What makes a particle detector click
Bibliographic record
Abstract
We highlight fundamental differences in the models of light-matter interaction between the behavior of Fock state detection in free space versus optical cavities. To do so, we study the phenomenon of the resonance of detectors with Fock wave packets as a function of their degree of monochromaticity, the number of spatial dimensions, the linear or quadratic nature of the light-matter coupling, and the presence (or absence) of cavity walls in space. In doing so we show that intuition coming from quantum optics in cavities does not straightforwardly carry to the free-space case. For example, in ($3+1$) dimensions the detector response to a Fock wave packet will go to zero as the wave packet is made more and more monochromatic and in coincidence with the detector's resonant frequency. This is so even though the energy of the free-space wave packet goes to the expected finite value of $\ensuremath{\hbar}\mathrm{\ensuremath{\Omega}}$ in the monochromatic limit. This is in contrast to the behavior of the light-matter interaction in a cavity (even a large one) where the probability of absorbing a Fock quantum is maximized when the quantum is more monochromatic at the detector's resonance frequency. We trace this crucial difference to the fact that monochromatic Fock states are not normalizable in the continuum; thus physical Fock states need to be constructed out of normalizable wave packets whose energy density goes to zero in the monochromatic limit as they get spatially delocalized.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.008 | 0.019 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.048 | 0.013 |
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".