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Record W4404574331 · doi:10.1126/sciadv.adw3893

X-ray phase measurements by time-energy correlated photon pairs

2025· article· en· W4404574331 on OpenAlexaff
Y. Klein, E. Strizhevsky, H. Aknin, Moshe Deutsch, Eliahu Cohen, Avi Pe’er, Kenji Tamasaku, Tobias U. Schülli, Ebrahim Karimi, S. Shwartz

Bibliographic record

VenueScience Advances · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsUniversity of Ottawa
FundersHORIZON EUROPE Framework ProgrammeIsrael Science FoundationEuropean Commission
KeywordsPhotonPhase (matter)Energy (signal processing)PhysicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.306
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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