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Record W3036294534 · doi:10.22215/etd/2015-10970

Quantum Communication Assisted MAC Protocol

2015· dissertation· en· W3036294534 on OpenAlexaff
Steve R. Cloutier

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceQuantum networkQuantum information scienceQuantum entanglementProtocol (science)Computer networkQuantum computerQuantumQuantum stateState (computer science)Distributed computingPhysicsQuantum mechanicsAlgorithm

Abstract

fetched live from OpenAlex

Quantum mechanics has been around since the early 1900s and computers made their first appearance in the late 1930s. In the decades after that, the two came together to bring about quantum computing. A sub field of quantum computing is quantum communications, the ability to transmit a quantum state from one place to another. This communication takes place between two entities. Communication over a classic network involves many entities each vying for network time. This is done through various network protocols, one of them being Medium Access Control (MAC). Although quantum computing is currently a one-to-one medium, it's properties can be used to assist the MAC protocol to enhance it's current abilities. In this thesis, we propose two different quantum communication assisted MAC protocols to achieve shared communication over a classic network. These protocols are based on quantum entanglement principles and contention-free collision avoidance algorithms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.031
GPT teacher head0.334
Teacher spread0.303 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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