing time is demonstrated to be relatively constant thus giving insight into the long lasting plateau in the relaxation rate.
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 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 | 0.000 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".