MétaCan
Menu
Back to cohort
Record W2108661017 · doi:10.5120/16281-5852

Reversible Architecture of Computer Arithmetic

2014· article· en· W2108661017 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Computer Applications · 2014
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceArithmeticArchitectureComputer architectureMathematicsVisual artsArt

Abstract

fetched live from OpenAlex

Reversible logic plays an important role in emerging low power designs and quantum computing. This paper presents an efficient way to realize reversible arithmetic circuits especially targeting toward reversible arithmetic logic unit (RALU). In literature for reversible logic, not a significant advancement is found in integrating both logical and arithmetical functions, commonly known as arithmetic logic unit (ALU), a key feature of any computing system architecture. Here, this work presents a novel reversible arithmetic logic unit (ALU) performing basic functions similar to classical ALU such as addition, subtraction, AND, OR and XOR operations. Additional functions such as, NAND, NOR, XNOR and logical functions with single input inverted, overflow detection and comparison can also be performed with this design. The integration of these operations in single module using less number of control signals is not available in any of existing approaches. The design and analysis based on different parameters of reversible circuitsnumber of gates, garbage bits and quantum cost as well as simulation results are presented here. The proposed design offers efficient programmability and more flexibility than other methods.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.870
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.243
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it