Bibliographic record
Abstract
It takes some convincing to realize that light has a polarization degree of freedom, as our eyes are usually ignorant of light's polarization. Since overcoming this hurdle of intuition, polarization has become a fantastic resource that can be easily manipulated both physically and mathematically, opening the door to a wide variety of applications. We have only recently begun to appreciate how many more doors are opened by the quantum mechanical degrees of freedom inherent to optical polarization. One use of optical polarization is for polarimetry: measuring the changes in light's polarization after it interacts with a material is an excellent procedure for nondestructively probing the characteristics and composition of the intervening material. More sensitive measurements require brighter probe light; however, sufficiently intense light will begin to destroy the sample being probed. In this thesis, we seek to provide more sensitive polarimetry without resorting to bright beams of light. Tailoring the quantum properties of various states of light has been shown to increase their usefulness for other estimation protocols and we show how to extend this paradigm to quantum enhancements in polarimetry. We begin by finding the quantum states underlying classical polarization. Each particular set of classical polarization properties corresponds to a large variety of quantum states. Next, we establish quantum descriptions of classical polarization transformations corresponding to arbitrary Jones and Mueller matrices, including quantum mechanical insights into the distinction between processes that can and cannot be described by Jones matrices. We propose candidates for the most likely quantum states underlying classical decompositions into polarized and unpolarized fractions, carefully inspecting how these quantum states behave under polarization transformations. This language allows us to inspect quantum-enhanced sensing in the multiparameter context of polarimetry. We show the dramatic possibilities for quantum enhancements in any metrological scenario that is mathematically equivalent to a rotation, of which polarization rotations are a primary example; in contrast, we also show most attenuating and depolarizing polarization transformations to forbid such dramatic enhancements. Finally, we discuss polarization and its generalizations in the context of generating quantum entanglement via linear optics. These applications serve as mere examples of the usefulness promised by light’s quantum polarization degrees of freedom.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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; both teacher heads agree on what is shown here.
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".