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Record W2345961343 · doi:10.1002/9781119324560.ch2

An Approach To “Quantumness” In Coherent Control

2017· preprint· en· W2345961343 on OpenAlexafffund
Torsten Scholak, Paul Brumer

Bibliographic record

VenueAdvances in chemical physics · 2017
Typepreprint
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsQuantum entanglementQuantum nonlocalityCoherence (philosophical gambling strategy)Coherent controlQuantum mechanicsQuantumControl (management)ErasurePhotonComputer scienceQuantum discordQuantum technologyPhysicsOpen quantum systemStatistical physicsArtificial intelligence

Abstract

fetched live from OpenAlex

This chapter examines quantum control from a foundational perspective, relying upon modern concepts in quantum mechanics, such as entanglement, quantum erasure, nonlocality, and Bell tests to see how a truly quantum phase control scenario can be tested and built. It provides a detailed approach to examining the role of quantum mechanics in control scenarios that is applicable to other coherent control and to optimal control scenarios. The chapter further discusses ways to demonstrate complementarity in new, unconventional scenarios of true quantum coherent phase control, scenarios in which nonlinear response theory cannot be applied. It then addresses the question of how and when nontrivial aspects of quantum interference affect phase control. In this context, quantum interference and quantum mechanics are essentially synonymous. Since these aspects are absent in conventional phase control, the chapter extends the search to unconventional scenarios. To do so, it introduces a novel type of two-path interferometer, the “coherent control interferometer” (CCI).

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)0.002
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.015
Scholarly communication0.0030.006
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.304
Teacher spread0.286 · 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
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

Citations0
Published2017
Admission routes2
Has abstractyes

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