QCA based cost efficient coplanar 1 × 4 <scp>RAM</scp> design with set/reset ability
Bibliographic record
Abstract
Abstract In this paper, a loop based coplanar random access memory (RAM) cell with set/reset ability using quantum‐dot cellular automata (QCA) technology is first proposed. The operation of the RAM cell is validated physically as well as by simulations using QCADesigner tool. The energy dissipation analysis of the proposed RAM cell demonstrates that the proposed design dissipates very low energy. Additionally, the fault tolerance to single cell missing and addition defects of the proposed RAM cell is also presented. Further, we designed a coplanar 1 × 4 RAM which consists of four proposed RAM cells, one 2:4 decoder and one 5‐input majority voter along with the control signals required for the proper operation of the RAM. The proposed RAM cell and 1 × 4 RAM designs achieve performance improvement of up to 88.16% and 79.28%, respectively from the existing design in terms of QCA circuit cost. These structures can therefore be used to design efficient higher order RAM structures.
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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 | 0.000 | 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".