Forming positive-negative images using conditioned partial measurements from reference arm in ghost imaging
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Bibliographic record
Abstract
A recent thermal ghost imaging experiment implemented in Wu's group [Chin. Phys. Lett. 279, 074216 (2012)] showed that both positive and negative images can be constructed by applying a novel algorithm. This algorithm allows us to form the images with the use of partial measurements from the reference arm (even which never passes through the object), conditioned on the object arm. In this paper, we present a simple theory that explains the experimental observation and provides an in-depth understanding of conventional ghost imaging. In particular, we theoretically show that the visibility of formed images through such an algorithm is not bounded by the standard value 1/3. In fact, it can ideally grow up to unity (with reduced imaging quality). Thus, the algorithm described here not only offers an alternative way to decode spatial correlation of thermal light, but also mimics a "bandpass filter" to remove the constant background such that the visibility or imaging contrast is improved. We further show that conditioned on one still object present in the test arm, it is possible to construct the object's image by sampling the available reference data.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it