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Record W4411069505 · doi:10.1038/s41598-025-98493-z

Design of an energy efficient approximate BinDCT module in quantum cellular automata

2025· article· en· W4411069505 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

VenueScientific Reports · 2025
Typearticle
Languageen
FieldComputer Science
TopicQuantum-Dot Cellular Automata
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsComputer scienceCellular automatonQuantumTheoretical computer scienceQuantum cellular automatonAlgorithmPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

The quantum cellular automata (QCA) paradigm offers an ultra-low-power approach for realizing nanocomputing circuits at the molecular level, offering high parallelism capabilities. This study introduces a coplanar and energy-efficient implementation of the approximate binary discrete cosine transform (BinDCT) module using QCA technology. The proposed BinDCT module integrates various sequential and combinatorial submodules, including multiplexers (MUXs), demultiplexers (DeMUXs), parallel-in-parallel-out right-shift registers (PIPO-RSRs), ripple carry adders (RCAs), and ripple borrow subtractors (RBSs). Each submodule is systematically designed following the standard single-layer design principles, which are crucial for maximizing circuit performance, enhancing reliability, and minimizing power dissipation. Extensive simulations were conducted to validate the logic operation and energy dissipation of each submodule. The simulation results demonstrate a significant reduction in power dissipation- up to [Formula: see text] and an improvement in circuit area efficiency by [Formula: see text] compared to previous QCA implementations.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.661
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.014
GPT teacher head0.234
Teacher spread0.220 · 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