An Algorithm for Quantum Template Matching
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
Quantum circuits are often generated by decomposing gates from networks with classical reversible gates. Only in rare cases, the results are minimal. Post-optimization methods, such as template matching, are employed to reduce the quantum costs of circuits. Quantum templates are derived from identity circuits. All minimal realizations, within certain limitations, can be embedded into templates. Due to this property, templates matching has the potential to reduce quantum costs of circuits. However, one of the difficulties in finding templates matches is due to the mobility of the gates within the circuit. Thus far, template matching procedures have employed heuristics to reduce the search space. This article presents an in-depth study of exact template matching with a set of algorithms. A graph structure with the corresponding circuits facilitates the discovery of potential sequences of templates to be matched, and how exact minimization of circuits can be accomplished. The significance of the proposed method is verified in benchmarks optimization.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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