20 µm resolution multipixel ghost imaging with high-energy x-rays
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hard x-ray imaging is indispensable across diverse fields owing to its high penetrability. However, the resolution of traditional x-ray imaging modalities, such as computed tomography (CT) systems, is constrained by factors including beam properties, the limitations of optical components, and detection resolution. As a result, the typical resolution in commercial imaging systems that provide full-field imaging is limited to a few hundred microns, and scanning CT systems are too slow for many applications. This study advances high-photon-energy imaging by extending the concept of computational ghost imaging to multipixel ghost imaging with x-rays. We demonstrate a remarkable resolution of approximately 20 µm for an image spanning 0.9 by 1 cm 2 , comprised of 400,000 pixels and involving only 1000 realizations. Furthermore, we present a high-resolution CT reconstruction using our method, revealing enhanced visibility and resolution. Our achievement is facilitated by an innovative x-ray lithography technique and the computed tiling of images captured by each detector pixel. Importantly, this method maintains reasonable timeframes and can be scaled up for larger images without sacrificing the short measurement time, thereby opening intriguing possibilities for noninvasive high-resolution imaging of small features that are invisible with the present modalities.
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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