Bibliographic record
Abstract
Over the past three decades, quantum mechanics has allowed the development of technologies that provide unconditionally secure communication. In parallel, the quantum nature of the transverse electromagnetic field has spawned the field of quantum imaging that encompasses technologies such as quantum ghost imaging and high-dimensional quantum key distribution (QKD). The emergence of such quantum technologies also highlights the need for the development of methods for characterizing the elusive quantum state itself. In this document, we describe new technologies that use the quantum properties of light for security. The first is a technique that extends the principles behind QKD to the field of imaging. By applying the polarization-based BB84 protocol to individual photons in an active imaging system, we obtained images that are secure against intercept-resend jamming attacks. The second technology presented in this article is based on an extension of quantum ghost imaging. We used a holographic filtering technique to build a quantum ghost image identification system that uses a few pairs of photons to identify an object from a set of known objects. The third technology addressed in this document is a high-dimensional QKD system that uses orbital-angular-momentum (OAM) modes of light for encoding. Moving to a high-dimensional state space in QKD allows one to impress more information on each photon, as well as introduce higher levels of security. We discuss the development of two OAM-QKD protocols based on the BB84 and Ekert QKD protocols. The fourth and final technology presented in this article is a relatively new technique called direct measurement that uses sequential weak and strong measurements to characterize a quantum state. We use this technique to characterize the quantum state of a photon with a dimensionality of d=27, and measure its rotation in the natural basis of OAM.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.046 | 0.018 |
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".