X-ray phase measurements by time-energy correlated photon pairs
Bibliographic record
Abstract
The resolution of a measurement system is fundamentally constrained by the wavelength of the used wave packet and the numerical aperture of the optical system. Overcoming these limits requires advanced interferometric techniques exploiting quantum correlations. While quantum interferometry can surpass the Heisenberg limit, it has been confined to the optical domain. Extending it to x-rays enables sub-angstrom spatial and zeptosecond temporal resolution, unlocking atomic-scale processes inaccessible to existing methods. Here, we demonstrate x-ray quantum interferometry using 17.5-kilo-electron volt ( [Formula: see text] = 70 picometers) photon pairs. Our approach introduces a phase measurement technique with exceptional noise resilience, mitigating the impact of mechanical instabilities, vibrations, and photonic noise-key challenges in x-ray interferometry. By generating and using entangled x-ray photons, we lay the foundation for next-generation techniques with unprecedented phase precision. This breakthrough carries far-reaching consequences for fundamental physics, high-resolution imaging, and spectroscopy, bringing to light quantum optical effects never before accessed in the x-ray regime.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".