Ultra-Low-Cost Design of Ripple Carry Adder to Design Nanoelectronics in QCA Nanotechnology
Bibliographic record
Abstract
Due to the development of integrated circuits and the lack of responsiveness to existing technology, researchers are looking for an alternative technology. Quantum-dot cellular automata (QCA) technology is one of the promising alternatives due to its higher switch speed, lower power dissipation, and higher device density. One of the most important and widely used circuits in digital logic calculations is the full adder (FA) circuit, which actually creates the problem of finding its optimal design and increasing performance. In this paper, we designed and implemented two new FA circuits in QCA technology and then implemented ripple carry adder (RCA) circuits. The proposed FAs and RCAs showed excellent performance in terms of QCA evaluation parameters, especially in cost and cost function, compared to the other reported designs. The proposed adders’ approach was 46.43% more efficient than the best-known design, and the reason for this superiority was due to the coplanar form, without crossovers and inverter gates in the designs.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".