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Record W2125662042 · doi:10.1109/nano.2008.103

Quantum Mechanical Simulation of QCA with a Reduced Hamiltonian Model

2008· article· en· W2125662042 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicQuantum-Dot Cellular Automata
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsQuantum dot cellular automatonCellular automatonQuantum cellular automatonHamiltonian (control theory)Computer scienceQuantumElectronic circuitQuantum computerCoupling (piping)Theoretical computer scienceStatistical physicsComputational scienceAlgorithmPhysicsMathematicsQuantum mechanicsMathematical optimizationEngineering

Abstract

fetched live from OpenAlex

Molecular quantum-dot cellular automata (QCA) is an emerging computing paradigm which utilizes electrostatic coupling between electronic configurations in neighboring molecules to perform information processing. A simulation tool for this technology, QCADesigner, exists and allows designers to quickly layout and simulate QCA circuits constructed with up to thousands of QCA cells. However, in general, large quantum mechanical systems are not suitable for efficient simulation on a classical computer, and as a result, QCADesigner uses the Hartree-Fock approximation to reduce the computational complexity of the simulation. Under certain circumstances, this approximation can lead to the incorrect ground state and hence, produce logically incorrect results at the outputs. In this work, we provide examples of problem circuits and propose a method to identify areas that must be simulated using the full Hamiltonian.

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: Empirical · Consensus signal: none
Teacher disagreement score0.598
Threshold uncertainty score0.430

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 science0.0010.000
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 head0.037
GPT teacher head0.251
Teacher spread0.213 · 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

Quick stats

Citations6
Published2008
Admission routes1
Has abstractyes

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