Quantum Dilation and Erosion
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
The dilation and erosion operations are the first fundamental step in classical image processing. They are important in many image processing algorithms to extract basic image features, such as geometric shapes; such shapes are then fed to higher level algorithms for object identification and recognition. In this paper, we present an improved quantum method to realize dilation and erosion in imaging processing. Unlike in the classical way, in the quantum version of imaging processing, all of the information is stored in quantum bits (qubits). We use qubits to code the location and other information of each pixel of the images and apply quantum operators (or quantum gates) to accomplish specific functions. Because of quantum entanglement and other nonintuitive features in quantum mechanics, qubits have many advantages over classical bits, but their nature presents challenges in designing quantum algorithms. We first built the quantum circuit theoretically, and then ran it on the IBM Quantum Experience platform to test and process real images. With this algorithm, we are looking forward to more potential applications in quantum computation.
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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