Novel Reversible Comparator Design in Quantum Dot-Cellular Automata with Power Dissipation Analysis
Bibliographic record
Abstract
In very large-scale integration (VLSI) circuits, a partial of energy lost leads to information loss in irreversible computing because, in conventional combinatorial circuits, each bit of information generates heat and power consumption, thus resulting in energy dissipation. When information is lost in conventional circuits, it will not be recoverable, as a result, the circuits are provided based on the reversible logic and according to reversible gates for data retrieval. Since comparators are one of the basic building blocks in digital logic design, in which they compare two numbers, the aim of this research is to design a 1-bit comparator building block based on reversible logic and implement it in the QCA with the minimum cell consumption, less occupied area, and lower latency, as well as to design it in a single layer. The proposed 1-bit reversible comparator is denser, cost-effective, and more efficient in quantum cost, power dissipation, and the main QCA parameters than that of previous works.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".