A Modular Approach to Designing an Online Testable Ternary Reversible Circuit
Bibliographic record
Abstract
Energy inefficiency in irreversible logic circuits is creating an obstruction on the path towards continued advancements in complexity and reductions in the size of today’s computer systems. Designing the component circuits in a reversible manner may offer a possible solution to this crisis, allowing significant reductions in power consumption and heat dissipation requirements. Multi-valued (MV) reversible logic can provide further advantages over binary reversible logic, such as better performance or reducing wiring congestion. The current literature, however, contains very little work on testability of such designs. This paper describes the design of an online testable block for ternary reversible logic. This block implements most ternary logic operations and provides online testability for a reversible ternary network composed of several of these blocks. The testable block is composed of reversible building blocks, and thus is itself reversible. Multiple such blocks can be combined to construct complex and complete, testable, ternary reversible circuits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".