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Record W7133047851

Quantum Measurements are Disturbing: Experiments studying the role of disturbance in postselected metrology, quantum pigeonholes, and entangled sheep

2024· dissertation· W7133047851 on OpenAlexfundno aff
Noah Benjamin Lupu-Gladstein

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldPhysics and Astronomy
TopicQuantum Mechanics and Applications
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilNational Science FoundationGirton College, University of CambridgeFetzer InstituteCanadian Institute for Advanced ResearchNatural Sciences and Engineering Research Council of CanadaJohn E. Fetzer Memorial Trust
KeywordsQuantumDisturbance (geology)Quantum measurementQuantum processQuantum operationQuantum error correctionWeak measurementQuantum fluctuationMeasure (data warehouse)
DOInot available

Abstract

fetched live from OpenAlex

This thesis details two experiments and one theoretical manuscript that explore the nature of measurement disturbance in quantum mechanics. The first experiment exploits measurement disturbance to enhance measurement precision by two orders of magnitude, and in principle even more. The second experiment investigates a paradox where three quantum pigeons seem to occupy two pigeonholes without any pair belonging to the same hole. It finds that measurement disturbance accounts for some, but not all of the counter-intuitive phenomena at play in the paradox. The final manuscript develops a new theoretical framework for studying quantum measurement and disturbance from the viewpoint of quantum agents. Our framework reveals how agents endowed with quantum memories might view measurement not as a stochastic collapse, but as a continuous flow of quantum information.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.316
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 designBench or experimental
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
Published2024
Admission routes1
Has abstractyes

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