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Record W1982064050 · doi:10.1145/1229175.1229177

Simulation of random cell displacements in QCA

2007· article· en· W1982064050 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

VenueACM Journal on Emerging Technologies in Computing Systems · 2007
Typearticle
Languageen
FieldComputer Science
TopicQuantum-Dot Cellular Automata
Canadian institutionsUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsCrossoverQuantum dot cellular automatonCellular automatonInverterDisplacement (psychology)Electronic circuitComputer scienceCoherence (philosophical gambling strategy)Electronic engineeringFunction (biology)AlgorithmMathematicsEngineeringElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

We analyze the behavior of quantum-dot cellular automata (QCA) building blocks in the presence of random cell displacements. The QCA cells are modeled using the coherence vector description and simulated using QCADesigner. We evaluate various fundamental circuits: the wire, the inverter, the majority gate, and the two-wire crossing approaches: the coplanar crossover and the multilayer crossover. Our results show that different building blocks have different displacement tolerances. The coplanar crossover and inverter perform the weakest. The wire is the most robust. We have found displacement tolerances to be a function of circuit layout and geometry rather than cell size.

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)0.004
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.299
Teacher spread0.278 · 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