MétaCan
Menu
Back to cohort
Record W2127064400 · doi:10.1142/s0219749915500446

Dynamics of entanglement and non-classical correlation for four-qubit GHZ state

2015· article· en· W2127064400 on OpenAlexaff
Pakhshan Espoukeh, Robabeh Rahimi, S. Salimi, Pouria Pedram

Bibliographic record

VenueInternational Journal of Quantum Information · 2015
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsQuantum entanglementQubitPhysicsDynamics (music)Quantum mechanicsGreenberger–Horne–Zeilinger stateQuantum teleportationStatistical physicsCorrelationState (computer science)Quantum correlationW stateQuantum discordQuantumQuantum channelComputer scienceMathematics

Abstract

fetched live from OpenAlex

Many-qubit entanglement is crucial for quantum information processing although its exploitation is hindered by the detrimental effects of the environment surrounding the many-qubit system. It is thus of importance to study the dynamics of general multipartite non-classical correlation, including but not restricted to entanglement, under noise. We did this study for four-qubit Greenberger–Horne–Zeilinga (GHZ) state under most common noises in an experiment and found that non-classical correlation is more robust than entanglement except when it is imposed to dephasing channel. Quantum discord presents a sudden transition in its dynamics for Pauli-X and Pauli-Y noises as well as Bell-diagonal states interacting with dephasing reservoirs and it decays monotonically for Pauli-Z and isotropic noises.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.264
Teacher spread0.245 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations9
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Quantum InformationSame topicQuantum Information and CryptographyFrench-language works237,207